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Knowledge-Based Spatial-Temporal Hierarchical MIMO Radar Waveform Design Method for Target Detection in Heterogeneous Clutter Zone

机译:异构杂波区域目标检测的基于知识的时空分层MIMO雷达波形设计方法

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摘要

Knowledge-based MIMO radar waveform design for target detection in heterogeneous clutter zone is addressed in this paper. In order to improve the detection probability efficiently, a new optimization cost function is developed via minimizing the output clutter peak level and peak sidelobe level of the correlation function on the premise of maintaining the output target signal energy. With constant modulus constraint of transmit waveform, the new cost function is an NP-hard problem. To tackle this problem, a spatial-temporal hierarchical optimization approach is proposed that can decompose the original problem to two hierarchical subproblems approximately. On the foundation of convex programming and cyclic algorithm, the first subproblem, i.e., knowledge-based transmit beampattern design, can be solved effectively. Based on CVX programming and the bi-iterative method, the joint mainlobe synthesized signal and mismatched receiving filter optimization method is proposed to solve the second subproblem. Numerical results show the efficiency of the proposed method.
机译:本文讨论了用于异类杂波区域目标检测的基于知识的MIMO雷达波形设计。为了有效地提高检测概率,在保持输出目标信号能量的前提下,通过最小化相关函数的输出杂波峰值水平和峰值旁瓣水平,开发了一种新的优化代价函数。在发射波形具有恒定模量约束的情况下,新的成本函数是一个NP难题。为了解决这个问题,提出了一种时空分层优化方法,可以将原始问题近似分解为两个分层子问题。在凸规划和循环算法的基础上,可以有效地解决第一个子问题,即基于知识的发射波束图案设计。基于CVX编程和双向迭代方法,提出了联合主瓣合成信号和失配接收滤波器的优化方法,以解决第二个子问题。数值结果表明了该方法的有效性。

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