Ultra-WideBand Backscatter Towards Multipath-resilient Passive IoT Localization

Passive IoT localization technology offers significant advantages across various applications due to its self-sustaining, maintenance-free, and low-cost nature. However, existing systems cannot effectively address the multipath problem in real-world deployments, leading to unreliable localization results in the severe multipath scenario. We propose to fill the gap with UWB2, the first ultra-wideband backscatter passive IoT system that can achieve centimeter-level 99th percentile accuracy even under severe multipath environments. The demo will illustrate UWB2's performance in localization accuracy, latency, operating range, and power consumption in severe multipath scenarios.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1145/3636534.3698844
Citations
1
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.21
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Ultra-WideBand Backscatter Towards Multipath-resilient Passive IoT Localization

Renjie Zhao, Yunfei Ma, Pengyu Zhang, Rilin Huang
1 citations
Indoor and Outdoor Localization Technologies
0.21
article

Ultra-WideBand Backscatter Towards Multipath-resilient Passive IoT Localization

Renjie Zhao, Yunfei Ma, Pengyu Zhang, Rilin Huang
article en
1 citations

Abstract

Passive IoT localization technology offers significant advantages across various applications due to its self-sustaining, maintenance-free, and low-cost nature. However, existing systems cannot effectively address the multipath problem in real-world deployments, leading to unreliable localization results in the severe multipath scenario. We propose to fill the gap with UWB2, the first ultra-wideband backscatter passive IoT system that can achieve centimeter-level 99th percentile accuracy even under severe multipath environments. The demo will illustrate UWB2's performance in localization accuracy, latency, operating range, and power consumption in severe multipath scenarios.

Johns Hopkins University (US), Uber AI (United States) (US), Seattle University (US), University of Baltimore (US)
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Openalex Percentile: Top 45%
Indoor and Outdoor Localization Technologies
0.21
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