Angle aided centralized multi-sensor multiple hypothesis tracking method

For multi-target tracking in heavily cluttered environment, the number of measurement-to-track association hypotheses in each scan grows rapidly in traditional centralized multi-sensor multiple hypothesis tracking (CMS-MHT) method, which leads that the uncertainty of data association greatly increases such that correct association can hardly be given using traditional track score resulting in high leakage rate and effects of track splitting. Based on the space distribution characteristics of false alarm and target measurement when the sensor measurement error is small, this paper proposes a new angle aided CMS-MHT method, which designs angle aided track score computation to reduce the uncertainty of measurement-to-track association. In such a way, the proposed angle aided CMS-MHT can provide better association hypotheses compared with traditional CMS-MHT. Experiment results illustrate that angle aided CMS-MHT reduces leakage rate and has better track integrity in heavily cluttered environment.