For improving the locating accuracy, the EKF algorithm is introduced to process the initial locating results.
为了提高定位精度，本文又引入扩展卡尔曼滤波算法对原始定位结果进行处理。
The simulation results indicate that the variable cycle RP-EKF algorithm can resolve the filtering instability of EKF for the bearing-only target tracking and the time-delay problem.
仿真结果表明变周期距离参数化扩展卡尔曼滤波算法能有效解决经典扩展卡尔曼滤波算法在纯方位角目标跟踪时可能出现的滤波发散现象，并能处理声音信号的传输时间延迟问题。
Two different Monte Carlo simulations show that the new algorithm cannot only improve state estimation accuracy but also is superior to EKF in estimation performance and computation efficiency.
两个不同的蒙特卡罗仿真表明，通过采用这一新算法引人径向速度测量，不仅可以大大提高状态估计的精度，而且其估计性能和计算效率优于传统的EKF。
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