Research On Small Target Tracking Method Based On Infrared Imaging/Radar Fusion

Multi-sensor fusion tracking technology has become an important development trend in the field of target tracking.Infrared detector and millimeter wave radar have their own advantages.Fusion of them can improve the tracking accuracy of the system and reduce the false alarm rate.Therefore,the fusion of infrared and millimeter wave radar has been widely used in military and civil fields.This thesis focuses on the key technologies involved in fusion tracking,including three parts: data registration between multi-sensors,small infrared target tracking in subsystems and distributed track fusion.Firstly,the basic theory and main process of multi-sensor fusion are introduced.Aiming at the problem of time registration,a fitting extrapolation registration method which can estimate time deviation adaptively is implemented.Then,aiming at the simultaneous registration of infrared and radar sensors,a space-time simultaneous registration method based on UKF is constructed.Finally,several time registration methods and space-time registration methods are compared and analyzed by simulation experiments.Then,aiming at the problem of target tracking in infrared subsystem,an improved particle filter tracking method is studied.Due to the lack of effective texture and shape features of small infrared targets,this thesis establishes the gray histogram of targets based on the idea of position weighting,and establishes the observation model of targets by combining local contrast value.In practical application scenarios,due to the jitter of imaging platform,the state of the target will change in a short time,which will reduce the effective coverage of particles to the target.To solve this problem,this thesis implements a method of generating sampled particles based on image saliency characteristics.This method can effectively improve the coverage rate of the real state of the target by calculating the saliency of the target to guide particle redistribution.Finally,aiming at the distributed fusion problem of different sensors,this thesis studies the common distributed multi-sensor fusion algorithm,and implements a hierarchical track fusion method based on the characteristic that the working frequency of infrared sensors is higher than that of millimeter-wave sensors.Firstly,the initial state estimation of the target is obtained by polynomial fitting of the local track output from the infrared system,and then the infrared target state estimation is fused with the local track of the radar system by using the adaptive track fusion method.Experiments show that the proposed method can effectively reduce the fusion tracking error of the system.