An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation

In UWB indoor navigation, the accuracy of navigation resolution is greatly affected by non line of sight(NLOS) ranging error, and low filtering precision is influenced by uncertain system noise. To solve these problems, an improved robust Kalman filtering based on innovation is proposed and applied in ultra wideband(UWB) indoor navigation. On the foundation of the linear UWB indoor navigation model, the new method uses single innovation values to construct the matrix with robust factors and eliminate the influence of NLOS ranging error. Meanwhile, the new method does real-time estimation and corrects the system noise covariance matrix. Experimental result verifies the effectiveness of the new method. It is shown that the new method can not only effectively eliminate the influence of NLOS ranging error on navigation resolution, but also can further improve the filter precision and reliability in indoor navigation.