[Paper Review] Accurate and Robust Indoor Localization Systems using Ultra-wideband Signals

Paul Meissner, Erik Leitinger+2 more|arXiv (Cornell University)|Apr 30, 2013

Indoor and Outdoor Localization Technologies3 references21 citations

TL;DR

This paper proposes Multipath-Assisted Indoor Navigation and Tracking (MINT), a robust UWB-based indoor localization system that leverages multipath propagation and virtual anchors (VAs) to overcome non-line-of-sight (NLOS) errors. By modeling reflected multipath components as signals from virtual base stations and using data association with an EKF, MINT achieves superior accuracy and robustness—especially under NLOS conditions—outperforming conventional ranging and tracking schemes across various bandwidths, including low-bandwidth scenarios where traditional systems fail.

ABSTRACT

Indoor localization systems that are accurate and robust with respect to propagation channel conditions are still a technical challenge today. In particular, for systems based on range measurements from radio signals, non-line-of-sight (NLOS) situations can result in large position errors. In this paper, we address these issues using measurements in a representative indoor environment. Results show that conventional tracking schemes using high- and a low-complexity ranging algorithms are strongly impaired by NLOS conditions unless a very large signal bandwidth is used. Furthermore, we discuss and evaluate the performance of multipath-assisted indoor navigation and tracking (MINT), that can overcome these impairments by making use of multipath propagation. Across a wide range of bandwidths, MINT shows superior performance compared to conventional schemes, and virtually no degradation in its robustness due to NLOS conditions.

Motivation & Objective

• To investigate the performance limitations of conventional UWB-based indoor localization systems under non-line-of-sight (NLOS) propagation conditions.
• To evaluate the robustness and accuracy of conventional tracking schemes using high- and low-complexity ranging algorithms in real-world indoor environments.
• To demonstrate that multipath components, typically considered impairments, can be exploited to enhance localization robustness in NLOS scenarios.
• To develop and validate a practical implementation of the MINT framework using real channel measurements and geometric floor plan data.
• To compare MINT’s performance against conventional EKF-based tracking using maximum-likelihood (ML) and JBSF ranging across varying signal bandwidths.

Proposed method

• The system uses ultra-wideband (UWB) signals with pulse durations from 0.2 ns to 4 ns to achieve high temporal resolution and improved multipath separation.
• Multipath components (MPCs) are extracted from measured channel impulse responses using a high-resolution channel estimation algorithm.
• Virtual anchors (VAs) are created by modeling reflected multipath signals as if they originated from virtual base stations located at image points relative to physical anchors and walls.
• A data association (DA) algorithm links detected MPCs to the most likely VA, using geometric constraints from the floor plan and signal delay.
• An extended Kalman filter (EKF) fuses range estimates from both direct and virtual anchor paths to estimate the user’s position in real time.
• Performance is evaluated using position error cumulative distribution functions (CDFs) and horizontal dilution of precision (HDOP) across LOS and NLOS scenarios.

Experimental results

Research questions

• RQ1 How do conventional UWB tracking systems based on ML and JBSF ranging perform under varying NLOS conditions in a real indoor environment?
• RQ2 To what extent can multipath propagation be exploited to improve localization accuracy and robustness in NLOS scenarios?
• RQ3 How does the performance of the MINT framework compare to conventional tracking schemes across different UWB signal bandwidths?
• RQ4 What are the limitations of MINT due to signal overlap and closely spaced multipath components?
• RQ5 How does the use of virtual anchors affect geometric dilution of precision (HDOP) and overall system robustness?

Key findings

• MINT using EKF-GADA (greedy data association) consistently outperforms all conventional tracking schemes, achieving the best position error CDF across all pulse durations.
• Conventional EKF systems using JBSF ranging suffer severe performance degradation in NLOS regions, with position errors increasing significantly due to large ranging biases.
• Even at a low bandwidth of 250 MHz (Tp = 4 ns), MINT achieves the largest performance and robustness gain, outperforming conventional systems that exhibit outliers due to NLOS-induced biases.
• For Tp = 0.2 ns and Tp = 1 ns, MINT with DA fails to outperform conventional schemes due to challenges in resolving clustered MPCs and pulse overlap, respectively.
• In NLOS conditions, MINT maintains HDOP values mostly below 1, indicating excellent geometric configuration, while conventional systems show high HDOP values, especially during ranging outages.
• The EKF with ML ranging performs well in MINT but is outperformed by MINT with EKF-GADA, indicating that data association significantly enhances performance.