Data-Driven Tracking Based on Kalman Filter
A good model of the target will extract useful information about the targets state from observations effectively.There are many models used to maneuvering target tracking, such as constant-velocity (CV) models, Singer acceleration model (zero-mean first-order Markov model) and current model (Mean-Adaptive Acceleration Model), etc.While due to the complexity of maneuvering target, to seek the target model which can get better performance is still a subject worthy of study.For the AR process, autocorrelation function is estimated by the random sampling points in this paper.We have the statistics relation between the autocorrelation function and variance based on a first-order stationary Markov process.Then the system parameters are obtained and a model is developed based on statistics relation, which neednt set unknown parameter.Simulation shows the model developed can adaptively get the model parameter and obtain good performance.
Maneuvering Target Target Model Statistics Relation State Estimation
Xue-bo Jin Jingjing Du Jia Bao
College of Computer and Information Engineering,Beijing Technology and Business University,Beijing,1 College of Informatics,Zhejiang Sci-Tech University,Hangzhou,310018,China
国际会议
上海
英文
2476-2479
2012-10-19（万方平台首次上网日期，不代表论文的发表时间）