討論了C. Beugnon 等提出的自適應(yīng)航跡融合算法,分析表明該算法中隱含一個(gè)不正確的假設(shè),即傳感器航跡與全局航跡之間互不相關(guān). 鑒于此,提出一種新的改進(jìn)算法,該算法修正了原算法中的錯(cuò)誤假設(shè),航跡相關(guān)性在兩種距離測(cè)度的計(jì)算中予以考慮;并在繼承原算法能自適應(yīng)系統(tǒng)環(huán)境變化的優(yōu)點(diǎn)的同時(shí)將航跡關(guān)聯(lián)與融合相結(jié)合,降低了融合計(jì)算的復(fù)雜度. 仿真結(jié)果表明,此算法對(duì)系統(tǒng)環(huán)境變化造成的跟蹤精度損失具有更強(qiáng)的魯棒性.
關(guān)鍵詞: 航跡融合;互相關(guān);自適應(yīng)融合
Abstract : 　Track2to2track fusion is an important part of multisensor multitarget tracking. Much research has been done in this area. An adaptive approach for track fusion in the multisensor environment proposed by C.Beugnon et al. is investigated in this paper. The algorithm chooses the method for calculating the global estimate according to a decision logic , based on the comparison between distance metric and threshold. Unfortunately , we found that the algorithm, in deriving distance metric , is established under an implicit assumption that sensor level tracks are uncorrelated with global tracks. However , even without process noise the global track and sensor2level track are cross2 correlated because they are based on common data. Based on this , a modified adaptive track fusion approach is
developed in this paper. The cross2correlation between sensor2level and global tracks is taken into account in the modified approach. The modified approach still reserves the flexible ability to react to the change of the sensor system and it also provides a natural link to track association. The simulation result illustrates that the modified approach is more robust to the change of the system environment.
Key Words : 　track2to2track fusion ;cross2correlation ;adaptive fusion