多传感器阵列的近场源联合参量估计优化  

Optimization of near-field source joint parameter estimation for multi-sensor arrays

作　　者：樊国根 蒙芳 Fan Guogen;Meng Fang(Guangzhou Huali Science and Technology Vocational College,uangzhou 511325,China;Huali College, Guangdong University of Technology,Guangzhou 511325,China)

机构地区：[1]广州华立科技职业学院,广州511325 [2]广东工业大学华立学院,广州511325

出　　处：《国外电子测量技术》2019年第6期145-149,共5页Foreign Electronic Measurement Technology

摘　　要：在多传感阵列参数估计中,需要进行近场源联合参数估计,提高目标检测和识别能力,提出一种基于高阶累积量分析的近场源联合参量估计算法。采用多分辨的高斯随机过程构建近场源目标阵列分布节点模型,采用多传感器联合跟踪识别方法进行近场源的传输信号和回波信号采样,采用MUSIC算法进行目标阵列节点的初始方位估计,根据方位估计结果进行空间波束形成处理,提取近场源阵列输出信号的高阶累积量,根据高阶累积量的动态特征进行频谱分离,采用最大似然估计算法实现对近场信源距离和方位角二维参数的联合估计。仿真结果表明,采用该方法进行了近场信源联合参量估计的精度较高,对阵列目标检测的准确性较好,抗干扰能力较强。In the multi-sensor array parameter estimation, the near-field joint parameter estimation is needed to improve the ability of target detection and recognition. A new algorithm based on high-order cumulant analysis is proposed for near-field joint parameter estimation. The distributed node model of near-field target array is constructed by using the multi-resolution Gaussian random process, and the transmission signal and echo signal sampling of near-field source is carried out by using multi-sensor joint tracking and identification method. The MUSIC algorithm is used to estimate the initial azimuth of the target array node, the spatial beamforming processing is carried out according to the azimuth estimation result,the higher-order cumulant of the output signal of the near-field source array is extracted, and the spectrum is separated according to the dynamic characteristics of the high-order cumulant. The maximum likelihood estimation algorithm is used to estimate the two dimensional parameters of near field source distance and azimuth. The simulation results show that the proposed method has high accuracy, good accuracy for array target detection and strong antijamming ability.

关 键 词：高阶累积量 阵列 信号 近场源 参量估计 波束形成 

分 类 号：TN911[电子电信—通信与信息系统] TP393[电子电信—信息与通信工程]