N$^2$LoS: Single-Tag mmWave Backscatter for Robust Non-Line-of-Sight Localization

TL;DR

N2LoS introduces a robust mmWave backscatter-based NLoS localization method that leverages multipath reflections and advanced signal processing to achieve high accuracy in complex environments.

Contribution

The paper presents a novel NLoS localization approach using a single mmWave radar and backscatter tag, with innovative signal design and super resolution algorithms.

Findings

Achieves median localization errors of ~11 cm at 5 m range in diverse environments.

Uses HFD to differentiate reflectors from targets effectively.

Employs FS-MUSIC for super resolution of multipath components.

Abstract

The accuracy of traditional localization methods significantly degrades when the direct path between the wireless transmitter and the target is blocked or non-penetrable. This paper proposes N2LoS, a novel approach for precise non-line-of-sight (NLoS) localization using a single mmWave radar and a backscatter tag. N2LoS leverages multipath reflections from both the tag and surrounding reflectors to accurately estimate the targets position. N2LoS introduces several key innovations. First, we design HFD (Hybrid Frequency-Hopping and Direct Sequence Spread Spectrum) to detect and differentiate reflectors from the target. Second, we enhance signal-to-noise ratio (SNR) by exploiting the correlation properties of the designed signals, improving detection robustness in complex environments. Third, we propose FS-MUSIC (Frequency-Spatial Multiple Signal Classification), a super resolution algorithm that extends the traditional MUSIC method by constructing a higher-rank signal matrix, enabling the resolution of additional multipath components. We evaluate N2LoS using a 24 GHz mmWave radar with 250 MHz bandwidth in three diverse environments: a laboratory, an office, and an around-the-corner corridor. Experimental results demonstrate that N2LoS achieves median localization errors of 10.69 cm (X) and 11.98 cm (Y) at a 5 m range in the laboratory setting, showcasing its effectiveness for real-world NLoS localization.