具有不同观测丢失率多传感器随机不确定系统的加权观测融合.PDF

31 2 Vol. 31 No. 2 2014 2 Control Theory Applications Feb. 2014 DOI: 10.7641/CTA.2014.30136 , , (1. , 150080; 2. , 150080) : , . , , . , . , . . : ; ; ; ; : TP273 : A Weighted measurement fusion estimation for stochastic uncertain systems with multiple sensors of different missing measurement rates WU Li-ming , MA Jing , SUN Shu-li (1. School of Electronic Engineering, Heilongjiang University, Harbin Heilongjiang 150080, China; 2. School of Mathematics Science, Heilongjiang University, Harbin Heilongjiang 150080, China) Abstract: This paper is concerned with the optimal linear estimation problem for a multisensor linear discrete-time stochastic uncertain system with missing measurements. Different sensors have different missing measurement rates. Firstly, multiplicative noises are transferred to additive noises. Then, based on full-rank decomposition of a matrix and weighted least-squares theory, the weighted measurement fusion estimation algorithms with small computational burden are developed. The steady-state property of the weighted measurement fusion estimation algorithms is analyzed. A suffi- cient condition for the existence of the steady state is given. The weighted measurement fusion estimators proposed here have the same accuracy as the centralized fusion estimators, i.e., they have the global optimality. A simulation example shows the effectiveness of the algorithms. Key words: multisensor; missing measurement; multiplicative noise; weighted measurement fusion; full-rank decom-