A New Thresholding Method for IR-UWB Radar-Based Detection Applications.

CFAR IR-UWB radar UWB detection false alarm miss-detection threshold

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
18 Apr 2020
Historique:
received: 05 03 2020
revised: 15 04 2020
accepted: 15 04 2020
entrez: 25 4 2020
pubmed: 25 4 2020
medline: 25 4 2020
Statut: epublish

Résumé

In this paper, we proposed a new thresholding method for impulse radio ultra-wideband (IR-UWB) radar-based detection applications by taking both the false alarm and miss-detection rates into consideration. The thresholding algorithm is the key point of the detection application, and there have been numerous studies on these developments. Most of these studies were related to the occurrence of false alarms, such as the constant false alarm rate algorithm (CFAR). However, very few studies have considered miss-detection, which is another crucial issue in detection applications. To mitigate this issue, our proposed algorithm considered miss-detection as well as the false alarms occurring during thresholding. In the proposed algorithm, a threshold is determined by combining a noise signal-based threshold, in which the focus point is the false alarm, with a target signal-based threshold, in which the focus point is a miss-detection, at a designed ratio. Therefore, a threshold can be determined based on the focus point by adjusting the designed ratio. In addition, the proposed algorithm can estimate the false alarm and miss-detection rates for the determined threshold, and thus, the threshold can be objectively set. Moreover, the proposed algorithm is better in terms of understanding the target signal for a given environment. A target signal can be affected by the clutter, installation height, and the angle of the radar, which are factors that noise-oriented algorithms do not consider. As the proposed algorithm analyzed the target signal, these factors were all considered. We analyzed the false alarm and miss-detection rates for the thresholds, which were determined by different combination ratios at various distances, and we experimentally verified the validity of the proposed algorithm.

Identifiants

pubmed: 32325654
pii: s20082314
doi: 10.3390/s20082314
pmc: PMC7219251
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT)
ID : No. 2017M3A9E2064626

Références

Sensors (Basel). 2017 Feb 04;17(2):
pubmed: 28165416
Sensors (Basel). 2019 Mar 23;19(6):
pubmed: 30909552
Sci Rep. 2019 Aug 15;9(1):11892
pubmed: 31417149
Sensors (Basel). 2015 Mar 19;15(3):6740-62
pubmed: 25808773
Sensors (Basel). 2017 Apr 11;17(4):
pubmed: 28398267
Sleep Breath. 2019 Aug 10;:
pubmed: 31401735

Auteurs

Xuanjun Quan (X)

Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimini-ro, Seongdong-gu, Seoul 04763, Korea.

Jeong Woo Choi (JW)

Xandar Kardian Inc., Seoul 04793, Korea.

Sung Ho Cho (SH)

Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimini-ro, Seongdong-gu, Seoul 04763, Korea.

Classifications MeSH