A TDOA technique with Super-Resolution based on the Volume Cross-Correlation Function

TL;DR

This paper introduces a novel super-resolution TDOA algorithm based on the Volume Cross-Correlation Function, offering high resolution in multipath environments with lower computational complexity and no need for prior signal knowledge.

Contribution

The paper presents a new TDOA algorithm utilizing a multi-dimensional cross-correlation function that improves resolution and reduces complexity compared to existing methods.

Findings

Achieves high time resolution in multipath environments

Lower computational complexity than state-of-the-art algorithms

Does not require prior knowledge of transmitted signals

Abstract

Time Difference of Arrival (TDOA) is widely used in wireless localization systems. Among the enormous approaches of TDOA, high resolution TDOA algorithms have drawn much attention for its ability to resolve closely spaced signal delays in multipath environment. However, the state-of-art high resolution TDOA algorithms still have performance weakness on resolving time delays in a wireless channel with dense multipath effect, as well as difficulties in implementation for their high computation complexity. In this paper, we propose a novel TDOA algorithm with super resolution based on a multi-dimensional cross-correlation function: the Volume Cross-Correlation Function (VCC). The proposed TDOA algorithm has excellent time resolution capability in multipath environment, and it also has a much lower computational complexity. Because our algorithm does not require priori knowledge about the waveform or power spectrum of transmitted signals, it has great potential of usage in various passive wireless localization systems. Numerical simulations is also provided to demonstrate the validity of our conclusion.