|
With the development of the next generation of intelligent battlefield situation awareness technology, infrared multi-target tracking plays an increasingly important role in complex background. However, the commonly used infrared target tracking algorithm, weak small target enhanced motion information ignores the apparent feature, large target enhanced apparent feature ignores the motion information. To solve the above problems, this paper proposes a target tracking method based on the fusion of location, detection and feature matching, constructs the target motion information predictor information and target detection response, so as to achieve fast target tracking. Firstly, the Bayesian multi-target filter is used, and the weight factor of the corresponding Gaussian component is added to the Kalman filter to obtain the number and state set of the targets in the scene at a certain time, and the target position predictor is established to complete the primary correlation based on the fast position prediction. Then, according to the feature distribution of the detection response, the secondary correlation based on the effective features of the targets is completed, Form the final complete track of the target. In this paper, the multi-target complex scene multi-target motion environment simulation experiments, the experimental results show that the algorithm can better track the target in complex motion environment.
|
