摘要
从减少系统模型噪声和量测噪声入手,引入自适应机动模型和新息滤波器对IMMA 进行改进,提出新息滤波交互式多模型自适应算法(IF-IMMAA),理论分析和仿真表明新算法的有效性.
Blom's Interacting Multi-Model(IMM) algorithm arouses considerable interest.But its probabiltiyweight characteristic is lacking in perfection and there exists rather large time delay in tracking.This is dueto that the maneuvering target model and the formula of weight calculation employed by Blom are some-what crude.In this paper,the authors propose a new algorithm,which we call IMM Adaptive InnovationFilter algorithm and which is believed to be better than Blom's algorithm.Our contributions are:1.Model error of the filter is reduced.This is accomplished through the adoption of“currentstatistic model as the sample of maneuvering target model of IMM.As is well known,“current”statisticmodel and the adaptive algorithm possess rather good performance for tracking maneuvering target.2.Sensitivity of probability weight to measuring noises is reduced.This is accomplished by em-ploying innovation filter to filter out the residual noises.Theoretical analysis and simulation show that the authors' algorithm improves effectively the per-formance of Blom's method,reduces the time delay,and improves the performance of tracking.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
1993年第2期211-217,共7页
Journal of Northwestern Polytechnical University
关键词
机动目标跟踪
交互式
多模型算法
target tracking
IMM(Interacting Multi-Model)filter
adaptive filter
probability weight
