One-Bit Radar Processing With Time-Varying Sampling Thresholds

Target parameter estimation in active sensing, and particularly radar signal processing, is a long-standing problem that has been studied extensively. In this paper, we propose a novel approach for target parameter estimation in cases where one-bit analog-to-digital-converters (ADCs), also known as signal comparators with time-varying thresholds, are employed to sample the received radar signal instead of high-resolution ADCs. The considered problem has potential applications in the design of inexpensive radar and sensing devices in civilian applications, and can likely pave the way for future radar systems employing low-resolution ADCs for faster sampling and high-resolution target determination. We formulate the target estimation as a multivariate weighted-least-squares optimization problem that can be solved in a cyclic manner. Numerical results are provided to exhibit the effectiveness of the proposed algorithms.

[1]  K.M. Strohm,et al.  Development of future short range radar technology , 2005, European Radar Conference, 2005. EURAD 2005..

[2]  Michael S. Nolan,et al.  Fundamentals of Air Traffic Control , 1990 .

[3]  Rayan Saab,et al.  One-Bit Compressive Sensing With Norm Estimation , 2014, IEEE Transactions on Information Theory.

[4]  Augusto Aubry,et al.  Knowledge-Aided (Potentially Cognitive) Transmit Signal and Receive Filter Design in Signal-Dependent Clutter , 2013, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Milica Stojanovic,et al.  Underwater sensor networks: applications, advances and challenges , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[6]  Arindam Bose,et al.  Constructing Binary Sequences With Good Correlation Properties: An Efficient Analytical-Computational Interplay , 2018, IEEE Transactions on Signal Processing.

[7]  Joseph R. Guerci,et al.  Optimum transmit-receiver design in the presence of signal-dependent interference and channel noise , 1999 .

[8]  Augusto Aubry,et al.  A Doppler Robust Design of Transmit Sequence and Receive Filter in the Presence of Signal-Dependent Interference , 2014, IEEE Transactions on Signal Processing.

[9]  Ingrid Daubechies,et al.  Single-Bit Oversampled A/D Conversion With Exponential Accuracy in the Bit Rate , 2007, IEEE Transactions on Information Theory.

[10]  Jian Li,et al.  One-Bit Radar Processing and Estimation with Time-Varying Sampling Thresholds , 2018, 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM).

[11]  Yonina C. Eldar,et al.  Deep Signal Recovery with One-bit Quantization , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[12]  Julian J. Bussgang,et al.  Crosscorrelation functions of amplitude-distorted gaussian signals , 1952 .

[13]  Edward M. Hofstetter,et al.  On the design of optimum radar waveforms for clutter rejection , 1967, IEEE Trans. Inf. Theory.

[14]  S. Kay,et al.  Optimal Signal Design for Detection of Gaussian Point Targets in Stationary Gaussian Clutter/Reverberation , 2007, IEEE Journal of Selected Topics in Signal Processing.

[15]  Onkar Dabeer,et al.  Signal Parameter Estimation Using 1-Bit Dithered Quantization , 2006, IEEE Transactions on Information Theory.

[16]  Jeong-Beom Ihn,et al.  Pitch-catch Active Sensing Methods in Structural Health Monitoring for Aircraft Structures , 2008 .

[17]  A. Bemis.  Radar in Meteorology , 1955, Transactions of the IRE Professional Group on Communications Systems.

[18]  Mojtaba Soltanalian,et al.  Signal Recovery From 1-Bit Quantized Noisy Samples via Adaptive Thresholding , 2018, 2018 52nd Asilomar Conference on Signals, Systems, and Computers.

[19]  Yaniv Plan,et al.  Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach , 2012, IEEE Transactions on Information Theory.

[20]  T. Zwick,et al.  Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band , 2012, IEEE Transactions on Microwave Theory and Techniques.

[21]  Alejandro Ribeiro,et al.  Bandwidth-constrained distributed estimation for wireless sensor Networks-part I: Gaussian case , 2006, IEEE Transactions on Signal Processing.

[22]  P. Lacomme,et al.  Synthetic Aperture Radar , 2001 .

[23]  Cheng-Xiang Wang,et al.  Wideband spectrum sensing for cognitive radio networks: a survey , 2013, IEEE Wireless Communications.

[24]  Yunhua Zhang,et al.  A MAP Approach for 1-Bit Compressive Sensing in Synthetic Aperture Radar Imaging , 2015, IEEE Geoscience and Remote Sensing Letters.

[25]  Anders Høst-Madsen,et al.  Effects of sampling and quantization on single-tone frequency estimation , 2000, IEEE Trans. Signal Process..

[26]  A. Weiss,et al.  DOA estimation using one-bit quantized measurements , 2002 .

[27]  Biyang Wen,et al.  Measurement of River Surface Currents With UHF FMCW Radar Systems , 2007 .

[28]  Mark R. Bell.  Information theory and radar waveform design , 1993, IEEE Trans. Inf. Theory.

[29]  Xiaohua Zhu,et al.  Locating the Few: Sparsity-Aware Waveform Design for Active Radar , 2017, IEEE Transactions on Signal Processing.

[30]  T. Fujisaka,et al.  Ocean wave observation by CW mm-wave radar with narrow beam , 2001, Proceedings of the 2001 IEEE Radar Conference (Cat. No.01CH37200).

[31]  Onkar Dabeer,et al.  Multivariate Signal Parameter Estimation Under Dependent Noise From 1-Bit Dithered Quantized Data , 2008, IEEE Transactions on Information Theory.

[32]  John D. Wolf,et al.  Radar Waveform Synthesis by Mean Square Optimization Techniques , 1969, IEEE Transactions on Aerospace and Electronic Systems.

[33]  Jian Li,et al.  Transmit codes and receive filters for radar , 2008, IEEE Signal Processing Magazine.

[34]  Elias Masry,et al.  The reconstruction of analog signals from the sign of their noisy samples , 1980, IEEE Trans. Inf. Theory.

[35]  P. P. Vaidyanathan,et al.  One-bit sparse array DOA estimation , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[36]  Jian Li,et al.  One-bit compressive sampling with time-varying thresholds for sparse parameter estimation , 2016, 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM).

[37]  Petre Stoica,et al.  Spectral Analysis of Signals , 2009 .

[38]  J. V. Vleck,et al.  The spectrum of clipped noise , 1966 .

[39]  Alejandro Ribeiro,et al.  Bandwidth-constrained distributed estimation for wireless sensor networks-part II: unknown probability density function , 2006, IEEE Transactions on Signal Processing.

[40]  Hao He,et al.  Waveform Design for Active Sensing Systems: A Computational Approach , 2012 .

[41]  Jian Li,et al.  Joint Design of the Receive Filter and Transmit Sequence for Active Sensing , 2013, IEEE Signal Processing Letters.

[42]  R. Bro,et al.  A fast non‐negativity‐constrained least squares algorithm , 1997 .

[43]  Steven M. Sussman,et al.  Least-square synthesis of radar ambiguity functions , 1962, IRE Trans. Inf. Theory.

[44]  Philip M. Woodward,et al.  Probability and Information Theory with Applications to Radar , 1954 .

[45]  Alessio Balleri,et al.  Waveform Design and Diversity for Advanced Radar Systems , 2012 .

[46]  Augusto Aubry,et al.  Cognitive design of the receive filter and transmitted phase code in reverberating environment , 2012 .

[47]  S. Haykin,et al.  Cognitive radar: a way of the future , 2006, IEEE Signal Processing Magazine.

[48]  Richard G. Baraniuk,et al.  1-Bit compressive sensing , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

[49]  S.R. Bussolari,et al.  Mode S data link applications for general aviation , 1995, Proceedings of 14th Digital Avionics Systems Conference.

[50]  B. Burke,et al.  An Introduction to Radio Astronomy , 1996 .

[51]  William D. Rummler.  A Technique for Improving the Clutter Performance of Coherent Pulse Train Signals , 1967, IEEE Transactions on Aerospace and Electronic Systems.

[52]  W. Brown.  Synthetic Aperture Radar , 1967, IEEE Transactions on Aerospace and Electronic Systems.

[53]  Stephen P. Boyd,et al.  Compressed Sensing With Quantized Measurements , 2010, IEEE Signal Processing Letters.

[54]  C. Pontbriand,et al.  An integrated, underwater optical /acoustic communications system , 2010, OCEANS'10 IEEE SYDNEY.

[55]  K. A. Browning,et al.  Uses of radar in meteorology , 1986 .

[56]  Hoon Sohn,et al.  Design of a wireless active sensing unit for structural health monitoring , 2004, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[57]  Hao He,et al.  Optimization of the Receive Filter and Transmit Sequence for Active Sensing , 2012, IEEE Transactions on Signal Processing.

[58]  Lloyd J. Spafford.  Optimum radar signal processing in clutter , 1968, IEEE Trans. Inf. Theory.

[59]  S. Blunt,et al.  Adaptive pulse compression via MMSE estimation , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[60]  Hao He,et al.  New Algorithms for Designing Unimodular Sequences With Good Correlation Properties , 2009, IEEE Transactions on Signal Processing.

[61]  Petre Stoica,et al.  Computational Design of Sequences With Good Correlation Properties , 2012, IEEE Transactions on Signal Processing.

[62]  H. Vincent Poor,et al.  Spectrum Exploration and Exploitation for Cognitive Radio: Recent Advances , 2015, IEEE Signal Processing Magazine.