Mobile Positioning in Multipath Environments: a Pseudo Maximum Likelihood approach

TL;DR

This paper introduces a low-complexity, adaptive pseudo maximum likelihood algorithm for mobile positioning in multipath environments, utilizing on-board processing and beamforming to improve accuracy under severe conditions.

Contribution

It presents a novel on-board, adaptive algorithm that estimates optimal projection matrices and associates line-of-sight in multipath scenarios, enhancing positioning accuracy.

Findings

Effective in severe multipath conditions

Outperforms natural competitors with minimal antennas and snapshots

Achieves integration gain through line-of-sight association

Abstract

The problem of mobile position estimation in multipath scenarios is addressed. A low-complexity, fully-adaptive algorithm is proposed, based on the pseudo maximum likelihood approach. The processing is done exclusively on-board at the mobile node by exploiting narrowband downlink radio signals. The proposed algorithm is able to estimate via adaptive beamforming (with spatial smoothing) the optimal projection matrices that maximize the likelihood; in addition, it can associate the line-of-sight over the trajectory, hence achieving an integration gain. The performance assessment shows that the proposed algorithm is very effective in (even severe) multipath conditions, outperforming natural competitors also when the number of antennas and snapshots is kept at the theoretical minimum.