Research on Moving Small Target Tracking Method in Low Contrast

With the constant development of science and technology, the method of small target tracking is widely used in military and civilian fields. But in the tracking process, the small target image is affected by the small proportion of pixels. Especially in conditions of low contrast, the tracking process is easy to appear the error tracking or the loss of target. For improving the motion small target trace ability in conditions of low contrast, this paper proposed a fusion based on filtering and data association positioning framework. Through the construction of small target track plots under the condition of low contrast and observation probability model, with the introduction of multi feature concept and the design of small target flight trajectory similarity probability, the relevance of target tracking data was improved. Simulation results show that the fusion technical method based on filtering and data association positioning framework improves efficiency compared with the traditional small targets tracking algorithm, which saves the computing time. Through the improvement of the small target tracking in the low contrast, a large number of tracking particles need not be wasted in the useless area, which saves the cost and improves the tracking efficiency.