The Particle Filter And Data Association Based Method For Tracking Of Moving Point Targets In Image Sequences

The image signal to noise ratio in the low-point target detection and tracking of the study, originated in long-range search and surveillance. In these applications, the target further away from the sensor, which in the imaging sensors to point target, relative to background noise, the target strength is weak; even by the noise was drowned. In the absence of shape, size, texture and other characteristics, can not use the traditional image processing technology. So low SNR circumstances point target detection will become satellite remote sensing, air defense early-warning and guidance in areas such as deep-space information processing in the core technology. Around the low signal to noise ratio under the conditions of weak infrared tracking issues, the paper introduced a moving target tracking the weak theory, based on a particle filter and associated data to move the target tracking algorithm. The algorithm organically combine the TBD detection algorithm, the particulate filter and associated data tracking algorithm to accurately detect the number of potential targets, as soon as possible targeted, and the best isolated from the track of each target. Particle filter is the emergence of a new algorithm in recent years which is not very mature. There are still a lot of issues to be resolved, the sampling method used in this paper there are still some shortcomings, need further study.Finally, this paper does simulation for the new dim target tracking arithmetic and works out performance analysis. This arithmetic has certain practicality.