Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar
Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar
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DOI：
10.1109/tsp.2016.2633242
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发表时间：
2017-03-01
影响因子：
5.4
通讯作者：
Kong, Lingjiang
中科院分区：
文献类型：
--
作者：
Cui, Guolong;Yu, Xianxiang;Kong, Lingjiang
研究了多输入多输出雷达空时发射码（STTC）和空时接收滤波器（STRF）的设计，以提高在信号相关干扰下的动目标检测能力。一个迭代的过程，其收敛性的分析证明，设计最大化的信号干扰加噪声比（SINR）占两个相似性约束和恒模要求的探测波形。算法的每次迭代都涉及到隐凸问题的求解。具体而言，无论是凸问题（其解决方案是在封闭的形式提供）和一组分数规划问题，可以在多项式时间内通过Dinkelback的程序，解决。计算复杂度与迭代次数成线性关系，与STTC和STRF的大小成多项式关系。特别是，所提出的技术提供了一个单调的信干噪比的改善，没有限制的相似性约束的大小，并确保收敛到一个固定点填补这些重要的空白，在公开文献。此外，报告的结果突出表明，新设计的过程优于在优化的SINR值和计算复杂度比现有的同行。
This paper deals with the design of multiple-input multiple-output radar space-time transmit code (STTC) and space-time receive filter (STRF) to enhance moving targets detection in the presence of signal-dependent interferences. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to interference plus noise ratio (SINR) accounting for both a similarity constraint and a constant modulus requirement on the probing waveform. Each iteration of the algorithm involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problems, that can be globally solved in polynomial time via the Dinkelback's procedure, are settled. The computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. In particular, the proposed technique provides a monotonic SINR improvement without limitations on the size of the similarity constraint and ensures convergence to a stationary point filling these important gaps in the open literature. Besides, the reported results highlight that the new devised procedure outperforms both in the optimized SINR value and the computational complexity than the available counterparts.