Research On Detection Methods For Dim And Small Targets In Complex Space-based Background

With the development of technology,the exploration of space is becoming more frequent,and the number of spacecraft in orbit is increasing rapidly.The resulting space environmental security issues have also received increasing attention.The space target monitoring has a great significance to perceive space state,avoid space collision and then maintain space environment security.Among them,space target detection is the key technology to achieve space target monitoring,which includes star image preprocessing technology,dim small target detection technology and space target positioning technology.Space target monitoring is mainly divided into two types: ground-based and spacebased.Compared with the traditional ground-based space target monitoring,spacebased space target monitoring is not affected by the atmospheric environment,which also has a wide range of detection coverage and strong detection capability.In recent years,it has become the key development direction of most countries.However,due to the particularity of space-based space target surveillance environment and detection target,it has also faced many challenges.The first challenge is image preprocessing.The complex noise and stray light in the space environment lead to the uneven distribution of image background intensity.If the uneven noise background cannot be effectively suppressed,these non-uniform noises will trigger a large number of false alarm targets and influence target dectection during image segmentation,thereby bringing a huge computational burden to the image in orbit processing.The second one is the detection of dim and small targets.In the space-based image,the imaging size,strength,moving speed and direction of space targets in different orbits are complex and diverse,making the detection more difficult,particularly in the context of similar interference of massive stars,it is difficult to effectively detect low SNR targets.The third one is high-precision positioning of space targets.Space targets have different orbital relative speeds,low-speed targets are imaged as dots while high-speed targets are imaged as strips.Space-based platform vibration and background noise will affect their imaging shape and gray value,thus resulting in target positioning errors.The above aspects are the key technical problems to realize effective space-based space target monitoring.However,the current studies on space-based space target detection is relatively few,and there are problems of insufficient pertinence and poor applicability.Consequently,this paper mainly conducts an in-depth and systematic research on the following three aspects,containing the suppression and elimination of non-uniform noises in space-based image background,the detection of space dim and small targets in space-based complex background,and the high-precision positioning of the centroids and endpoints of space-based space targets.This research mainly carried out the following work:(1)Research on space-based image preprocessing algorithmThe main purpose of star map preprocessing is to suppress or eliminate the influence of non-uniform noises in background on target segmentation and detection.Aiming at the problem that the traditional image denoising algorithm is not applicable to the denoising process of space-based star maps.First of all,the paper analyses the source,composition and characteristics of non-uniform noises in the background of space-based star map,and summarize the cause of the smear effect and its influence on imaging.Then,the paper analyzes the strengths and shortcomings of the traditional background suppression methods.Finally,on the basis of the above research,the paper proposes a new algorithm to suppress or eliminate the non-uniform noises in spacebased image background,which is based on one-dimensional self-adaptive median iteration.The research results illustrate that the proposed method in this paper can accurately eliminate the non-uniform noises in the star map background and the bright lines caused by the Smear effect,meanwhile,the information of the weak and small targets is not lost,it also has strong robustness in different scenarios.(2)Research on detection algorithm of dim small targets in complex space-based backgroundIn order to solve the problem of difficult detection of dim small targets under space-based complex conditions(such as multi-target moving speed,different directions,target tailing,low signal-to-noise ratio,obscured by stars,discontinuous moving track,nonlinearity,etc.),we make full use of the space-time characteristics of spatial targets,proposing a new method of spatial target detection using multi-frame sequence images.Based on the classic multi-level hypothesis testing idea,this method introduces the pipeline detection method in the space-time domain,improving the way to obtain the candidate points of space target trajectory,which can greatly reduce the number of false alarm targets and the time cost of the algorithm.We utilize the proposed self-adaptive search interval to effectively and simultaneously detect multiple targets in different orbits without any prior information of the target.Finally,the effectiveness of the proposed algorithm is verified by the simulation star map and the actual star map experiments.The results indicate that the target detection rate can reach 100% when the target SNR is 3,and the detection rate is still 92% when the target SNR is as low as 1.5.In addition,the algorithm has strong robustness and less computation,which can effectively detect dim and small targets in the complex space-based background.(3)Research on space-based space target positioning technologyHigh-precision target positioning has a great significance to the description of target motion state,the determination of orbit parameters and the cataloging of spatial location.Accordingly,an in-depth research is conducted on space target positioning technology.First of all,this paper starts from the traditional gray-scale centroid positioning algorithm,analyzing its application scope and limitations.Then,the source of the error in the traditional method is analyzed.We present a weighted centroid positioning algorithm based on bilinear interpolation iteration.More specifically,the target centroid positioning accuracy is improved by adopting interpolation and window iteration.The experimental outcomes show that when the SNR of the target is as low as 3,the location accuracy of the new algorithm improved can reach 0.124 pixel,which is far better than the traditional gray centroid method.Finally,as for the problem that single centroid information is difficult to describe the position and motion state of strip target accurately,we propose a method of strip target endpoint location based on Harris corner.The experimental results reveal that this approach can effectively locate the end point of the strip target,while the positioning of the end point of the strip target can provide necessary information for the determination of the target position and the estimation of the angular velocity.Also,this method has important reference significance for the follow-up research.