Joint Transmitter Selection and Resource Management Strategy Based on Low Probability of Intercept Optimization for Distributed Radar Networks

被引:33
作者
Shi, C. G. [1 ]
Wang, F. [1 ]
Salous, S. [2 ]
Zhou, J. J. [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Key Lab Radar Imaging & Microwave Photon, Minist Educ, Nanjing, Jiangsu, Peoples R China
[2] Univ Durham, Sch Engn & Comp Sci, Durham, England
基金
中国国家自然科学基金;
关键词
l probability of intercept (LPI); intercept probability; transmitter selection; resource management; target tracking; radar networks; WAVE-FORM SELECTION; TARGET-TRACKING; POWER ALLOCATION; MIMO RADAR; SYSTEMS; INFORMATION; BENCHMARK; CLUTTER; DESIGN; TIME;
D O I
10.1029/2018RS006584
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
In this paper, a joint transmitter selection and resource management (JTSRM) strategy based on low probability of intercept (LPI) is proposed for target tracking in distributed radar network system. The basis of the JTSRM strategy is to utilize the optimization technique to control transmitting resources of radar networks in order to improve the LPI performance while guaranteeing a specified target-tracking accuracy. The weighted intercept probability and transmit power of radar networks is defined and subsequently employed as the optimization criterion for the JTSRM strategy. The resulting optimization problem is to minimize the LPI performance criterion of radar networks by optimizing the revisit interval, dwell time, transmitter selection, and transmit power subject to a desired target-tracking performance and some resource constraints. An efficient and fast three-step solution technique is also developed to solve this problem. The presented mechanism implements the optimal working parameters based on the feedback information in the tracking recursion cycle in order to improve the LPI performance for radar networks. Numerical simulations are provided to verify the superior performance of the proposed JTSRM strategy.
引用
收藏
页码:1108 / 1134
页数:27
相关论文
共 47 条
[1]   Benchmark for radar allocation and tracking in ECM [J].
Blair, WD ;
Watson, GA ;
Kirubarajan, T ;
Bar-Shalom, Y .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1998, 34 (04) :1097-1114
[2]   Adaptive MFR parameter control: fixed against variable probabilities of detection [J].
Boers, Y ;
Driessen, H ;
Zwaga, J .
IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION, 2006, 153 (01) :2-6
[3]  
Boyd L., 2004, CONVEX OPTIMIZATION
[4]  
Chen J, 2014, 2014 IEEE CHINA SUMMIT & INTERNATIONAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (CHINASIP), P777, DOI 10.1109/ChinaSIP.2014.6889350
[5]  
Chen T, 2013, CONTEMPORARY THEORY AND PRAGMATIC APPROACHES IN FUZZY COMPUTING UTILIZATION, P1, DOI 10.4018/978-1-4666-1870-1
[6]   Adaptive Distributed MIMO Radar Waveform Optimization Based on Mutual Information [J].
Chen, Yifan ;
Nijsure, Yogesh ;
Yuen, Chau ;
Chew, Yong Huat ;
Ding, Zhiguo ;
Boussakta, Said .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2013, 49 (02) :1374-1385
[7]   Adaptive resource management algorithm for target tracking in radar network based on low probability of intercept [J].
Shi, Chenguang ;
Zhou, Jianjiang ;
Wang, Fei .
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING, 2018, 29 (04) :1203-1226
[8]  
DAEIPOUR E, 1994, PROCEEDINGS OF THE 1994 AMERICAN CONTROL CONFERENCE, VOLS 1-3, P2093
[9]   Spatial diversity in radars-models and detection performance [J].
Fishler, E ;
Haimovich, A ;
Blum, RS ;
Cimini, LJ ;
Chizhik, D ;
Valenzuela, RA .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (03) :823-838
[10]  
Godrich H, 2012, PR IEEE SEN ARRAY, P153, DOI 10.1109/SAM.2012.6250453