一种改进的自适应航迹融合算法

A modified adaptive track-to-track fusion approach

讨论了C.Beugnon等提出的自适应航迹融合算法,分析表明该算法中隐含一个不正确的假设,即传感器航迹与全局航迹之间互不相关.鉴于此,提出一种新的改进算法,该算法修正了原算法中的错误假设,航迹相关性在两种距离测度的计算中予以考虑;并在继承原算法能自适应系统环境变化的优点的同时将航迹关联与融合相结合,降低了融合计算的复杂度.仿真结果表明,此算法对系统环境变化造成的跟踪精度损失具有更强的鲁棒性.

Tracktotrack 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 sensorlevel track are crosscorrelated because they are based on common data. Based on this, a modified adaptive track fusion approach is developed in this paper. The crosscorrelation between sensorlevel 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.