This paper focuses on the opportunity to use multiple star trackers to help space situational awareness and space surveillance. Catalogs of space debris around Earth are usually based on ground-based measurements, which rely on data provided by ground-based radar observations and ground-based optical observations. However, space-based observations offer new opportunities because they are independent of the weather and the circadian rhythms to which the ground system is subjected. Consequently, space-based optical observations improve the possibility of space debris detection and cataloging. This work deals with a feasibility study of an innovative strategy, which consists of the use of a star sensor with a dedicated algorithm to run directly on board. This approach minimizes the impact on the original mission of the satellite, and on this basis, it has also the function of space debris monitoring. Therefore, theoretically, every satellite with a star tracker can be used as a space surveillance observer. In this paper, we propose a multi-star space debris detecting and positioning method with constant geocentric observation. Using the multi-star tracker joint positioning method, the angle measurement data of the star tracker is converted into the spatial coordinates of the target. In addition, the Gaussian MMSE difference correction algorithm is used to realize the target positioning of multiple optical observations, and the spatial target position information of the multi-frame images is fused, thus completing the solution of the orbit equation. The simulation results show that the proposed method is sufficient to detect and position space debris. It also demonstrates the necessity and feasibility of cooperative network observation by multiple star trackers.

This paper describes the multilayer voting algorithm, a novel autonomous star identification method for spacecraft attitude determination. The proposed algorithm includes two processes: an initial match process and a verification process. In the initial match process, a triangle voting scheme is used to acquire candidates of the detected stars, in which the triangle unit is adopted as the basic voting unit. During the identification process, feature extraction is implemented, and each triangle unit is described by its singular values. Then the singular values are used to search for candidates of the imaged triangle units, which further improve the efficiency and robustness of the algorithm. After the initial match step, a verification method is applied to eliminate incorrect candidates from the initial results and then outputting the final match results of the imaged stars. Experiments show that our algorithm has more robustness to position noise, magnitude noise, and false stars than the other three algorithms, the identification speed of our algorithm is largely faster than the geometric voting algorithm and optimized grid algorithm. However, it takes more memory, and SVD also seems faster.

As an important part of space situational awareness, space-based surveillance of space debris is of great significance for understanding and protecting space resources. With the increasing number of spacecraft operating in the Earth's orbit, both the environment and the space security situation have gradually deteriorated. The accurate detection of small, dim targets in space is the technical basis of space-based debris monitoring; however, several difficulties exist in this field. Since space targets reflect low light energy, the number of pixels occupied by the target is small, and they do not reveal shape or texture characteristics. Space debris is therefore easily confused with background stars, leading to many false alarm targets, and making source detection, recognition, and tracking challenging. Accurate source positions for small and dim space targets are therefore important motivators in our project. However, the positioning accuracy of existing space-based monitoring platforms is limited by the position of the observation platform and the observable time period, due to the high-speed movements of the satellite platform and the observation target. The observation efficiency of existing space-based monitoring platforms is also low, which has certain limitations in practical applications. The high-precision measurement of target positions is thus inhibited when using existing space-based monitoring platforms. The aim of this research is to use an autonomous recognition algorithm based on a compound calibration star grid pattern for star identification. This study utilized a national advanced research project from the National High Technology Research and Development Program and used a star sensor for space debris monitoring, allowing dim and small space debris to be distinguished from stars. This research proposes a target detection technology path based on local sky reference star image comparison to detect weak and small targets in the background of star images. This technology enables the rapid, effective recognition and high-precision positioning of small, dim space targets.

Image navigation sensor is one of the most important sensing means for human to explore the extraterrestrial space environment, and optical system is a key component of image navigation sensor, directly determines the amount of information perceived. The optical system requirements of image navigation sensors are gradually developing towards large field of view and miniaturization. The fisheye lens is the first choice for large field of view imaging by selecting the appropriate optical structure, without adding other additional components, and has the advantages of small size and strong perception energy. However, as the image surface illuminance of fisheye lens will decrease sharply with the increase of the field of view, the change of temperature will also degrade the imaging quality of the system, and strong stray light sources such as the sun will easily enter the field of view, which will greatly affect the perception ability of the system. Because of this, effective design of these systems is quite difficult. In this paper, a reverse-telephoto structure was used for large-field imaging, and the degradation of imaging quality caused by temperature changes was eliminated by selecting appropriate optical and mechanical materials. Designed with a focal length of 6.7mm, an F number of 3.6, a viewing angle of 130°, a working band of 0.45μm to 0.65μm, an after work distance of 7mm, a total system length≤60mm, we tested our system in a -40°C to +60°C temperature range and measured the image quality. Through simulation analysis, the system in the whole field of view within our spot diagrams was≤5.5μm, optical transfer function was greater than 0.2 at 90lp/mm, and no vignetting occurred. Furthermore, the imaging illumination of the edge field of view was 0.72 times that of the center field of view, the f – tan (θ) relative distortion value of the center field of view was≤2.3%, and the f – θ relative distortion value of the edge field of view was≤2.7%. Compared to normal temperatures, the optical transfer function changes at -20°C and +40°C were 0.02 and 0.01, respectively. Thus, the system displayed the characteristics of excellent image quality, small size, high energy utilization rate and good non-thermal performance.