Genetic Interacting Multiple Model Algorithm Based on H∞ Filter for Maneuvering Target Tracking

被引:3
|
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
关键词
Genetic algorithm; H-infinity filter; interacting multiple model; maneuvering target tracking; IMM ESTIMATOR;
D O I
10.1007/s12555-011-0116-4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
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.
引用
收藏
页码:125 / 131
页数:7
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