Robust cognitive transmit waveform and receive filter design for airborne MIMO radar in signal-dependent clutter environment

被引:12
|
作者
Zhou, Qingsong [1 ]
Li, Zhihui [1 ]
Shi, Junpeng [1 ]
Mao, Yunxiang [1 ]
机构
[1] Natl Univ Def Technol, Hefei 230037, Peoples R China
基金
中国国家自然科学基金;
关键词
Airborne multiple-input multiple-output radar; Transmit waveform and receive filter; Constant modulus; Similarity constraint; Iterative optimization algorithm; CODE DESIGN; TARGET DETECTION; OPTIMIZATION; STAP; INFORMATION; SEQUENCE; PERFORMANCE; ACCURACY; PAPR; BANK;
D O I
10.1016/j.dsp.2020.102709
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
This paper investigates the robust cognitive joint design of transmit waveform and receive filter to improve the system performance of airborne multiple-input multiple-output (MIMO) radar. Considering the target Doppler frequency and spatial cone angle uncertainties are present, we formulate the averaged signal-to-clutter-plus-noise ratio (SCNR) as the optimization goal. Specifically, the averaged SCNR is maximized under only constant modulus constraint and that under constant modulus and similarity constraints. Four iterative optimization algorithms are developed to deal with the joint design problem. The first kind of iterative optimization algorithm is based on semidefinite programming (SDP) relaxation and randomization or rank-one decomposition techniques. The second kind of computational efficient iterative optimization algorithm utilizes the fractional programming and power method-like iteration. The proposed algorithms can achieve a monotonic output SCNR enhancement and are robust against the inaccuracies of target parameters. Several simulations results are implemented to validate the superiority of the proposed algorithms considering the output SCNR, space-time beampattern and computational complexity. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页数:15
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