自举滤波器在非线性目标跟踪系统中的应用  

Application of Bootstrap Filter in Nonlinear Target Tracking Systems

作　　者：曾涛[1] 徐涛[1] 李栋[1] 崔智社[1] 

机构地区：[1]北京理工大学信息科学技术学院电子工程系,北京100081

出　　处：《北京理工大学学报》2004年第5期450-453,共4页Transactions of Beijing Institute of Technology

摘　　要：为了解决目标跟踪领域中非线性、非高斯系统问题,研究了贝叶斯滤波算法及其一种实现方法,即自举滤波算法(BSF),并在滤波精度、运算量等方面与扩展卡尔曼滤波算法(EKF)进行比较分析.最后基于一个典型的非线性模型对BSF和EKF进行了仿真比较.仿真结果表明,自举滤波算法的性能优于扩展卡尔曼滤波算法的性能.To solve nonlinear, non-Gaussian system problems in target tracking, the paper focuses on Bayesian filters and its realization, the bootstrap filter (BSF), which is compared with the extended Kalman filter (EKF) as to the accuracy, computational load, and other aspects. A simulation of a typical model is presented to compare the performances of BSF and EKF. The simulation shows that the performance of BSF is superior to that of EKF.

关 键 词：目标跟踪 非线性 扩展卡尔曼滤波 自举滤波 

分 类 号：TN959.9[电子电信—信号与信息处理]