在单站无源定位与跟踪中，扩展卡尔曼滤波算法对初始值依赖性较强，在观测方程非线性较强时收敛速度和稳定性无法满足要求，因此文中提出了一种优先估计慢变化参量的定位跟踪算法，通过仿真比较验证了该算法具有较好的收敛速度和稳定性，具有对滤波初始值的依赖性小的优点。

In passive tracking and location, the extend kalman filter exhibits unstable behavior characteristic and low convergence speed in bad nonlinear observation function, and relies on the initialization fully. In this paper, an algorithm for estimating slow -changing parameters firstly is given. It is proved by simulation that this new algorithm has high convergence speed and stability, and relies on the initialization slightly.

TN958.97

总装武器装备预研基金项目