Abstract: In order to improve the location precision and reduce the location error, a novel single passive location algorithm based on improved extended kalman filter is proposed in this paper. Firstly, position information of target is collected and the mathematic model of passive location is established, and then improved extended kalman filter is used to estimate the object position, finally, the simulation experiments are carried out on some data. The result shows that the proposed algorithm can implements an equivalent KALMAN gain matrix built by introducing predicted residuals. In order to improve the location precision of single passive location and has great reduce the affect of error compared extended kalman filter algorithm.

Key words: single passive location, extended Kalman filter, location accuracy, estimating error

摘要： 为了提高单站无源定位精度，降低定位误差，针对扩展卡尔曼滤波算法存在的不足，提出一种基于改进扩展卡尔曼滤波算法的单站无源定位方法。首先通过采集目标的相关信息，构建单站无源定位数学模型，然后利用改进扩展卡尔曼滤波算法目标位置进行估计，最后采用数据进行仿真对比实验。结果表明，相对于扩展卡尔曼滤波算法，改进扩展卡尔曼滤波提高了目标定位的精度，削弱异常误差对位置估值的影响。

关键词: 单站无源定位, 扩展卡尔曼滤波算法, 定位精度, 估计误差