Limiting Performance of Radar-Based Positioning Solutions for the Automotive Scenario

Road safety applications for automotive scenarios rely on the ability to estimate vehicle positions with high precision. Global navigation satellite systems (GNSS) and, in particular, the global positioning system (GPS), are commonly used for self localization. But, especially in urban vehicular scenarios, due to obstructions, they may not provide the requirements for crucial position-based applications. In this paper, we investigate the potential of GPS-free positioning schemes and, in particular, we compute the ultimate performance, i.e., Cramér-Rao lower bounds (CRLB), of localization schemes in which each vehicle estimates its position exploiting range and/or angle measurements of an assigned set of landmarks with a known position.

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Publication Details

Journal
Sensors
Published
2024-12-12
DOI
https://doi.org/10.3390/s24247940
Citations
1
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.21

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article

Limiting Performance of Radar-Based Positioning Solutions for the Automotive Scenario

Giuseppe Ricci, Francesco Bandiera
1 citations
Sensors
Indoor and Outdoor Localization Technologies
0.21
article

Limiting Performance of Radar-Based Positioning Solutions for the Automotive Scenario

Giuseppe Ricci, Francesco Bandiera
article en
1 citations

Abstract

Road safety applications for automotive scenarios rely on the ability to estimate vehicle positions with high precision. Global navigation satellite systems (GNSS) and, in particular, the global positioning system (GPS), are commonly used for self localization. But, especially in urban vehicular scenarios, due to obstructions, they may not provide the requirements for crucial position-based applications. In this paper, we investigate the potential of GPS-free positioning schemes and, in particular, we compute the ultimate performance, i.e., Cramér-Rao lower bounds (CRLB), of localization schemes in which each vehicle estimates its position exploiting range and/or angle measurements of an assigned set of landmarks with a known position.

SensorsVol. 24(24)
University of Salento (IT), Innovation Engineering (Italy) (IT)
European Commission
Sustainable cities and communities
Openalex Percentile: Top 45%
Indoor and Outdoor Localization Technologies
0.21
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