Intense L-Band Solar Radio Bursts Detection Based on GNSS Carrier-To-Noise Ratio Decrease Over Multi-Satellite and Multi-Station

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Article Intense L-Band Solar Radio Bursts Detection Based on GNSS Carrier-To-Noise Ratio Decrease over Multi-Satellite and Multi-Station

Fan Yang , Xuefen Zhu *, Xiyuan Chen and Mengying Lin

School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China; [email protected] (F.Y.); [email protected] (X.C.); [email protected] (M.L.) * Correspondence: [email protected]

Abstract: Intense solar radio bursts (SRBs) can increase the energy noise and positioning error of the bandwidth of global navigation satellite system (GNSS). The study of the interference from intense L-band SRBs is of great importance to the steady operation of GNSS receivers. Based on the fact

that intense L-band SRBs lead to a decrease in the carrier-to-noise ratio (C/N0) of multiple GNSS satellites over a large area of the sunlit hemisphere, an intense L-band SRB detection method without the aid of a radio telescope is proposed. Firstly, the valley period of a single satellite at a single monitoring station is detected. Then, the detection of SRBs is achieved by calculating the intersection of multiple satellites and multiple stations. The experimental results indicate that the detection rates of GPS L2 and GLONASS G2 are better than those of GPS L1 L5, GLONASS G1, and Galileo E1 E5. The detection rate of SRBs can reach 80% with a ﬂux density above 800 solar ﬂux unit (SFU) at the L2 frequency of GPS. Overall, the detection rate is not affected by the satellite distribution relative to the Sun. The proposed detection method is low-cost and has a high detection rate and low false Citation: Yang, F.; Zhu, X.; Chen, X.; alarm rate. This method is a noteworthy reference for coping with interference in GNSS from intense Lin, M. Intense L-Band Solar Radio Bursts Detection Based on GNSS L-band SRBs. Carrier-To-Noise Ratio Decrease over Multi-Satellite and Multi-Station. Keywords: global navigation satellite system; solar radio bursts; carrier-to-noise ratio; detection rate Sensors 2021, 21, 1405. https:// doi.org/10.3390/s21041405

Academic Editor: Jaume 1. Introduction Sanz Subirana Global navigation satellite system (GNSS) is currently widely used in both military and civilian fields [1,2]. It is extremely important to keep this system free of interference. Received: 6 January 2021 Types of interference with GNSS include multipath [3,4], ionospheric scintillation [5], Accepted: 12 February 2021 spoofing [6,7], electromagnetic interference, satellite signal anomalies, and intense L-band Published: 17 February 2021 solar radio bursts (SRBs) [8]. SRB is a strong signal in the microwave band from solar plasma radiation and cyclotron synchrotron radiation. The entire radiation bandwidth Publisher’s Note: MDPI stays neutral extends from the millimeter to the kilometer wave band. L-band SRB (1415 MHz) interferes with regard to jurisdictional claims in with the GNSS signal most significantly due to the fact that it is close to GNSS frequencies, published maps and institutional affil- such as GPS (L1: 1575.42 MHz, L2: 1227.60 MHz, L5: 1176.45 MHz), GLONASS (G1: 1602 iations. MHz, G2: 1246 MHz) and Galileo (E1: 1575.42 MHz, E5: 1191.795 MHz). Strong radio noise can cause the carrier-to-noise ratio (C/N0) of a GNSS receiver to decrease, which directly affects the tracking and acquisition of the GNSS signal. In worse interference cases, cycle slip, loss of lock, interruption and other phenomena may occur [9]. Copyright: © 2021 by the authors. Researchers have studied the impact of SRB on GNSS since 2005. Chen et al. [10] Licensee MDPI, Basel, Switzerland. analyzed the phenomenon of GPS loss of lock due to a SRB event on 28 October 2003. This article is an open access article They pointed out that the flux density threshold of the solar radio bursts affecting GPS distributed under the terms and signals is between 4000 and 12,000 solar flux unit (SFU). Cerruti et al. [11] analyzed the conditions of the Creative Commons effects of several SRB events in December 2006 on the C/N of GPS and found a strong Attribution (CC BY) license (https:// 0 C N creativecommons.org/licenses/by/ correlation between / 0 and solar radio emission power. Through theoretical analysis, 4.0/). Demyanov et al. [12] found that SRBs with emission power of 1000 SFU or higher may

Sensors 2021, 21, 1405. https://doi.org/10.3390/s21041405 https://www.mdpi.com/journal/sensors Sensors 2021, 21, 1405 2 of 18

lead to GPS or GLONASS tracking faults. The effect is especially prevalent at the L2 frequency, which is lower than the threshold proposed by Chen et al. [10]. Yue et al. [13] analyzed the influence of SRBs on GPS C/N0 and concluded that the threshold value of solar radio burst effects on GNSS is approximately 1807 SFU. Sreeja et al. [14,15] studied the impact of the SRB event on 24 September 2011 on a single-point precise positioning service and the performance of GNSS receivers. Subsequently, Muhammad et al. [16] studied the event with higher sampling GPS data and evaluated the impact of SRBs on GPS signal characteristics, including the signal-to-noise ratio, loss of lock, and phase tracking. The study of [17] shows that SRBs are not limited to the vicinity of sunspot maxima. Huang et al. [18] specifically analyzed the influence of a SRB event on 13 December 2006 on GNSS performance and positioning error in several regions in China. The effects of the SRB event on 6 September 2017 on GNSS signals and the corresponding response of the ionosphere were studied in [19–22]. Recently, a number of automatic detection and classification methods for SRBs have been proposed. Ma et al. [23] proposed a multimodal deep learning method for SRB classification. An autoencoder (AE) together with structured regularization was used to enforce and learn the modality-specific sparsity and density of each modality. The proposed network can effectively learn the representation of the solar radio spectrum. Sub- sequently, Chen et al. [24] utilized a convolutional neural network (CNN) for the classification of solar radio spectra and obtained better experimental results than Ma et al. [23]. Zhang et al. [25,26] designed an event recognition-analysis system that can automatically detect solar type III radio bursts and mine burst information from the dynamic spectra observed by the Nancay Decameter Array (NDA). Singh et al. [8] proposed an automated method to detect SRBs. Although the method does not classify the types of radio bursts, it is able to discriminate between dynamic spectra with and without SRBs. At present, although there have been some SRB automatic recognition algorithms, most of the methods utilize radio telescopes to obtain observation data and then classify SRBs according to the spectra. As radio telescopes are expensive and sparsely distributed, we urgently need a method to efficiently detect SRBs in real time without utilizing radio telescopes. Since 2005, many studies have focused on the impact of SRBs on GNSS receiver observation data. However, there is a lack of specific algorithms or experimental verification to detect SRBs using its impact on GNSS receiver observation data. Despite the impact of SRBs on GNSS cannot be completely eliminated, some measures can be taken to reduce or alleviate the interference caused by SRBs. Furthermore, real-time and accurate identification of SRBs is an essential prerequisite for suppressing the interference. In this paper, intense L-band SRB events are detected using the fact that SRBs lead to a decrease in the C/N0 of several GNSS satellites over a large area of the Earth’s surface. Other interference, such as ionospheric scintillation and multipath, may also cause a decrease in the C/N0, but this phenomenon does not simultaneously occur on multiple satellites over a large area of the sunlit hemisphere, which is a significant feature that distinguishes SRBs from other types of interference. During the detection process, the “falling moments” and “rising moments” are first selected to determine the valley period of a single satellite at a single monitoring station. Then, the detection of a single station is obtained by comparing multiple satellites over the station. Finally, the detection of intense L-band SRBs is calculated by comparing multiple stations. The proposed method, which does not rely on radio telescopes, has a high recognition rate and low false alarm rate, is low-cost, and offers all-weather real-time monitoring.

2. Effect of SRBS on GPS Receiver Noise Floor Solar ﬂares produce an increase in solar noise, which is measured in units of SFU, 10−22 W m−2 Hz−1, or −220 dBWHz−1. These SRBs are wideband noise, which increase the noise power of the receiver and result in a lower C/N0. Measuring the solar radio emission power at the GPS receiver antenna output is critical to the steady operation of the GPS system. Sensors 2021, 21, 1405 3 of 18

The antenna directive gain is deﬁned as the ratio between the power of the actual antenna P(β) and the power of the signal generated by the ideal radiation unit P0 at the same point in space under the conditions of equal input power. This parameter quantitatively describes the degree to which an antenna radiates the input power, which can be deﬁned as D(β) = P(β)/P0, (1) where β is the elevation angle of the GPS signal. Obviously, the directive gain is closely related to the elevation angle of the antenna. The gain is usually computed in units of dB and expressed as G(β) = 10 · lg(D(β)). There- sults [27] for the gain corresponding to different elevation angles are shown in Table1.

Table 1. Directive characteristics of a navigation receiver antenna.

◦ Elevation Angle, β G(β)in (dB) D(β)=P(β)/P0 0 < β < 5 −7.5 ≤ G(β) ≤ −5 0.1775 ≤ D(β) ≤ 0.316 5 < β < 15 −4.5 ≤ G(β) 0.354 ≤ D(β) β > 15 −2 ≤ G(β) 0.63 ≤ D(β)

A GPS antenna needs to be able to receive as many GPS signals as possible so that its gain is very low in all directions. Moreover, the reception cross-section of the GPS antenna is low, especially near the horizon. The antenna effective area is deﬁned as

4π · D(β) A (β) = , (2) e λ2 where λ is the wavelength of the received signal. The calculated results of the antenna effective area Ae(β) for different elevation angles at GPS frequency bands are shown in Table2.

Table 2. Antenna effective area.

2 Ae(β)in (m ) Elevation Angle, β◦ λ = 0.190 in (m)(L1) λ = 0.244 in (m)(L2) −4 −4 0 < β < 5 5.099 × 10 ≤ Ae(β) 8.409 × 10 ≤ Ae(β) ≤ 9.077 × 10−4 ≤ 1.497 × 10−3 −3 −3 5 < β < 15 1.01 × 10 ≤ Ae(β) 1.677 × 10 ≤ Ae(β) −3 −3 β > 15 1.809 × 10 ≤ Ae(β) 2.984 × 10 ≤ Ae(β)

The radio emissions of a solar ﬂare can be taken as Gaussian white noise for GPS signals. The solar radio emission intensity is constant within the bandwidth ∆Fn, so the radio emission power within the frequency bands of GPS signal can be calculated in a similar way and is deﬁned as Pn = ∆Fn · N0. (3) Therefore, without considering the polarization loss and atmospheric attenuation, the solar radio noise at the receiver antenna output can be expressed as [12]

Pn = ∆Fn · k · N0 · Ae(β), (4)

−22 −2 −1 where k is the rate of the solar radio emission flux in terms of SFU and N0 = −10 W m Hz . Finally, the solar radio noise power at the receiving antenna output for solar elevation ◦ angles > 15 at the central solar radio emission frequency f = 1415 MHz (we assumed −3 2 λ = 0.212 m, Ae = 2.253 × 10 m ) is calculated and shown in Table3[ 12]. Note that the solar radio noise is computed in units of dBW, and the front-end passband of the GPS receiver radio path (∆FGPS) is 3 MHz [27]. Sensors 2021, 21, x FOR PEER REVIEW 4 of 18

where k is the rate of the solar radio emission flux in terms of SFU and

−−−2221 N0 =−10W mHz . Finally, the solar radio noise power at the receiving antenna output for solar elevation angles 15 at the central solar radio emission frequency f =141 5 MH z (we as-

−32 sumed  =0 . 2 1 2 m , Ae =2 . 2 5 3 1 0 m ) is calculated and shown in Table 3 [12]. Note that the solar radio noise is computed in units of dBW, and the front-end passband of the GPS

receiver radio path ( FG P S ) is 3 MHz [27].

Table 3. Rate of the solar radio emission flux.

Sensors 2021, 21, 1405 4 of 18 LP=1 0 lg Rate of The Solar Radio Emission Flux (k), SFU nn( ) , dBW 1 102 103 104 105 106

05 Table 3. Rate of the− solar187.1 radio emission−167.1 ﬂux. −157.1 −147.1 −137.1 −127.1

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01:00 02:00 03:00 04:00 05:00 06:00 4 10 UTC Figure 2. Solar radio flux at 1415 MHz observed at station Sagamore Hill provided by radio solar telescopeSFU network (RSTN) during the intense L-band solar radio bursts (SRB) event that occurred 3 on 1013 December 2006. The sampling frequency was 1 Hz, and the burst period was mainly approximately 02:30, 03:30 and 04:00 (UTC).

10We2 select stations CEDU and ALIC in Australia as well as stations TWTF and KUNM

in China to analyze the influence of the SRB on the CN0 on 13 December 2006. The solar 01:00 02:00 03:00 04:00 05:00 06:00 elevation angles of the four stations were 80.7°,UTC 84.9°, 42.5° and 36.0°, respectively. Figure 3 shows the decrease in the of different satellites at each station for the GPS L1 fre- FigureFigurequency. 2. Solar 2. TheSolar radio data ﬂuxradio atwere 1415 flux MHzprovided at 1415 observed MHz by at stationthe observed International Sagamore at Hillstation provided GNSS Sagamore byService radio solarHill (IGS), telescopeprovided and network the by sam- radio (RSTN) solar during the intense L-band solar radio bursts (SRB) event that occurred on 13 December 2006. The sampling frequency was 1 telescopepling period network was 30(RSTN) s. Figure during 3 shows the intense that the L -band solarof each radio station bursts decreased (SRB) event to varying that occurred Hz, and the burst period was mainly approximately 02:30, 03:30 and 04:00 (UTC). ondegrees 13 December during 2006.the SRB. The sampling frequency was 1 Hz, and the burst period was mainly approximately 02:30, 03:30 and 04:00 (UTC). 60 60 G31G31 60 60 G25G25 40604060 G31G31 40606040 G25G25 20402040 20404020 02020We0 select stations CEDU and ALIC in Australia200 200 as well as stations TWTF and KUNM 60 0600 600 060 6060 6060 in 40China40 to analyze the influenceG27 ofG27 the SRB on40 40the CN0 on 13 December 2006.G20G20 The solar 20402040 G27G27 20404020 G20G20 elevation020200 angles of the four stations were 80.7°,200 20 084.9°, 42.5° and 36.0°, respectively. Figure

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C/N C/N 602020602020 C/N 20202020 60 60 6060 6060 400 400 00 G13G13 00 00 40 40 4040 4040 G13G13 206060206060 G13G13 60606060 20 20 G13G13 40202040 40 40 2020 0 40040 G03G03G03G03 4040 0 0 G11G11G11G11 00:00200202000:00200 01:0001:00 02:0002:00 03:0003:00 04:0004:00 05:0005:00 06:0006:00 20202020 00:000 000:00 01:0001:00 02:0002:00 03:0003:00 04:0004:00 05:0005:00 06:0006:00 000:00000:0000 01:0001:00 02:0002:00 UTC03:00UTC03:00 04:0004:00 05:0005:00 06:0006:00 00 00 00:0000:00 01:0001:00 02:0002:00 03:0003:00 04:0004:00 05:0005:00 06:0006:00 00:0000:0000:0000:00 01:0001:0001:0001:00 02:0002:0002:00 03:0003:00UTC03:00UTC 04:0004:00 04:0004:00 05:0005:0005:0005:00 06:0006:0006:0006:00 00:0000:0000:0000:00 01:0001:0001:0001:00 02:0002:0002:00 03:0003:0003:00 04:00UTC04:0004:00UTC04:00UTC 05:0005:00 05:0005:0006:0006:0006:0006:00 (a)UTC (a)CEDUUTCUTC CEDU UTCUTCUTC (b) (b)ALIC ALIC (c)(a) (c)TWTF(a) CEDUTWTF CEDU (b)(b) ALIC ALIC (c)(c) TWTF( cTWTF()a ) (d)(d)( (d)dKUNM )KUNM KUNM(b) 60 60 60 60 6060 G19G19 6060 FigureFigure40 40 3. 3. TheC N CN values at the GPS L1 frequencyG19G19 for International40 40 Global Navigation Satellite 4040 The / 0 values0 at the GPS L1 frequency for International Global4040 Navigation Satellite System Service (IGS)G28G28G28G28 20202020 20202020 stationsSystem0 0 CEDU Service (a), ALIC (IGS (b) ),stations TWTF (c CEDU) and KUNM (a), ALIC (d) during (b), TWTF the intense (c)0 L-bandand0 KUNM SRB event (d) thatduring occurred the intense on 13 December L- 0 0 ◦ ◦ ◦0 0 ◦ 2006.band6060 The6060 SRB solar event elevation that angles occurred of the fouron 13 stations December were 80.7 2006., 84.9 The, 42.5 solar6060and6060 elevation 36.0 respectively. angles of The the sampling four stations period was 40 40 40 40 30were s. 4040 80.7°, 84.9°, 42.5° and 36.0° respectively.G11G11G11G11 The sampling40 period40 was 30 s. G27G27G27G27 20202020 20202020

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Figure 3. The CN0 values at the GPS L1 frequency for International Global Navigation Satellite System Service (IGS) stations CEDU (a), ALIC (b), TWTF (c) and KUNM (d) during the intense L- band SRB event that occurred on 13 December 2006. The solar elevation angles of the four stations were 80.7°, 84.9°, 42.5° and 36.0° respectively. The sampling period was 30 s.

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The influence of the SRB on the C/N0 of the GNSS receiver increased with increasing solar elevation angle, which is consistent with the conclusions in the literature [18]. Station ALIC and station CEDU in Australia were closer to the subsolar point, and consequently, their C/N0 values showed a stronger decline. The C/N0 values of the four satellites at station CEDU decreased sharply, and all of them had a loss of lock at 03:31 (UTC), with a maximum duration of approximately 450 s. In contrast, none of the four satellites at station KUNM had a loss of lock, despite the significant decline in C/N0 of approximately 12 dB-Hz. However, the fading trends of all the GPS satellites at the different stations were almost the same. In other words, most satellites had valleys at the same time despite their different degrees of decline, especially at approximately 3:31 (UTC). Based on the above analysis, we propose an intense L-band SRB detection method using the fact that SRBs lead to a decrease in the C/N0 values for signals from several GNSS satellites over a large area of the Earth’s surface. In this process, data preprocessing is initially performed, and the specific details are as follows: • The solar elevation angle of all the IGS stations is calculated to select the stations close to the subsolar point. • The data of improperly working receivers are excluded, such as some stations with incomplete data. • The data type of C/N0 is set to an integer to eliminate the impact of the differences in the data precision of various types of receivers on the results. • The elevation mask angle is set to 10◦. Note that the elevation mask angle is lower than normal to increase the amount of observation data. Due to the fact that GPS L5 and GALILEO E5 include few satellites that can be observed at the same time from the data provided by the IGS. In addition, multipath cannot lead to a simultaneous decrease in the C/N0 values of multiple satellites over a large area close to the subsolar point. Hence, the proposed method can prevent the impact of multipath to some extent, which is reflected in the low false alarm rate in the subsequent experiments. Then, the valley periods of a single satellite at a single station are calculated, and finally, the detection result of an intense L-band SRB is obtained by comparing multiple satellites and multiple stations.

3.1. Detection of a Single Satellite The detection procedure for a single satellite includes two signiﬁcant modules: ﬁnding the falling/rising moments and determining the valley periods.

3.1.1. Determination of the “Falling Moments” and “Rising Moments”

We deﬁne the moment at which C/N0 is higher than that at the next moment as the falling moment. This is denoted as ai(1 ≤ i ≤ N), where N is the number of falling moments. The set of falling moments, which is denoted as A, can be expressed as A = {ai|1 ≤ i ≤ N}. Likewise, the moment at which C/N0 is higher than that at the previous moment is deﬁned as the rising moment and denoted bj(1 ≤ j ≤ M). For this expression, M is the number of rising moments, and the set of rising moments, which is denoted as B, can be expressed as B = bj 1 ≤ j ≤ M . To illustrate the model with an example, the C/N0 values of G13 at the GPS L2 frequency observed at station CEDU during the SRB event on 13 December 2006 are shown in Figure4. The green points are the falling moments, while the purple points represent the rising moments. SensorsSensors 20212021, 21,, 21x ,FOR 1405 PEER REVIEW 7 of 18 7 of 18

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40 04:00 04:02 04:04 04:06 04:08 04:10 UTC

Figure 4. The C/N0 of GPS L1 G13 at IGS station CEDU during an intense L-band SRB event that Figure 4. The CN0 of GPS L1 G13 at IGS station CEDU during an intense L-band SRB event that occurredoccurred on on 13 December13 December 2006. The2006. sampling The sampling period was period 30 s. was 30 s. 3.1.2. Determination of the Valley Period 3.1.2.The Determination valley period is deﬁnedof the asValley the period Period between the falling moment and the rising momentThe and valley must beperiod satisﬁed is asdefined follows: as the period between the falling moment and the rising •momentThe time and of must the rising be momentsatisfied is as higher follows: than the falling moment. • The C/N0 at any time in this period is less than the smaller of that at the falling • momentThe time and of that the at therising rising moment moment. is higher than the falling moment.

• TheThe set ofCN valley0 at periods, any time which in this is denoted period as isP, less can be than expressed the smaller as of that at the falling moment and that (at the rising moment. ) ai < bj, ∀t ∈ ai, bj , P = a , b , (5) The set of valley periods,i j C whichN < is denotedC N C asN P , can be expressed as / 0t Min / 0ai , / 0bj  ai b j,,,  t ( a i b j ) where t is the moment within the period (ai,bj). C/N0t, C/N0ai and C/N0bj represent the P = (aij,b ) , (5) ratio of the carrier to noise at moments t, ai andCNCNNbj, respectively. Min As ,anC example, the valley 0t 0 aij 0 b ) periods in Figure4 are marked in magenta. Additionally, we( show two valley periods in Figure4 to indicate that the proposed method can effectively distinguish various valley where t is the moment within the period ( a , ). CN , and represent i bj 0t CN0 a CN periods. i 0 bj Similarly, the valley period of each satellite over the same station at a selected fre- the ratio of the carrier to noise at moments t , ai and bj , respectively. As an example, the quency can be calculated and deﬁned as Ps(1 ≤ s ≤ l), where s and l represent the correspondingvalley periods satellite in Figure and the 4 numberare marked of observed in magenta. satellites, Additionally, respectively. we show two valley periods in Figure 4 to indicate that the proposed method can effectively distinguish various 3.2.valley Intersection periods. of Different Satellites at the Same Monitoring Station TheSimi valleylarly, periods the valley common period to multiple of each satellites satellite at a single over station the aresame denoted stationG and at a selected fre- can be expressed as quency can be calculated and defined as Ps (1sl ) , where s and l represent the corre- G = P1 ∩ P2 ∩ · · · ∩ Pl, (6) sponding satellite and the number of observed satellites, respectively. where Ps(1 ≤ s ≤ l) represents the valley period set of satellite s. Similarly, the valley periods common to all satellites at each station can be calculated and3.2. deﬁnedIntersection as Gk (of1 ≤Differentk ≤ m), Satellites where m isat the the number Same Monitoring of stations and StationGk is the valley periodThe set at valley station periodsk. common to multiple satellites at a single station are denoted G 3.3.and Intersection can be expressed of Multiple Monitoringas Stations

Likewise, the valley periods common toGPPP multiple=  stations   are denoted by U and can 12 l , (6) be expressed as U = G1 ∩ G2 ∩ · · · ∩ Gm. (7) where Ps (1)sl represents the valley period set of satellite s . Similarly, the valley periods common to all satellites at each station can be calculated

and defined as Gkmk (1) , where m is the number of stations and Gk is the valley period set at station k .

3.3. Intersection of Multiple Monitoring Stations Likewise, the valley periods common to multiple stations are denoted by U and can be expressed as

UGGG=    12 m . (7)

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All the moments in the set of U are the ﬁnal detection results.

4. Results and Discussion In this work, we first study the influence of the number of satellites and the number of stations on the detection results. Based on these results, the influence of the satellite distribution on the detection rate is analyzed. Finally, the detection rates at different frequency bands of different GNSS systems are compared. All the GNSS observation data used in the experiment are taken from the IGS data center. The sampling period is 30 s, and each sampling point is counted as an event. The solar radio emission power value at 1415 MHz provided by RSTN is compared with our detected samples. The emission power values of different magnitudes are separately counted. Accordingly, the detection rate, which is used to represent the detection performance, is defined as the ratio between the number of predicted SRB samples and the number of real samples (from RSTN) in each emission power interval. We define the minimum emission power corresponding to the detection rate of 80% as the detection threshold in the experiments. Table4 presents the detailed information of each station used in the experiments, including ID, latitude, longitude and country.

Table 4. The ID, latitude, longitude and country of the IGS stations used in the experiments.

ID Latitude/◦ Longitude/◦ Country ISPA 110 W 27 S Chile AREQ 72 W 16 S Peru BOGT 75 W 4 N Colombia MDO1 105 W 30 N USA CHPI 45 W 22 S Brazil CRO1 65 W 17 N USA KOUR 53 W 5 N Guyana NNOR 116 E 31 S Australia PERT 115 E 31 S Australia SUNM 153 E 27 S Australia TIDB 148 E 35 S Australia PIMO 121 E 14 N Philippines CCJM 142 E 27 N Japan KUNM 102 E 25 N China GUAM 144 E 13 N Guam USUD 138 E 36 N Japan TSKB 140 E 36 N Japan DARW 131 E 12 S Australia TOW2 147 E 19 S Australia RABT 7 W 33 N Morocco MAS1 16 W 27 N Spain SFER 7 W 36 N Spain VILL 4 W 40 N Spain YEBE 4 W 40 N Spain KOKB 160 W 22 N USA TLSE 1 E 43 N France MBAR 30 E 0 N Uganda HARB 27 E 25 S Africa EBRE 0 E 40 N Spain MATE 14 E 40 N Italy MAT1 14 E 40 N Italy

4.1. Detection of a Single Satellite The data from station NNOR on 13 December 2006 are used for the detection of a single station. The detection period is 00:00:00–10:00:00 (UTC), and the time of the peak solar radio emission power is approximately 03:30:00 (UTC), with a solar incident angle of Sensors 2021, 21, x FOR PEER REVIEW 9 of 18

MAT1 14 E 40 N Italy

described in Section 3.1. The valley period common to at least Nsat satellites is judged as

the◦ detection result of a single station. In this section, different values of N are compared 77.1 . All satellites observed at the peak time are detected separately using the method sat describedand analyzed. in Section 3.1. The valley period common to at least Nsat satellites is judged as the detectionFigure result 5 presents of a single the station. detection In this section, rates differentcorresponding values of N tosat differentare compared for GPS. At both and analyzed. theFigure L1 and5 presents L2 frequencies, the detection ratesthe correspondingdetection rate to differentdecreasesNsat withfor GPS. increasing At both for any flux therange L1 and due L2 frequencies,to the increasingly the detection severe rate decreases restriction. with increasingMoreover,Nsat regardlessfor any flux of the value of , range due to the increasingly severe restriction. Moreover, regardless of the value of Nsat, thethe detection detection rate atrate the at L2 the frequency L2 frequency is significantly is significantly higher than that higher at the L1than frequency. that at the L1 frequency. AA possible possible reason reason for this for is thatthis flux is that or power flux densityor power at different density frequencies at different of GNSS frequencies of GNSS maymay have have a big a differencebig difference even for even the same for L-bandthe same SRB eventL-band [22]. SRB event [22].

Nsat=5 Nsat=4 Nsat=3 Nsat=2 1.0

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FigureFigure 5. Detection 5. Detection rate of r GPSate L1of andGPS L2 L1 at IGSand station L2 at NNOR IGS station during an NNOR intense L-bandduring SRB an eventintense L-band SRB thatevent occurred that onoccurred 13 December on 2006.13 December The histogram 2006. shows The the histogram number of samples shows in the each number ﬂux range. of samples in each flux range. In the case of Nsat = 5, only a few ﬂux ranges have a detection rate of ≥80%. For GPS L1, only 8–9 kSFU and 9–10 kSFU reach 80%; for GPS L2, only 1–2 kSFU, 4–5 kSFU, 7–8 kSFUIn, 8–9the kSFU,case andof 9–10 = kSFU 5, only reach a 80%.few Overall,flux ranges the detection have a rate detection is quite low rate in of  80%. For GPS theL1, case only of N 8sat–9= kSFU 5. and 9–10 kSFU reach 80%; for GPS L2, only 1–2 kSFU, 4–5 kSFU, 7–8 kSFU, 8–9 kSFU, and 9–10 kSFU reach 80%. Overall, the detection rate is quite low in the case of = 5.

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Conversely, in the case of Nsat = 2, the detection rate at both frequencies reaches the highest for all the flux ranges due to the less severe restriction. However, the detection rates of GPS L1 and L2 in the range of 0–100 SFU reach 12.87% and 51.82%, respectively. Note that the flux density under normal circumstances is below 100 SFU, and thus, the detection rate of this range represents the false alarm rate. As mentioned above, the false alarm rate is much higher in the case of Nsat = 2. Furthermore, in the case of Nsat = 3 or Nsat = 4, the detection rate in the range of 0–100 SFU is close to 0, with higher reliability. Regarding GPS L1, for the ranges of 5–6 kSFU, 7–8 kSFU, 8–9 kSFU, and 9–10 kSFU, the detection rate of Nsat = 3 is equivalent to that of Nsat = 4. However, the detection rate of Nsat = 3 is significantly higher than that of Nsat = 4 when the flux is lower. Regarding GPS L2, for the range of 0.1–1 kSFU, the detection rate of Nsat = 3 is slightly higher than that of Nsat = 4, with a difference of 6.15%, and the detection rates of the other ranges are equivalent. From the above discussion, we conclude that the optimal value of Nsat is 3 due to its obvious advantage of low flux.

4.2. Analysis of Multiple Stations In this section, to expand data coverage, we analyze additional three typical intense L-band SRB events. For each event, seven stations close to the subsolar point are selected. Table5 lists the detailed information for each SRB event, including the period when the SRB occurred, the RSTN stations, the time of the peak of flux density, the IGS stations and the solar incident angle. Due to the incompleteness of the RSTN and IGS data, it is impossible to guarantee that the flux density data for different events are from the same RSTN station and that all seven stations are the stations closest to the subsolar point. For each SRB event, the valley period common to at least Nstation stations is judged as the final detection result. In addition, for each station, we take the value Nsat = 3 from the optimization in Section 4.1.

Table 5. Information on four intense L-band SRBs. The solar radio emission power is obtained from different RSTN stations due to the incompleteness of the RSTN data.

RSTN Date Period Peak Time IGS Station ID and Solar Incident Angle/(◦) Station Sagamore- AREQ: BOGT: MDO1: CHPI: CRO1: KOUR: 06.12.06 12:11–20:24 19:30 ISPA: 83.5 Hill 58.3 50.6 37.6 34.8 34.5 32.3 NNOR: PERT: SUNM: TIDB: PIMO: CCJM: KUNM: 13.12.06 00:00–10:00 Learmonth 03:30 77.1 76.3 66.6 68.5 52.4 38.0 36.0 PIMO: GUAM: USUD: TSKB: DARW: KUNM: TOW2: 15.02.11 02:04–10:45 Learmonth 03:00 75.8 80.0 72.6 72.2 59.0 58.8 50.4 Sagamore- RABT: MAS1: CHPI: SFER: KOUR: YEBE: 24.09.11 11:00–22:00 13:00 VILL: 48.8 Hill 56.2 63.0 53.4 53.2 51.7 48.8

Figure6 presents the results corresponding to different values of Nstation for GPS. In addition to the time when the SRB occurred, the period detected in this experiment includes normal conditions. We can effectively test the false alarm rate based on the 2589 samples in the range of 0–100 SFU. Generally, the number of samples gradually decreases with increasing solar radio ﬂow. The range of ≥10 kSFU is not further divided, as a ﬂux density of more than 10 kSFU is quite easy to be detected. SensorsSensors 2021,2021 21,, x21 FOR, 1405 PEER REVIEW 11 of 18 11 of 18

Nstation=2 Nstation=3 Nstation=4 Nstation=5 1.0

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100 0–0.1 0.1–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10 ≥10 kSFU

FigureFigure 6. 6.Detection Detection rate forrate 4 for intense 4 intense L-band L SRB-band events. SRB The events. histogram The shows histogram the number shows of the number of sam- samplesples in in each each ﬂuxflux range. range.

With increasing Nstation, the detection rates of both frequencies gradually decrease and reach approximatelyWith increasing 0% in theNstation range of, the 0.1–1 detection kSFU, proving rates that of the both proposed frequencies method has gradually decrease aand low false reach alarm approximately rate and high reliability. 0% in Furthermore, the range the of low 0.1 false–1 kSFU, alarm rate proving indicates that the proposed thatmethod the proposed has a low method false can alarm avoid therate impact and ofhigh multipath reliability. to some Furthermore, extent. In other the low false alarm words, if multipath interference is detected as SRB by mistake, the predicted samples are distributedrate indicates in each that ﬂux the range proposed instead of mostmethod being can in the avoid ranges the above impact 100 SFU. of multipath to some extent. In othTheer detection words, rate if multipath at GPS L2 is muchinterference higher than is detected that at GPS as L1, SRB which by is mistake, consistent the predicted sam- withples Figure are distributed5. For GPS L1, in there each are flux a small range number instead of ﬂux of ranges most with being a detection in the ranges rate above 100 SFU. of 80%. In the case of N = 2, only 3–4 kSFU, 7–8 kSFU, 8–9 kSFU, and 10 kSFU have The detectionstation rate at GPS L2 is much higher than that at GPS L1, which is consistent detection rates ≥ 80%. However, for GPS L2, in cases of Nstation = 2, 3, and 4, the detection thresholdswith Figure that meet 5. For the detectionGPS L1, rate there of 80% are are a insmall the ranges number of 1–2 of kSFU, flux 1–2 ranges kSFU, andwith a detection rate 2–3of kSFU,80%. respectively.In the case There of is a sudden = 2, and only obvious 3–4 kSFU, drop in 7 the–8 range kSFU, of 9–108–9 kSFUkSFU, at and 10 kSFU have both the L1 frequency and L2 frequency. A possible reason for this is that merely 7 samples aredetection in the range rates of 9–10 80%. kSFU. However, for GPS L2, in cases of = 2, 3, and 4, the detection thresholdsDue to the that detection meet rate the at the detection L2 frequency rate being of higher80% are than in that the at theranges L1 frequency, of 1–2 kSFU, 1–2 kSFU, weand further 2–3 dividekSFU, the respectively. range of 0.1–1 There kSFU at is the a sudden L2 frequency and for obvious more in-depth drop analysis.in the range of 9–10 kSFU As shown in Figure7, there is a trend of fewer samples and a higher detection rate with at both the L1 frequency and L2 frequency. A possible reason for this is that merely 7 samples are in the range of 9–10 kSFU. Due to the detection rate at the L2 frequency being higher than that at the L1 frequency, we further divide the range of 0.1–1 kSFU at the L2 frequency for more in-depth analysis. As shown in Figure 7, there is a trend of fewer samples and a higher detection rate with increasing solar radio emission power. In the case of = 3, 4 or 5, there are no flux ranges with detection rates reaching 80%. However, in the case of = 2, the flux density threshold for a detection rate of 80% is in the range of 800–900 SFU. Specifi- cally, the detection rates of 500–600 SFU, 600–700 SFU, and 700–800 SFU reach 80%, 75.68%, 79.17%, and 76.19%, respectively. As mentioned above, we can conclude that the optimal value of is 2.

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increasing solar radio emission power. In the case of Nstation = 3, 4 or 5, there are no flux ranges with detection rates reaching 80%. However, in the case of Nstation = 2, the flux density threshold for a detection rate of 80% is in the range of 800–900 SFU. Specifically, the detection rates of 500–600 SFU, 600–700 SFU, and 700–800 SFU reach 80%, 75.68%, 79.17%, SensorsSensors 2021 2021, ,21 21, ,x x FOR FOR PEER PEER REVIEW REVIEWand 76.19%, respectively. As mentioned above, we can conclude that the optimal value1212 ofof of1818

Nstation is 2.

N =2 N =3 N =4 N =5 Nstationstation=2 Nstationstation=3 Nstationstation=4 Nstationstation=5 5 1.01.0 10105

4 0.80.8 10104

3 0.60.6 10103

2 0.40.4 10102

1 Number of samples Number of samples Detection rate ofL2 1 Detection rate ofL2 0.20.2 1010

0 0.00.0 10100 1–21–2 2–32–3 3–43–4 4–54–5 5–65–6 6–76–7 7–87–8 8–98–9 9–109–10 0.1kSFU 0.1kSFU FigureFigure 7.7. Detection Detection rate rate in in thethe the rangerange range ofof of 0.1–10.1 0.1––11 kSFUkSFU kSFU at at at the the the GPS GPS GPS L2 L2 L2 frequency f frequencyrequency for for for 4 4 intense4 intense intense L-band L L--bandband SRB events.SRBSRB events. events. The histogramThe The histogram histogram shows shows shows the number the the number number of samples of of samples samples in each in in each ﬂuxeach range.flux flux range. range.

4.3.4.3. Influence InﬂuenceInfluence of of Satellite Satellite Distribution Distribution onon thethe DetectionDetection RateRate InIn thisthis section,section, thethe GPSGPS L1L1 L2L2 datadata ofof fourfour typicaltypical SRBSRB eventsevents in in TableTable5 5 5are areare used usedused to toto analyzeanalyze thethe signiﬁcancesignificancesignificance ofof thethe satellitesatellite distributiondistribution on on the the detection detection rate.rate. rate. TheThe satellitessatellites areare divideddivided with withwith respect respectrespect to toto the thethe incident incidentincident direction directiondirection of oftheof thethe Sun SunSun into intointo two twotwo categories: categories:categories: “near-satellites” ‘‘near‘‘near--satel-satel- andlites’’lites’’ “distant-satellites”. and and ‘‘distant ‘‘distant--satellites’’.satellites’’. FigureFigure8 8 8shows showsshows a aa sky skysky image imageimage of ofof the ththee KUNM KUNMKUNM station stationstation at atat 03:30:00 03:30:0003:30:00 (UTC)(UTC) (UTC) on onon 13 1313 December DecemberDecember 2006.2006. TheTheThe star-marked starstar--markedmarked point pointpoint represents representsrepresents the thethe position positionposition of theofof thethe Sun. Sun.Sun. The TheThe near-satellites nearnear--satellitessatellites G11 andG11G11 G27andand areG27G27 consistent areare consistentconsistent with the withwith direction thethe directiondirection of the elevationofof thethe elevationelevation of the Sun, ofof thethe while Sun,Sun, the whilewhile distant-satellites thethe distantdistant-- G08satellitessatellites and G28 G08G08 areand and in G28 G28 opposite are are in in directions.o oppositepposite directions. directions.

NN DistantDistant--satellitessatellites

315 315 3030 4545

GG1919 GG2828 6060 GG0808

GG2727 WW EE

GG1111

G17 G17 SunSun

GG1313 135135 225225

Near-satellites S Near-satellites S Figure 8. Sky image of IGS station KUNM at 03:30:00 (UTC) on 13 December 2006. Figure 8. Sky image of IGS station KUNM at 03:30:00 (UTC) on 13 December 2006.

TableTable 6 6 lists lists the the azimuth azimuth ( (AzAz)) and and elevation elevation ( (ElEl)) of of the the Sun Sun and and the the satellites satellites atat 03:30:0003:30:00 (UTC). (UTC). Two Two near near--satellitessatellites and and two two distant distant--satellitessatellites are are selected selected for for each each station. station.

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Table6 lists the azimuth ( Az) and elevation (El) of the Sun and the satellites at 03:30:00 (UTC). Two near-satellites and two distant-satellites are selected for each station.

Table 6. Location information of the Sun and selected satellites at seven stations at 03:30:00 (UTC) on 13 December 2006.

Sun Distant-Satellites Near-Satellites Station Az/◦ El/◦ SVID Az/◦ El/◦ SVID Az/◦ El/◦ G13 272 45 G11 5 52 NNOR 80.9 77.1 G23 215 66 G20 140 65 G13 275 45 G11 7 52 PERT 78.9 76.3 G23 217 66 G20 140 65 G25 145 45 G20 210 60 SUNM 279.8 66.6 G31 140 35 G23 230 32 G25 135 47 G20 220 70 TIDB 301.2 68.5 G31 135 40 G23 243 45 G19 20 29 G11 210 80 PIMO 169.9 52.4 G27 305 70 G13 230 20 G03 50 40 G11 230 50 CCJM 196.3 38.0 G19 10 55 G16 120 30 G08 325 50 G11 135 60 KUNM 151.8 36.0 G28 310 28 G27 300 80

There are few satellites that meet the requirements of “near-satellites” or “distant- satellites”, and thus, the values of Nsat = 3 and Nstation = 2 from the optimization in Sections 4.1 and 4.2 cannot be used for this section. This part of the experiment includes the following two steps: • For a single station, the intersection of the valley periods of two near-satellites (distant- satellites) is taken. • For each SRB event, the valley period common to at least two stations is judged as the final detection result. The detection results of each flux range for four typical intense L-band SRB events in Table5 are shown in Figure9. For GPS L1, the detection results of the near-satellites and distant-satellites are different in several flux ranges. The results for the two categories are generally equivalent. Specifically, the detection rate of the distant-satellites is higher in the ranges of 1–2 kSFU, 3–4 kSFU, and 7–8 kSFU but lower in the ranges of 4–5 kSFU, 6–7 kSFU, and 8–9 kSFU. For GPS L2, the differences between the detection rate of the near-satellites and that of the distant-satellites are −3.70%, 5.00%, −5.56%, and −6.25%, respectively, which are smaller than those at the L1 frequency. Moreover, the detection rate at the L2 frequency is much smoother than that at the L1 frequency. Consequently, the distribution of the satellites relative to the Sun has no effect on the overall detection rate. Figure 10 presents the carrier-to-noise ratio observation data of GPS, GLONASS, and Galileo at the HARB station during 11:30:00–12:30:00 (UTC) on 6 September 2017, and the shaded area indicates the period when the SRB occurred. At the time of the peak flux density (12:02:30), the C/N0 values of GPS L2, GPS L5, GLONASS G2 and Galileo E5 drop sharply by approximately 5–7 dB-Hz. Additionally, there is a slight drop near 12:08:00 (UTC). In each subdiagram of Figure 10, the decline degree of C/N0 at each satellite appears to be similar at the same frequency. However, the C/N0 values at various frequencies are affected by the SRB to different extents. The C/N0 values of the high frequencies of GNSS (GPS L1, GLONASS G1, and Galileo E1) show an inconspicuous decrease, which is consistent with the conclusions of the study in [22]. They also pointed out that a possible reason for this is the different sensibilities of the GNSS frequencies and systems to SRB Sensors 2021, 21, 1405 14 of 18

Sensors 2021, 21, x FOR PEER REVIEWinterference. Accordingly, this phenomenon leads to a difference in the detection14 of 18 rates at different GNSS frequencies in subsequent experiments.

Near-satellites Distant-satellites 1.0

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0.0 0–0.1 0.1–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10 ≥10 kSFU Figure 9. Influence of satellite distribution on the detection rate for 4 typical intense L-band SRB Sensors 2021, 21, x FOR PEER REVIEWFigure 9. Inﬂuence of satellite distribution on the detection rate for 4 typical intense L-band15 SRBof 18 events in Table 5. events in Table5. Figure 10 presents the carrier-to-noise ratio observation data of GPS, GLONASS, and Galileo at the HARB station during 11:30:00–12:30:00 (UTC) on 6 September 2017, and the GPS L1 shaded50 area indicates the period when the SRB occurred. At G03the time of the peak flux

density30 (12:02:30), the CN0 values of GPS L2, GPS L5, GLONASS G26 G2 and Galileo E5 drop G32 sharply10 by approximately 5–7 dB-Hz. Additionally, there is a slight drop near 12:08:00 (UTC). In each subdiagram of Figure 10, the declineGPS L2 degree of at each satellite ap- 50 G03 pears30 to be similar at the same frequency. However, the G26values at various frequen- cies10 are affected by the SRB to different extents. The values G32 of the high frequencies of GNSS (GPS L1, GLONASS G1, and Galileo E1)GPS show L5 an inconspicuous decrease, which 50 G03 is consistent with the conclusions of the study in [22]. They also pointed out that a possible 30 G26 reason for this is the different sensibilities of the GNSS frequencies G32 and systems to SRB 10 interference. Accordingly, this phenomenon leadsGLONASS to a difference G1 in the detection rates at different50 GNSS frequencies in subsequent experiments. R04

(dB-Hz) 30 R05 0 10 R15 C/N GLONASS G2 50 R04 30 R05 10 R15 GALILEO E1 50 E02 30 E08 E14 10 GALILEO E5 50 E02 30 E08 E14 10 11:30 11:45 12:00 12:15 12:30 UTC

Figure 10. The CN values of different GNSS systems at IGS station HARB during an intense L- Figure 10. The C/N00 values of different GNSS systems at IGS station HARB during an intense L-bandband SRB SRB event event that that occurred occurred on on 6 6September September 2017. 2017. The The sampling sampling period period was was 30 30 s. s.The The elevation elevation maskmask angleangle waswas 1010°.◦.

Figure 11 shows the detection results at different frequencies for different systems. The detection performance at GPS L2 is the best of all systems. Specifically, the detection rates at GPS L2 of the flux ranges  1 kSFU are 100%, with a low false alarm rate. Moreo- ver, the detection performance at GLONASS G2 is second only to that at GPS L2 and achieves 100% on the condition of flux ranges 3 kSFU.

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Figure 11 shows the detection results at different frequencies for different systems. The detection performance at GPS L2 is the best of all systems. Specifically, the detection Sensors 2021, 21, x FOR PEER REVIEWrates at GPS L2 of the flux ranges ≥ 1 kSFU are 100%, with a low false alarm rate. Moreover, 16 of 18 the detection performance at GLONASS G2 is second only to that at GPS L2 and achieves 100% on the condition of flux ranges ≥ 3 kSFU.

1.0 0.8 0.6

0.4 L1 L2 0.2 L5 Detection rate of GPS of rate Detection 0.0 1.0 0.8 0.6 0.4 R1 0.2 R2

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0.0 Detection rate of Galileo of rate Detection 103 270 215 102 73 15 15 1 9 10 4 2 Number of samples 1 1 1 1 100 0–0.10.1–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10 ≥10 kSFU

Figure 11.FigureDetection 11. Detection results of different results GNSS of different systems atGNSS various systems frequencies at various during an frequencies intense during an in- L-bandtense SRB event L-band that occurred SRB event on 6 Septemberthat occurred 2017. on 6 September 2017.

Overall, a comparison of Figures 10 and 11 shows that the more obvious the response to the SRBOverall, system a is,comparison the better the of detection Figure performance 10 and Figure is. The 11 detection shows thresholdsthat the more obvious the ofresponse GPS L1 L5, to GLONASS the SRB G1, system and GALILEO is, the E1 better E5, under the thedetection condition performance of a detection is. The detection thresholds of GPS L1 L5, GLONASS G1, and GALILEO E1 E5, under the condition of a detection rate above 80%, are 8–9 kSFU, 8–9 kSFU, 8–9 kSFU, 8–9 kSFU, and 7–8 kSFU, respectively, indicating worse performance than other frequencies and systems. However,

the responses of the CN0 values of GPS L5 and GALILEO E5 to SRB is still evident, which appears to contradict the above trend. Through ample analysis, we found that the data of GPS L5 and GALILEO E5 from the IGS contain few satellites that can be observed simultaneously (the values vary from 4 to 6 and 5 to 8, respectively). Hence, the values of

Nsat = 3 and Nst at i on = 2 from the optimization in Sections 4.1 and 4.2 are not suitable for GPS L5 and GALILEO E5. Through specific experiments, the optimal values for and for GPS L5 are 2 and 2, respectively. For GALILEO E5, the values are 1 and 4, respectively. Although we modified the optimal values for and for GPS L5 and GALILEO E5 to adapt to their smaller number of satellites and obtain better performance, the detection performance still appears to be unsatisfactory, as shown in Figure 11. The reason is that the core step of the proposed method is the comparison of multiple

Sensors 2021, 21, 1405 16 of 18

rate above 80%, are 8–9 kSFU, 8–9 kSFU, 8–9 kSFU, 8–9 kSFU, and 7–8 kSFU, respectively, indicating worse performance than other frequencies and systems. However, the responses of the C/N0 values of GPS L5 and GALILEO E5 to SRB is still evident, which appears to contradict the above trend. Through ample analysis, we found that the data of GPS L5 and GALILEO E5 from the IGS contain few satellites that can be observed simultaneously (the values vary from 4 to 6 and 5 to 8, respectively). Hence, the values of Nsat = 3 and Nstation = 2 from the optimization in Sections 4.1 and 4.2 are not suitable for GPS L5 and GALILEO E5. Through specific experiments, the optimal values for Nsat and Nstation for GPS L5 are 2 and 2, respectively. For GALILEO E5, the values are 1 and 4, respectively. Although we modified the optimal values for Nsat and Nstation for GPS L5 and GALILEO E5 to adapt to their smaller number of satellites and obtain better performance, the detection performance still appears to be unsatisfactory, as shown in Figure 11. The reason is that the core step of the proposed method is the comparison of multiple satellites and multiple stations, and thus, a reduction in the number of satellites can have a great impact on the detection results. Sato et al. [21] determined the impacts of the SRB at the GPS L2 and L5 frequencies but not at the L1 frequency during the SRB event on 6 September 2017. Beyond their work, our analysis indicates that this SRB event may have an impact at the L1 frequency. The impact of this SRB event on the C/N0 at the L1 frequency is difficult to observe with the naked eye but can be reflected by the experimental results of the proposed method. As shown in Figure 11, the detection rate is much higher in the ranges above 100 SFU than at 0–100 SFU. Although the number of samples for 6–7 kSFU, 8–9 kSFU, 9–10 kSFU, and ≥10 kSFU is merely 1, the number of samples in other ranges is sufficient. The detection rate of 0–100 SFU is close to 0%, while the number of samples in this range accounts for almost half of all samples. Most of the predicted samples are in flux density ranges above 100 SFU, and this phenomenon does not seem to be an accident.

5. Conclusions

Based on the influence of intense L-band SRBs on the C/N0 of GNSS, a new method for detecting intense L-band SRB events is proposed. The influence of the number of satellites, number of monitoring stations, satellite distribution and different GNSS systems on the detection results are analyzed through several experiments. The conclusions can be summarized as follows: 1. The detection rate of intense L-band SRBs reaches more than 80% for the flux density above 800 SFU at the L2 frequency of GPS. 2. The detection results of GPS L2 and GLONASS G2 are better than those of GPS L1 L5, GLONASS G1 and Galileo E1 E5. 3. The distribution of the satellites relative to the Sun has no impact on the overall detection rate. 4. Statistically, the proposed detection algorithm is proven to have high reliability, with a false alarm rate of approximately 0% for historical SRB events detection with the optimal Nsat and Nstation. The integrity, continuity, availability and accuracy of GNSS are important evaluation indexes for navigation satellite systems, and the interference of solar radio noise is a critical factor affecting the performance of GNSS. With the rapid development of GNSS, it is necessary to assess the negative impact of intense L-band SRBs on the system. Dispensing with expensive radio telescopes, we propose an intense L-band SRB detection method with high recognition rate, low false alarm rate, low cost, and all-weather real-time monitoring. The proposed method and insights in this paper can be conducive to the identification of intense L-band SRBs, which is a key component of attempting to suppress SRBs interference on GNSS in the future.

Author Contributions: Conceptualization, F.Y. and X.Z.; methodology, F.Y. and X.Z.; software, F.Y.; validation, F.Y.; investigation, F.Y.; writing—original draft preparation, F.Y.; writing—review and Sensors 2021, 21, 1405 17 of 18

editing, X.C. and M.L.; visualization, F.Y.; funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by the National Key Research and Development Plan of China under Grant 2018YFB0505103. 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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