Towards Reliable UAV-Enabled Positioning in Mountainous Environments: System Design and Preliminary Results

TL;DR

This paper presents a UAV-enabled positioning system designed for mountainous environments, addressing NLoS challenges by modeling terrain-based reliability and proposing methods to enhance service dependability.

Contribution

The study introduces a novel UAV positioning system with a terrain-aware NLoS probability model and reliability prediction, advancing the design of reliable positioning in complex terrains.

Findings

Reliability prediction method effectively evaluates system performance.

Terrain-based NLoS model improves fault detection in positioning.

Voting-based method enhances overall service reliability.

Abstract

Reliable positioning services are extremely important for users and devices in mountainous environments as it enables a variety of location-based applications. However, in such environments, the service reliability of conventional wireless positioning technologies is often disappointing. Frequent non-line-of-sight (NLoS) propagation and poor geometry of available anchor nodes are two significant challenges. Due to the high maneuverability and flexible deployment of unmanned aerial vehicles (UAVs), UAV-enabled positioning could be a promising solution to these challenges. Compared with satellites and terrestrial base stations, UAVs are capable of flying to places where both the propagation conditions and geometry are favorable for positioning. The eventual aim of this research project is to design a novel UAV-enabled positioning system that uses a low-altitude UAV platform to provide highly reliable services for ground users in mountainous environments. In this article, we introduce the recent progress made in the first phase of our project, including the following. First, the structure of the proposed system and the positioning method used are determined after comprehensive consideration of various factors. Utilizing the digital elevation model of the realistic terrain, we then establish a geometry-based NLoS probability model so that the NLoS propagation can be treated as a type of fault during the reliability analysis. Most importantly, a reliability prediction method and the corresponding metric are developed to evaluate the system's ability to provide reliable positioning services. At the end of this article, we also propose a voting-based method for improving the service reliability. Numerical results demonstrate the tremendous potential of the proposed system in reliable positioning.