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Detection of direct path component absence in NLOS UWB channel

Marcin Kolakowski, Jozef Modelski

TL;DR

The paper tackles accurate UWB ranging in NLOS by distinguishing whether the direct path is present or blocked, a key factor for bias mitigation. It introduces a two-step SVM approach that uses DW1000-derived power, waveform, and signal-statistic features, including a new variance measure before the first path, to separately identify LOS, DP-NLOS, and NDP-NLOS scenarios. Experimental results from a furnished apartment show strong LOS/NLOS discrimination with selected features and demonstrate the feasibility of distinguishing DP-NLOS from NDP-NLOS, with best performance achieved by a combination of energy-related and delay-spread features, aided by noise-variance information. This yields a practical method for real-time NLOS identification and improved ranging reliability in complex indoor environments.

Abstract

In this paper a novel NLOS (Non-Line-of-Sight) identification technique is proposed. In comparison to other methods described in the literature, it discerns a situation when the delayed direct path component is available from when it's totally blocked and introduced biases are much higher and harder to mitigate. In the method, NLOS identification is performed using Support Vector Machine (SVM) algorithm based on various signal features. The paper includes description of the method and the results of performed experiment.

Detection of direct path component absence in NLOS UWB channel

TL;DR

The paper tackles accurate UWB ranging in NLOS by distinguishing whether the direct path is present or blocked, a key factor for bias mitigation. It introduces a two-step SVM approach that uses DW1000-derived power, waveform, and signal-statistic features, including a new variance measure before the first path, to separately identify LOS, DP-NLOS, and NDP-NLOS scenarios. Experimental results from a furnished apartment show strong LOS/NLOS discrimination with selected features and demonstrate the feasibility of distinguishing DP-NLOS from NDP-NLOS, with best performance achieved by a combination of energy-related and delay-spread features, aided by noise-variance information. This yields a practical method for real-time NLOS identification and improved ranging reliability in complex indoor environments.

Abstract

In this paper a novel NLOS (Non-Line-of-Sight) identification technique is proposed. In comparison to other methods described in the literature, it discerns a situation when the delayed direct path component is available from when it's totally blocked and introduced biases are much higher and harder to mitigate. In the method, NLOS identification is performed using Support Vector Machine (SVM) algorithm based on various signal features. The paper includes description of the method and the results of performed experiment.
Paper Structure (6 sections, 1 equation, 3 figures, 2 tables)

This paper contains 6 sections, 1 equation, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Problem formulation
  3. Proposed approach
  4. NLOS identification
  5. Experiment results
  6. Conclusion

Figures (3)

  • Figure 1: Signal magnitude recorded by DW1000 radio chip decawave_ltd_dw1000_2015 in: a) LOS conditions, b) NLOS conditions with received Direct Patch Component, c) NLOS conditions in absence of Direct Path Component. Time 0 ns corresponds to the moment of first component detection.
  • Figure 2: Histograms of variance of signal preceding first path detection in: a) LOS b) DP-NLOS, c) NDP-NLOS
  • Figure 3: Classification method workflow