Study of Trajectory Filtering Methods for ADS-B Based on VSIMM-RSRCKF

Abstract

In this paper, an advanced ADS-B trajectory filtering method combining Variable Structure Interactive Multi-Modeling (VSIMM) and Reduced Square Root Volume Kalman Filter (RSRCKF) is proposed. After deeply analyzing the operational characteristics of ADS-B system and the application requirements in the field of aviation, this paper aims to improve the accuracy of ADS-B trajectory tracking by this novel filtering method. In order to cope with the tracking performance problems that may be caused by the model set selection in the traditional interacting multi-model algorithm, the Variable Structure Interacting Multi-Model (VSIMM-RSRCKF) algorithm based on the Simplified Square Root Volume Kalman Filtering is adopted in this study for trajectory filtering. By constructing a comprehensive VSIMM model set to describe the dynamic system of maneuvering targets, the filtering method in this paper simplifies the computational process and reduces the computational complexity by squaring the covariance matrix in the iteration, and at the same time ensures the non-negative qualitative nature of the covariance matrix, which effectively avoids the divergence problem that may occur in the filtering process. The goal of this research is to significantly improve the positioning accuracy and reliability of aircraft using the ADS-B system.