Polarimetric multiple-radar architectures with distributed antennas for discriminating between radar targets and deception jamming

Abstract The potential abilities of polarimetric multiple-radar architectures with distributed antennas in electronic counter-countermeasures (ECCMs) are analyzed based on differences between target echoes and deception jamming in scattering coefficients properties. According to the differences in generation mechanism between the target scatter and jamming, a signal model of real targets and deception jamming for two-dimensional vector sensors is established. By applying the Neyman-Pearson (NP) criterion and a hybrid NP-Maximum Posteriori (MAP) criterion, a two-stage detection/discrimination algorithm is proposed. In our proposed algorithm, the targets and jamming are detected in the first stage from a Gaussian noise background. Then, a discriminator based on the generalized likelihood ratio test is designed by exploiting the property of polarization discrimination. A theoretical analysis is also given to evaluate the performance of the second stage of the algorithm. Moreover, the discrimination performance can be improved by optimizing the transmitter polarization parameters. Simulation results indicate that the proposed ECCM strategy is effective against DRFM jamming, especially when JNR is high and transmit polarization is optimally designed.

[1]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[2]  Yong Liu,et al.  Main-Lobe Jamming Suppression Method of using Spatial Polarization Characteristics of Antennas , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[3]  M. Gouws,et al.  Modern wideband DRFM architecture and real-time DSP capabilities for radar test and evaluation , 2013, 2013 Saudi International Electronics, Communications and Photonics Conference.

[4]  K Olivier,et al.  Design and performance of wideband DRFM for radar test and evaluation , 2011 .

[5]  Yoshio Yamaguchi,et al.  On the basic principles of radar polarimetry: the target characteristic polarization state theory of Kennaugh, Huynen's polarization fork concept, and its extension to the partially polarized case , 1991 .

[6]  A. Tamhane,et al.  Multiple Comparison Procedures , 1989 .

[7]  S. D. Berger,et al.  Digital radio frequency memory linear range gate stealer spectrum , 2003 .

[8]  Nan Liu,et al.  Adaptive detection with conic rejection to suppress deceptive jamming for frequency diverse MIMO radar , 2017, Digit. Signal Process..

[9]  Tao Wang,et al.  Maximum Likelihood Approach to the Estimation and Discrimination of Exoatmospheric Active Phantom Tracks using Motion Features , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[10]  Alexander M. Haimovich,et al.  Spatial Diversity in Radars—Models and Detection Performance , 2006, IEEE Transactions on Signal Processing.

[11]  Yu Zhou,et al.  Discrimination of Deception Targets in Multistatic Radar Based on Clustering Analysis , 2016, IEEE Sensors Journal.

[12]  L.J. Cimini,et al.  MIMO Radar with Widely Separated Antennas , 2008, IEEE Signal Processing Magazine.

[13]  Danilo Orlando,et al.  Detection Algorithms to Discriminate Between Radar Targets and ECM Signals , 2010, IEEE Transactions on Signal Processing.

[14]  Hanyang Li,et al.  Study of spectrum sensing exploiting polarization: From optimal LRT to practical detectors , 2016, Digit. Signal Process..

[15]  Olivier Besson,et al.  An Improved Adaptive Sidelobe Blanker , 2008, IEEE Transactions on Signal Processing.

[16]  Weimin Su,et al.  Improved Interrupted Sampling Repeater Jamming based on DRFM , 2014 .

[17]  Huanyao Dai,et al.  Novel discrimination method of digital deceptive jamming in mono-pulse radar , 2011 .

[18]  Danilo Orlando,et al.  A Subspace-Based Adaptive Sidelobe Blanker , 2008, IEEE Transactions on Signal Processing.

[19]  S. P. Xiao,et al.  Discrimination of exo-atmospheric active decoys using acceleration information , 2010 .

[20]  Jianyu Yang,et al.  Distributed target detection with polarimetric MIMO radar in compound-Gaussian clutter , 2012, Digit. Signal Process..

[21]  Sandeep Gogineni,et al.  Polarimetric MIMO Radar With Distributed Antennas for Target Detection , 2009, IEEE Transactions on Signal Processing.

[22]  Yu Zhou,et al.  Signal Fusion-Based Algorithms to Discriminate Between Radar Targets and Deception Jamming in Distributed Multiple-Radar Architectures , 2015, IEEE Sensors Journal.

[23]  A. Farina,et al.  Combined effect of phase and RGPO delay quantization on jamming signal spectrum , 2005, IEEE International Radar Conference, 2005..

[24]  XueSong Wang,et al.  Polarization discrimination between repeater false-target and radar target , 2009, Science in China Series F: Information Sciences.

[25]  Baixiao Chen,et al.  Transmitter polarization optimization with polarimetric MIMO radar for mainlobe interference suppression , 2017, Digit. Signal Process..

[26]  D. Giuli,et al.  Polarization diversity in radars , 1986, Proceedings of the IEEE.

[27]  Danilo Orlando,et al.  A Novel Noise Jamming Detection Algorithm for Radar Applications , 2017, IEEE Signal Processing Letters.

[28]  Zhuang Zhao-wen Research on High-resolution Polarization Discrimination Algorithm of Active Decoy and Radar Target , 2004 .

[29]  Guoqing Liu,et al.  Polarimetric SAR target feature extraction and image formation via semi-parametric methods , 2004, Digit. Signal Process..