為提高復雜數據融合系統中的航跡關聯正確率,在ZHOU B 的DC 和AC 算法基礎上提出了一種新的近似多傳感器多目標聯合概率數據關聯算法。它以一個目標為中心的近似聚為構造關聯事件的起點,并在計算中將DC 和AC 結合得到的一種全鄰的點跡2航跡關聯算法,在雜波下目標密集、航跡復雜的數據融合系統中進行實驗,對關聯正確率、關聯時耗等與最近鄰法進行了比較,效果較好。它能有效提高目標點跡2航跡的關聯正確率,在計算時上較完全聯合概率法少得多,能滿足工程中實時性的要求。
關鍵詞:近似聯合概率數據關聯;最近鄰法;數據融合
Abstract : To improve the correct association rate of track in complex data fusion system , a new association algorithm2 approximate multi2sensor multi2target joint probabilistic data association (AMSJ PDA) is presented in the paper based on DC and AC brought by ZHOU B. AMSJ PDA is a neighbor plot2track association algorithm in which the approximate set
of a target is made as the start2point to construct associations and DC is united with AC. It is tested in the data fusion system of compacted targets under scatter wave and complex track. Compared to nearest neighbor , it shows better effects of the correct association rate and association time. It can improve the correct association rate and target plot2track and demand less time needed than joint probabilistic data association. The AMSJ PDA can meet the requirements of real2time in engineering.
Keywords :Approximate multi2sensor multi2target joint probabilistic data association ;Nearest neighbor ;Data fusion.