基于卡尔曼滤波的TDOA/AOA混合定位算法

TDOA/AOA hybrid positioning algorithm based on Kalman filter in NLOS environment

提出了一种利用两次卡尔曼滤波实现非视距环境中TDOA/AOA混合定位方法。根据类正态分布密度曲线是最小二乘意义下对指数分布密度曲线的最优拟合的思想建立TDOA误差模型,先利用卡尔曼滤波对TOA测量值进行预处理以消除NLOS误差,再把经过预处理的TOA测量值输入到卡尔曼滤波器来实现TDOA/AOA混合定位。仿真结果表明,该方法的定位误差性能明显优于单纯的TDOA定位方法以及服从指数分布误差模型下的TDOA定位方法。

A novel TDOA（Time-Difference-Of Arrival）/AOA（Angle-Of-Arrival） wireless position scheme in NLOS （Non-Line-Of-Sight）environment which uses two Kalman filters is proposed. According to a thought that the type of nor-mal distribution density curve is the optimal fitting for exponential distribution density curve in the least-squares sense, TDOA error model is established. First, a Kalman filter is used to preprocess the TOA（Time-Of Arrival）measurements for eliminating the NLOS errors. Then these preprocessed measurements are input to the TDOA/AOA hybrid location which uses another Kalman filter. The simulation results show that the method of positioning error is better than pure TDOA location method and the TDOA location which error is exponential distribution model.