Abstract
In order to solve the problem of unknown target birth intensity in multi-target tracking, an improved GM-PHD filtering algorithm based on virtual track is proposed. According to the measurement set in the monitoring area, the virtual tracks of the birth targets are established by using the motion model of the targets. The false tracks modeled by the clutter are eliminated by PHD filter, and the states of the birth targets are extracted. The simulation results show that the algorithm performs well in dense clutter environment.
Export citation and abstract BibTeX RIS
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.