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Non-Recurrent Wideband Continuous Active Sonar

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Non-Recurrent Wideband Continuous Active Sonar Non-recurrent Wideband Continuous Active Sonar by Jonathan B. Soli Department of Electrical and Computer Engineering Duke University Date: Approved: Jeffrey L. Krolik, Supervisor Loren W. Nolte Leslie M. Collins Donald B. Bliss Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Electrical and Computer Engineering in the Graduate School of Duke University 2014 ABSTRACT Non-recurrent Wideband Continuous Active Sonar by Jonathan B. Soli Department of Electrical and Computer Engineering Duke University Date: Approved: Jeffrey L. Krolik, Supervisor Loren W. Nolte Leslie M. Collins Donald B. Bliss An abstract of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Electrical and Computer Engineering in the Graduate School of Duke University 2014 Copyright c 2014 by Jonathan B. Soli All rights reserved except the rights granted by the Creative Commons Attribution-Noncommercial Licence Abstract The Slow-time Costas or \SLO-CO" Continuous Active Sonar (CAS) waveform shows promise for enabling high range and velocity revisit rates and wideband processing gains while suppressing range ambiguities. SLO-CO is made up of non-recurrent wideband linear FM chirps that are frequency staggered according to a Costas code across the pulse repetition interval. SLO-CO is shown to provide a near-thumbtack ambiguity functions with controllable sidelobes, good Doppler and range resolution at high revisit rates. The performance of the SLO-CO waveform was tested using the Sonar Simulation Toolset (SST) as well as in the shallow water Target and Re- verberation Experiment 2013 (TREX13). For both the real and simulated results, the performance of the SLO-CO is compared to the conventional CAS waveform. Amplitude-Range-Velocity (ARV) processing of SLO-CO experimental trials reveal that relatively high direct blast sidelobes mask the target peak. Methods of sup- pressing the direct blast are discussed including adaptive filtering and re-designing the waveform. iv Contents Abstract iv List of Figures vii Acknowledgements ix 1 Introduction1 2 Active Sonar for Target Detection4 2.1 Target range and Doppler........................4 2.2 The simple pulse and Linear FM (LFM) chirp.............6 2.3 Matched Filtering.............................7 2.4 Binary hypothesis testing......................... 11 3 Ambiguity Functions and Waveform Design 14 3.1 The Ambiguity Function (AF)...................... 14 3.2 The AF of the simple pulse....................... 16 3.3 The AF of the LFM chirp........................ 20 3.4 Pulse compression............................. 22 3.5 Pulse burst waveforms.......................... 24 3.5.1 Range-folding of pulse burst waveforms............. 25 4 Continuous Active Sonar (CAS) 27 4.1 Non-Recurrent Waveforms (NRWFs).................. 28 4.2 The conventional CAS waveform and processing............ 29 v 4.2.1 Conventional CAS viewed as a NRWF............. 29 4.3 The Slow-time Costas-Coded (SLO-CO) NRWF............ 31 4.3.1 Costas Codes........................... 32 4.4 Amplitude-Range-Velocity (ARV) processing.............. 34 4.4.1 Comparison of conventional CAS and SLO-CO ARVs..... 35 5 Simulation Model and Simulated Results 38 5.1 The Sonar Simulation Toolset (SST).................. 38 5.2 SST simulations of the SLO-CO waveform............... 39 6 Target and Reverberation Experiment 2013 (TREX13) Results 46 6.1 Conventional CAS result......................... 48 6.2 The TREX13 SLO-CO direct blast sidelobe level issue........ 49 6.3 Attempts at recovering SLO-CO experimental results......... 54 6.3.1 Adaptive filtering......................... 54 6.3.2 Waveform re-design........................ 58 7 Conclusions 64 Bibliography 66 vi List of Figures 2.1 Comparison of simple pulse and LFM chirp waveforms........ 10 2.2 Binary hypothesis detector block diagram............... 12 3.1 The AF of the simple pulse waveform.................. 18 3.2 The AF of the LFM waveform...................... 21 3.3 Diagram explaining pulse compression................. 23 3.4 Simple pulse and LFM chirp pulse burst waveforms.......... 25 3.5 Range-folded pulse burst waveform................... 26 4.1 Spectrogram of conventional CAS waveform.............. 29 4.2 Conventional CAS processing...................... 30 4.3 Conventional CAS viewed as a NRWF................. 30 4.4 Spectrogram of TREX13 SLO-CO waveform submission........ 32 4.5 Example Costas frequency sequence................... 33 4.6 Various steps of the autocorrelation of a Costas frequency sequence. 34 4.7 ARV processing chain........................... 35 4.8 Comparison of conventional CAS and SLO-CO ARVs......... 36 4.9 Comparison conventional CAS and SLO-CO matched filter outputs. 37 5.1 Component model structure of SST................... 39 5.2 Comparison of MATLAB and SST-generated SLO-CO ARVs..... 40 5.3 SST simulation geometry and parameters................ 43 5.4 ARVs of SST-generated signal components............... 44 vii 5.5 ARVs of SST-generated results with varying geometries........ 45 6.1 Conventional CAS and SLO-CO TREX13 signal levels........ 47 6.2 Spectrograms of conventional CAS and SLO-CO TREX13 realizations 48 6.3 TREX-13 Conventional CAS power vs. range vs. time surface.... 49 6.4 CAS and SLO-CO ARVs......................... 50 6.5 Element-level TREX13 matched filter outputs............. 51 6.6 TREX13 conventional CAS trial beamformed and match filtered... 52 6.7 TREX13 conventional SLO-CO trial beamformed and match filtered. 52 6.8 TREX13 conventional CAS and SLO-CO trials after beamforming and matched filtering............................. 53 6.9 Schematic diagram of adaptive direct blast canceler.......... 55 6.10 Snapshot setup of the adaptive direct blast canceller.......... 56 6.11 TREX13 conventional CAS result with and without direct blast can- cellation.................................. 57 6.12 SLO-CO SLL due with varying the Costas sequence length M .... 58 6.13 SLO-CO spectrograms with varying sub-chirp BW overlap...... 62 6.14 SLO-CO ARVs with varying sub-chirp BW overlap.......... 63 6.15 ARV of recommended re-design of TREX13 SLO-CO waveform... 63 viii Acknowledgements I would like to thank Dr. Jeffrey Krolik for his support and direction over the last two and a half years. Also I would like to thank Dr. Loren Nolte, Dr. Leslie Collins, and Dr. Donald Bliss for serving on my master's committee. Special thanks to Dr. Granger Hickman and Itay Cnnan-on who laid the foundation for the work in this thesis and with whom I continue to actively collaborate. Special thanks to Juan Ramirez Jr., my other fellow lab mates, and others who have offered me help during my time at Duke. This work was supported by the Office of Naval Researche (ONR). ix 1 Introduction Conventional active sonars use short, high-energy pulses or chirps to highlight targets with long delays between consecutive pulses or chirps to avoid range ambiguities. In this thesis, we present the Slow-time Costas Costas Coded (SLO-CO) waveform, a Continuous Active Sonar (CAS) waveform that is meant to be transmitted at 100% duty cycle with no delays between transmissions. The benefit of transmitting continuously is that it enables the potential for higher range and velocity revisit rates. The SLO-CO waveform was first introduced at the Oceans IEEE conference in 2012 by Hickman and Krolik [1]. The conventional CAS waveform consists of a long (e.g. 20 sec) Linear Frequency Modulated (LFM) chirp that is processed in narrowband segments via a Short Time Fourier Transform (STFT). The conventional CAS waveform and processing enable frequent range updates, but poor instantaneous velocity resolution. Because conven- tional CAS processing is narrowband, it has the undesirable effect of limiting gains due to pulse compression. The SLO-CO waveform is made up of short LFM chirps that are frequency- staggered based on a circular Costas code. Frequency-staggered chirps are what 1 causes SLO-CO to be a Non-Recurrent Waveform (NRWF). Successful implementa- tion of the SLO-CO waveform promises high range and velocity revisit rates as well as wideband processing gains. Costas frequency staggering mitigates range ambiguities that are commonly associated with other pulse-burst waveforms [2]. The Ambigu- ity Function (AF) of the SLO-CO waveform resembles the desirable thumbtack-like shape with a tall, narrow mainlobe with uniform delay and Doppler sidelobes. The first reference in which the term NRWF was coined was written by Clancy et. al. in 1999 [3]. In this paper a Quadratic Phase Coding (QPC) was applied to a conventional LFM chirp train. It was shown that applying QPC reduced range ambiguities in the Over The Horizon (OTH) radar application. It was found that direct implementation of the QPC method to the CAS problem was not feasible. After some research, it was found that Costas codes could be used to achieve a non-recurrent waveform with good range and Doppler characteristics [4]. Costas frequency-staggered LFM chirps were first researched for radar by Levanon and Mozeson who coined the name \Modified Costas Signal" [5]. The use of circular Costas codes as well as the application to the continuous active sonar problem is what makes SLO-CO unique. The performance of the SLO-CO waveform was tested in both computer sim- ulations using the Sonar Simulation Toolset (SST) as well as in the Target and Reverberation Experiment 2013 (TREX13) sea trial. In simulation, SLO-CO per- formed as expected. However processing the TREX13 data was not as successful as anticipated. Recovery of the target in the experimental data was unsuccessful due to high sidelobes of the direct blast return. The direct blast is the direct path from the continually transmitting source to the array. The severity of this issue was not apparent in our simulations preceding the experiment. Despite the setback, methods were investigated to recover the SLO-CO TREX13 results including applying an adaptive filter to mitigate the direct blast as well as 2 redesigning the waveform to reduce the overall sidelobe level. This thesis highlights each of these topics in Chapter6.
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