Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)

Shi Chen-guang; Wang   Fei; Zhou  Jian-jiang; Chen   Jun

doi:10.3724/SP.J.1300.2014.13140

Volume 3 Issue 4

Dec. 2014

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Shi Chen-guang, Wang Fei, Zhou Jian-jiang, Chen Jun. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)[J]. Journal of Radars, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140

Citation:

Shi Chen-guang, Wang Fei, Zhou Jian-jiang, Chen Jun. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)[J]. Journal of Radars, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140

Citation:

Shi Chen-guang, Wang Fei, Zhou Jian-jiang, Chen Jun. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)[J]. Journal of Radars, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140

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Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)

doi: 10.3724/SP.J.1300.2014.13140

(Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Funds:

Supported by the National Natural Science Foundation of China (61371170), Funding of Jiangsu Innovation Program for Graduate Education (CXLX13_154), the Fundamental Research Funds for the Central Universities, the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA), and Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics.

Received Date: 2013-12-23
Rev Recd Date: 2014-05-29
Publish Date: 2014-08-28

Abstract

Abstract

A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI) technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA) is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.
- Radar network systems,
- Low Probability of Intercept (LPI),
- Schleher intercept factor,
- Target tracking,
- Kullback-Leibler (KL) divergence