摘要
在非线性非高斯状态空间下,粒子滤波器是一种有效的非线性滤波算法,它的关键问题包括粒子权重的计算、粒子重采样和状态估计等。本文根据粒子滤波算法思想和双站无源定位跟踪的非线性,将粒子滤波算法用于双站无源定位跟踪问题,给出了一种改进的粒子滤波算法,并对其关键问题根据双站无源定位跟踪的特殊性进行了改进。利用Matlab进行了仿真实验,与最小二乘算法、扩展卡尔曼滤波算法进行了比较,结果表明所提算法定位跟踪精度优于其他方法。
Particle filtering algorithm is an effective non-linear filter in the non-linear and non- Gaussian state. Its key issues are weights computing, resampling and state estimation. According to the particle filter and the nonlinear of passive location, a new passive location algorithm based on an improvement particle filter is presented that is used in passive location tracking, and its key issues are improved on the particularity of passive location tracking. It is compared with linear minimum mean-square error filtering and extended Kalman filtering in passive location. Experiments are made in Matlab. It is proved that the location error by an improvement particle filtering is less than that by other algorithms.
出处
《电子信息对抗技术》
2007年第6期19-22,49,共5页
Electronic Information Warfare Technology
关键词
粒子滤波
最小二乘滤波
扩展卡尔曼滤波
无源定位
算法
particle filtering
linear minimum mean-square error fihering
extended Kalman filtering
passive location
algorithm
