双站基于角度和时差的近似无偏定位算法  

A Nearly Unbiased Passive Location Algorithm for Two Stations Based on Direction of Arrival and Time Differences of Arrival Measurements

作　　者：王鼎[1] 林四川[1] 李长胜[2] 

机构地区：[1]解放军信息工程大学信息工程学院,河南郑州450002 [2]解放军信息工程大学理学院,河南郑州450004

出　　处：《雷达科学与技术》2008年第5期371-377,共7页Radar Science and Technology

摘　　要：联合角度(DOA)和时差(TDOA)信息对运动目标进行无源定位实质上是一种非线性估计问题。针对将非线性观测方程转化为伪线性方程会产生有偏估计的缺点,该文基于双站定位中获得的角度和时差信息,给出了一种对三维空间目标定位跟踪的近似无偏估计滤波算法,它只需要对一对矩阵束进行广义特征分解,即可获得目标坐标和速度的估计值。计算机仿真结果表明,相比有偏估计滤波算法,如伪线性卡尔曼滤波(PLKF)算法或者最小二乘(LS)算法,该算法具有更高的定位精度,并且当观测误差增大时,其优势更加明显。The target motion analysis based on direction of arrival（DOA） and time differences of arrival （TDOA） measurements is a nonlinear estimation problem because of the nonlinearity of its observation equation. The biased or divergent solution will be resulted from the pseudo linear equation derived from the observation equation. The paper presents an efficient and nearly unbiased algorithm for 3-D moving emitters based on DOA and TDOA measurements by two stations. The target coordinates and velocity can be obtained via the generalized eigen-decomposition of a matrix pencil. The computer simulation shows that it has more location accuracy than the unbiased algorithms, for example, the pseudo-linear Kalman filter（PLKF） algorithm and the least squares（LS） algorithm. When the measurement estimation variance increases, it has a significant advantage.

关 键 词：无源定位 角度 时差 近似无偏估计 广义特征分解 

分 类 号：TN911.7[电子电信—通信与信息系统] TN957.51[电子电信—信息与通信工程]