柱面共形阵列DOA与极化参数高效联合估计算法  

A DOA and Polarization Parameters Efficient Estimation Algorithm of Cylindrical Conformal Array Antenna

作　　者：齐子森[1] 彭大林 许华[1] 宋佰霖 QI Zisen;PENG Dalin;XU Hua;SONG Bailin(Information and Navigation College,Air Force Engineering University,Xi’an 710077,China;Unit 95865,Beijing 102200,China)

机构地区：[1]空军工程大学信息与导航学院,西安710077 [2]95865部队,北京102200

出　　处：《空军工程大学学报（自然科学版）》2021年第3期55-61,共7页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：国家自然科学基金(61601500)。

摘　　要：针对共形阵列天线信源方位与极化状态联合估计算法计算量大的问题,给出了一种基于多级维纳滤波器前向递推的柱面共形阵列天线信源方位与极化参数高效联合估计算法。新算法推导了柱面共形阵列天线多级维纳滤波器的前向递推。算法以某一期望信号的训练信号为已知条件,通过多级维纳滤波器的前向递推,来实现信号子空间和噪声子空间的快速估计,避免了协方差矩阵估计与特征值分解,大大减少了已有联合估计算法的运算量,使计算量由原来的O(N^(3)+N^(2)L)降低到O(N^(2)L)。仿真实验表明:算法在降低算法复杂度的同时,可保证算法的估计精度,在信噪比大于10 dB时,与已有算法具有近似相同的估计精度,证明了算法的有效性。Aimed at the problem that computation measure is comparatively heavy by the joint estimation algorithm of information source azimuth and polarization state of conformal array antenna,a forward recursion method of multi-stage wiener filter for cylindrical conformal array antenna is derived,and an efficient joint estimation algorithm of information source azimuth and polarization parameters based on fast subspace estimation is presented.Taking the signal of a desired signal as known conditions,this algorithm realizes the signal subspace and noise subspace quick estimate through multistage wiener filter forward recursive,avoiding the covariance matrix estimation and eigenvalue decomposition,greatly reducing the computational cost for joint estimation algorithm,and reducing amount of calculation from the original O(N^(3)+N^(2)L)to O(N^(2)L).The computer Monte Carlo simulation experiment shows that the algorithm can guarantee the estimation accuracy and simultaneously reduce the complexity of the algorithm.When the SNR is greater than 10 dB,the algorithm has approximately the same estimation accuracy compared with the existing algorithm.And the algorithm is valid.

关 键 词：柱面共形阵列天线 联合估计 DOA 快速子空间估计 

分 类 号：TN911.7[电子电信—通信与信息系统]