Abstract
The data fusion can come down to a process that combines the state vectors from different sources to obtain a more accurate result. Compare to the achieved results that depend on single source, the method has gained an improved performance and reduced the computational complexity and bandwidth of transmission as well. This paper makes use of Probabilistic Data Association (PDA) algorithm and Joint Probabilistic Data Association (JPDA) algorithm to track the Multi-target for each local sensor in a clutter environment. Furthermore, a method based on statistical double-threshold association algorithm and covariance-weighted fusion algorithm is proposed in this paper. Meanwhile, the simulation result shows that the performance has been improved significantly in multi-sensor and multi-target tracking progress with the proposed method in the paper.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Sensors Wireless Communications and Controle
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
