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Low PAR robust waveform design of cognitive radar for extended target detection under random TIR

机译:随机TIR下用于扩展目标检测的认知雷达的低PAR稳健波形设计

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The existing joint design methods of transmit waveform and receive filter for cognitive radar(CR) radar are all based on the precise previous information about the target and interference, also the efficiency of transmitter has not been taken into account in practical applications. For these problems, a low peak-to-average power ratio (PAR) robust waveform and receive filter design algorithm is proposed under the assumption of random target impulse response (TIR) and signal-dependent interference. So a signal model is constructed according to the Max-Min method and the value of the uncertainty region about the covariance matrix of TIR and the clutter impulse response (CIR) under the worst-case signal-to-interference-and-noise rate (SINR) is given. Then the semi-definite relaxation (SDR) method is used to transform the nonconvex problem into a convex problem to maximize the worst-case SINR. On the basis of this, the optimal transmit waveform and receiver filter are obtained by using cyclic iteration idea. The simulation results show the effectiveness of the proposed method.
机译:现有的认知雷达(CR)雷达的发射波形和接收滤波器联合设计方法都是基于关于目标和干扰的精确的先前信息,在实际应用中也没有考虑到发射机的效率。针对这些问题,在随机目标脉冲响应(TIR)和信号相关干扰的假设下,提出了一种低峰均功率比(PAR)鲁棒波形和接收滤波器设计算法。因此,根据Max-Min方法以及在最坏情况下的信噪比(TIR)下杂波脉冲响应(CIR)的TIR协方差矩阵的不确定区域的值,构建信号模型。 SINR)。然后使用半定松弛(SDR)方法将非凸问题转换为凸问题,以使最坏情况的SINR最大化。在此基础上,采用循环迭代思想,得到了最优的发射波形和接收滤波器。仿真结果表明了该方法的有效性。

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