Survey on Positioning System: Sampling methods

TL;DR

This survey reviews various sampling methods for UWB positioning systems, highlighting the advantages of compressed sensing techniques over traditional sequential sampling in achieving millimeter-level accuracy.

Contribution

The paper compares different TDOA-based UWB sampling methods, especially focusing on compressed sensing algorithms for improved high-resolution signal reconstruction.

Findings

Compressed sensing methods outperform sequential sampling in accuracy.

BCS, OMP, and BP algorithms show promising results in 2D and 3D simulations.

CS-UWB achieves sub-mm positioning precision.

Abstract

Millimeter-accuracy Ultra-Wideband (UWB) positioning systems using the Time Difference Of Arrival (TDOA) algorithm are able to be utilized in military and many other important applications. Previous research on UWB positioning system has achieved up to mm or sub-mm accuracy. However, one bottleneck in UWB system is at sampling high resolution UWB signals, as well as high resolution timing information. In this paper, UWB positioning systems are surveyed and we focus on sampling methods for handling UWB signals. Among different sampling methods, one traditional way is the sequential sampling method, which is not a real time sampling method and blocks UWB positioning system to achieve higher precision. Another way is by applying Compressed Sensing (CS) to UWB system for achieving sub-mm positioning accuracy. In this paper, we compare different TDOA-based UWB systems with different sampling methods. In particular, several CS-UWB algorithms for UWB signal reconstruction are compared in terms of positioning accuracy. Simulation results in 2D and 3D experiments demonstrate performance of different algorithms including typical BCS, OMP and BP algorithms. CS-UWB is also compared with UWB positioning system based on the sequential sampling method.