# Outlier-tolerant relative positioning method based on multi-source information fusion for unmanned aerial vehicles

## TL;DR

This paper introduces a new method for improving the reliability of UAV relative positioning by making it more tolerant to outliers.

## Contribution

A novel loss function is proposed to enhance outlier tolerance in multi-source information fusion for UAV positioning.

## Key findings

- The new method shows good outlier tolerance in simulations.
- It avoids adverse effects of outliers without significantly reducing positioning accuracy.
- The method improves the reliability of UAV relative positioning calculations.

## Abstract

Relative positioning is a key technology that needs to be addressed for unmanned aerial vehicles (UAVs) to achieve flight mission involving autonomous aerial refueling, cluster formation and cooperative control. To address the shortcomings of the least squares (LS)-based multi-source information fusion method, such as poor outlier-tolerance, the idea of outlier-tolerance is used to improve the LS method. A novel loss function is proposed by replacing the parabolic function with a piecewise function, and a multi-source information outlier-tolerant relative positioning method based on the novel loss function is established. The simulation results show that the established method has a good outlier tolerance ability, which can avoid the adverse effects of outliers and ensure the reliability of the calculation results without significantly affecting the accuracy of the relative positioning.