False star detection and isolation during star tracking based on improved chi-square tests

Abstract

The star sensor is a precise attitude measurement device for a spacecraft. Star tracking is the main and key working mode for a star sensor. However, during star tracking, false stars become an inevitable interference for star sensor applications, which may result in declined measurement accuracy. A false star detection and isolation algorithm in star tracking based on improved chi-square tests is proposed in this paper. Two estimations are established based on a Kalman filter and a priori information, respectively. The false star detection is operated through adopting the global state chi-square test in a Kalman filter. The false star isolation is achieved using a local state chi-square test. Semi-physical experiments under different trajectories with various false stars are designed for verification. Experiment results show that various false stars can be detected and isolated from navigation stars during star tracking, and the attitude measurement accuracy is hardly influenced by false stars. The proposed algorithm is proved to have an excellent performance in terms of speed, stability, and robustness.

A New Adaptive Federated Cubature Kalman Filter Based on Chi-Square Test for SINS/GNSS/SRS/CNS Integration

“…However, the value of information sharing factor does not always reflect the differences between each state variable. e chi-square test is a statistical method for the real-time detection of abnormal changes in a dynamic system [30,31].…”