Multi-sensor IMM Estimator for Uncertain Measurement

被引：0

作者：

Cen, Ming ^{[1
]}

Liu, Xingfa ^{[2
]}

Luo, Daisheng ^{[3
]}

机构：

[1] Chongqing Univ Posts & Telecommun, Sch Automat, Chongqing, Peoples R China

[2] Chinese Acad Sci, Inst Opt Elect, Chengdu, Peoples R China

[3] Sichuan Univ, Sch Elect & Informat Sci, Chengdu, Peoples R China

来源：

2009 5TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-8 | 2009年

关键词：

measurement fusion; IMM; uncertain measurement; state feedback; MANEUVERING TARGET TRACKING; FUSION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Interacting Multiple Model (IMM) estimator can provide better performance over the single model Kalman filter. In multi-sensor system ordinarily, availability of measurement from different sensors is stochastic, and it is difficult to construct uniform global observation vector and observation matrix appropriately in current method. Then an IMM estimator for uncertain measurement is presented. By the method invalid measurement is regarded as outlier, and approximation is reconstructed by feedback of system state estimation of fusion center. Then nominally generalized certain measurement can be obtained by substituting reconstructed one for invalid one. The generalized certain measurement can be centralized to construct global measurement and provided to IMM estimator, and current multi-sensor IMM estimation method is generalized to uncertain environment. Theoretical analysis and simulation results show the effectiveness of the method.

引用

页码：3437 / +

页数：2

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