文献类型：期刊文献

英文题名：Genetic Interacting Multiple Model Algorithm Based on H-infinity Filter for Maneuvering Target Tracking

作者：Ma, Haiping[1];Ruan, Xieyong[1];Pan, Zhangxin[1]

机构：[1]Shaoxing Univ, Dept Phys & Elect Engn, Shaoxing, Zhejiang, Peoples R China

年份：2011

卷号：9

期号：1

起止页码：125

外文期刊名：INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000287124600016)、、WOS

基金：This work was supported by Zhejiang Provincial Natural Science Foundation of China under grant No. Y1090866.

语种：英文

外文关键词：Genetic algorithm; H-infinity filter; interacting multiple model; maneuvering target tracking

外文摘要：In order to have a good performance for maneuvering target tracking, a genetic interacting multiple model (GIMM) algorithm based on the H-infinity filter is proposed in this paper. It introduces the H-infinity filter as model-conditional filter, which keeps its robustness by constantly adjusting parameters, to improve the performance and the precision. Meanwhile, it optimizes model probabilities using the genetic algorithm (GA), chooses sub-models which are close to true models from a set of models, adjusts the number of models and parameters in real-time, reduces excessive competition, and improves the performance of the algorithm. The simulation results indicate that, the algorithm has higher tracking accuracy and stronger robustness than the standard IMM algorithm.