Research On Target Detection Technology Of Space-based Space Surveillance System

With the increase of human space activities,more and more spacecraft have been sent into space.A large number of orbiting spacecraft and space debris make the space environment more complex.As an important means of spacecraft collision warning,space debris monitoring and ensuring the smooth launch of spacecraft,space surveillance is of great significance to the security of space environment.Space surveillance system is mainly divided into ground-based space surveillance system and space-based space surveillance system.Compared with ground-based space surveillance system,space-based space surveillance system is not affected by atmospheric environment changes,has a wide range of detection and flexibility,and has become the main development direction of various countries.However,due to the particularity of the working environment and observation target of space-based surveillance system,space-based surveillance also faces many difficulties.Firstly,in the process of image preprocessing,the intensity distribution of star map background is uneven under the influence of spatial stray light,complex noise is similar to small and small targets,and the target signal-to-noise ratio is reduced under the influence of image movement.These factors cause the target to be easily submerged in the background and noise,which affects the segmentation of the target.On the other hand,the space-based monitoring system has a long observation distance and a wide range,and there are a large number of stars in the field of view to interfere with the detection of dim targets.Moreover,the intensity,size,motion speed and direction of different orbital targets are complex and diverse,which increases the difficulty of target detection.Therefore,aiming at the problem of complex background and noise removal in spacebased images and the problem of spatial dim small target detection under complex conditions,this paper studies two technologies of image preprocessing and spatial target detection.(1)Space-based image preprocessing--removing non-uniform background and noise of space-based imageFirstly,the imaging characteristics of star map components(stars,targets and background noise)are analyzed.Then,a star map preprocessing algorithm based on local contrast and target features is proposed.The algorithm uses the target significance to filter the background region and enhance the target region,and uses the target imaging features to set the feature threshold to remove the noise.Experimental results show that the proposed method can effectively remove the non-uniform background and noise,and significantly improve the target saliency.(2)Space-based dim dim target detection--space dim dim target detection under complex conditionsFirstly,the motion characteristics of the target in the star map are analyzed.According to the difference of time-domain characteristics between the star and the dim target,an adaptive fixed pipeline filtering algorithm is proposed to remove the interference of the star on dim target detection.Then,the spatial motion model of small and weak targets is established,which is convenient to predict the moving regions of targets between frames.Finally,an adaptive dim small target detection algorithm of moving pipeline filtering is proposed.The algorithm uses the initial frame and pipeline parameters to determine the frame to obtain the size and motion information of the target,and establishes the pipeline in the subsequent target search frame.By matching the size and motion information of the target in the pipeline,the target detection is completed.The experimental results show that the algorithm can effectively detect the target in a variety of complex conditions.When the target signal-to-noise ratio is 3,the detection rate can reach 100%,and when the signal-to-noise ratio is 1.5,the detection rate can still reach 95%.