A UAV-Assisted Search and Localization Strategy in Non-Line-of-Sight Scenarios

Yuan, Bin; He, Ruisi; Ai, Bo; Chen, Ruifeng; Wang, Gongpu; Ding, Jianwen; Zhang, Zhong

doi:10.1109/jiot.2022.3188557

Cited by 20 publications

(8 citation statements)

References 41 publications

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“…Several studies have implemented mobile anchors in 3-dimensional environments such as underwater WSN (UWSN) [35,45,46]. and aerial anchors [47,48]. Model topic 3 relates to UWB, indoor, localization, positioning, RFID, ultra-wideband, particle, and system.…”

Section: Fig 12 Topic Modellingmentioning

confidence: 99%

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Research Trend Topic Area on Mobile Anchor Localization

Indah Hapsari,

Munadi,

Erfianto

et al. 2023

Int. j. electr. comput. eng. syst. (Online)

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Localization in a dynamic environment is one of the challenges in WSN localization involving dynamic sensor nodes or anchor nodes. Mobile anchors can be an efficient solution for the number of anchors in a 3-dimensional environment requiring more local anchors. The reliability of a localization system using mobile anchors is determined by various parameters such as energy efficiency, coverage, computational complexity, and cost. Various methods have been proposed by researchers to build a reliable mobile anchor localization system. This certainly shows the many research opportunities that can be carried out in mobile anchor localization. The many opportunities in this topic will be very confusing for researchers who want to research in this field in choosing a topic area early. However, until now there is still no paper that discusses systematic mapping studies that can provide information on topic areas and trends in the field of mobile anchor localization. A systematic Mapping Study (SMS) was conducted to determine the topic area and its trends, influential authors, and produce modeling topics and trends from the resulting modeling topics. This SMS can be a solution for researchers who are interested in research in the field of mobile anchor localization in determining the research topics they are interested in for further research. This paper gives information on the mobile anchor research area, the author who has influenced mobile anchor localization research, and the topic modeling and trend that potentially promissing research in the future. The SMS includes a chronology of publications from 2017-2022, bibliometric co-occurrence, co-author analysis, topic modeling, and trends. The results show that the development of mobile anchor localization publications is still developing until 2022. There are 10 topic models with 6 of them included in the promising topic. The results of this SMS can be used as preliminary research from the literacy stage, namely Systematic Literature Review (SLR).

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Section: Fig 12 Topic Modellingmentioning

confidence: 99%

“…The last topic is the 10th topic model related to the keywords indoor, localization, aerial, positioning, vehicles, navigation, UWB, arrival, and unmanned. UWB is used to position the robot which can be a UAV that is carried out indoors as a navigation function as proposed in papers [52][53][54][55].…”

Section: Fig 12 Topic Modellingmentioning

confidence: 99%

Research Trend Topic Area on Mobile Anchor Localization

Indah Hapsari,

Munadi,

Erfianto

et al. 2023

Int. j. electr. comput. eng. syst. (Online)

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“…However, the multilateral ranging method is essentially a single-source localization method, and the ranging information is prone to fluctuations, resulting in a large positioning deviation. In recent years, scholars have fused two or more localization technologies to improve the accuracy and stability of positioning [12], [39], [40]. In [39], the UWB ranging and IMU fusion positioning scheme based on EKF is used to improve localization accuracy in a small area,.…”

Section: Related Workmentioning

confidence: 99%

“…Recently, much research has concentrated on energyefficient UAV path planning [12], [13] and area coverage [14], [15] for static UE localization. These works are based on two assumptions: accurate UAV coordinates and stationary UEs.…”

Section: Introductionmentioning

confidence: 99%

Multi-UAV Collaboration and IMU Fusion Localization Method in Partial GNSS-Denied Scenarios

Zheng,

Xie,

2023

IEEE Access

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When it comes to disaster rescue, quickly and accurately locating the trapped people will not miss the golden rescue time, thereby improving the success rate of rescue. The existing research has focused on the use of unmanned aerial vehicles (UAVs) to locate stationary user equipment (UE). However, the simultaneous movement of the UAVs and the UE brings about problems of UAV coordinate deviation and range interference, resulting in poor accuracy and stability of UE localization. To solve the mentioned issues above, a fusion localization method based on multi-UAV collaborative ranging and user-side inertial measurement unit (IMU) module was proposed for GNSS-denied scenarios. First, the initial coordinate deviations of the UAVs were corrected by multi-UAV collaboration; Then, a pre-processing scheme based on density peaks clustering (DPC) was proposed to eliminate the abnormal interference in the ranging data; Finally, the unscented Kalman filter (UKF) was used to realize the fusion localization based on multi-UAV ranging and user-side IMU module. The simulation results showed that the proposed scheme can maintain the accuracy and stability of UE localization in the presence of ranging interference, and the positioning error was reduced by 21.4% compared with the commonly used extended Kalman filter (EKF). Moreover, the proposed localization scheme had a better performance in low-altitude rather than high-altitude flight scenarios.INDEX TERMS Density peaks clustering (DPC), fusion localization, inertial measurement unit (IMU), unmanned aerial vehicle (UAV), unscented Kalman filter (UKF)

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“…The rapid advancement of UAVs has placed them in an advantageous position in auxiliary communications, due to their high mobility and ease of deployment [ 12 ]. A UAV-assisted search and location strategy was proposed, to locate victims in disaster non-LoS (NLoS) situations [ 13 ]. Article [ 14 ] proposed a UAV-to-vehicle (U2V) mmWave communication channel model, to research the relevant channel characteristics.…”

Section: Introductionmentioning

confidence: 99%

Channel Modeling and Characteristics Analysis under Different 3D Dynamic Trajectories for UAV-Assisted Emergency Communications

Zhang,

Liu,

Huang

et al. 2023

Sensors

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This study involved channel modeling and characteristics analysis of unmanned aerial vehicles (UAVs) according to different operating trajectories. Based on the idea of standardized channel modeling, air-to-ground (AG) channel modeling of a UAV was carried out, taking into consideration that both the receiver (Rx) and the transmitter (Tx) ran along different types of trajectories. In addition, based on Markov chains and a smooth-turn (ST) mobility model, the influences of different operation trajectories on typical channel characteristics—including time-variant power delay profile (PDP), stationary interval, temporal autocorrelation function (ACF), root mean square (RMS) delay spread (DS), and spatial cross-correlation function (CCF)—were studied. The multi-mobility multi-trajectory UAV channel model matched well with actual operation scenarios, and the characteristics of the UAV AG channel could be analyzed more accurately, thus providing a reference for future system design and sensor network deployment of sixth-generation (6G) UAV-assisted emergency communications.

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A UAV-Assisted Search and Localization Strategy in Non-Line-of-Sight Scenarios

Cited by 20 publications

References 41 publications

Research Trend Topic Area on Mobile Anchor Localization

Research Trend Topic Area on Mobile Anchor Localization

Multi-UAV Collaboration and IMU Fusion Localization Method in Partial GNSS-Denied Scenarios

Channel Modeling and Characteristics Analysis under Different 3D Dynamic Trajectories for UAV-Assisted Emergency Communications

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