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作 者:陈建明 焦爽 陈光辉 CHEN Jian-ming;JIAO Shuang;CHEN Guang-hui(College of Electric Power,North China University of Water Resources and Electric Power,Henan 450046,China;College of Microelectronics and Communication Engineering,Chongqing University,Chongqing 400044,China)
机构地区:[1]华北水利水电大学电力学院,河南郑州450046 [2]重庆大学微电子与通信工程学院,重庆400044
出 处:《计算机仿真》2022年第3期17-21,257,共6页Computer Simulation
基 金:国家自然科学基金(U1504622)。
摘 要:针对仅发射分集的多输入多输出(Multiple Input Multiple Output,MIMO)雷达在低信噪比(Signal-to-Noise Ratio,SNR)下来波方向(Direction of Arrival,DOA)的估计精度被严重降低的问题,提出了一种改进的多重信号分类(Multiple Signal Classification,MUSIC)方法。改进方法首先引入线性运算代替MUSIC算法的特征值分解,降低算法的计算量;其次,MUSIC算法的空间谱函数在DOA处是断点且趋近于较大值,而求导可以使断点处的峰值更加明显,因此通过对空间谱函数求一阶导数构造一个新的空间谱函数,可以有效的提高低SNR下DOA的估计精度。仿真结果表明,改进算法在低SNR下有效的提高了仅发射分集的MIMO雷达的DOA估计精度。Aiming at the problem that the DOA estimation accuracy of MIMO radar with transmit-only diversity is seriously reduced under low SNR,this paper proposes an improved MUSIC method.Firstly,linear operations are used to replace the eigenvalue decomposition of MUSIC algorithm,which reduces the amount of calculation of the algorithm.Secondly,the spatial spectral function of MUSIC algorithm is a breakpoint and tends to a larger value at DOA.Derivation can make the peak of spatial spectrum at the breakpoint more obvious.Thus,a new spatial spectral function is constructed by finding the first derivative of spatial spectral function of MUSIC,which can effectively improve the DOA estimation accuracy under low SNR.Simulation results also show that this algorithm can effectively improves the DOA estimation accuracy of MIMO radar with transmit-only diversity under low SNR.
关 键 词:波达方向 多重信号分类算法 多输入多输出雷达 低信噪比 高精度
分 类 号:TN911.7[电子电信—通信与信息系统]
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