Real-time Asynchronous Fusion Algorithm Based on Covariance Intersection

摘要

The fusion center generally processed information periodically in multi-sensor tracking system, and the local sensor often provided synchronous data; however, it's not that case in fact. Passive sensors are bearings-only tracking systems with a higher accuracy of target bearing information, but cannot effectively hold target tracks separately. Generally speaking, refresh rate of positive sensor is lower than the passive sensor. Thus, the sensors data were needed to be aligned to the same moment, and then applied synchronous fusion algorithms to obtain a better fusion result. This paper focuses on detection system made up of positive and passive sensors, and according to the time interval, the sensor-to-sensor fusion and sensor-to-system fusion architectures for distributed fusion systems had been used. Covariance intersection algorithm (Cl) was used to process the related data to complete asynchronous data alignment and fusion. Simulation results showed that the algorithm had better convergence results.