In the South Atlantic Anomaly (SAA) area, due to the influence of transient noise caused by space radiation, a star sensor can easily stay in the lost-in-space (LIS) mode for a long time. To solve this problem, this paper proposes a fast star identification (FSI) algorithm. First, a noise suppression method based on scale assessment and neighborhood comparison is developed. Next, a fast and accurate search technique of multiple main stars based on the k-vector technique is used to realize star identification. The search technique builds a self-defined attribute database of stars, and a fast search method of a repeated star identity is proposed to realize the positioning of the main star. Lastly, the final main stars are obtained through the comparison of field of view and verification of angular distance. The experimental results showed that when the star sensor works at a speed of 0.1°/s and the level of transient noise signals is lower than 900, the successful identification rate is higher than 70%. In addition, compared with the triangle algorithm, match group algorithm, and multi-pole algorithm (MPA), the proposed FSI algorithm has the advantages of a higher successful identification rate and a faster execution speed.

To improve the detection efficiency of a long-distance dim point target based on dynamic programming (DP), this paper proposes a multi-frame target detection algorithm based on a merit function filtering DP ring (MFF-DPR). First, to reduce the influence of noise on the pixel state estimation results, a second-order DP named the MFF-DP is proposed. The current states of pixels on an image plane are estimated by maximizing the addition of the merit functions of the previous two frames and the observation data of the current frame. In addition, to suppress the diffusion of the merit function, the sequential and reverse observation data are connected in a head-to-tail manner to form a ring structure. The MFF-DP is applied to the ring structure, and the merit function of the MFF-DPR is obtained by averaging the merit functions of the sequential and reverse MFF-DPs. Finally, the target trajectory is obtained by correlating the extreme points of the merit functions of the MFF-DPR. The simulation and analysis results show that by merely adding a ring structure, the detection probability of the traditional DP can be improved by up to 40% when detecting point targets under the SNR of 1.8. The point target detection algorithm based on the MFF-DPR can achieve significantly better performance in point target detection compared with the traditional DPs with or without a ring structure. The proposed algorithm is suitable for radars and infrared point target detection systems.

Single-pixel noise commonly appearing in a star sensor can cause an unexpected error in centroid extraction. To overcome this problem, this paper proposes a star image denoising algorithm, named Improved Gaussian Side Window Filtering (IGSWF). Firstly, the IGSWF algorithm uses four special triangular Gaussian subtemplates for edge protection. Secondly, it exploits a reconstruction function based on the characteristic of stars and noise. The proposed IGSWF algorithm was successfully verified through simulations and evaluated in a star sensor. The experimental results indicated that the IGSWF algorithm performed better in preserving the shape of stars and eliminating the single-pixel noise and the centroid estimation error (CEE) value after using the IGSWF algorithm was eight times smaller than the original value, six times smaller than that after traditional window filtering, and three times smaller than that after the side window filtering.

Stray light, such as sunlight, moonlight, and earth-atmosphere light, can bring about light spots in backgrounds, and it affects the star detection of star sensors. To overcome this problem, this paper proposes a star detection algorithm (CMLCM) with multidirectional local contrast based on curvature. It regards the star image as a spatial surface and analyzes the difference in the curvature between the star and the background. It uses a facet model to represent the curvature and calculate the second-order derivatives in four directions. According to the characteristic of the star and the complex background, it enhances the target and suppresses the complex background by a new calculation method of a local contrast map. Finally, it divides the local contrast map into multiple 256 × 256 sub-regions for a more effective threshold segmentation. The experimental results indicated that the CMLCM algorithm could effectively detect a large number of accurate stars under stray light interference, and the detection rate was higher than other compared algorithms with a lower false alarm rate.

The field of view (FOV)-gated optical imaging system can relieve the contradiction between a wide FOV and the effective suppression of sky background radiation, making it particularly suitable for all-time star sensors. The detection capability of this novel optical imaging system during daytime differs significantly from that of traditional optical systems. This paper presents the principle of suppressing sky background radiation through FOV-gated imaging. Subsequently, the detection capabilities, including detectable limiting stellar magnitude and the probability of detecting at least three stars, are analyzed for applications on airborne platforms operating at altitudes of no less than 3km. Based on the analysis results, an FOV-gated imaging system operating in the shortwave infrared wavelength band was designed. Additionally, stray light analysis software, ASAP, was employed to simulate the illumination of stellar signals and sky background radiation on the detector. The evaluation of the detection capability of the designed FOV-gated optical system, based on simulation data, aligns with the theoretical analysis value. It demonstrates the system’s ability to detect multiple stars with a high probability during the daytime, thereby providing a theoretical foundation for the practical application of the FOV-gated optical imaging system on airborne platforms.

Aiming at the application requirements of a field of view (FOV) gated imaging system for all-time star sensors, a key device of a microshutter array with large unit size, high duty cycle, and fast response speed based on the electromagnetic actuation is designed. The proposed microshutter array adopts the principle that the current-carrying coil is subjected to the magnetic force in the magnetic field. The coil element is deflected by the loading current and acts as a light barrier in realizing the optical switch function. The effects of the coil element parameters on the magnetic force torque, torsion beam resistance torque, and switch response time are analyzed, and the structural parameters of the coil element are determined. A sample of the proposed microshutter array based on the electromagnetic actuation with a 4-mm period and a 2.8-mm aperture is fabricated and tested. The test results demonstrate the good switching function of the proposed microshutter array and show that the switch response time of the microshutter element is approximately 2.5 ms. This proposed microshutter array is used to gate an instantaneous small FOV to suppress the sky’s background radiation and make a FOV-gated imaging system realize the multi-stars detection by switching the gated FOV rapidly. This will solve the problem that only one star can be detected within the FOV by a traditional all-time star tracker and promote the all-time star sensor to realize star pattern recognition and autonomous astronomical navigation in the daytime.