Design of Adaptive Filtering Algorithm for Relative Navigation

Recently, relative navigation has been considered as one of the most important issues in navigation field. It is purposed to enable more accurate formation flying of aircrafts and satellites and more accurate monitoring of two-body ground vehicles carrying extremely hazardous materials. For the improvement of accuracy and consistency of navigation filter, adaptive method has been widely used to adjust system parameters and error models autonomously based on actual error statistics depicted in innovation sequences. This study aims to develop an efficient approach for adaptive filtering applicable to relative navigation between one master and multiple slave devices based on Global Positioning System (GPS) and Inertial Navigation System (INS). The proposed adaptive method is based on dual filters; One is the adaptive carrier-smoothed-code (CSC) filter in position domain and the other is the adaptive velocity-aided Kalman filter. The adaptive CSC filter takes the role of accurate position estimation and provides noise covariance matrix. The adaptive Kalman filter takes the role of GPS/INS integration with appropriate noise covariance received by adaptive CSC filter. Performance of the proposed adaptive method was evaluated by a simulation which considers a two-body land vehicle.