ArticleSensors (Basel, Switzerland)2020
Low-Complexity MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Multi-Target Parameter Estimation of the FMCW-MIMO Radar Based on the Pseudo-Noise Resampling Method.Sensors (Basel, Switzerland) · 2022Article
- FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area.Sensors (Basel, Switzerland) · 2022Article
- An Experimental Multi-Target Tracking of AM Radio-Based Passive Bistatic Radar System via Multi-Static Doppler Shifts.Sensors (Basel, Switzerland) · 2021Article
- High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation.Sensors (Basel, Switzerland) · 2021Article
- Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning.Sensors (Basel, Switzerland) · 2021Article
- Machine Learning-Based Human Recognition Scheme Using a Doppler Radar Sensor for In-Vehicle Applications.Sensors (Basel, Switzerland) · 2020Article
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4 authors.
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Abstract
This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30°, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment.
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