针对移动目标的非线性融合集员滤波定位OA

This paper proposes a self-adaptive nonlinear fusion set-membership filtering(NFSMF)algorithm for indoor location of mobile targets based on received signal strength indicator(RSSI).Firstly,based on interval mathematics theory,the boundary of the high-order residual term in the linearization of nonlinear systems is determined,which reduces the error generated by linearizing nonlinear systems.Secondly,the dynamic parameters required for local filters in the current positioning environment are adaptively obtained by solving a specific semi-definite programming(SDP)problem.Then,all data information from local sensors is processed and fused using information sharing coefficients to calculate an elliptical region containing the position coordinates of the mobile tar-get.Finally,the effectiveness of the proposed algorithm is verified through experiments and simulations.The results show that in the same positioning environment,NFSMF has higher localization accuracy compared to existing algorithms,with an average position-ing error of less than 0.2 m,and can obtain the optimal elliptical region containing the true position of the target.