A Modified IAE Algorithm for GNSS and IMU Integration

Abstract

Innovation-based adaptive estimation (IAE), which is one of the proved Adaptive Kalman Filter (AKF) algorithms, can improve the accuracy of GNSS/IMU combined navigation system based on the condition that the received GNSS measurements are independently accurate enough. However, IAE is more likely to be subjected to bias and non-convergence with degraded measurements accuracy due to GNSS signal outage or low-cost receiver. In order to maintain the performance of integrated GNSS/IMU system with the coexistence of less accurate measurements, a modified IAE algorithm is proposed in this paper. The algorithm, named “IAE with measurements discarding strategy” (IAE-D), monitors the quality of the estimations and measurements in real-time, and discards the measurements when the estimations are accurate enough or the measurements are less qualified. Field test was carried out. Noise was imported to simulate different levels of measurements deterioration. Performance comparison between Extended Kalman Filter (EKF), IAE and IAE-D has been executed with real data. The results demonstrate that IAE-D has magnificent advantage over EKF and IAE in regard to stability and accuracy when the power level of measurements interference is relatively high.