Multiple Targets Tracking By Using Probability Data Association And Cubature Kalman Filter
2018 10TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP)(2018)
Abstract
In this paper, we investigate the problem of tracking multiple underwater targets when bearing-only measurements from multiple acoustic sensors are available. In this challenging scenario, we exploit the probability data association (PDA) to complete the measurement-target association task and the Cubature Kalman filter to deal with the nonlinear filtering problem encountered in the bearing measurement. Finally, simulation results show that the proposed method works better than the Unscented Kalman filter based counterpart.
MoreTranslated text
Key words
Underwater target tracking, Nonlinear filtering, Data association, Cubature Kalman filter
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined