Although large star sensors, both domestically and internationally, are capable of meeting the accuracy and reliability standards for measuring satellite platform attitude and orbit control, their mass, size, and cost far surpass the predetermined limits set for satellite missions. Conversely, micro star sensors at home and abroad fulfill the lightweight design requirements in terms of mass and size for satellite platforms, but they lack the necessary accuracy and reliability for precise attitude and orbit control measurements. With the constraints of cost and volume imposed by commercial satellites, coupled with the evolution of space technology and increasingly complex space missions, there is a growing emphasis on achieving higher accuracy, miniaturization, and cost-effectiveness in satellite platform systems. The future trajectory of start sensor development is oriented toward achieving both high precision and miniaturization. However, existing domestic and foreign star sensors fail to satisfy the demands for lightweight and high precision in satellite platform attitude control. Therefore, there arises a necessity for the development of star sensors that offer high accuracy, compact size, low cost, and reliable performance. The demand for high-precision terrain mapping and centimeter-level surface deformation detection necessitates that the resolution of the next generation of commercial remote sensing satellites surpasses 0.5 m. Nevertheless, due to budget and volume limitations, there exists a delicate balance between ensuring detection capability and minimizing volume size in the optical system’s aperture. While advancements have been made in enhancing the accuracy of microstar sensors, conventional methods employed for large star sensors are not directly applicable. Augmenting the aperture can enhance the luminous flux, with common approaches including narrowing the field of view, improving pixel angular resolution, and regulating the focal plane temperature of the refrigerator to mitigate detection noise. Therefore, it holds significant practical engineering value to identify the key characteristics influencing the star sensor accuracy, devise a rational optical detection system, optimize key detection parameters, improve software algorithms, and employ other methodologies to bolster accuracy.

To address the technical challenges outlined in the abovementioned engineering context, we initially present a comprehensive overview of the key parameter logic diagram that influences the accuracy of star sensors. The precision of star sensors primarily hinges on three main factors: the accuracy of single star positioning, the quantity of fixed attitude stars, and the significance of star points. Specifically, the precision of single star positioning is intricately linked to the calibration accuracy of angle measurement and detector parameters. Factors impacting angle measurement accuracy include pixel resolution and pixel subdivision precision, while calibration accuracy is influenced by optical system distortion, optical calibration procedures, calibration algorithms, and instrument precision. Detector parameters include exposure time, analog gain, digital gain, correlated double sampling value, and digital offset. The number of fixed attitude stars is correlated with the star library with key factors affecting the star library including the star catalog, sensitivity, field of view, optical system color temperature, wavelength, and quantum rate.

We primarily focus on enhancing the accuracy of single star centroid positioning through detector parameter optimization. By carefully calibrating and fine-tuning key parameters such as exposure time, gain, correlated double sampling value, and offset, the detector’s responsiveness can be optimized, noise reduced, correlation double sampling improved, and fixed pattern noise (FPN) minimized. This leads to the elimination of pixel fragments in black, enhancing the imaging quality of star targets, and consequently elevating the accuracy of single star centroid extraction. The ultimate objective is to enhance single star measurement accuracy. Identifying the optimal register for each parameter and amalgamating them into a set of optimal parameters establishes a default parameter configuration for micro star sensors. Due to variances among detectors in batches, the detection parameters of each star sensor can be individually calibrated during subsequent development and production phases. Secondly, we delve into optimizing the selection of fixed attitude stars and attitude calculation based on the weighting of star points. Weight calculation for each star is contingent upon the magnitude of error in the star vector. During attitude calculation, fixed attitude stars are selected based on their respective weights, and they contribute to the optimal attitude solution. The QUEST algorithm is employed to evaluate the optimal state of spacecraft attitude calculation, effectively enhancing attitude accuracy in the backend attitude calculation process. Finally, the efficacy of the aforementioned methodology in enhancing the accuracy of the micro star sensor is validated through testing, involving adjustments to detector parameters and the dynamic weight algorithm.

We undertake design and validation research on high-precision micro star sensors, aligning with the demands for higher precision and miniaturization put forth by the commercial aerospace sector. In accordance with the requirements for detection capability while considering constraints in both quality and sizes, sensitivity and aperture analyses are conducted. By carefully adjusting key parameters of the detector, such as analog gain, digital gain, exposure time, offset, and correlated double sampling, the accuracy of extracting the centroid of a single constant star point is enhanced, consequently improving the overall attitude solution accuracy of the star sensor. Following the optimization of detection parameters, the accuracy of the X-direction centroid positioning of the star sensor sees an improvement of 19.35%, while the accuracy of the Y-direction centroid positioning witnesses a remarkable improvement of 48.52%. To address the diverse errors inherent in various constant star vectors within the star sensor imaging model, a method involving the assignment of dynamic weights to each star vector is employed to improve the accuracy of star sensor attitude calculation. Following optimization utilizing the dynamic weight algorithm, the instantaneous error observed in ground observation experiments increases by 40.68% in the X direction and 25.76% in the Y direction. Moreover, the noise equivalent angle exhibits an increase of 46.27% in the X direction and 52.17% in the Y direction. Nevertheless, the total accuracy error of the star sensor witnesses an improvement, decreasing from 2.01″ on the X-axis and 2.07″ on the Y-axis to 1.08″ on the X-axis and 0.99″ on the Y-axis.

The logical guidance diagram for the key parameters of star sensor accuracy serves not only to enhance the accuracy design of micro star sensors but also to offer logical guidance and theoretical analysis for the accuracy design of space situational awareness sensors. In terms of the methods for analyzing detection capability, optimizing detection parameters, devising attitude solving algorithms, and conducting testing and validation to enhance the accuracy of star sensors, substantial improvements have been achieved compared to current domestic and foreign micro star sensors. These enhancements adequately fulfill the requirements of commercial satellites for high-resolution observation of star sensor attitude measurement accuracy. Furthermore, future advancements in star sensors and other space situational awareness sensors can be achieved by optimizing their detection capabilities, employing more advanced detectors, aligning corresponding optical systems and parameter configurations, and optimizing traditional star map recognition and attitude calculation methods. In addition, leveraging artificial intelligence algorithms on high-performance processing platforms can expedite the acquisition of attitude information, rendering it more precise and efficient.