A new fast algorithm for multitarget tracking in dense clutter
Weihua QIN
Fei HU
Chaoyin QIN
摘要：A fast joint probabilistic data association (FJPDA) algorithm is proposed in this paper. Cluster probability matrix is approximately calculated by a new method, whose elements βli(K) can be taken as evaluation functions. According to values of βti(K), N events with larger joint probabilities can be searched out as the events with guiding joint probabilities, thus, the number of searching nodes will be greatly reduced. As a result, this method effectively reduces the calculation load and makes it possible to be realized on real-time. Theoretical analysis and Monte Carlo simulation results show that this method is efficient.
机标关键词：multitarget trackingprobabilistic data associationsimulation resultsMonte Carlonew method
分类号：O1(数学)
论文发表日期：2005-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：4( 383-386 )
英文信息