Abstract:
A self-calibration Kalman filter(SKF)method, whose model and recursive algorithm were established, was presented. In most practical cases, such as deep space exploration and engine fault diagnosis, because of the effect of unknown inputs, such as gust, fault and unknown system error, the well-known Kalman filter will lead to greater filtering error in recursive process. To solve this problem, the proposed SKF, which is applied to estimate and compensate the unknown inputs, efficiently reduces the effect of the unknown inputs and enhances filtering accuracy. For some spacecraft navigation simulation, the mean and variance of estimated state errors by SKF decreased by at least 400% and 300%, respectively. The SKF method can be effective to improve the performance of filter, simple to calculate and easy to apply in engineering.
