一种新的非线性目标跟踪方法

New nonlinear target tracking method

在实际的目标跟踪场景中,普遍存在非高斯过程噪声和/或量测噪声,以及非高斯先验信息等情况,针对这一问题,提出一种新的解决非线性/非高斯系统滤波问题的非线性滤波算法,即高斯和求积分卡尔曼滤波(GSQKF)算法。仿真实验将新算法与标准的粒子滤波算法进行了比较,表明新算法是一种非常有效的非线性滤波算法。

In practical target tracking problem,there have eristed the situation of non-Gaussian process and/or measurement noise and non-Gaussian prior information universially.In order to resolve this problem,a new nonlinear filtering algorithm,Gaussian SUM QUADRATURE Kalman Filter（GSQKF） is proposed.The simulation compares the new algorithm with the standard particle filter.The result illustrates the new algorithm is an effective nonlinear filtering method.