Adaptive filtering design for in-motion alignment of INS

Misalignment angles estimation of strapdown inertial navigation system (INS) using global positioning system (GPS) data is highly affected by measurement noises, especially with noises displaying time varying statistical properties. Hence, adaptive filtering approach is recommended for the purpose of improving the accuracy of in-motion alignment. In this paper, a simplified form of Celso's adaptive stochastic filtering is derived and applied to estimate both the INS error states and measurement noise statistics. To detect and bound the influence of outliers in INS/GPS integration, outlier detection based on jerk tracking model is also proposed. The accuracy and validity of the proposed algorithm is tested through ground based navigation experiments.