Mutual information-based LPI optimisation for radar network

被引：6

作者：

Shi, Chenguang ^{[1
]}

Zhou, Jianjiang ^{[1
]}

Wang, Fei ^{[1
]}

Chen, Jun ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Minist Educ, Key Lab Radar Imaging & Microwave Photon, Nanjing 210000, Jiangsu, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ELECTRONICS | 2015年 / 102卷 / 07期

基金：

中国国家自然科学基金;

关键词：

low probability of intercept (LPI); radar network; Schleher intercept factor; mutual information (MI); MIMO RADAR; TARGET LOCALIZATION; POWER ALLOCATION; LOW PROBABILITY;

D O I：

10.1080/00207217.2014.964335

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

引用

页码：1114 / 1131

页数：18

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