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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。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。
Under non-linear non-Gaussian state space, particle filter is an effective non-linear filtering algorithm. Its key problems include particle weight calculation, particle resampling and state estimation. According to the idea of particle filter algorithm and the non-linearity of bistatic passive locating and tracking, a particle filter algorithm is applied to the dual-station passive locating and tracking problem. An improved particle filter algorithm is given, The specificity of source location tracking has been improved. The simulation experiments with matlab are compared with the least square algorithm and extended Kalman filter. The results show that the proposed algorithm has better positioning and tracking accuracy than other methods.