Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances

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Article Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances

Jongmin Ahn 1 , Hojun Lee 1 , Yongcheol Kim 1, Wanjin Kim 2 and Jaehak Chung 1,*

1 Department of Electronics Engineering, INHA University, Inhceon 22201, Korea; [email protected] (J.A.); [email protected] (H.L.); [email protected] (Y.K.) 2 Agency of Defense Development, Changwon-si 51682, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-032-860-7421

Abstract: Underwater acoustic (UWA) biomimicking communications have been developed for covert communications. For the UWA covert communications, it is difﬁcult to achieve the bit error rate (BER) and the degree of mimic (DoM) performances at the same time. This paper proposes a biomimicking covert communication method to increase both BER and DoM (degree of mimic) performances based on the Time Frequency Shift Keying (TFSK). To increase DoM and BER performances, the orthogonality requirements of the time- and frequency-shifting units of the TFSK are theoretically derived, and the whistles are multiplied by the sequence with a large correlation. Two-step DoM assessments are also developed for the long-term whistle signals. Computer simulations and practical lake and ocean experiments demonstrate that the proposed method increases the DoM by 35% and attains a zero BER at −6 dB of Signal to Noise Ratio (SNR). Keywords: convert communication; bio-mimetic; signal processing; underwater communication; Citation: Ahn, J.; Lee, H.; Kim, Y.; MOS test Kim, W.; Chung, J. Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER 1. Introduction Performances. Sensors 2021, 21, 2184. Underwater acoustic (UWA) covert communication requires covertness and conﬁden- https://doi.org/10.3390/s21062184 tiality. The conventional UWA covert communication schemes achieve the covertness using the spread spectrum that spreads out the communication signal over a wide frequency Academic Editor: Theodore band, which is considered as background noise [1–7]. However, the narrow bandwidth of E. Matikas the UWA communication cannot utilize a large spreading factor, and a low transmit power for the covertness causes a short available communication range [1–7]. As an alternate, Received: 5 February 2021 biomimetic communications have been developed, which mimic the dolphin whistles to Accepted: 17 March 2021 Published: 20 March 2021 increase the covertness [8–13]. The idea of biomimetic communications is to make the enemy confuse the communication signals with dolphin sounds [8–14].

Publisher’s Note: MDPI stays neutral The CV-CFM (continuously varying-carrier frequency modulation) method was de- with regard to jurisdictional claims in veloped for biomimetic communication [12]. The CV-CFM selects one whistle among published maps and institutional afﬁl- many whistles, and divides the whistle into many short-time periods, and modulates iations. binary bits to the periods using the conventional digital communication modulations (i.e., Chirp Spread Spectrum (CSS), Frequency Shift Keying (FSK), and Phase Shift Keying (PSK)) [9,10,12]. The short division of the whistle increased the frequency bandwidth of the whistle pattern, which decreased the degree of mimic (DoM) and Bit Error Ratio (BER) performances. To increase the DoM and BER performances, the time-frequency shift Copyright: © 2021 by the authors. keying (TFSK) method was researched [13]. The TFSK method did not allocate the binary Licensee MDPI, Basel, Switzerland. This article is an open access article information bits to the divided whistles, but to the shifted locations in the time-frequency of distributed under the terms and the whistles [13]. However, the BER performance of the TFSK varied with the transmitted conditions of the Creative Commons whistle patterns, and the time- and frequency-shifting units that satisfy the orthogonality Attribution (CC BY) license (https:// in the time- and frequency-domains were not derived. If a few whistle patterns with a creativecommons.org/licenses/by/ low BER are used for a long data sequence, the DoM of Ref. [13] decreases by the repeated 4.0/). similar whistles. For the practical biomimetic covert communication, the large DoM and

Sensors 2021, 21, 2184. https://doi.org/10.3390/s21062184 https://www.mdpi.com/journal/sensors Sensors 2021, 21, 2184 2 of 18

the low BER need to be simultaneously achieved and to be evaluated according to various parameters of the real dolphin sounds, e.g., long-term signal duration, bandwidth, etc. [8–14]. In general, the time duration and the frequency bandwidth of the dolphin whistles vary from several hundred milliseconds to two seconds and from several hundred Hz to tens of kHz, respectively [15–19]. Thus, the DoM evaluation needs to be performed for a long-term period. This paper proposes a TFSK-based biomimetic communication method increasing the DoM and BER performances. We theoretically derive the orthogonality requirements in the time- and frequency-domains and utilizes various whistle patterns with sequences with the large autocorrelation to increases the DoM and BER performances. To evaluate the long-term DoM of the proposed method, a two-step DoM assessment is developed. The computer simulation and the ocean experiments were executed to show that the proposed method demonstrated better DoM and BER performances than the conventional convert communications. The main contributions of the paper are summarized as follows: 1. The time- and frequency-shifting unit requirements of the TFSK are theoretically derived for the orthogonality in the time- and frequency-domains. The requirements guarantee the low BER. 2. For the large DoM and the low BER, the sequence with a large correlation is multiplied to the whistles, which enables to use of various dolphin whistles without any restrictions. In addition, the orthogonality requirements for the proposed method are also derived. 3. Since the sequence makes the whistle spread in the frequency domain, the DoM assessments are conducted to find the unrecognizable spreading parameter. Thus, a two-step DoM assessment is proposed: The 1st step is conducted to find the best length of the sequence. The 2nd step is executed to confirm whether the long-term whistles signal with the selected sequence length is acceptable for the covert communication. 4. The computer simulations and the practical lake and ocean experiments were conducted and demonstrated the proposed method had the large DoM and the lower BER compared with the conventional covert communication methods. This paper is organized as follows. In Section2, the orthogonal requirement of the TFSK according to a whistle pattern is derived, and the proposed biomimetic communication method is described. Section3 explains the DoM assessment method for the proposed biomimetic communication signals. In Section4, the BER and DoM performances of the proposed method are analyzed. In Section5, the proposed biomimetic communication method demonstrated the large DoM and the low BER through computer simulations and practical lake and ocean experiments. Section6 concludes the paper.

2. Proposed Method The conventional TFSK scheme modulates binary bits to the shifted time-frequency position of the whistles [13]. Ref. [13] does not provide the requirements of the time- and frequency-shifting units which guarantee the orthogonality of whistles, and if zero-chirp rate whistles are transmitted, the detection performance degrades by the time ambiguity. Thus, few selected whistles may be utilized to attain the large BER. Figure1 shows the spectrograms of the real whistles. In Figure1, the zero-chirp rate whistles are frequently found. If these zero-chirp rate whistles are not transmitted to avoid the detection ambiguity of the TFSK, the DoM of the TFSK decreases for the long-term observation. Sensors 2021, 21, x FOR PEER REVIEW 3 of 19

in the time- and frequency-domains and utilizes various whistle patterns with sequences with the large autocorrelation to increases the DoM and BER performances. To evaluate the long-term DoM of the proposed method, a two-step DoM assessment is developed. The computer simulation and the ocean experiments were executed to show that the proposed method demonstrated better DoM and BER performances than the conventional convert communications. The main contributions of the paper are summarized as follows: 1. The time- and frequency-shifting unit requirements of the TFSK are theoretically derived for the orthogonality in the time- and frequency-domains. The requirements guarantee the low BER. 2. For the large DoM and the low BER, the sequence with a large correlation is multiplied to the whistles, which enables to use of various dolphin whistles without any restrictions. In addition, the orthogonality requirements for the proposed method are also derived. 3. Since the sequence makes the whistle spread in the frequency domain, the DoM assessments are conducted to find the unrecognizable spreading parameter. Thus, a two-step DoM assessment is proposed: The 1st step is conducted to find the best length of the sequence. The 2nd step is executed to confirm whether the long-term whistles signal with the selected sequence length is acceptable for the covert communication. 4. The computer simulations and the practical lake and ocean experiments were conducted and demonstrated the proposed method had the large DoM and the lower BER compared with the conventional covert communication methods. This paper is organized as follows. In Section 2, the orthogonal requirement of the TFSK according to a whistle pattern is derived, and the proposed biomimetic communication method is described. Section 3 explains the DoM assessment method for the proposed biomimetic communication signals. In Section 4, the BER and DoM performances of the proposed method are analyzed. In Section 5, the proposed biomimetic communication method demonstrated the large DoM and the low BER through computer simulations and practical lake and ocean experiments. Section 6 concludes the paper.

2. Proposed Method The conventional TFSK scheme modulates binary bits to the shifted time-frequency position of the whistles [13]. Ref. [13] does not provide the requirements of the time- and frequency-shifting units which guarantee the orthogonality of whistles, and if zero-chirp rate whistles are transmitted, the detection performance degrades by the time ambiguity. Thus, few selected whistles may be utilized to attain the large BER. Figure 1 shows the spectrograms of the real whistles. In Figure 1, the zero-chirp rate whistles are frequently Sensors 2021, 21, 2184 3 of 18 found. If these zero-chirp rate whistles are not transmitted to avoid the detection ambiguity of the TFSK, the DoM of the TFSK decreases for the long-term observation.

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Figure 1. Spectrograms of the various realreal Delphinus delphisdelphis whistles.whistles.

We theoreticallyWe derive theoretically the orthogonality derive the orthogonalityrequirements requirementsin time- and frequency-shift- in time- and frequency-shifting ing units and proposeunits and a novel propose scheme a novel that scheme multiplies that the multiplies sequence the with sequence the large with autocor- the large autocorrela- relation to the tionwhistles to the to whistles increase to the increase BER performance the BER performance in time. inThus, time. all Thus, whistles all whistles are are utilized utilized for the fortransmission the transmission whistles, whistles, which whichincreases increases the DoM. the DoM.

2.1. TFSK Performance Analysis According to Whistle Pattern 2.1. TFSK Performance Analysis According to Whistle Pattern For the derivation of the time- and frequency-shifting unit requirements, the whistles For the derivationare mathematically of the time- and modeled, frequenc andy-shifting the orthogonality unit requirements, requirements the whistles are derived. Assume are mathematically modeled, and the orthogonality requirements are derived. Assume that the whistle pattern is modeled as a function ( fw(t)), which is presented as [12]: that the whistle pattern is modeled as a function (()), which is presented as [12]: Z w(t) = cos f (t)dt . (1) () =() . w (1)

Since the conventionalSince the TFSK conventional modulation TFSK sc modulationheme shifts scheme the whistle shifts thepatterns whistle by patterns the by the time time and the frequencyand the frequency according according to transmit to transmitthe binary the bits, binary let the bits, time- let the and time- frequency- and frequency-shifting shifting units beunits ∆ beand∆t ∆and, respectively,∆ f , respectively, and and the the total total number number of of time time and and frequencyfrequency grids be M and grids be andN , respectively., respectively. If theIf the whistle whistle is modulatedis modulated with with input input bits, bits, a reference a reference whistle is shifted M− M− N− N− whistle is shiftedfrom from−∆t −∆1 to ∆ tto ∆1 in the in time the domain time domain and from and−∆ fromf 1 −∆to ∆ f 1toin the frequency 2 2 2 2 domain, respectively. Gray coding to the time-frequency mapping may be utilized to ∆ in the frequency domain, respectively. Gray coding to the time-frequency map- increase the BER. For M and N grids, the TFSK modulation conveys ( log2(N) + log2(M)) ping may be utilized to increase the BER. For and grids, the TFSK modulation con- bits per one whistle. ( () + ()) veys If the whistle bits per is modulatedone whistle. with m and n grid, which is an integer less than M and M, If the whistle is modulated with and grid, which is an integer less than and respectively, the TFSK modulated whistle (STF(t)) is expressed as: , respectively, the TFSK modulated whistle (()) is expressed as: j2πn∆ f t STF(t) = [δ(t − m∆t∆) ⊗ w(t)] × e , (2) () = [( − ∆) ⊗ ()] × , (2) where ⊗ denoteswhere a convolutional⊗ denotes a operation. convolutional Figure operation. 2 shows the Figure two different2 shows TFSK the two mod- different TFSK ulated whistle examples.modulated whistle examples.

01 bit modulated 11 bit modulated 01 bit modulated 11 bit modulated whistle whistle Ambiguity whistle whistle 10 10 ∆ ∆ 11 Frequency Frequency ∆ ∆ 11 01 0 0 01 00 00 00 01 11 10 Bits 00 01 11 10 Bits Time Time

(a) (b)

Figure 2. ExamplesFigure 2. ofExamples Time Frequency of Time Frequency Shift Keying Shift (TFSK) Keying modulated (TFSK) modulated signals: (a )signals: zero-chirp (a) zero-chirp rate whistle rate pattern (chirp whistle pattern (chirp rate: 0 Hz/s), (b) Up-chirp whistle pattern (chirp rate is larger than 0 Hz/s). rate: 0 Hz/s), (b) Up-chirp whistle pattern (chirp rate is larger than 0 Hz/s).

In Figure 2, Inand Figure are2, fourM and eachN andare foura total each of four and abits total are of allocated. four bits The are allocated.gray- The gray- colored whistlecolored denotes whistle a reference denotes whistle, a reference and blue whistle, and red and whistles blue and denote red whistles the TFSK denote the TFSK modulated ones.modulated In Figure ones. 2a, a Inzero-chirp Figure2a, ra ate zero-chirp whistle is ratemodulated. whistle isThe modulated. red and blue The red and blue whistles are modulated by 01 and 11 in time, respectively, and by 10 in frequency. In Fig- ure 2b, a whistle with a large-chirp rate is modulated. The red and blue ones are modulated by 01 and 11 in time, respectively, and by 10 in frequency. In Figure 2a, the blue and the red whistles are overlapped in the time-frequency domain because of the zero-chirp rate whistle and the small ∆, and the receiver is unable to correctly determine the transmitted bits by the overlapped region. If ∆ is larger than that of the whistle length, two whistles are separated in the time domain and the detection of the whistle has no ambiguity. Then, the receiver correctly decodes the transmitted bits. In Figure 2b, however, even though the same ∆ is utilized, two modulated whistles are orthogonal in the time- frequency domain, and the receiver has a low BER. Thus, the BER performance of the TFSK method depends on the whistle pattern, and to increase the BER, finding the good

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whistles are modulated by 01 and 11 in time, respectively, and by 10 in frequency. In Figure2b , a whistle with a large-chirp rate is modulated. The red and blue ones are modulated by 01 and 11 in time, respectively, and by 10 in frequency. In Figure2a, the blue and the red whistles are overlapped in the time-frequency domain because of the zero-chirp rate whistle and the small ∆t, and the receiver is unable to correctly determine the transmitted bits by the overlapped region. If ∆t is larger than that of the whistle length, two whistles are separated in the time domain and the detection of the whistle has no ambiguity. Then, the receiver correctly decodes the transmitted bits. In Figure2b , Sensors 2021, 21, x FOR PEER REVIEWhowever, even though the same ‘∆t is utilized, two modulated whistles are orthogonal5 of 19 in

the time-frequency domain, and the receiver has a low BER. Thus, the BER performance of the TFSK method depends on the whistle pattern, and to increase the BER, ﬁnding the ∆good and∆ ∆t and satisfying∆ f satisfying the orthogonal the orthogonal requirements requirements of the TFSK of the needs TFSK for needs the forgiven the whis- given tlewhistle pattern. pattern. For ∆ f , the calculation of the orthogonality requirement for an arbitrary whistle For ∆, the calculation of the orthogonality requirement for an arbitrary whistle pat- pattern is difﬁcult. However, if the receiver demodulates the received signal using the tern is difficult. However, if the receiver demodulates the received signal using the mul- multiplication of the complex conjugate to the transmitted whistle, the demodulated signal tiplication of the complex conjugate to the transmitted whistle, the demodulated signal has a zero-chirp rate pattern. Then, the orthogonality requirement of ∆ f becomes similar has a zero-chirp rate pattern. Then, the orthogonality requirement of ∆ becomes similar to that of the conventional FSK modulation. When the time length of the whistle is L , the to that of the conventional FSK modulation. When the time length of the whistle isw , ∆ f satisfying orthogonal requirements of the TFSK is given as: the ∆ satisfying orthogonal requirements of the TFSK is given as: ∆ f > 1/L . (3) ∆ >1/w. (3)

ForFor ∆∆,t ,more more manipulation manipulation is is need needed.ed. Firstly, Firstly, assume assume that that ∆∆t isis lessless thanthan Lw.. IfIf∆ ∆t is islarger larger than than Lw,, no no overlapoverlap andand nono misdetection occur, occur, but but the the data data rate rate decreases. decreases. Thus, Thus, thisthis case case is is not not considered inin thisthis paper. paper. Since Since the the whistle whistle patterns patterns are are varied varied and and non-linear non- linearfunction, function, the derivation the derivation of the of orthogonality the orthogonality requirement requirement of ∆t for of the∆ forwhistles the whistles is difficult. is difficult.If the non-linear If the non-linear whistle patternwhistle is pattern divided is into divided short-intervals, into short-intervals, a piece of thea piece whistle of the can whistlesimply can be modeledsimply be as modeled a linear functionas a linear ( fw (functiont)), e.g., 1(fw((t))),= e.g.,at + b(with) =+ a chirp with rate (a ), chirpwhich rate is defined(), which as a =is ddefinedf /∆t where as =d/∆∆t and d f wheredenote ∆ the and time- d and denote frequency-differences, the time- and frequency-differences,respectively. Thus, if ∆respectively.t is derived fromThus, the if ∆ smallest is derived chirp-rate from ofthe the smallest whistle, chirp-rate the derived of the∆t whistle,satisfies the the derived orthogonality ∆ satisfies of the the whistle orthogonality with the length of the (whistleLw). with the length (). AssumeAssume that that θ is is thethe declinedecline of of the the whistle whistle in in the the time-frequency time-frequency domain domain and and defined de- − finedas θ as= tan=1(df /(d/∆)∆t). To. calculateTo calculate the the orthogonality orthogonality requirement requirement of of the the whistle whistle with witha , we, we rotate rotate two two whistles whistles to toθ clockwise clockwise in thein the time-frequency time-frequency domain domain in Figurein Figure3. The 3. The two twomodulated modulated whistles whistles are are separated separated in the in time-frequencythe time-frequency domain domain keeping keeping the orthogonality. the orthogonality.In Figure In 3Figurea, if one 3a, whistle if one whistle is shifted is shifted by ∆t inby the∆ time in the domain, time domain, the overlapped the overlapped time is ( − ) timegiven is given as Lw as (∆t and−∆) the and frequency the frequency difference difference is given is asgivend f Hz. as In Figure Hz. In3 b,Figure after 3b, the rotation by θ, the time duration of (L − ∆t)/cos θ is overlapped in the time domain and after the rotation by , the time durationw of ( −∆)/ is overlapped in the time domainthe frequency and the gap frequency of cosθ ×gapd fofis obtained × in is the obtained frequency in the domain. frequency domain.

overlapped region

× ( −∆)/ ∆ Frequency

Frequency −∆ Time Time

(a) (b)

FigureFigure 3. 3. TFSKTFSK modulation modulation whistle; whistle; (a ()a Normal,) Normal, (b ()b Rotation) Rotation by by θ. .

If the frequency gap in Figure 3b is larger than the inverse of the overlapped time duration, two whistles satisfy the orthogonality in the time-frequency domain. Therefore, the orthogonality requirement for ∆ is calculated as:

× ≥ /( −∆), 0<∆<. (4) Since is equal to ∆ in Figure 3a, Equation (4) is rewritten as:

≥ 1/(( − ∆)∆) 0 < ∆ < . (5)

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If the frequency gap in Figure3b is larger than the inverse of the overlapped time duration, two whistles satisfy the orthogonality in the time-frequency domain. Therefore, the orthogonality requirement for ∆t is calculated as:

cosθ × d f ≥ cosθ/(Lw − ∆t),0 < ∆t < Lw. (4)

Since d f is equal to a∆t in Figure3a, Equation (4) is rewritten as:

a ≥ 1/((Lw − ∆t)∆t) and 0 < ∆t < Lw. (5)

For the whistle with the length of Lw, the minimum a that distinguishes the whistle 2 2 slops is calculated by 2 [20]. Thus, if a is smaller than 2 , the whistle is considered Lw Lw 2 as the zero-slop whistle and ∆t is set as L . If a is larger than 2 , ∆t is derived w Lw from Equation (5). In Equation (5), ∆t is the variable of the 2nd order convex function, q 2 q 2 Lw Lw 1 Lw Lw 1 and the solution of ∆t is obtained as 2 − 4 − a ≤ ∆t ≤ 2 + 4 − a . Since the minimum ∆t is of interest, the orthogonality requirement for the minimum ∆t to a and Lw is obtained as:  2  2  ∆t = Lw, a < L w . (6) q 2 2  Lw − Lw − 1 ≤ ∆t, 2 ≤ a  2 4 a Lw If ∆t dissatisﬁes Equation (6), the different two whistles are not orthogonal in the time-frequency region. For the orthogonal requirement of the zero-chirp rate whistle, ∆t needs to be equal to Lw, which decreases the data rate of the biomimetic TFSK. Note that the whistle duration is several hundred msec to a few seconds. If the conventional biomimetic TFSK uses few available whistles for the small ∆t, the same whistles are frequently re-transmitted, which results in the low DoM. Therefore, this paper proposes the TFSK-based biomimetic modulation using all whistle patterns to increase the DoM.

2.2. Proposed Bio-Mimetic TFSK Modulation Method For the large DoM and the low BER, all types of whistles including the zero-slop whistles need to be utilized and the orthogonal requirements of the short-time unit are crucial. The proposed method utilizes the sequence with a large autocorrelation to solve the orthogonality problem for the zero-slop-like whistles and the short-time unit problem for the high data rate. The sequence with the large autocorrelation performance is widely used in digital communications to detect the exact time-frequency location when multiple signals exist at the same time [21–25]. If the different good and long sequences are multiplied to the multiple whistles, the time location of each whistle is precisely detected when the multiplied sequence at the receiver is the same as that used in the transmitted whistle. This is because the autocorrelation value of the sequence is large only at the time zero. Thus, if the sequence is utilized in the TFSK, the receiver can detect the exact time location even though ∆t is smaller than that in the minimum in Equation (6) and the zero-slop whistles exist. If the sequence is the vector whose size is 1 × L, the sequence (C) is represented as C = [c1,..., cl,..., cL], where cl denotes the l-th element of the sequence with a value of 1 or −1, and L is the length of the sequence, i.e., cardinality. The ideal C satisﬁes the following property [21–25]:

2 |c | , n = 0 c × c = ∑l l , (7) ∑ l l−n 6= l 0, n 0

where ∑l cl × cl−n denotes the autocorrelation value of the sequence and n denotes a time- lag. Equation (7) is only satisﬁed when the sequence length (L) is inﬁnite. However, if the Sensors 2021, 21, 2184 6 of 18

sequence with a small L has a good autocorrelation characteristic, the autocorrelation at n 6= 0 has a very small value which can be considered as zero in Equation (7). Sensors 2021, 21, x FOR PEER REVIEW When the sequence C is multiplied to the whistle, the whistle is divided by7 of the 19 cardinality of C and each vector element is sequentially multiplied to the divided whistles. Since the cardinality of C is L, the length (Lw) of the whistle is divided by L, and a piece (τ) of the whistle is obtained by Lw/L. The proposed transmission signal multiplied by the / (sequence) of the iswhistle modeled is obtained as: by . The proposed transmission signal multiplied by the sequence is modeled as: j2πn∆ f t S(t) = [δ(t − m∆t) ⊗ {ct/τ × w(t)}] × e ∆, (8) () =[(−∆) ⊗{/ ×()}] × , (8) wherewhere Adenotes denotes the the ceiling ceiling function function of Aof. In. EquationIn Equation (8), (8), since sinceτ is inversely is inversely proportional propor- tionalto the to time the resolution,time resolution, if L increases, if increases, the time the detectiontime detection resolution resolution of the of whistle the whistle also alsoincreases, increases, whereas whereas the frequencythe frequency bandwidth bandwidt ofh the of whistlethe whistle is spread is spread out, out, which which distorts dis- tortsthe originality the originality of the of whistle.the whistle. Thus, Thus, the bestthe bestL needs needs to be to determined be determined to maximize to maximize the thetime time resolution resolution and and to to minimize minimize the the whistle whistle distortion. distortion.In In thisthis paper,paper, the maximum L isis determined determined by by satisfying satisfying the the undistorted undistorted whistle whistle requirement requirement that that human human does does not rec- not ognizerecognize the thedistortion distortion of the of thewhistle. whistle. The Thehuman human assessment assessment method method is described is described in Sec- in tionsSections 3 and3 and 4. 4. Assuming the best length of the sequence is L , the spread frequency (B ) of the whistle Assuming the best length of the sequence is c, the spread frequency (c ) of the whis- tleis calculatedis calculated as: as: Bc = Lc/Lw. (9) =/. (9) To satisfy Equation (7), ∆t needs to be larger than half of τ, and to satisfy the orthogo- nalityTo in satisfy the frequency Equation domain, (7), ∆ ∆ needsf needs to be to larger be greater thanthan half of the twice, and to of satisfyBc. Thus, the the orthog- time- onalityand orthogonality-requirements in the frequency domain, of ∆ the needs proposed to be method greater arethan derived the twice as: of . Thus, the time- and orthogonality-requirements of the proposed method are derived as: τ/2 ≤ ∆t /2 ≤ ∆ . (10) 2Bc ≤ ∆ f . (10) 2 ≤∆ NoteNote that that if if the the sequence sequence length length is large, is large, ∆ ∆ int Equationin Equation (10) (10)is smaller is smaller than thanthe min- the imumminimum value value in Equation in Equation (6). (6).The Theblock block diagra diagramm of the of theproposed proposed transmitter transmitter is shown is shown in Figurein Figure 4. 4.

gray bit mapping ,

original () whistle () ∆, ∆ () whistle generation time-freq. shift

FigureFigure 4. BlockBlock diagram diagram of of the the proposed proposed transmitter.

ForFor the the communication communication of of the the proposed proposed meth method,od, transmission frames are utilized as inin the the conventional conventional TFSK TFSK [13]. [13]. Every Every frame frame has has a a preamble preamble which which is is made by a whistle withwith a large chirp rate, and the consecutive whistle patterns and the original time- and frequency-locationsfrequency-locations of of the the whistles whistles in in the the frame frame are are known known to tothe the transmitter transmitter and and the there- receiver. Thus, the reference information of t = 0 and f = 0 for every whistle is known, ceiver. Thus, the reference information of =0 and =0 for every whistle is known, too. What the receiver needs to detect is to estimate the time- and frequency-differences too. What the receiver needs to detect is to estimate the time- and frequency-differences from the reference information. from the reference information. For the precise detection of the time- and frequency information from the received For the precise detection of the time- and frequency information from the received TFSK whistles, the maximum likelihood (ML) based receiver is proposed. Assume that the TFSK whistles, the maximum likelihood (ML) based receiver is proposed. Assume that whistle is shifted by m∗∆t in frequency and n∗∆ f in time for an arbitrary input. Then, the the whistle is shifted by ∗∆ in frequency and ∗∆ in time for an arbitrary input. Then, the modulated whistle (∗,∗()) is transmitted. If ∗,∗() passes through the underwater acoustic (UWA) channel (ℎ()), the received signal (()) is modeled as:

() =ℎ() ⊗∗,∗() + (), (11) where () denotes AWGN. For the ML detection, the receiver generates the conjugate ∗ of the transmitted whistle (,()) for all available time-frequency shifts, in which and vary from −∆ to ∆ and −∆ to ∆ , respectively. Then, all conjugate whistles are multiplied to the received whistle and each multiplication result is integrated.

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modulated whistle (Sm∗,n∗ (t)) is transmitted. If Sm∗,n∗ (t) passes through the underwater acoustic (UWA) channel (h(t)), the received signal (r(t)) is modeled as:

r(t) = h(t) ⊗ Sm∗,n∗ (t) + n(t), (11) Sensors 2021, 21, x FOR PEER REVIEW 8 of 19 where n(t) denotes AWGN. For the ML detection, the receiver generates the conjugate of ∗ the transmitted whistle (Sm,n(t)) for all available time-frequency shifts, in which m and n vary from −∆ f N to ∆ f N and −∆t M to ∆t M , respectively. Then, all conjugate whistles This procedure is2 the same2 as calculating2 the2 correlation value ((, )) at and . are multiplied to the received whistle and each multiplication result is integrated. This (, ) is obtained as: procedure is the same as calculating the correlation value (R(m, n)) at n and m. R(m, n) is (, ) = ()∗ () obtained as: Z , . (12) R(m n) = r(t)S∗ (t)dt If ∆ and ∆ satisfy Equation, (10), (, )m ,hasn the. largest value at =∗ (12)and =∗ (, ) If ,∆ otherwise,t and ∆ f satisfy Equation has a (10),veryR small(m, n )value.has the Thus, largest the value estimated at m = m and∗ and n of= then∗, otherwise,transmittedR indices(m, n) has is calculated a very small by: value. Thus, the estimated nˆ and mˆ of the transmitted indices is calculated by: arg max (,) = (, ). (13) argmax, (mˆ , nˆ) = R(m, n). (13) The estimated time-frequency indicesm using, n Equation (13) are de-mapped to obtain the transmittedThe estimated bits. time-frequency The block diagram indices of usingthe proposed Equation ML (13) receiver are de-mapped is shown toin obtainFigure the5. transmitted bits. The block diagram of the proposed ML receiver is shown in Figure5.

received () 1,1 ~(, ) estimate gray rx bits signal , de-mapping ∗ ,~,

1~ 1~ ∗() × time shift freq. shift

FigureFigure 5.5. Block diagram ofof thethe proposedproposed receiver.receiver. The proposed method utilizes the sequence multiplied whistles to transmit any whistle The proposed method utilizes the sequence multiplied whistles to transmit any whis- patterns including the zero-slop whistles and increases the DoM. However, the multiplica- tle patterns including the zero-slop whistles and increases the DoM. However, the multi- tion of the sequence to the whistle causes the frequency spread, and the amount of spread plication of the sequence to the whistle causes the frequency spread, and the amount of is determined by the sequence length Lc. In practice, a small amount of frequency spread is spread is determined by the sequence length . In practice, a small amount of frequency unrecognizable to the human. Thus, if a sequence length that generates the unrecognizable spread is unrecognizable to the human. Thus, if a sequence length that generates the un- frequency spread is chosen, the proposed method can increase the BER without sacriﬁcing therecognizable DoM. frequency spread is chosen, the proposed method can increase the BER without sacrificingThe next section the DoM. describes how to ﬁnd the unrecognizable sequence length for mini- mizingThe∆ tnext, and section the DoM describes assessment how forto find the proposedthe unrecognizable method. sequence length for mini- mizing ∆, and the DoM assessment for the proposed method. 3. Proposed DoM Assessment Method 3. ProposedThe DoM DoM is one Assessment of the criteria Method to evaluate the covertness of biomimetic communication. The quantitativeThe DoM is one and of qualitative the criteria measurements to evaluate the are covertness proposed of to biomimetic assess the communica- DoM of the biomimetiction. The quantitative communication: and qualitative The quantitative measurements method measuresare proposed the similarity to assess ofthe the DoM signal of shapethe biomimetic between onecommunication: real dolphin andThe onequantitative biomimetic method signal measures using the the spectral similarity correlation. of the Thesignal qualitative shape between method one measures real dolphin the similarity and one of biomimetic the sound betweensignal using one realthe dolphinspectral andcor- onerelation. biomimetic The qualitative signal using method a mean measures opinion the score similarity (MOS) test of the based sound on human between perception. one real Thus,dolphin the and qualitative one biomimetic method signal is more using practical a mean than opinion the quantitative score (MOS) method test based to measure on hu- theman DoM. perception. Thus, the qualitative method is more practical than the quantitative methodTwo to conventional measure the measurementDoM. methods have been executed for only one whistle, and theTwo DoM conventional of the many measurement consecutive methods whistles have over been a long-term executed duration for only has one not whistle, been evaluated.and the DoM In practice,of the many the dolphins consecutive sequentially whistles generateover a long-term various whistle duration patterns has not for been the long-time,evaluated. andIn practice, the transmitter the dolphins consecutively sequentially transmits generate many various whistles whistle over patterns a long for time the long-time, and the transmitter consecutively transmits many whistles over a long time to transmit many bits. Thus, for the more practical DoM assessment, the consecutive long- term biomimicking whistles need to be tested. In this paper, a two-step assessment method is performed to measure the DoM of the proposed biomimetic communication. For the 1st step, the various sizes of the sequences are tested to find the sequence length () that humans do not recognize. For the 2nd step, the long-term biomimicking whistles using the selected sequence length () are evaluated to check whether the size () is acceptable for the large DoM. If the evaluation fails, a

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to transmit many bits. Thus, for the more practical DoM assessment, the consecutive long-term biomimicking whistles need to be tested. In this paper, a two-step assessment method is performed to measure the DoM of the proposed biomimetic communication. For the 1st step, the various sizes of the sequences are tested to ﬁnd the sequence length (Lc) that humans do not recognize. For the 2nd step, the long-term biomimicking whistles using the selected sequence length (Lc) are evaluated to check whether the size (Lc) is acceptable for the large DoM. If the evaluation fails, a smaller Lc is applied and the 2nd step is executed again. The time of the consecutive whistle is set to 10 s for the 2nd step. The DoM assessments of each step are based on the MOS test (BS1284) given by the International Telecommunication Union (ITU) [26,27]. The DoM assessment procedure of the 1st step is described in Table1.

Table 1. The 1st step Degree of Mimic (DoM) assessment.

1. Modulate the whistles with various sequence lengths (L) for the test sets 2. Prepare the test sets of the modulated whistles and a real dolphin whistle 3. Firstly, listeners listen to the real dolphin whistle 4. Then, listeners sequentially listen to the randomly selected whistles among the test set including the real dolphin whistle. Note that the real dolphin whistle is also evaluated for the reference assessment 5. Listeners grade the amount of similarity for all tested whistles by how close the test whistle is to the real dolphin whistle according to the MOS grade score. 6. The DoM for a speciﬁc sequence length (L) is obtained by averaging MOS scores of the modulated whistles.

If the MOS score of the modulated whistles by the sequence with L is close to that of the real dolphin whistle, the L is chosen for the sequence length that has unrecognizable frequency spreading. As a result of the 1st step assessment, many Ls are attained. Since the ∆ f is inversely proportional to the L, the maximum L among the acceptable Ls is selected to maximize the data rate and is set to Lc. For the 2nd step, whistles are modulated by the selected Lc and the consecutive long- term whistles with a 10-s duration are generated. Then, the 10-s long consecutive long-term whistles are evaluated for the similarity to the real dolphin whistles. The DoM assessment of the 2nd step is described in Table2.

Table 2. The 2nd step DoM assessment.

1. Generate 10-s long consecutive whistles using the modulated whistles with Lc 2. Make the test set using the modulated whistles and 10-s long real dolphin whistles 3. Listeners listen to the signals of the test set in random order 4. Listeners evaluate how close the test whistles are to the real dolphin whistles according to the MOS grade score 5. The DoM for a speciﬁc test signal is obtained by averaging MOS scores.

If the DoM of the proposed method is larger than or close to that of real dolphin whistles, we consider that people may be unable to distinguish the proposed biomimetic consecutive whistles from the real dolphin whistles. Since listeners have no prior information about the test set, the conﬁdence of the evaluation is achieved. In the next section, the BER performance of the proposed method is analyzed, and Lc is selected through the 1st step DoM assessment, and the selected Lc is evaluated through the 2nd step DoM assessment. Sensors 2021, 21, x FOR PEER REVIEW 10 of 19 Sensors 2021, 21, 2184 9 of 18

4. Proposed DoM Assessment Method 4. Proposed DoM Assessment Method This section shows that the derived requirement ∆푡 in Equation (10) is correct using computer simulationsThis sectionand that shows the BERs that theof the derived proposed requirement method ∆aret in better Equation than (10)that isin correct using Ref. [13]. Additionally,computer simulationsthe 1st step andDoM that assessment the BERs was of theconducted proposed to methodfind the areadequ betterate than that in Ref. [13]. Additionally, the 1st step DoM assessment was conducted to ﬁnd the adequate 퐿푐, and the 2nd step DoM assessment was executed for the DoM of the long-term signal Lc, and the 2nd step DoM assessment was executed for the DoM of the long-term signal modulated with the 퐿푐. modulated with the Lc. 4.1. Communication Performance Assessment 4.1. Communication Performance Assessment For the BER analyses of various whistle patterns, computer simulations were exe- For the BER analyses of various whistle patterns, computer simulations were executed cuted under AWGN channel environments. For simplicity, assume that the whistle pat- under AWGN channel environments. For simplicity, assume that the whistle patterns were terns were modeled as a linear function of 푎푡 + 푏. The length (퐿𝑤) of the tested whistles modeled as a linear function of at + b. The length (Lw) of the tested whistles was ﬁxed was fixed by 200 ms, the carrier frequency was set as 2 kHz, and four chirp rates (푎) of 0 by 200 ms, the carrier frequency was set as 2 kHz, and four chirp rates (a) of 0 H/s, 1, H/s, 1, 2.5, and 5 kHz/s were selected. Then, ∆푡s that satisfy the orthogonality require- 2.5, and 5 kHz/s were selected. Then, ∆ts that satisfy the orthogonality requirements in ments in Equation (6) with the given 퐿𝑤 and four chirp rates were calculated. The calcu- Equation (6) with the given Lw and four chirp rates were calculated. The calculated whistle lated whistleparameters parameters were were displayed displayed in in Table Table3. 3.

Table 3. Whistle parameters. Table 3. Whistle parameters. Parameter Values Parameter Values 푏 (kHz) 2 b 푎 (kHz/s) (kHz)0 1 2.5 2 5 a (kHz/s) 0 1 2.5 5 ∆푡 (ms) ∆t (ms)200 ≤ ∆ 200푡 ≤ ∆t 5 ≤ ∆푡 5 ≤ ∆t 2 ≤ ∆푡 2 ≤ ∆t1 ≤ ∆푡 1 ≤ ∆t

Based on Table 3, the simulation parameters were set. 퐿s were chosen as 20, 60, and Based on Table3, the simulation parameters were set. Ls were chosen as 20, 60, and 120, which were also used for the MOS tests. The Kasami sequences for the three sequence 120, which were also used for the MOS tests. The Kasami sequences for the three sequence lengths were chosen for good autocorrelation performance [28–30]. Then, ∆푡s were se- lengths were chosen for good autocorrelation performance [28–30]. Then, ∆ts were selected lected 1, 2, and 5 ms to modulate the whistles. In this simulation, the 200 ms of ∆푡 was 1, 2, and 5 ms to modulate the whistles. In this simulation, the 200 ms of ∆t was excluded excluded because when the ∆푡 exceeded 200 ms, the misdetection by the overlap region because when the ∆t exceeded 200 ms, the misdetection by the overlap region did not exist, did not exist, and the data rate was too low to be utilized as a communication system. The and the data rate was too low to be utilized as a communication system. The modulation modulation indices of 푀 and 푁 were set as four each, and the total data rate was 20 indices of M and N were set as four each, and the total data rate was 20 bits/s. The BER bits/s. The BER results of the four chirp rate whistles of the proposed scheme and the results of the four chirp rate whistles of the proposed scheme and the conventional methods conventional methods of Ref. [13] with three ∆푡s were shown in Figure 6. of Ref. [13] with three ∆ts were shown in Figure6.

∗ Proposed∆푡 m 퐿 2 ∗ Proposed∆푡 m 퐿 2 ∗ ∆푡 2m 퐿 ∗ ∆푡 2m 퐿 ∗ ∆푡 1m 퐿 12 ∗ ∆푡 1m 퐿 12 ∆푡 m ∆푡 m ∆푡 2m ∆푡 2m ∆푡 1m ∆푡 1m

−25 −20 −15 −10 −5 −25 −20 −15 −10 −5

(a) (b)

Figure 6. Cont.

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100 100

10-1 10-1

10-2 10-2

∆:5msec :20 ∗ Proposed Proposed∆: 5msec : 20 Proposed∆:2msec :60 ∗ -3 ∗ -3 Proposed∆: 2msec : 60 ∆: 1msec : 120 ∗ 10 ∗ Proposed 10 Proposed∆: 1msec : 120 ∆: 5msec ∗ Ref 13 Ref 13 ∆: 5msec ∆: 2msec Ref 13 Ref 13 ∆: 2msec RefProposed 13 ∆: 1msec ∗ ∆푡 m 퐿 2 RefProposed 13 ∆: 1msec∆푡 m 퐿 2 -4 -4 ∗ 10 ∗ ∆푡 2m 퐿 10 ∆푡 2m 퐿 ∗ -25−25 ∗ -20−20∆푡 1m -15− 퐿15 12 − -1010 −5 -5 -25−25 -20 − 20 ∆푡 1m − -15 퐿15 12 − -1010 −5 -5 ∗ ∆푡 m ∆푡 m SNR(dB) SNR(dB) ∆푡 2m ∆푡 2m ∆푡 1m (c) ∆푡 1m ( d ) −25 −20 −15 −10 −5 −25 −20 −15 −10 −5 Figure 6. Bit Error Rate (BER) in Additive White Gaussian Noise (AWGN) chirp-rate (); (a) 0 Hz/s, (b) 1 kHz/s, (c) 2.5 (kHz/s,c) (d) 5 kHz/s. (d)

Figure 6. BitFigure ErrorIn Figure Rate6. Bit (BER)Error 6a, Ratefor in Additive the(BER 0) inkHz WhiteAdditive chirp Gaussian Whiterate wh Gaussian Noiseistle, (AWGN)the Noise BER (AWGN chirp-rate of the) chirpconventional (a);-rate (a) ( 0푎); Hz/s, (a TFSK) 0 (b) 1 kHz/s, (c) 2.5 kHz/s,methodHz (d)/s 5, kHz/s.(b did) 1 kHz not/s decrease, (c) 2.5 kHz lower/s, (d )than 5 kHz 0.05/s. , whereas that of the proposed scheme with a good correlation sequence (Kasami) decreases regardless of any ∆. In Figure 6b, for the 1 kHz Inchirp Figure rate whistle, 6aIn, for Figure the the 06conventional a, kHz for chirp the 0 rate kHzTFSK whistle, chirp in Ref. rate the[13] whistle, BERshowed of the the the BER conventionalpoor of BER the perfor- conventional TFSK TFSK mancemethod for didthe methodnotsmaller decrease did∆ thannot lower decrease 5 ms than because lower . , thanthewhereas minimum0.05 ,that whereas of∆ the was that proposed calculated of the proposed scheme as 5 ms schemewith by a with a good Equationgood correlation (6). Incorrelation Figure sequence 6c, sequencefor (Kasami) the 2.5 (Kasami) kHz decreases chirp decreases rate regardless whistle, regardless ofthe any conventional of∆푡 any. In ∆Figuret. InTFSK Figure 6b in, for Ref.6 b,the for the 1 kHz [13]1 kHz also chirp showed ratechirp poorwhistle, rate BER whistle, the performance conventional the conventional with TFSK 1 ms TFSK in Ref.of in∆ [13] Ref., which showed [13] showedwas the smaller poor the poor BERthan BER perfor-2 ms performance for thatmance was forthe theminimumthe smaller smaller ∆∆푡 ∆ calculatedtthanthan 5 5 m mss by because because Equation the the (6).minimum minimum However, ∆푡t thewaswas BERs calculatedcalculated of the proposedasas 55 msms byby Equation (6). schemeEquation were (6). notIn In FigureFigureaffected6 6cc, for,for for all thethe ∆ 2.5. ThiskHz resultchirp chirp rateproved rate whistle, whistle, that the the conventionalBER conventional performance TFSK TFSK of in the inRef. Ref. [ 13] also showed poor BER performance with 1 ms of ∆t, which was smaller than 2 ms that was the conventional[13] also showed TFSK poorin Ref. BER [13] performance depended on with both 1 thems chirpof ∆푡 rate, which and was∆, whereassmaller thanthe pro- 2 ms minimum ∆t calculated by Equation (6). However, the BERs of the proposed scheme were posedthat was method the minimum kept on the ∆푡 good calculated BER performa by Equationnce for(6). anyHowever, whistle the pattern. BERs of In the Figure proposed 6a– not affected for all ∆ts. This result proved that the BER performance of the conventional d,scheme when were was not 20, affectedthe BER for performance all ∆푡푠. This of resultthe proposed proved thatmethod the BERwas performancegood and similar of the TFSK in Ref. [13] depended on both the chirp rate and ∆t, whereas the proposed method toconventional that of the larger TFSK ins. Ref. [13] depended on both the chirp rate and ∆푡, whereas the proposed methodkept kept on on the the good good BER BER performance performance for anyfor any whistle whistle pattern. pattern. In Figure In Figure6a–d, 6 whena– L was 20, the BER performance of the proposed method was good and similar to that of the larger Ls. 4.2.d, Communicationwhen 퐿 was 20, Performance the BER performance Assessment of the proposed method was good and similar to that of the larger 퐿s. In this subsection,4.2. Communication the DoM experiments Performance were Assessment conducted by the proposed assessment procedures of the modulated whistles in Section 3. The 1st step of the proposed assess- 4.2. CommunicationIn Performance this subsection, Assessment the DoM experiments were conducted by the proposed assessment ment was to findprocedures that of provides the modulated unrecognizable whistles in mimicking Section3. The and 1st determined step of the proposedthe se- assessment In this subsection, the DoM experiments were conducted by the proposed assessment quence length was. In to the ﬁnd 2ndL step,that the provides assessment unrecognizable was executed mimicking for the DoM and with determined the con- the sequence procedures of the modulatedc whistles in Section 3. The 1st step of the proposed assess- secutive long-termlength whistlesL. In the based 2nd on step, the the obtained assessment . was executed for the DoM with the consecutive ment was to find 퐿 that provides unrecognizable mimicking and determined the se- For the 1stlong-term step DoM푐 whistles assessment, based various on the obtained whistles Lwere. chosen from three species, quence length 퐿. In the 2nd step, the assessment was executed for the DoM with the con- i.e., White-sided dolphin,For the Delphinus 1st step DoM delphi assessment, dolphin, variousKiller dolphin, whistles from were the chosen Watkins from ma- three species, i.e., secutive long-term whistles based on the obtained 퐿. rine mammal White-sideddatabase [31]. dolphin, Three Delphinuswhistles per delphi species dolphin, were Killerchosen dolphin, [31]. The from whistle the Watkins marine For the 1st step DoM assessment, various whistles were chosen from three species, lengths of White-sidedmammal dolphin, database Delphinus [31]. Three delph whistlesi dolphin, per species and Killer were chosendolphin [31 were]. The about whistle lengths of i.e., White-sided dolphin, Delphinus delphi dolphin, Killer dolphin, from the Watkins ma- 0.3, 0.4, and 1.3White-sided s, respectively. dolphin, The Delphinusspectrograms delphi of the dolphin, selected and whistles Killer dolphinare shown were in about 0.3, 0.4, rine mammal database [31]. Three whistles per species were chosen [31]. The whistle Figure 7. and 1.3 s, respectively. The spectrograms of the selected whistles are shown in Figure7. lengths of White-sided dolphin, Delphinus delphi dolphin, and Killer dolphin were about 0.3, 0.4, and 1.3 s, respectively. The spectrograms of the selected whistles are shown in Figure 7.

(a) (b) (c)

Figure 7. Cont. (a) (b) (c)

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(d) (e) (f)

(g) (h) (i) Figure 7. Mean Opinion Score (MOS) test whistle of white sided dolphin of (a) flat, (b) moderate Figure 7. Mean Opinion Score (MOS) test whistle of white sided dolphin of (a) flat, (b) moderate variation, (c) dramatic variation, (c) dramatic variation; Delphinus delphis of (d) flat, (e) moderate variation, (f) dramatic variation; Delphinus delphis of (d) flat, (e) moderate variation, (f) dramatic variation; Killer whale of (g) flat, (h) moderate variation; Killer whale of (g) flat, (h) moderate variation, and (i) dramatic variation. variation, and (i) dramatic variation. For the 1st stepFor DoM the assessment, 1st step DoM the assessment, sequences thewith sequences of 20,with 60, 100,Ls ofand 20, 120 60, were 100, and 120 were multiplied to multipliedthe whistles to for the the whistles modulation. for the A modulation. set of assessment A set of whistles assessment consisted whistles of consisted of one of the originalone of dolphin the original whistles dolphin in Figure whistles 7 and in Figurefour biomimetic7 and four whistles biomimetic that whistleswere that were modulated frommodulated the real fromdolphin the realwhistles dolphin with whistles four withs. Noises four Lweres. Noises added were to the added real- to the real- and and the modulated-whistlesthe modulated-whistles with 10 and with 20 10 dB and of SNRs 20 dB ofto SNRsanalyze to the analyze noise the effects noise to effects the to the DoM DoM assessments.assessments. The number The of number listeners of was listeners 30. The was ages 30. of The the ages listeners of the were listeners from were10 from 10 to to 60 s, and the60 age s, and of thelisteners age of are listeners uniforml arey uniformly distributed. distributed. The 1st step The DoM 1st step assessment DoM assessment was was conductedconducted in Table 1. in The Table listeners1. The graded listeners the graded similarity the similarity to the real to dolphin the real whistles dolphin whistles by by Table 4. Table4.

Table 4. MOS gradesTable 4.forMOS the 1st grades step forDoM the assessment. 1st step DoM assessment.

1 12 23 34 45 5 Different SlightlyDifferent differentSlightly different Similar Similar Very similar Very similar same same

For the assessment test, Terratec D/A convertor and AKG-K52 headphone were utilized. The assessmentFor results the assessment are shown test, in Table Terratec 5. D/A convertor and AKG-K52 headphone were utilized. The assessment results are shown in Table5. Table 5. Results of the 1st step DoM assessment. Table 5. Results of the 1st step DoM assessment. Sequence Length () Species Noise Real Dolphin Sequence Length (L) Species Noise Real Dolphin20 60 100 120 10 dB 4.7 3.8 3.220 3.1 60 3.2 100 120 Killer 10 dB 4.7 3.8 3.2 3.1 3.2 Killer 20 dB 4.8 3.9 3.0 2.9 3.1 20 dB 4.8 3.9 3.0 2.9 3.1 10 dB 4.1 4.3 4.3 4.2 4.3 Delphinus delphis 10 dB 4.1 4.3 4.3 4.2 4.3 Delphinus delphis20 dB 4.2 4.3 4.0 4.1 4.1 20 dB 4.2 4.3 4.0 4.1 4.1 10 dB 4.2 4.1 4.1 4.2 4.1 Whistle sided 10 dB 4.2 4.1 4.1 4.2 4.1 Whistle sided20 dB 4.4 4.2 4.2 4.2 4.2 20 dB 4.4 4.2 4.2 4.2 4.2

In Table 5, as the SNR decreased, the average MOS of the modulated whistles increased. This is because the background noise hindered distinguishing the difference between the modulated- and the original-whistles. The MOSs of real Delphinus delphis and White-sided dolphin for all sequence lengths were approximately 4.2. As a result of the

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In Table5, as the SNR decreased, the average MOS of the modulated whistles increased. 1st step assessment,This the is because human the does background not reco noisegnize hindered the difference distinguishing between the difference real whistle between the modulated- and the original-whistles. The MOSs of real Delphinus delphis and White- and whistle multiplied with the sequence length of 120. Thus, the maximum sequence sided dolphin for all sequence lengths were approximately 4.2. As a result of the 1st length for Delphinusstep delphi assessment,s and the White-sided human does is not 120, recognize and the the spreading difference betweenbandwidth real whistle() and was calculated aswhistle 300 Hz multiplied using Equation with the sequence(9). The lengthMOS ofscore 120. Thus,of a real the maximumkiller whale sequence was length higher than whistlesfor Delphinusmultiplied delphis with the and sequence. White-sided If we is 120, used and a thesmaller spreading sequence bandwidth length, (B c) was the MOS score of sequencecalculated asmultiplied 300 Hz using whistle Equation increased. (9). The In MOS this score paper, of a Delphinus real killer whale delphis was higher was selected as a thanmimetic whistles model multiplied because with the the MOSs sequence. of Delphinus If we used delphis’s a smaller sequencereal whistle length, the MOS score of sequence multiplied whistle increased. In this paper, Delphinus delphis was and sequence multipliedselected aswhistle a mimetic were model the becausesame. Based the MOSs on ofthis Delphinus assessment, delphis’s the real largest whistle and length of the sequencesequence by multipliedthe 1st step whistle DoM were assessment the same. Based was onselected this assessment, as 120 and the largest was length of chosen as 300 Hz. the sequence by the 1st step DoM assessment was selected as 120 and Bc was chosen as The 2nd step 300DoM Hz. assessment was conducted using the result of the 1st step. For the 2nd step DoM assessment,The 2nd eight step Delphinus DoM assessment delphis was dolphin conducted whistles using thewere result modulated of the 1st by step. For the 2nd step DoM assessment, eight Delphinus delphis dolphin whistles were modulated TFSK and each whistle was multiplied by the sequence that has 300 Hz of . The spec- by TFSK and each whistle was multiplied by the sequence that has 300 Hz of Bc. The trograms of the modulatedspectrograms whistles of the modulated are shown whistles in Figure are shown 8. in Figure8.

(a) (b) (c) (d)

(e) (f) (g) (h)

FigureFigure 8. Whistle 8. Whistle for the for 2nd the step 2nd DoM step assessment DoM assessment (a) moderate (a) moderate change, (b )change, moderate (b) change, moderate (c) dramatic change, change,(c) (d) dramaticdramatic change, change, (e) ﬂat, (d) (dramaticf) ﬂat, (g) dramatic change, change, (e) flat, (h (f)) moderate flat, (g) change.dramatic change, (h) moderate change.

Two consecutive Twolong-term consecutive whistle long-term signals whistle with signalsa 10-s withduration a 10-s were duration made: were the made: first the first signal consisted of eight whistles in Figure8. The second one was composed of two signal consisted ofwhistles eight whistles in Figure in8c,g. Figure The first 8. The and second the second one signals was composed were utilized of two for the whis- MOS tests tles in Figure 8c,g.of The the first proposed and the method second and signals the conventional were utilized method, for respectively. the MOS tests For of the the fair MOS proposed methodcomparison and the conventional tests, the BERs method, of the two respectively. methods needed For to the be thefair same. MOS Since compari-∆t was set as son tests, the BERs5 ms,of the the two whistles meth thatods satisfied needed the to∆ tbein Equationthe same. (6) Since were (c)∆ and was (g) set in Figureas 5 ms,8. the whistles that satisfiedThe testthe sets∆ in consisted Equation ofthe (6) twowere generated (c) and whistles(g) in Figure and a 8. 10-s long real dolphin The test sets whistle.consisted Listeners of the graded two generated how close thewhistles test set and sounds a 10-s were long to the real real dolphin whistle sound by Table3. The listeners and equipment used in the 2nd assessment were the same whistle. Listeners asgraded in the firsthow experiment. close the Thetest 2ndset assessmentsounds were results to arethe shown real dolphin in Table6 .whistle sound by Table 3. The listeners and equipment used in the 2nd assessment were the same as in the first experiment. The 2nd assessment results are shown in Table 6.

Table 6. Average MOS result for the 2nd assessment.

Real Dolphin Proposed Method Conventional Method (Ref. [13]) 3.72 3.81 2.81

In Table 6, the MOS of the proposed method was 3.81, and the MOS of the real dolphin was 3.72. This result meant humans were unable to distinguish the modulated whistles by the proposed method from the real dolphin whistles. However, the MOS of the conventional method in Ref. [13] was 2.81, which was lower than that of the real dolphin whistles. In other words, humans recognized the modulated whistles by the conventional

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Table 6. Average MOS result for the 2nd assessment.

Real Dolphin Proposed Method Conventional Method (Ref. [13]) 3.72 3.81 2.81

Sensors 2021, 21, x FOR PEER REVIEW 14 of 19 In Table6, the MOS of the proposed method was 3.81, and the MOS of the real dolphin was 3.72. This result meant humans were unable to distinguish the modulated whistles by the proposed method from the real dolphin whistles. However, the MOS of the one.conventional This was methodbecause inrepeatedly Ref. [13] wastransmitted 2.81, which whistles was lowerenabled than humans that of to the recognize real dolphin the dwhistles.ifference Inbetween other words, the artificial humans whistles recognized and the the real modulated ones. whistles by the conventional one.The This MOS was becausetest demonstrated repeatedly that transmitted humans whistlescould not enabled distinguish humans the tolong recognize-term con- the secutivedifference whistles between by thethe artificialproposed whistles method and from the the real real ones. dolphin whistle sound. Therefore, the proposedThe MOS method test demonstrated achieved the that large humans DoM couldthat was not one distinguish of two goals, the long-term i.e., large consec- DoM andutive low whistles BER, of by the the covert proposed communications. method from the In realthe dolphinnext section, whistle the sound. other goal, Therefore, i.e., low the BER,proposed is demonstrated method achieved through the the large computer DoM that simulation was one with of two the goals, UWA i.e., channels large DoM and andthe practicallow BER, lake of the and covert ocean communications. experiments. In the next section, the other goal, i.e., low BER, is demonstrated through the computer simulation with the UWA channels and the practical 5.lake Simulations and ocean and experiments. Experiments The BER comparison of the proposed method and the conventional one was executed 5. Simulations and Experiments by the simulation and practical lake and ocean experiments. For the fair BER comparisons, the DoMsTheBER of the comparison two methods of the needed proposed to be method the same, and and the all conventional whistles inone Figure was 8 executed needed by the simulation and practical lake and ocean experiments. For the fair BER comparisons, to be utilized. The TFSK modulation parameters of 푀 and 푁 were four each and 퐵푐 was the DoMs of the two methods needed to be the same, and all whistles in Figure8 needed chosen as 300 Hz as in Section 4. Since the shortest whistle time in Figure 8 was measured to be utilized. The TFSK modulation parameters of M and N were four each and B was by 0.13 s, the minimum sequence length was set as 39 by Equation (9) and the Kasamic chosen as 300 Hz as in Section4. Since the shortest whistle time in Figure8 was measured sequence with the length of 39 was used for the proposed method. When the sequence by 0.13 s, the minimum sequence length was set as 39 by Equation (9) and the Kasami length was 39, ∆푡 was chosen as 5 ms and ∆푓 was set to 600 Hz by Equation (10). The sequence with the length of 39 was used for the proposed method. When the sequence modulation parameters of 푀, 푁, ∆푡, and ∆푓 were the same for the proposed method and length was 39, ∆t was chosen as 5 ms and ∆ f was set to 600 Hz by Equation (10). The the conventional one. modulation parameters of M, N, ∆t, and ∆ f were the same for the proposed method and the conventional one. 5.1. Simulation Experiments 5.1. SimulationThe UWA Experimentsenvironments were modeled from a point of Taean in the West Sea of S. Korea,The and UWA the UWA environments channel was were modeled modeled by from Bellhop a point based of Taeanon the in environments. the West Sea The of S. dopplerKorea, andspread the UWAwas set channel as 2 Hz, was which modeled was bymeasured Bellhop at based the same on the location environments. [32,33]. The The delaydoppler profile spread and was sound set v aselocity 2 Hz, p whichrofile (SVP) was measured of the UWA at the channel same locationare shown [32 in,33 Figure]. The 9.delay profile and sound velocity profile (SVP) of the UWA channel are shown in Figure9.

(a) (b) (a) (b)

FigureFigure 9. 9. SimulationSimulation channel channel ( (aa)) delay delay profile, proﬁle, ( (bb)) s soundound v velocityelocity p proﬁlerofile (SVP). (SVP).

TheThe BER BER obtained obtained by by the the UWA UWA channel channel in Figure 99 isis shownshown inin FigureFigure 10 10..

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Proposed ∆: 5msec ∆푡 m Ref[13] ∆: 5msec ∗∗ ∆푡 m

−−2020 −−1515 −−1010 −−55 0

Figure 10. BER result in Under Water Acoustic (UWA) channel. FigureFigure 10. 10. BERBER result result in in Under Under Water Water Acoustic ( (UWA)UWA) channel. In Figure 10, the red- and green-line denote the BERs of the proposed- and the con- InIn Fig Figureure 10, 10 ,the the red red-- and and green green-line-line denote denote the theBERs BERs of the of proposed the proposed-- and the and con- the ventional-methods, respectively. When the conventional TFSK signals passed through the ventionalconventional-methods,-methods, respectively. respectively. When When the conventional the conventional TFSK TFSK signals signals passed passed through through the multipath channels, the time spreading occurred, which caused the detection ambiguity multipaththe multipath channels, channels, the thetime time spreading spreading occurred, occurred, which which caused caused the the detection detection ambiguity ambiguity for the zero-chirp rate whistles. Thus, the BER of the conventional method had an error forfor the the ze zero-chirpro-chirp rate rate whistles. whistles. Thus, Thus, the the BER BER of of the the conventional conventional method method had had an an error error floor at 10−2, even though the SNR is large, e.g., SNR > −10 dB. However, the BER of the floorfloor at at 10 −2,2 ,even even though though the the SNR SNR is is large, large, e.g., e.g., SNR SNR > > −−1010 d dB.B. However, However, the the BER BER of of the proposed method did not have the error floor at ∆ of 5 ms which satisfies the orthogo- proposedproposed method diddid notnot havehave the the error error floor floor at at∆ t∆of푡 5of ms 5 ms which which satisfies satisfies the orthogonalitythe orthogo- −4 nalitynarequirementlity requirement requirement by Equation by by Equation Equation (7) and (7) (7) and showed and showed showed less less than less than 10than− 410 10at−4 aat at− a 5a − dB−55 dB dB SNR, SNR, SNR, which which which was was was an ananacceptable acceptable acceptable value value value for for for the the the practical practical practical communications. communications. communications.

5.2.5.2.5.2. Lake Lake Lake and and and Ocean Ocean Ocean Experiments Experiments Experiments TheTheThe lake lake and and ocean oceanocean experiments experimentsexperiments were were conductedconducted conducted toto to verify verify verify the the the BER BER BER performance performance performance of of theof thetheproposed proposed proposed method method method and and and the the conventionalthe conventional conventional one. on one. Thee. The The communication communication communication parameters parameters parameters in thein in the lakethe lakelakeand and and ocean ocean ocean experiment experiment experiment were were were the thesame the sa sameme as inas as the in in thecomputer the computer computer simulations. simulations. simulations. TheTheThe lake lake lake experiments experiments experiments were were were executed executed executed at at at Lake Lake Lake Kyungchun Kyungchun Kyungchun on on on 13 13 13 May May May 2020. 2020 2020. .The The The trans- trans- trans- mittermittermitter was was was deployed deployed deployed at at at a a adepth depth depth of of of 10 10 10 m m m from from the the surface, surface, and and a a Neptune-D17BB Neptune Neptune-D17BB-D17BB with with a a frequencyfrequencyfrequency band band band from from from 12.5 12.5 12.5 to to to 19.5 19.5 19.5 kHz kHz kHz was was was us used. used.ed. Since Since Since the the the available available available frequency frequency frequency band band band of of of the the the transmittertransmittertransmitter was was was greater greater greater than than than that that that of of of the the the real real real dolphin dolphin dolphin whistles, whistles, whistles, the the the real real real dolphin dolphin whistles whistles whistles werewerewere shifted shifted up up up to to thethe the availableavailable available frequency frequency frequency band band band of theof of the transmitter. the transmitter. transmitter. Note Note Note that thethat that frequency- the the fre- fre- quency-shiftedquencyshifted- whistleshifted whistle whistle patterns patterns patterns were the were were same the the as same thesame real as as the dolphinthe real real dolphin whistledolphin ones.whistle whistle TC4032 ones. ones. wasTC4032 TC4032 used waswasfor used theused hydrophone for for the the hydrophone hydrophone at a 25 m at depth.at a a 25 25 m Them depth. depth. distance The The distance betweendistance between transmitterbetween transmitter transmitter and receiver and and wasre- re- ceiverceiver200 m. was was In 200 Figure200 m. m. In 11In Figure ,Figure the location, 11, 11, the the location conﬁgurations,location,, configurations, configurations, measured measur measured delayed proﬁle, delay delay profile, andprofile doppler ,and and spread were displayed. dopplerdoppler spread spread were were displayed. displayed.

Distance 200m

Source Depth 10m Hydrophone Tx Depth 25m Depth 51m

(a(a) ) (b(b) ) Figure 11. Cont.

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FigureFigure 11. Lake 11. LakeexperimentsFigure experiments 11. environmentsLake environments experiments (a) Location, (a environments) Location, (b) Configuration, (b) (Configuration,a) Location, (c) (delayb ()c Conﬁguration,) delay profile, profile, and and (c) delay proﬁle, and doppler spread. doppler spread. doppler spread.

In FigureIn Figure 11c, the11c, rmsIn the Figure delayrms delay and11c, theand the dopple the rms dopple delayr spreadr andspread were the were dopplermeasured measured spread as 100 as were ms,100 2ms, measuredHz, 2 Hz, as 100 ms, respectively.respectively. 2 Hz, respectively. The oceanThe ocean experiments experimentsThe ocean were were experimentsperformed performed on were 13 on September performed 13 September 2020. on 13 2020. The September experimentThe experiment 2020. spot The spot experiment spot was was7 km 7 farkm away far wasaway from 7 from km the far coast the away coast of Sinjin from of Sinjin thedo, coastTaean-gun,do, Taean-gun, of Sinjindo, S. Korea. S. Taean-gun, Korea. The equipmentThe S. equipment Korea. used The used equipment used in thein oceanthe ocean experiments experimentsin the ocean was was experimentsthe samethe same as in was as the in the lakethe same lakeexperiments. as experiments. in the lake The experiments.Thetransmitter transmitter was The was transmitter was deployeddeployed at a depthat adeployed depth of 5 mof from5 at m a from depththe sea the of level, sea 5 mlevel, Two-channels from Two-channels the sea level,of TC4032 of Two-channels TC4032 were were used ofused for TC4032 the for the were used for receiverreceiver at 5 mat and5 mthe 7and m receiver depths.7 m depths. at The 5 m distanceThe and distance 7 m between depths. between transmitter The transmitter distance and between receiverand receiver transmitter was was1 km. 1 andkm. receiver was FigureFigure 12 from 12 from (a)1 to km.(a) (e) to Figureshowed (e) showed 12 the from experiment the (a) experiment to (e) location, showed location, thethe experimentconfigurations the configurations location, of the of theexper- the conﬁgurations exper- of the iments,iments, SVP, SVP, and theandexperiments, estimated the estimated SVP,delay delay and profile the profile estimatedand dopplerand doppler delay spread, proﬁle spread, respectively. and respectively. doppler spread, respectively.

(a) (a) (b) (b) (c) (c)

(d) (d) (e) (e)

Figure 12.FigureOceanFigure 12. experimentsOcean 12. Ocean experiments experiments environments:( environments:( environments:(a) Location,a) Location,a ()b Location,) Conﬁguration, (b) Configuration, (b) Configuration, (c) SVP, (c) Delay SVP, (c) SVP,Delay proﬁle Delay profile and profile doppler spread: (d) 12:30and p.m., dopplerand (e) doppler 5:44 spread: p.m. spread: (d) 12:30 (d) 12:30 p.m., p.m., (e) 5:44 (e) p.m.5:44 p.m.

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InIn Figure Figure 12d,e, 12d,e, the the estimated estimated delay delay pro proﬁlesfiles and and the the doppler doppler spread spread were were demon- demon- stratedstrated at at 12:30 12:30 p.m. p.m. and and 5:44 5:44 p.m., p.m., respectively. respectively. The The same same doppler doppler spread spread were were calculated calculated asas 2 2Hz Hz for for two two cases. cases. Even Even though though the the parameters parameters were were measured measured at at the the same same location, location, thesethese UWA UWA channels channels were were different different be becausecause of of the the large large tide tide difference. difference. FigureFigure 13 13 exhibited exhibited the the examples examples of of the the re receivedceived signals signals of of the the lake lake and and the the ocean ocean experiments.experiments. The The number number of transmittedtransmitted bits bits for for the the lake lake and and ocean ocean experiments experiments were were 4000 4000and and 10,000, 10,000, respectively. respectively.

Frequency (kHz) 12 25 26 27 28 29 30 Time (sec) (a)

(b)

FigureFigure 13. 13. ExperimentsExperiments received received signals: signals: (a ()a )Ocean, Ocean, (b (b) )Lake. Lake.

TheThe BERs BERs obtained obtained from from the the lake lake and and the the ocean ocean experiments experiments were were shown shown in in TableTable 7.7 . TheThe proposed proposed method method demonstrated demonstrated a azero-error zero-error rate rate for for two two experiments, experiments, whereas whereas the the conventionalconventional method method exhibited exhibited 0.14 0.14 and and 0.24 0.24 for forthe thelake lake and and the ocean the ocean experiments, experiments, respectively.respectively. In Inocean ocean experiments, experiments, the the SNR SNR of ofthe the received received signal signal was was estimated estimated as as −−6 6dB. dB. SinceSince the the zero zero error error among among 10,000 10,000 bits bits was was found, found, the the BER BER was was expected expected to to less less than 10 −4,4 , whichwhich was was well well matched matched with with th thee BER BER by by the the computer computer simulation simulation results results in in FigureFigure 10. 10 . However,However, at at the the same same SNR, SNR, the the BER BER of of the the co conventionalnventional method method was was 0.24 0.24 which which was was large large andand was was not not acceptable acceptable to to practical practical communications. communications.

TableTable 7. 7. BERBER results results of of the the lake lake and and the the ocean ocean experiments. experiments.

LocationLocation Demodulation Demodulation Scheme Scheme BER ProposedProposed method method 0.00 LakeLake ConventionalConventional method method (Ref. (Ref. [13]) [13 ]) 0.14 ProposedProposed method method 0.00 OceanOcean ConventionalConventional method method (Ref. (Ref. [13]) [13 ]) 0.24

6.6. Conclusions Conclusions ThisThis paper paper proposes proposes a biomimicking modulationmodulation method method with with the the large large DoM DoM and and the thelow low BER. BER. The The proposed proposed method method utilizes utilizes the sequencethe sequence with with a large a large correlation correlation characteristic charac- teristicto enhance to enhance the conventional the conventional TFSK and TFSK develops and develops the ML the detector ML detector for the transmittedfor the transmit- signal tedand signal derives and the derives orthogonality the orthogonality requirements requirements for the time- for andthe time- frequency-shift and frequency-shift units. The units.proposed The proposed method also method develops also develops a two-step a two-step MOS assessment MOS assessment for evaluating for evaluating the DoM the for DoMthe long-termfor the long-term whistle whistle signal. Thesignal. 1st The step 1st assessment step assessment determines determines the minimum the minimum length lengthof the of sequence the sequence and theand 2nd the step2nd step conﬁrms confirms the selectedthe selected length length of the of the sequence sequence for for the consecutive long-term whistles. By the assessments, the fact that the modulated whistles by

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the proposed scheme cannot be distinguished from that by the real dolphin sound is shown. Computer simulations demonstrate that the BER performance of the proposed method is better than that of the conventional one, and the practical lake and ocean experiments demonstrate zero error when 4000 bits and 10,000 bits were transmitted, respectively.

Author Contributions: Conceptualization, J.A.; Data curation, J.A, H.L. and Y.K.; Formal analysis, J.A. and H.L.; Funding acquisition, W.K.; Methodology, J.A.; Project administration, J.A. and J.C.; Resources, J.A.; Software, J.A.; Supervision, J.C.; Validation, J.A.; Visualization, J.A.; Writing—original draft, J.A.; Writing—review & editing, J.A., W.K. and J.C. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Agency for Defense Development, South Korea, under Grant UD200010DD. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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