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Volume 43 Issue 5
May  2021
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Bin HE, Hongtao SU. A Review of Game Theory Analysis in Cognitive Radar Anti-jamming[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1199-1211. doi: 10.11999/JEIT200843
Citation: Bin HE, Hongtao SU. A Review of Game Theory Analysis in Cognitive Radar Anti-jamming[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1199-1211. doi: 10.11999/JEIT200843

A Review of Game Theory Analysis in Cognitive Radar Anti-jamming

doi: 10.11999/JEIT200843
Funds:  The National Natural Sciences Foundation of China (61372134)
  • Received Date: 2020-09-29
  • Rev Recd Date: 2021-03-19
  • Available Online: 2021-04-16
  • Publish Date: 2021-05-18
  • The core research contents of radar countermeasures are the games of countermeasures between jamming strategies and anti-jamming strategies. As a hotspot in the field of electronic warfare, radar countermeasures have been paid much attention by scholars. This paper summarizes that the scholars employ the cooperative and non-cooperative game methods to analyze the radar against jamming while probing targets. Different radar systems make use of cognitive techniques perceive and learn the complex electromagnetic environment, and reasonably allocate transmitting power, control coding sequence, design waveform, investigate detection and tracking methods and allocate resources of radar communication etc. In this way, radar can not only reduce power consumption, but also search and track the target without being detected by the enemy. Thus, radar can achieve its optimal performance in the complex and changeable modern battlefield environment. Finally, game theory in cognitive radar anti-jamming is summarized and prospected, and it also points out some potential problems and challenges of game theory in cognitive radar anti-jamming.
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  • [1]
    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
    [2]
    黎湘, 范梅梅. 认知雷达及其关键技术研究进展[J]. 电子学报, 2012, 40(9): 1863–1870. doi: 10.3969/j.issn.0372-2112.2012.09.025

    LI Xiang and FAN Meimei. Research advance on cognitive radar and its key technology[J]. Acta Electronica Sinica, 2012, 40(9): 1863–1870. doi: 10.3969/j.issn.0372-2112.2012.09.025
    [3]
    HAYKIN S. Cognition is the key to the next generation of radar systems[C]. The 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, Marco Island, USA, 2009: 463–467.
    [4]
    赵国庆. 雷达对抗原理[M]. 2版. 西安: 西安电子科技大学出版社, 2012.

    ZHAO Guoqing. Principle of Radar Countermeasure[M]. 2nd ed. Xi’an: Xidian University Press, 2012.
    [5]
    李光久, 李昕. 博弈论简明教程[M]. 镇江: 江苏大学出版社, 2013.

    LI Guangjiu and LI Xin. A Brief Tutorial on Game Theory[M]. Zhenjiang: Jiangsu University Press, 2013.
    [6]
    TOPKIS D M. Supermodularity and Complementarity[M]. Princeton: Princeton University Press, 1998: 212–214.
    [7]
    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
    [8]
    XUE Yanbo. Cognitive radar: Theory and simulations[D]. [Ph. D. dissertation], The McMaster University, 2010.
    [9]
    HAYKIN S, XUE Yanbo, and SETOODEH P. Cognitive radar: Step toward bridging the gap between neuroscience and engineering[J]. Proceedings of the IEEE, 2012, 100(11): 3102–3130. doi: 10.1109/JPROC.2012.2203089
    [10]
    GUERCI J R. Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach[M]. Boston: Artech House, 2010.
    [11]
    左群声, 王彤. 认知雷达导论[M]. 北京: 国防工业出版社, 2017.

    ZUO Qunsheng and WANG Tong. Introduction to Cognitive Radar[M]. Beijing: National Defense Industry Press, 2017.
    [12]
    张良, 祝欢, 杨予昊, 等. 机载预警雷达技术及信号处理方法综述[J]. 电子与信息学报, 2016, 38(12): 3298–3306. doi: 10.11999/JEIT161007

    ZHANG Liang, ZHU Huan, YANG Yuhao, et al. Overview on airborne early warning radar technology and signal processing methods[J]. Journal of Electronics &Information Technology, 2016, 38(12): 3298–3306. doi: 10.11999/JEIT161007
    [13]
    SHARAGA N, TABRIKIAN J, and MESSER H. Optimal cognitive beamforming for target tracking in MIMO radar/sonar[J]. IEEE Journal of Selected Topics in Signal Processing, 2015, 9(8): 1440–1450. doi: 10.1109/JSTSP.2015.2467354
    [14]
    BEN KILANI M, NIJSURE Y, GAGNON G, et al. Cognitive waveform and receiver selection mechanism for multistatic radar[J]. IET Radar, Sonar & Navigation, 2016, 10(2): 417–425. doi: 10.1049/iet-rsn.2015.0319
    [15]
    YAO Yu, MIAO Pu, and CHEN Zhimin. Cognitive waveform optimization for phase-modulation-based joint radar-communications system[J]. IEEE Access, 2020, 8: 33276–33288. doi: 10.1109/ACCESS.2020.2974787
    [16]
    ESMAEILI-NAJAFABADI H, LEUNG H, and MOO P W. Unimodular waveform design with desired ambiguity function for cognitive radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 56(3): 2489–2496. doi: 10.1109/TAES.2019.2942411
    [17]
    BELL K L, BAKER C J, SMITH G E, et al. Cognitive radar framework for target detection and tracking[J]. IEEE Journal of Selected Topics in Signal Processing, 2015, 9(8): 1427–1439. doi: 10.1109/JSTSP.2015.2465304
    [18]
    GUI Ronghua, WANG Wenqin, PAN Ye, et al. Cognitive target tracking via angle-range-Doppler estimation with transmit subaperturing FDA radar[J]. IEEE Journal of Selected Topics in Signal Processing, 2018, 12(1): 76–89. doi: 10.1109/JSTSP.2018.2793761
    [19]
    WEN Cai, HUANG Yan, WU Jianxin, et al. Cognitive anti-deception-jamming for airborne array radar via phase-only pattern notching with nested ADMM[J]. IEEE Access, 2019, 7: 153660–153674. doi: 10.1109/ACCESS.2019.2948507
    [20]
    KIRK B H, NARAYANAN R M, GALLAGHER K A, et al. Avoidance of time-varying radio frequency interference with software-defined cognitive radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 55(3): 1090–1107. doi: 10.1109/TAES.2018.2886614
    [21]
    KARIMI V, MOHSENI R, and SAMADI S. Adaptive OFDM waveform design for cognitive radar in signal-dependent clutter[J]. IEEE Systems Journal, 2020, 14(3): 3630–3640. doi: 10.1109/JSYST.2019.2943809
    [22]
    LIU Xinghua, XU Zhenhai, WANG Luoshengbin, et al. Cognitive dwell time allocation for distributed radar sensor networks tracking via cone programming[J]. IEEE Sensors Journal, 2020, 20(10): 5092–5101. doi: 10.1109/JSEN.2020.2970280
    [23]
    DU Yi, LIAO Kefei, OUYANG Shan, et al. Time and aperture resource allocation strategy for multitarget ISAR imaging in a radar network[J]. IEEE Sensors Journal, 2020, 20(6): 3196–3206. doi: 10.1109/JSEN.2019.2954711
    [24]
    KRISHNAMURTHY V, ANGLEY D, EVANS R, et al. Identifying cognitive radars - inverse reinforcement learning using revealed preferences[J]. IEEE Transactions on Signal Processing, 2020, 68: 4529–4542. doi: 10.1109/TSP.2020.3013516
    [25]
    GOGINENI S and NEHORAI A. Game theoretic approach for polarimetric MIMO radar waveform design[C]. 2012 International Waveform Diversity & Design Conference, Kauai, USA, 2012: 59–62.
    [26]
    Dix J P. Game-theoretic applications[J]. IEEE Spectrum, 1968, 5(4): 108–117. doi: 10.1109/MSPEC.1968.5214595.
    [27]
    ZETTERBERG L H. Signal detection under noise interference in a game situation[J]. IRE Transactions on Information Theory, 1962, 8(5): 47–52. doi: 10.1109/TIT.1962.1057773
    [28]
    LIPFORD J. A game theoretic method of obtaining a given return from a minimum weight of radar reflectors[J]. IEEE Transactions on Antennas and Propagation, 1963, 11(2): 193. doi: 10.1109/TAP.1963.1137988
    [29]
    SPEYER J L. A stochastic differential game with controllable statistical parameters[J]. IEEE Transactions on Systems Science and Cybernetics, 1967, 3(1): 17–20. doi: 10.1109/TSSC.1967.300103
    [30]
    徐友云, 李大鹏, 钟卫, 等. 认知无线电网络资源分配: 博弈模型与性能分析[M]. 北京: 电子工业出版社, 2013.

    XU Youyun, LI Dapeng, ZHONG Wei, et al. Resource Management of Cognitive Radio Networks: Game Theoretic Modeling and Performance Analysis[M]. Beijing: Publishing House of Electronics Industry, 2013.
    [31]
    MITOLA J and MAGUIRE G Q. Cognitive radio: Making software radios more personal[J]. IEEE Personal Communications, 1999, 6(4): 13–18. doi: 10.1109/98.788210
    [32]
    BACHMANN D J, EVANS R J, and MORAN B. Game theoretic analysis of adaptive radar jamming[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(2): 1081–1100. doi: 10.1109/TAES.2011.5751244
    [33]
    冯明月, 何明浩, 郁春来, 等. 相控阵雷达噪声干扰博弈分析[J]. 现代雷达, 2014, 36(5): 10–14, 30. doi: 10.16592/j.cnki.1004-7859.2014.05.010

    FENG Mingyue, HE Minghao, YU Chunlai, et al. Game theory analysis of noise jamming for phased array radar[J]. Modern Radar, 2014, 36(5): 10–14, 30. doi: 10.16592/j.cnki.1004-7859.2014.05.010
    [34]
    PANOUI A, LAMBOTHARAN S, and CHAMBERS J A. Game theoretic power allocation technique for a MIMO radar network[C]. The 2014 6th International Symposium on Communications, Control and Signal Processing, Athens, Greece, 2014: 509–512.
    [35]
    BACCI G, SANGUINETTI L, GRECO M S, et al. A game-theoretic approach for energy-efficient detection in radar sensor networks[C]. The 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, Hoboken, USA, 2012: 157–160.
    [36]
    GODRICH H, PETROPULU A P, and POOR H V. Power allocation strategies for target localization in distributed multiple-radar architectures[J]. IEEE Transactions on Signal Processing, 2011, 59(7): 3226–3240. doi: 10.1109/TSP.2011.2144976
    [37]
    SLIMENI F, LE NIR V, SCHEERS B, et al. Optimal power allocation over parallel Gaussian channels in cognitive radio and jammer games[J]. IET Communications, 2016, 10(8): 980–986. doi: 10.1049/iet-com.2015.0976
    [38]
    PANOUI A, LAMBOTHARAN S, and CHAMBERS J A. Game theoretic power allocation for a multistatic radar network in the presence of estimation error[C]. 2014 Sensor Signal Processing for Defence, Edinburgh, UK, 2014: 1–5.
    [39]
    DELIGIANNIS A, PANOUI A, LAMBOTHARAN S, et al. Game-theoretic power allocation and the nash equilibrium analysis for a multistatic MIMO radar network[J]. IEEE Transactions on Signal Processing, 2017, 65(24): 6397–6408. doi: 10.1109/TSP.2017.2755591
    [40]
    DELIGIANNIS A and LAMBOTHARAN S. A Bayesian game theoretic framework for resource allocation in multistatic radar networks[C]. 2017 IEEE Radar Conference, Seattle, USA, 2017: 546–551.
    [41]
    WAN Kaifang, GAO Xiaoguang, LI Bo, et al. Optimal power management for antagonizing between radar and jamming based on continuous game theory[J]. Transactions of Nanjing University of Aeronautics and Astronautics, 2014, 31(4): 386–393. doi: 10.3969/j.issn.1005-1120.2014.04.005
    [42]
    SUN Bin, CHEN Haowen, WEI Xizhang, et al. Power allocation for range-only localisation in distributed multiple-input multiple-output radar networks - a cooperative game approach[J]. IET Radar, Sonar & Navigation, 2014, 8(7): 708–718. doi: 10.1049/iet-rsn.2013.0260
    [43]
    CHEN Haowen, TA Shiying, and SUN Bin. Cooperative game approach to power allocation for target tracking in distributed MIMO radar sensor networks[J]. IEEE Sensors Journal, 2015, 15(10): 5423–5432. doi: 10.1109/JSEN.2015.2431261
    [44]
    SHI C G, SALOUS S, ZHOU J J, et al. Cooperative game-theoretic power allocation algorithm for target detection in radar network[C]. The 32nd General Assembly and Scientific Symposium of the International Union of Radio Science, Montreal, Canada, 2017: 1–4.
    [45]
    SHI Chenguang, SALOUS S, WANG Fei, et al. Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy[J]. Radio Science, 2017, 52(8): 1030–1045. doi: 10.1002/2017RS006332
    [46]
    LIU Yanqing and DONG Liang. Spectrum sharing in MIMO cognitive radio networks based on cooperative game theory[J]. IEEE Transactions on Wireless Communications, 2014, 13(9): 4807–4820. doi: 10.1109/TWC.2014.2331287
    [47]
    GAO Hai, WANG Jian, JIANG Chunxiao, et al. Equilibrium between a statistical MIMO radar and a jammer[C]. IEEE Radar Conference, Arlington, USA, 2015: 461–466.
    [48]
    WONDERLEY D, SELEE T, and CHAKRAVARTHY V. Game theoretic decision support framework for electronic warfare applications[C]. 2016 IEEE Radar Conference, Philadelphia, USA, 2016: 1–5.
    [49]
    WANG Lulu, WANG Liandong, ZENG Yonghu, et al. Radar and jammer power allocation strategy based on matrix game[J]. Procedia Computer Science, 2017, 107: 478–483. doi: 10.1016/j.procs.2017.03.093
    [50]
    DELIGIANNIS A, ROSSETTI G, PANOUI A, et al. Power allocation game between a radar network and multiple jammers[C]. 2016 IEEE Radar Conference, Philadelphia, USA, 2016: 1–5.
    [51]
    HENAREH N and NOROUZI Y. Game theory modeling of MIMO radar and ARM missile engagement[C]. The 2016 8th International Symposium on Telecommunications, Tehran, Iran, 2016: 515–520.
    [52]
    SONG Xiufeng, WILLETT P, ZHOU Shengli, et al. The power game between a MIMO radar and jammer[C]. 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, Kyoto, Japan, 2012: 5185–5188.
    [53]
    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.2011.216925
    [54]
    ZHANG Xinxun, MA Hui, WANG Jianlai, et al. Game theory design for deceptive jamming suppression in polarization MIMO radar[J]. IEEE Access, 2019, 7: 114191–114202. doi: 10.1109/ACCESS.2019.2931604
    [55]
    SONG Xiufeng, WILLETT P, and ZHOU Shengli. Jammer detection and estimation with MIMO radar[C]. 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2012: 1312–1316.
    [56]
    LI Kang, JIU Bo, and LIU Hongwei. Game theoretic strategies design for monostatic radar and jammer based on mutual information[J]. IEEE Access, 2019, 7: 72257–72266. doi: 10.1109/ACCESS.2019.2920398
    [57]
    NOROUZI T and NOROUZI Y. Scheduling the usage of radar and jammer during peace and war time[J]. IET Radar, Sonar & Navigation, 2012, 6(9): 929–936. doi: 10.1049/iet-rsn.2012.0049
    [58]
    LIU Xiaowen, ZHANG Qun, LUO Ying, et al. ISAR imaging task allocation for multi-target in radar network based on potential game[J]. IEEE Sensors Journal, 2019, 19(23): 11192–11204. doi: 10.1109/JSEN.2019.2936423
    [59]
    PIEZZO M, AUBRY A, and BUZZI S, et al. Non-cooperative code design in radar networks: A game-theoretic approach[J]. EURASIP Journal on Advances in Signal Processing, 2013, 2013: 63. doi: 10.1186/1687-6180-2013-63
    [60]
    GOGINENI S and NEHORAI A. Game theoretic design for polarimetric MIMO radar target detection[J]. Signal Processing, 2012, 92(5): 1281–1289. doi: 10.1016/j.sigpro.2011.11.024
    [61]
    DELIGIANNIS A, LAMBOTHARAN S, and CHAMBERS J A. Game theoretic analysis for MIMO radars with multiple targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(6): 2760–2774. doi: 10.1109/TAES.2016.150699
    [62]
    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
    [63]
    DANIYAN A, GONG Yu, and LAMBOTHARAN S. Game theoretic data association for multi-target tracking with varying number of targets[C]. 2016 IEEE Radar Conference, Philadelphia, USA, 2016: 1–4.
    [64]
    DANIYAN A, ALDOWESH A, GONG Yu, et al.. Data association using game theory for multi-target tracking in passive bistatic radar[C]. 2017 IEEE Radar Conference, Seattle, USA, 2017: 42–46.
    [65]
    CHAVALI P and NEHORAI A. Concurrent particle filtering and data association using game theory for tracking multiple maneuvering targets[J]. IEEE Transactions on Signal Processing, 2013, 61(20): 4934–4948. doi: 10.1109/TSP.2013.2272923
    [66]
    CHAVALI P and NEHORAI A. Distributed data association for multiple-target tracking using game theory[C]. 2013 IEEE Radar Conference, Ottawa, Canada, 2013: 1–6.
    [67]
    BOGDANOVIĆ N, DRIESSEN H, and YAROVOY A. Track selection in multifunction radars for multi-target tracking: An anti-coordination game[C]. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, Shanghai, China, 2016: 3131–3135.
    [68]
    BOGDANOVIĆ N, DRIESSEN H, and YAROVOY A G. Target selection for tracking in multifunction radar networks: Nash and correlated equilibria[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(5): 2448–2462. doi: 10.1109/TAES.2018.2819798
    [69]
    LEE S J, PARK S S, and CHOI H L. Potential game-based non-myopic sensor network planning for multi-target tracking[J]. IEEE Access, 2018, 6: 79245–79257. doi: 10.1109/ACCESS.2018.2885027
    [70]
    XIE Mingchi, YI Wei, and KONG Lingjiang. Joint selection and power allocation strategy for target tracking in decentralized multiple radar systems[C]. 2016 IEEE Radar Conference, Philadelphia, USA, 2016: 1–6.
    [71]
    XIE Mingchi, YI Wei, and KONG Lingjiang. Joint node selection and power allocation for multitarget tracking in decentralized radar networks[C]. The 2016 19th International Conference on Information Fusion, Heidelberg, Germany, 2016: 45–52.
    [72]
    XIE Mingchi, YI Wei, KIRUBARAJAN T, et al. Joint node selection and power allocation strategy for multitarget tracking in decentralized radar networks[J]. IEEE Transactions on Signal Processing, 2018, 66(3): 729–743. doi: 10.1109/TSP.2017.2777394
    [73]
    CHAVALI P and NEHORAI A. Scheduling and power allocation in a cognitive radar network for multiple-target tracking[J]. IEEE Transactions on Signal Processing, 2012, 60(2): 715–729. doi: 10.1109/TSP.2011.2174989
    [74]
    HAN Keyong and NEHORAI A. Joint frequency-hopping waveform design for MIMO radar estimation using game theory[C]. 2013 IEEE Radar Conference, Ottawa, Canada, 2013: 1–4.
    [75]
    HAN Keyong and NEHORAI A. Jointly optimal design for MIMO radar frequency-hopping waveforms using game theory[J]. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(2): 809–820. doi: 10.1109/TAES.2015.140408
    [76]
    PANOUI A, LAMBOTHARAN S, and CHAMBERS J A. Game theoretic distributed waveform design for multistatic radar networks[J]. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(4): 1855–1865. doi: 10.1109/TAES.2016.150378
    [77]
    SHI Chenguang, WANG Fei, SALOUS S, et al. Distributed power allocation for spectral coexisting multistatic radar and communication systems based on stackelberg game[C]. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK, 2019: 4265–4269.
    [78]
    SHI Chenguang, WANG Fei, SALOUS S, et al. A robust stackelberg game-based power allocation scheme for spectral coexisting multistatic radar and communication systems[C]. 2019 IEEE Radar Conference, Boston, USA, 2019: 1–5.
    [79]
    SHI Chenguang, DING Lintao, WANG Fei, et al. Low probability of intercept-based collaborative power and bandwidth allocation strategy for multi-target tracking in distributed radar network system[J]. IEEE Sensors Journal, 2020, 20(12): 6367–6377. doi: 10.1109/JSEN.2020.2977328
    [80]
    SHI Chenguang, QIU Wei, SALOUS S, et al. Power control scheme for spectral coexisting multistatic radar and massive MIMO communication systems under uncertainties: A robust Stackelberg game model[J]. Digital Signal Processing, 2019, 94: 146–155. doi: 10.1016/j.dsp.2019.05.007
    [81]
    MISHRA K V, MARTONE A, and ZAGHLOUL A I. Power allocation games for overlaid radar and communications[C]. 2019 URSI Asia-Pacific Radio Science Conference, New Delhi, India, 2019: 1–4.
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