| As the basic key link of air defense command and control system,target decision-making directly affects the formulation of target prevention-control and the effect of prevention-control.The research on threat assessment and tracking methods of incoming multi-target is an important content of current research on target early warning command and control system.Aiming at the decision-making problem of visible light detection system facing multiple "low,slow and small" targets and the target tracking problem of Strapdown image seeker guidance,this paper uses mathematical modeling and related algorithms to study the threat assessment and tracking methods of typical "low,slow and small" targets represented by UAV.1)The detection principle of Strapdown image seeker and the features of "low,slow and small" targets are studied.The visible light detection system of Strapdown image seeker is analyzed,the target sight distance estimation model is established,the image properties of "low,slow and small" targets are analyzed,and the overall research scheme of multi-target decision-making and tracking of Strapdown image seeker is determined.2)Target recognition is carried out for air attack targets.Through the preprocessing and image segmentation of the air target image collected by the visible light detection system,the statistical features of the gray histogram of the target,the geometric features of the image target and the Hu invariant distance feature are extracted to form a feature vector as the final classification feature.The recognition method of self-adaptive neuro fuzzy inference system is used to recognize five kinds of typical "low,slow and small" targets.The simulation results show that the average recognition accuracy of the system is 80%.3)Based on the correct target identification,the threat degree of five types of "low,slow and small" targets collected at a certain time is evaluated.In view of the problem that the objectivity of target situation data and the subjectivity brought by expert decision-making cannot be completely combined in target threat assessment,a weighting method combining Analytic Hierarchy Process,entropy weight and CRITIC method is designed,the relevant model is established,the combined weight is calculated,and the Technique For Order Preference By Similarity To Ideal Solution method is used for threat ranking.Finally,the combination weighting method is compared with the single evaluation method,and the results prove the rationality of the combination weighting method.4)Aiming at the jitter phenomenon in the acquisition target sequence of Strapdown image seeker,an image stabilization algorithm based on improved optical flow method is designed.The algorithm is designed by combining optical flow method and Kalman filter,the electronic image stabilization preprocessing is carried out for dithered video,and the image stabilization effect is simulated and verified by qualitative and quantitative analysis methods.After analysis,the PSNR value of the video sequence after image stabilization is increased by about 5d B.The standard deviation of adjacent frames in x direction,y direction and rotation angle after image stabilization are less than that of the original dithered video sequence,which verifies the effectiveness of the algorithm.5)Aiming at the occlusion problem when the seeker tracks the target,the KCF al gorithm is improved.Based on the in-depth study of KCF algorithm,a comparative ex periment of KCF algorithm,traditional tracking algorithm TLD and Struck algorithm is carried out on the public data set OTB100.In view of the poor tracking effect of K CF algorithm when occlusion occurs,the target position is predicted by adding URTSEM（Unscented Rauch Tung Striebel-Expectation Maximum）smoothing function,and the position information is transmitted to KCF filter.Through qualitative analysis and quantitative analysis,the results show that the algorithm has excellent performance in dealing with occlusion,the accuracy increases by 16.8% and the success rate increases by 7.1%. |
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