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

机译：强大的认知传输波形和信号依赖性杂波环境中的机载MIMO雷达接收滤波器设计

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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.
机译：本文调查了传输波形的强大认知关节设计，接收过滤器，提高机载多输入多输出（MIMO）雷达的系统性能。考虑到存在目标多普勒频率和空间锥角不确定性，我们将平均信号到杂波和噪声比（SCNR）分配为优化目标。具体地，平均SCNR仅在恒定模数约束下最大化，并且在恒定模量和相似度约束下。开发了四种迭代优化算法来处理联合设计问题。第一种迭代优化算法基于SEMIDEFINITE编程（SDP）松弛和随机化或秩一分解技术。第二种计算有效的迭代优化算法利用分数编程和电源方法迭代。所提出的算法可以实现单调输出SCNR增强，并且对目标参数的不准确性是鲁棒的。实现了几种模拟结果以验证考虑输出SCNR，时空波线图案和计算复杂性的提出算法的优越性。 （c）2020 Elsevier Inc.保留所有权利。

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