Citation: Qi, F.; Zhu, M.; Li, Z.; Lei,
T.; Xia, J.; Zhang, L.; Yan, Y.; Wang, J.;
Lu, G. Automatic Air-to-Ground
Recognition of Outdoor Injured
Human Targets Based on UAV
Bimodal Information: The Explore
Study. Appl. Sci. 2022, 12, 3457.
https://doi.org/10.3390/
app12073457
Academic Editors: Andrzej
Łukaszewicz, Wojciech Giernacki,
Zbigniew Kulesza, Jaroslaw Pytka
and Andriy Holovatyy
Received: 4 March 2022
Accepted: 26 March 2022
Published: 29 March 2022
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Article
Automatic Air-to-Ground Recognition of Outdoor Injured
Human Targets Based on UAV Bimodal Information:
The Explore Study
Fugui Qi
1,†
, Mingming Zhu
1,2,†
, Zhao Li
1
, Tao Lei
1
, Juanjuan Xia
1
, Linyuan Zhang
1
, Yili Yan
1
, Jianqi Wang
1
and Guohua Lu
1,
*
1
Department of Military Biomedical Engineering, Air Force Military Medical University, Xi’an 710032, China;
qifgbme@outlook.com (F.Q.); 15928198580@163.com (M.Z.); lizhaofmmu@fmmu.edu.cn (Z.L.);
pan-ds@live.com (T.L.); magnolxia@163.com (J.X.); zly2947@163.com (L.Z.); richard1207@163.com (Y.Y.);
wangjq@fmmu.edu.cn (J.W.)
2
Drug and Instrument Supervisory & Test Station of Xining Joint Service Support Center, PLA,
Lanzhou 730050, China
* Correspondence: lugh1976@fmmu.edu.cn; Tel.: +86-29-84711471
† These authors contributed equally to this work.
Abstract:
The rapid air-to-ground search of injured people in the outdoor environment has been a hot
spot and a great challenge for public safety and emergency rescue medicine. Its crucial difficulties lie
in the fact that small-scale human targets possess a low target-background contrast to the complex
outdoor environment background and the human attribute of the target is hard to verify. Therefore,
an automatic recognition method based on UAV bimodal information is proposed in this paper.
First, suspected targets were accurately detected and separated from the background based on
multispectral feature information only. Immediately after, the bio-radar module would be released
and would try to detect their corresponding physiological information for accurate re-identification
of the human target property. Both the suspected human target detection experiments and human
target property re-identification experiments show that our proposed method could effectively realize
accurate identification of ground injured in outdoor environments, which is meaningful for the
research of rapid search and rescue of injured people in the outdoor environment.
Keywords: air-to-ground search; human target; multispectral imagery; bio-radar
1. Introduction
The search for injured people in outdoor environments has always been a hot topic in
the field of social public safety and emergency rescue medicine, and mainly include two
types [
1
]. The first search scenario is about the trapped survivors under ruins in an abnormal
post-disaster environment, such as natural or sudden disasters (earthquakes, building
collapses, landslides, etc.). The detection challenge under this scenario is how to penetrate
the ruins to reliably detect weak physiological movements of surviving human beings in
the post-disaster site with relatively limited area. To address this problem, a new bio-radar
detection technology, which is a combination of biomedical engineering technology and
radar technology, was firstly proposed by our group in the academic field. Bio-radar emits
electromagnetic waves to detect survivors’ physiological activities (breathing and heartbeat)
through the ruins and corresponding vital signs would be acquired by demodulating the
radar echo. Leveraging the bio-radar and various signal processing technologies [
2
–
4
],
a series of bio-radar equipment was developed, and corresponding functions are gradually
enriched so that we can not only detect the vital signs [
5
–
8
] but also localized information.
Specifically, with our proposed equipment and algorithms, we can even detect multiple
(Max. 3) survivors simultaneously [
9
,
10
]. Currently, our latest technologies are aiming to
distinguish between human and animals (non-human targets) under ruins [
11
,
12
], and even
Appl. Sci. 2022, 12, 3457. https://doi.org/10.3390/app12073457 https://www.mdpi.com/journal/applsci
