Research On Non-Cooperative Point Target Detection Methods In Narrow Field Of View In Space

With the increase of human space activities,there are more and more noncooperative objects,such as rocket ejectors,faulty spacecraft and space debris,which pose a serious threat to the normal operation of spacecraft.Space-based photoelectric detection system has the ability to continuously observe non-cooperative targets and has the characteristics of high mobility.It is a research hotspot of space noncooperative target detection system.Stellar recognition technology is one of the main techniques to achieve noncooperative target detection in space,and has broad application prospects in longrange faint space target detection.The recognition rate and timeliness of the stellar recognition algorithm are the key factors affecting the success or failure of target detection.At present,there are two main problems in using stellar recognition technology to achieve high-precision space non-cooperative target detection under narrow field-of-view conditions.On the one hand,due to the constraint of the field of view of the space camera,the conventional star recognition algorithm has a low dimension of spatial feature construction,which is difficult to be applied to the detection of spatial non-cooperative targets under narrow field of view conditions.On the other hand,the detection of spatial non-cooperative point targets requires target extraction in a very short time,but the wide detection brightness range of the detector makes the stellar library to be stored by the space camera huge,resulting in a slow matching search speed of the algorithm.To address the above problems,this thesis proposes a long-range faint target detection algorithm for space narrow field of view to achieve fast and high-precision detection of space non-cooperative point targets,and proves the effectiveness of the algorithm by means of theoretical derivation,algorithm simulation and hardware verification,the main research contents are as follows:(1)Aiming at the problems of uneven distribution of companion stars in the process of constructing radial features and unstable feature values in the process of matching with annular features in the traditional radial and annular feature star identification algorithms,a star identification algorithm combining equal area circular division and companion star vector angle is proposed.By choosing the dynamic radius to make the circles under the radial features equal in area,the probability of the companion stars falling in each circle is guaranteed to be equal,which effectively improves the recognition rate of the radial matching process.The vector angle feature of the companion star composition is used to filter the redundant navigation stars after radial matching,which improves the accuracy of star identification.From the simulation analysis,it is clear that the star identification success rate reaches 95%when the added position noise is 1 pixel,and 98% when the number of pseudo-stars is2;(2)In order to solve the problems of low recognition rate of stars at the edge of the field of view and low timing of angular distance matching,based on the invariance of angular distance of stars,the stars located at the edge are recognized to achieve the purpose of eliminating all the stars in the image,and the QUEST algorithm and K vector are applied to the angular distance matching search to narrow the search range and speed up the matching speed at the same time.After locking the target,the motion trajectory of the target was obtained by superimposing multiple frames on the image and morphological processing of it after superimposing with the original image.The simulation results show that the recognition success rate of the algorithm is 98%~90% when 1~3 targets are added,and the average recognition time of the algorithm is 45.4ms,achieving fast and accurate detection of non-cooperative point targets under a narrow field of view in space;(3)The ZYNQ7020 hardware architecture was used to build the algorithm operation platform and carry out the verification of the space target detection algorithm with stellar background suppression.A Lab VIEW host computer was used for image transmission,the PL side ran the mass extraction algorithm module and the PS side ran the target detection algorithm module.The experimental results show that the average running time of the algorithm is 7.8ms when 1~3 targets are added,and the position error is less than 0.01 pixel,which is consistent with the theoretical analysis and verifies the effectiveness of the method proposed in this thesis.In summary,this thesis applies the stellar recognition technology to realize the method research of non-cooperative point target detection under narrow field of view in space,and achieves the purpose of fast and high precision non-cooperative point target detection.The feasibility of the algorithm is verified by means of software and hardware simulations,and the corresponding conclusions can provide some reference values for the detection of non-cooperative targets in space under narrow field of view conditions.