Research on Radar Waveform Design Strategy under Game Condition

Wei LI; Honglin WANG; Jiayi ZHENG; Jianye XU; Junlong ZHAO; Kun ZOU

doi:10.11999/JEIT190114

Volume 41 Issue 11

Nov. 2019

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(11): 2654-2660

Wei LI, Honglin WANG, Jiayi ZHENG, Jianye XU, Junlong ZHAO, Kun ZOU. Research on Radar Waveform Design Strategy under Game Condition[J]. Journal of Electronics & Information Technology, 2019, 41(11): 2654-2660. doi: 10.11999/JEIT190114

Citation:

Wei LI, Honglin WANG, Jiayi ZHENG, Jianye XU, Junlong ZHAO, Kun ZOU. Research on Radar Waveform Design Strategy under Game Condition[J]. Journal of Electronics & Information Technology, 2019, 41(11): 2654-2660. doi: 10.11999/JEIT190114

Citation:

PDF( 1817 KB)

Research on Radar Waveform Design Strategy under Game Condition

doi: 10.11999/JEIT190114

Wei LI^{1, 2},
Honglin WANG^{1
,
,},
Jiayi ZHENG³,
Jianye XU¹,
Junlong ZHAO¹,
Kun ZOU¹

1.
Information and Navigation College, Aire Force Engineering University, Xi’an 710077, China
2.
Collaborative Innovation Center of Information Sensing and Understading, Xi’an 710077, China
3.
95019 troop of the PLA, Xiangyang 441800, China

Funds: The National Natural Science Foundation of China (61571456), The Aeronautical Science Foundation of China (20160196001)

Received Date: 2019-02-26
Rev Recd Date: 2019-09-01

Available Online: 2019-09-05

Publish Date: 2019-11-01

Abstract

Abstract

In order to improve missile-borne radar detection performance in modern electronic warfare, a radar waveform design method based on Nash equilibrium is proposed. Firstly, the radar and jammer game signal models are established in electronic warfare. Based on maximum Signal-to-Interference-plus-Noise Ratio (SINR), waveform strategies of radar and jammer are designed respectively. Secondly, the existence of Nash equilibrium solution is demonstrated by mathematical derivation and verified in experimental simulation. A multiple iterative water-filling method which repeatedly eliminates strict disadvantages is designed to achieve Nash equilibrium. The maxmin scheme of disequilibrium game is deduced by two-step water-filling method. Finally, the radar detection performance of optimization strategies is tested by simulation experiments. Simulation results reveal that the radar waveform design based on Nash equilibrium is beneficial to improve the radar detection performance under game conditions. Compared with no-game and maxmin strategies, the radar detection probability of Nash equilibrium strategy can be increased by 12.02% and 3.82%, respectively. It is proved that the Nash equilibrium strategy of this paper is closer to the Pareto optimality.
- Radar waveform design,
- Nash equilibrium,
- Signal-to-Interference-plus-Noise Ratio (SINR),
- Iterative water-filling method,
- Maxmin method

FullText(HTML)

References(21)

References

HAYKIN S. Cognitive radar: A way of the future[J]. IEEE Signal Processing Magazine, 2006, 23(1): 30–40. doi: 10.1109/MSP.2006.1593335

翁木云, 郑家毅, 李伟, 等. 低RCS目标检测的制导雷达波形优化方法[J]. 华中科技大学学报: 自然科学版, 2019, 47(2): 41–46. doi: 10.13245/j.hust.190208

WENG Muyun, ZHENG Jiayi, LI Wei, et al. Guidance radar waveform optimization method for low RCS target detection under interference conditions[J]. Journal of Huazhong University of Science and Technology:Natural Science Edition, 2019, 47(2): 41–46. doi: 10.13245/j.hust.190208

BELL M R. Information theory and radar waveform design[J]. IEEE Transactions on Information Theory, 1993, 39(5): 1578–1597. doi: 10.1109/18.259642

PILLAI S U, OH H S, YOULA D C, et al. Optimal transmit-receiver design in the presence of signal-dependent interference and channel noise[J]. IEEE Transactions on Information Theory, 2000, 46(2): 577–584. doi: 10.1109/18.825822

KAY S. Optimal signal design for detection of Gaussian point targets in stationary Gaussian clutter/reverberation[J]. IEEE Journal of Selected Topics in Signal Processing, 2007, 1(1): 31–41. doi: 10.1109/jstsp.2007.897046

ROMERO R A, BAE J, and GOODMAN N A. Theory and application of SNR and mutual information matched illumination waveforms[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(2): 912–927. doi: 10.1109/TAES.2011.5751234

AUBRY A, DEMAIO A, FARINA A, et al. Knowledge-aided (potentially cognitive) transmit signal and receive filter design in signal-dependent clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(1): 93–117. doi: 10.1109/TAES.2013.6404093

WU Linlong, BABU P, and PALOMAR D P. Transmit waveform/receive filter design for MIMO radar with multiple waveform constraints[J]. IEEE Transactions on Signal Processing, 2018, 66(6): 1526–1540. doi: 10.1109/TSP.2017.2787115

IMANI S, NAYEBI M M, and GHORASHI S A. Colocated MIMO radar SINR maximization under ISL and PSL constraints[J]. IEEE Signal Processing Letters, 2018, 25(3): 422–426. doi: 10.1109/LSP.2018.2796603

BUTT F A, NAQVI I H, and RIAZ U. Hybrid phased-MIMO radar: A novel approach with optimal performance under electronic countermeasures[J]. IEEE Communications Letters, 2018, 22(6): 1184–1187. doi: 10.1109/LCOMM.2018.2828408

WANG Li, WU Huaqing, and STÜBER G L. Cooperative jamming-aided secrecy enhancement in P2P communications with social interaction constraints[J]. IEEE Transactions on Vehicular Technology, 2017, 66(2): 1144–1158. doi: 10.1109/TVT.2016.2553121

GUAN Yanpeng and GE Xiaohua. Distributed secure estimation over wireless sensor networks against random multichannel jamming attacks[J]. IEEE Access, 2017, 5: 10858–10870. doi: 10.1109/ACCESS.2017.2713807

WANG Lulu, WANG Hongqiang, WONG K K, et al. Minimax robust jamming techniques based on signal-to-interference-plus-noise ratio and mutual information criteria[J]. IET Communications, 2014, 8(10): 1859–1867. doi: 10.1049/iet-com.2013.1054

FENG Dejun, XU Letao, PAN Xiaoyi, et al. Jamming wideband radar using interrupted-sampling repeater[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(3): 1341–1354. doi: 10.1109/TAES.2017.2670958

SONG Xiufeng, WILLETT P, ZHOU Shengli, et al. The MIMO radar and jammer games[J]. IEEE Transactions on Signal Processing, 2012, 60(2): 687–699. doi: 10.1109/TSP.2011.2169251

GAO Hao, WANG Jian, JIANG Chunxiao, et al. Equilibrium between a statistical MIMO radar and a jammer[C]. 2015 IEEE Radar Conference, Arlington, USA, 2015: 461–466. doi: 10.1109/RADAR.2015.7131043.

LAN Xing, LI Wei, WANG Xingliang, et al. MIMO radar and target stackelberg game in the presence of clutter[J]. IEEE Sensors Journal, 2015, 15(12): 6912–6920. doi: 10.1109/JSEN.2015.2466812

KAY S M and LUO Pengfei. Fundamentals of Statistical Signal Processing: Estimation and Detection Theory[M]. Beijing: Publishing House of Electronics Industry, 2014: 425–445.

邹鲲. 认知雷达的未知目标检测[J]. 电子与信息学报, 2018, 40(1): 166–172. doi: 10.11999/JEIT170254

ZOU Kun. Unknown target detection for cognitive radar[J]. Journal of Electronics &Information Technology, 2018, 40(1): 166–172. doi: 10.11999/JEIT170254

CARABALLO M A, MÁRMOL A M, MONROY L, et al. Cournot competition under uncertainty: Conservative and optimistic equilibria[J]. Review of Economic Design, 2015, 19(2): 145–165. doi: 10.1007/s10058-015-0171-z

FUDENBERG D and TIROLE J. Game Theory[M]. Cambridge: MIT Press, 1991: 18–26.

Relative Articles

Supplements(0)

Cited By

Proportional views