Waveform Design for Compressive Sensing Radar in the Presence of Interference and Noise
HE Ya-peng1,2, ZHU Xiao-hua1, LI Hong-tao1, GU Chen1
1. School of Electronic and Optical Engineering, Nanjing University Science and Technology, Nanjing, Jiangsu 210094, China;
2. China Academy of Space Technology at Xi'an, Xi'an, Shaanxi 710000, China
摘要 为改善压缩感知雷达（Compressive Sensing Radar，CSR）在干扰噪声背景下目标检测及距离-多普勒参数的估计性能，该文提出一种感知矩阵平均相干系数（Averaged Coherence of the Sensing Matrix，ACSM）与信干噪比（Signal to Interference and Noise Ratio，SINR）联合优化的波形设计方法.文中首先建立了CSR距离-多普勒二维参数感知模型，推导了波形联合优化设计的目标函数，其次以多相编码信号作为优化码型并采用模拟退火（Simulated Annealing，SA）算法对目标函数进行优化求解.与传统CSR波形相比，优化设计的波形提高了CSR在低信干噪比条件下的成功检测概率，同时有效降低了目标距离-多普勒参数估计误差，由此改善了CSR在干扰噪声背景下的距离-多普勒成像质量.计算机仿真验证了该方法的有效性.
Abstract：Aiming at improving the performance of targets detection and range-Doppler parameters estimation for compressive sensing radar (CSR) amid interference and noise,a CSR joint optimal waveform design method is proposed to minimize the averaged coherence of the sensing matrix (ACSM) and the signal to interference and noise ratio (SINR) simultaneously.First,a CSR two-dimensional sensing model for range-Doppler estimation is established and a waveform joint optimization object function is derived.Then,the simulated annealing (SA) algorithm is employed to obtain the optimal solution,where the poly phase coded signal is taken into account.Compared with the traditional CSR waveforms,the optimized waveform enhances the CSR successful detection probability in the low SINR conditions,and also effectively reduces the target range-Doppler parameter estimation error,thereby improving the CSR range-Doppler imaging quality.Simulation results show the effectiveness of the proposed method.
贺亚鹏, 朱晓华, 李洪涛, 顾陈. 噪声干扰背景下压缩感知雷达波形优化设计[J]. 电子学报, 2014, 42(3): 469-476.
HE Ya-peng, ZHU Xiao-hua, LI Hong-tao, GU Chen. Waveform Design for Compressive Sensing Radar in the Presence of Interference and Noise. Chinese Journal of Electronics, 2014, 42(3): 469-476.
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2014, Vol. 42 
