一种基于改进重采样的粒子滤波算法

摘要

针对传统粒子滤波算法中存在的样本贫化问题,提出一种基于改进重采样的粒子滤波算法.为了验证算法的有效性,对机动目标跟踪和分时恒值估计两类问题进行了仿真.结果表明,所提出的算法能够解决样本贫化问题,且具有较小的估计误差和较短的运算耗时.%Aiming at the sample impoverishment problems that exists in traditional particle filter, a particle filter algorithm based on improved resampling is presented. In order to verify the effectiveness of the algorithm, two examples on manoeuvring target tracking and time-constant values estimation are simulated. Simulation results show that the proposed algorithm can solve the sample impoverishment problem, and has better performance in both estimation error and computing time.