A Novel Two-Stage Adaptive Filtering Model-Based GNSS/INS Tightly Coupled Precise Relative Navigation Algorithm for Autonomous Aerial Refueling

Ling Wu,Xiyu Fu,Rui Xu,Yongrong Sun,Francisco Ronay Lopez Estrada

doi:10.1155/2022/8546466

Abstract

Autonomous aerial refueling (AAR) has generated great interest in recent years. However, much research has focused on the vision-based close docking stage; few studies have been conducted on the navigation algorithm for the rendezvous and following stages. High-precision relative navigation in following stage can provide favourable conditions for successful docking. Aiming at precise relative navigation in the complex high dynamic environment of aerial refueling rendezvous and following stages, a two-stage adaptive filtering architecture is exploited in this paper. An adaptive main Kalman filter (AKF) is realized for ambiguity eliminated GNSS/INS tightly coupled integrated system, and a robust adaptive subfilter is developed for GNSS individually. Particularly, aiming at the influence of pseudorange observation multipath outliers and state abnormal disturbances in unmanned air vehicle- (UAV-) tanker proximity, an INS-aided bifactor robust and classified factor adaptive filtering (IBRCAF) algorithm for single-frequency ambiguity resolution is proposed. Finally, the effectiveness of the algorithm is verified by the simulation experiments for UAV-tanker. The results indicate that the IBRCAF algorithm can efficiently suppress the influence of pseudorange multipath gross errors and abnormal state disturbances and greatly raise the success rate of ambiguity resolution, and the two-stage adaptive filtering algorithm of IBRCAF-AKF can significantly improve relative navigation performance and achieve centimeter-level accuracy.

Highlights

The autonomous aerial refueling (AAR) has played an important part in the military field, which is considered a “technical challenge” by the US Air Force [1]
In order to simulate the multipath gross errors caused by the strong reflection effect and state outliers emerged by airflow interference in unmanned air vehicle- (UAV-)tanker proximity, the data is processed as follows to test the various algorithms for ambiguity resolution (AR)
High precision relative navigation based on the global navigation satellite system (GNSS)/inertial navigation system (INS) integrated system is one of the key technologies for AAR mission

Summary

Introduction

The autonomous aerial refueling (AAR) has played an important part in the military field, which is considered a “technical challenge” by the US Air Force [1]. In the boom-andreceptacle refueling method, the tanker is an active part that steers a rigid retractable boom fitted to the rear of the tanker to a socket installed on the top of UAV; while in the probeand-drogue refueling method, the tanker drags a refueling drogue linked in the end of the flexible hose, and the refueling probe attached on the UAV is controlled to dock into the drogue The characteristics of the former method are that the speed of oil delivery is fast and it is not sensitive to air turbulence, but the structure of refueling device is complex and it only fuels one aircraft at a time [3]. Compared to the boom-based refueling method, the structure of the drogue-based refueling method is simpler and more flexible, which can refuel two or more aircraft at the same time, but the drogue is susceptible to atmospheric turbulence [4]

Methods

Results

Conclusion