典型文献
Adaptive cubature Kalman filter based on variational Bayesian inference under measurement uncertainty
文献摘要：
A novel variational Bayesian inference based on adaptive cubature Kalman filter ( VBACKF ) algorithm is proposed for the problem of state estimation in a target tracking system with time-varying measurement noise and random measurement losses. Firstly, the Inverse-Wishart ( IW) distribution is chosen to model the covariance matrix of time-varying measurement noise in the cubature Kalman filter framework. Secondly, the Bernoulli random variable is introduced as the judgement factor of the measurement losses, and the Beta distribution is selected as the conjugate prior distribution of measurement loss probability to ensure that the posterior distribution and prior distribution have the same function form. Finally, the joint posterior probability density function of the estimated variables is approximately decoupled by the variational Bayesian inference, and the fixed-point iteration ap-proach is used to update the estimated variables. The simulation results show that the proposed VBACKF algorithm considers the comprehensive effects of system nonlinearity, time-varying meas-urement noise and unknown measurement loss probability, moreover, effectively improves the accu-racy of target state estimation in complex scene.
文献关键词：
中图分类号：
作者姓名：
HU Zhentao;JIA Haoqian;GONG Delong
作者机构：
School of Artificial Intelligence,Henan University,Zhengzhou 450046,P.R.China;Laboratory and Equipment Management Office,Henan University,Zhengzhou 450046,P.R.China
文献出处：
引用格式：
[1]HU Zhentao;JIA Haoqian;GONG Delong-.Adaptive cubature Kalman filter based on variational Bayesian inference under measurement uncertainty)[J].高技术通讯（英文版）,2022(04):354-362
A类：
VBACKF
B类：
Adaptive,cubature,Kalman,filter,variational,Bayesian,inference,under,measurement,uncertainty,novel,adaptive,algorithm,proposed,problem,state,estimation,target,tracking,system,varying,noise,random,losses,Firstly,Inverse,Wishart,IW,distribution,chosen,model,covariance,matrix,framework,Secondly,Bernoulli,introduced,judgement,Beta,selected,conjugate,prior,probability,ensure,that,posterior,have,same,function,form,Finally,joint,density,estimated,variables,approximately,decoupled,by,fixed,point,iteration,proach,used,update,simulation,results,show,considers,comprehensive,effects,nonlinearity,unknown,moreover,effectively,improves,accu,racy,complex,scene
AB值：
0.501992
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