运动目标DOA自适应跟踪算法

战场区域移动通信系统中,指挥中心实时地将主波束对准作战分队来波方向,而将其他方向的来波作为干扰置零陷,不仅提高了抗干扰能力,而且还可对作战分队进行定位。这一过程是通过跟踪移动用户信号的波达角(DOA)来实现的,传统的高分辨率DOA估计算法,如MUSIC、ESPRIT等算法,无法实现自适应、实时跟踪,因为它需要对接收信号的协方差矩阵反复进行特征值分解或奇异值分解,计算量大。针对这一问题,引入基于改进的信号子空间自适应跟踪的卡尔曼(Kalman)滤波算法,该算法直接从信号子空间中提取DOA的更新,无需从协方差矩阵中提取。仿真结果表明,该算法不仅降低了运算量,而且可跟踪多用户的DOA。

Research on Self Adaptive Tracking Algorithm Based on Mobile Tracking DOA

In the battlefield area mobile communication system,the command center aims at the direction of the war party wave real time with its main wave beam and regards other direction wave as interference to place zero sink.The measure not only improves the anti-interference ability of the communication network but also positions the combat unit.The wave beam ought to track the change of the mobile user position real time in the smart antenna technology.The user position is gotten by estimating the DOA of user signal in the tracking procedure,but some classic algorithms example for MUSIC,ESPRIT tracking.Because these algorithms have to repeatedly decompose the received data covariance matrix to get the eigenvalue and singular decompo sition value and characteristic vector when the new signal is received,the procedure costs large amount of time.Aiming at this problem,the paper advances the Kalman filter tracking algorithm based on the signal subspace self adaptative tracking theory directly Abstracts the DOA update from the signal subspace and has no use for the data covariance matrix.The simulation result indicates the algorithm not only degrades the calculation but also has the ability of tracking mulit-user DOA.