An Adaptive Track Fusion Method with Unscented Kalman Filter

We herein proposed an adaptive track fusion algorithm based on unscented kalman filter (UKF) to improve the tracking accuracy of ground combat targets. This algorithm improved the distributed multi-sensor data fusion system and was used to fuse the data collected from the light, radar and vision sensors on one single combat platform to obtain local track estimation. Then, the local trajectory estimates of all combat platforms in the cluster are combined using an adaptive track synthesis algorithm to obtain the target track Simulation results showed that this method can obtain more accurate trajectories of tracking targets.