CLC number: TN958
On-line Access: 2022-04-20
Received: 2020-11-19
Revision Accepted: 2022-05-04
Crosschecked: 2021-06-23
Cited: 0
Clicked: 5165
Citations: Bibtex RefMan EndNote GB/T7714
Bin HE, Hongtao SU. Supermodular interference suppression game for multistatic MIMO radar networks and multiple jammers with multiple targets[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2000652 @article{title="Supermodular interference suppression game for multistatic MIMO radar networks and multiple jammers with multiple targets", %0 Journal Article TY - JOUR
多目标存在的多基地MIMO组网雷达与多干扰机之间的超模干扰抑制博弈1西安电子科技大学雷达信号处理国家重点实验室,中国西安市,710071 2中国电子科技集团公司第五十四研究所,中国石家庄市,050081 摘要:为应对新一代电子战的威胁,本文建立一种非合作对抗博弈模型,分析了多基地多入多出(MIMO)雷达与多干扰机之间的功率分配和干扰抑制问题。首先,根据功率分配策略,构造了一种具有固定权矢量的超模功率分配博弈框架。同时,建立了一种极大化雷达效用函数的约束优化模型。基于效用函数,分别得到雷达和干扰机的最佳功率分配策略,并证明该超模博弈的纳什均衡的存在性和唯一性。然后,提出一种具有固定权矢量的超模博弈算法,该算法收敛于博弈的纳什均衡。此外,采用自适应波束形成方法抑制互通道干扰,如干扰机到雷达的直达波干扰。为抑制这些干扰,提出一种联合功率分配和波束形成的超模博弈算法。该算法在保证最佳功率分配的同时,提高了MIMO雷达的干扰抑制能力。最后通过数值结果验证了两种算法的优越性和收敛性。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
Reference[1]Bachmann DJ, Evans RJ, Moran B, 2011. Game theoretic analysis of adaptive radar jamming. IEEE Trans Aerosp Electron Syst, 47(2):1081-1100. [2]Bogdanović N, Driessen H, Yarovoy AG, 2018. Target selection for tracking in multifunction radar networks: Nash and correlated equilibria. IEEE Trans Aerosp Electron Syst, 54(5):2448-2462. [3]Chavali P, Nehorai A, 2013. Concurrent particle filtering and data association using game theory for tracking multiple maneuvering targets. IEEE Trans Signal Process, 61(20):4934-4948. [4]Chen HW, Ta SY, Sun B, 2015. Cooperative game approach to power allocation for target tracking in distributed MIMO radar sensor networks. IEEE Sens J, 15(10):5423-5432. [5]Chernyak VS, 1998. Fundamentals of Multisite Radar Systems: Multistatic Radars and Multiradar Systems. Routledge, London, UK. [6]Dahrouj H, Yu W, 2010. Coordinated beamforming for the multicell multi-antenna wireless system. IEEE Trans Wirel Commun, 9(5):1748-1759. [7]Deligiannis A, Lambotharan S, Chambers JA, 2016a. Game theoretic analysis for MIMO radars with multiple targets. IEEE Trans Aerosp Electron Syst, 52(6):2760-2774. [8]Deligiannis A, Rossetti G, Panoui A, et al., 2016b. Power allocation game between a radar network and multiple jammers. Proc IEEE Radar Conf, p.1-5. [9]Deligiannis A, Panoui A, Lambotharan S, et al., 2017. Game-theoretic power allocation and the Nash equilibrium analysis for a multistatic MIMO radar network. IEEE Trans Signal Process, 65(24):6397-6408. [10]Frost O III, 1972. An algorithm for linearly constrained adaptive array processing. Proc IEEE, 60(8):926-935. [11]Gogineni S, Nehorai A, 2012. Game theoretic design for polarimetric MIMO radar target detection. Signal Process, 92(5):1281-1289. [12]Han KY, Nehorai A, 2016. Jointly optimal design for MIMO radar frequency-hopping waveforms using game theory. IEEE Trans Aerosp Electron Syst, 52(2):809-820. [13]Hershey JE, 1990. Counter-intuitive results cast in an electronic warfare framework. IEEE Trans Aerosp Electron Syst, 26(3):506-510. [14]Lan X, Li W, Wang XL, et al., 2015. MIMO radar and target Stackelberg game in the presence of clutter. IEEE Sens J, 15(12):6912-6920. [15]Li J, Stoica P, 2009. MIMO Radar Signal Processing. John Wiley & Sons, New York, USA. [16]Li ZJ, Xie JW, Zhang HW, et al., 2020. Adaptive sensor scheduling and resource allocation in netted collocated MIMO radar system for multi-target tracking. IEEE Access, 8:109976-109988. [17]Liu XW, Zhang Q, Luo Y, et al., 2019. ISAR imaging task allocation for multi-target in radar network based on potential game. IEEE Sens J, 19(23):11192-11204. [18]Moragrega A, Closas P, Ibars C, 2013. Supermodular game for power control in TOA-based positioning. IEEE Trans Signal Process, 61(12):3246-3259. [19]Niu C, Zhang YS, Guo JR, 2018. Pareto optimal layout of multistatic radar. Signal Process, 142:152-156. [20]Norouzi T, Norouzi Y, 2012. Scheduling the usage of radar and jammer during peace and war time. IET Radar Sonar Navig, 6(9):929-936. [21]Panoui A, Lambotharan S, Chambers JA, 2016. Game theoretic distributed waveform design for multistatic radar networks. IEEE Trans Aerosp Electron Syst, 52(4):1855-1865. [22]Piezzo M, Aubry A, Buzzi S, et al., 2013. Non-cooperative code design in radar networks: a game-theoretic approach. EURASIP J Adv Signal Process, 2013(1):63. [23]Rihan M, Huang L, 2018. Non-orthogonal multiple access based cooperative spectrum sharing between MIMO radar and MIMO communication systems. Dig Signal Process, 83:107-117. [24]Saad W, Han Z, Debbah M, et al., 2009. Coalitional game theory for communication networks. IEEE Signal Process Mag, 26(5):77-97. [25]Shi CG, Wang F, Sellathurai M, et al., 2018. Non-cooperative game-theoretic distributed power control technique for radar network based on low probability of intercept. IET Signal Process, 12(8):983-991. [26]Shi CG, Wang F, Salous S, et al., 2019a. Distributed power allocation for spectral coexisting multistatic radar and communication systems based on Stackelberg game. Proc IEEE Int Conf on Acoustics, Speech and Signal Processing, p.4265-4269. [27]Shi CG, Qiu W, Wang F, et al., 2019b. Power control scheme for spectral coexisting multistatic radar and massive MIMO communication systems under uncertainties: a robust Stackelberg game model. Dig Signal Process, 94:146-155. [28]Shi CG, Ding LT, Wang F, et al., 2020a. Joint target assignment and resource optimization framework for multitarget tracking in phased array radar network. IEEE Syst J, 15(3):4379-4390. [29]Shi CG, Ding LT, Wang F, et al., 2020b. Low probability of intercept-based collaborative power and bandwidth allocation strategy for multi-target tracking in distributed radar network system. IEEE Sens J, 20(12):6367-6377. [30]Shi CG, Wang YJ, Wang F, et al., 2021. Joint optimization scheme for subcarrier selection and power allocation in multicarrier dual-function radar-communication system. IEEE Syst J, 15(1):947-958. [31]Song XF, Willett P, Zhou SL, et al., 2012. The MIMO radar and jammer games. IEEE Trans Signal Process, 60(2):687-699. [32]Souden M, Benesty J, Affes S, 2010. A study of the LCMV and MVDR noise reduction filters. IEEE Trans Signal Process, 58(9):4925-4935. [33]Stephens JP, 1996. Advances in signal processing technology for electronic warfare. IEEE Aerosp Electron Syst Mag, 11(11):31-38. [34]Sun B, Chen HW, Wei XZ, et al., 2014. Power allocation for range-only localisation in distributed multiple-input multiple-output radar networks—a cooperative game approach. IET Radar Sonar Navig, 8(7):708-718. [35]Tang B, Li J, Zhang Y, et al., 2016. Design of MIMO radar waveform covariance matrix for clutter and jamming suppression based on space time adaptive processing. Signal Process, 121:60-69. [36]Tang L, Gong XW, Wu JH, et al., 2013. Target detection in bistatic radar networks: node placement and repeated security game. IEEE Trans Wirel Commun, 12(3):1279-1289. [37]Wang LL, Zhang Y, 2019. MIMO radar and jammer power allocation game based on MMSE. Proc 20th Int Radar Symp, p.1-7. [38]Yi W, Yuan Y, Hoseinnezhad R, et al., 2020. Resource scheduling for distributed multi-target tracking in netted colocated MIMO radar systems. IEEE Trans Signal Process, 68:1602-1617. [39]Yu HL, Zhang J, Zhang LR, et al., 2019. Polarimetric multiple-radar architectures with distributed antennas for discriminating between radar targets and deception jamming. Dig Signal Process, 90:46-53. [40]Yuan Y, Yi W, Kirubarajan T, et al., 2019. Scaled accuracy based power allocation for multi-target tracking with colocated MIMO radars. Signal Process, 158:227-240. [41]Yukawa M, Sung Y, Lee G, 2013. Dual-domain adaptive beamformer under linearly and quadratically constrained minimum variance. IEEE Trans Signal Process, 61(11):2874-2886. 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