Description
In this paper, we propose car occupancy detection using ultra-wideband (UWB) radar to detect the breathing motion of a person. The target signal and multipath propagation inside the car are modeled as a pinhole channel. We show that the received signal can be described by the Kronecker product of the channel and breathing motion vectors. Thus, the covariance can be computed from the delay profile of the channel and the power spectrum of the chest motion. An estimator-correlator is applied for the detection. Measurements have been performed to confirm the structural assumptions about the received signal whereas Monte-Carlo simulations are used to evaluate the detection performance. The simulations demonstrate an improved detection rate in low signal-to-noise ratio (SNR) conditions compared to a windowed energy detector or FFT-detector.Period | 6 Apr 2022 |
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Event title | 18th European Radar Conference: EuRAD 2021 |
Event type | Conference |
Conference number | 18 |
Location | London, United KingdomShow on map |
Degree of Recognition | International |
Keywords
- ultra wideband radar
- motion detection
- detection algorithms
- Vehicle Safety
ASJC Scopus subject areas
- Signal Processing
Related content
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Publications
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Car Occupancy Detection Using Ultra-Wideband Radar
Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
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Projects
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SEAMAL Front - Securely Applied Machine Learning
Project: Research project