Localization Techniques of Wireless Sensor Networks: A Review

Sivasakthiselvan, S.; Nagarajan, V.

doi:10.1109/iccsp48568.2020.9182290

Cited by 27 publications

(9 citation statements)

References 9 publications

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“…In general, ranging algorithms are based on the geometrical parameters of the operating environment, such as angles of signal reception and the distance between the sensor and an object. A large number of ranging algorithms have been developed in order to meet various requirements [ 9 , 10 ]. Algorithms that provide high accuracy and can be potentially used for proximity detection in an underground CAS design are introduced in this section, including Time-Of-Flight (TOF), Time-Of-Arrival (TOA), Time-Difference-Of-Arrival (TDOA) and Angle-Of-Arrival (AOA).…”

Section: Ranging Algorithms and Positioning Techniquesmentioning

confidence: 99%

Survey of Collision Avoidance Systems for Underground Mines: Sensing Protocols

Qian

Zhao

et al. 2022

Sensors

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With the growing number of unintentional interactions occurring in underground mines, Collision Avoidance System (CAS) establishment and maintenance has become an urgent need for mining industries to enhance their risk profile and improve construction safety. Usually, most collision accidents can be divided into three different categories in line with the involved participants and infrastructure condition. The accidents pose a great risk of financial cost to mining companies and even cause casualties. In detail, this paper presents an intensive study survey of positioning techniques, including ranging algorithms, to accommodate the demands of various proximity sensors and improve the capability of situational awareness. Then, we exploit the importance of the communication system, prevalent low-power wide-area technologies and related communication protocols. The effectiveness of communication systems decides and facilitates the success of the final integrated system that can be used to fundamentally address the problem of collision avoidance. For the purpose of collaboration between communication systems and other executive departments, a series of systematic comparisons of pertinent technologies and algorithms is given near the end, followed by a brief discussion on the best choice among these options. In the proposed solution, the overall end-to-end delay can be minimised to a few nanoseconds and the localisation accuracy can achieve centimetre level when operating in the range of 100 m.

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Section: Ranging Algorithms and Positioning Techniquesmentioning

confidence: 99%

Survey of Collision Avoidance Systems for Underground Mines: Sensing Protocols

Qian

Zhao

et al. 2022

Sensors

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“…In WSN, nodes can determine their location by using external auxiliary positioning or self-positioning techniques. These localization algorithms include two categories: range-based localization algorithm or range-free localization algorithm [8][9][10]. The range-based localization algorithm gets the distance from sensor nodes to different sensor nodes using measuring information, such as received signal strength indicator (RSSI) [5,11,12], time of arrival (TOA), time difference of arrival (TDOA), and angle of arrival (AOA) [13].…”

Section: Related Workmentioning

confidence: 99%

Research on improved localization algorithms RSSI-based in wireless sensor networks

Qiao

Hou

Gao

et al. 2021

Meas. Sci. Technol.

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The localization problem is a key supporting technology in wireless sensor network (WSN). The performance of commonly used positioning algorithms in WSN in terms of node density, beacon node ratio and different terrain is firstly analyzed and compared in this paper. The analysis shows that the magnitude of the positioning error of the trilateration method based on the received signal strength indicator (RSSI) ranging technology is 10 −15 , which is far lower than other positioning algorithms, but the node proportion that cannot be located is 20%-50% or so, which is much higher than other algorithms. Therefore, an improved trilateration positioning method based on RSSI ranging (ITRSS) is proposed, that is, the unknown nodes that have been located is used as new beacon nodes to locate other unknown nodes. MATLAB simulation shows that the positioning error of the proposed ITRSS method is only reduced by an order of magnitude, moreover, the proportion of nodes that cannot be located is reduced to about 1%, which is only some remote individual node out of the communication range in the area. The Zigbee network established by the CC2530 chip is used for preliminary experimental verification. The experimental results show that the nodes that could not be located at first can be located, and the positioning error does not exceed the set threshold of 3 m. Thus shows the proposed ITRSS method is of feasibility and effectiveness, which help to improve the positioning capability of the entire WSN network.

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“…According to existing work, localization can be done in a range‐free or range‐based manner 12 . The difference is range based localization requires external hardware and high computational time, whereas range‐free localization does not 13,14 .…”

Section: Introductionmentioning

confidence: 99%

Improvement of amorphous localization algorithm in WSN using ALO and GWO

Tripathy,

Khilar

2024

Concurrency and Computation

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SummaryThe process of node identification is referred to as localization, and it is rapidly gaining popularity in the field of WSN. Different node identification processes have different findings, benefits, challenges, costs, effectiveness, and applications. In this work, the position error of the Amorphous algorithm is minimized by optimizing the hop size. For optimization of the hop size of the Amorphous algorithm, two different optimization algorithms, such as ALO and GWO, are considered. Proposed Amorphous‐ALO and Amorphous‐GWO provide higher accuracy rates of 33.89% and 4.22% than traditional Amorphous as well as ensemble approaches. Amorphous‐ALO and Amorphous‐GWO provide position errors 2.9161 and 2.9164 respectively, which are very similar. Therefore, to determine the suitable optimization algorithm for Amorphous, the minimum, average, and maximum execution times of Amorphous‐ALO and Amorphous‐GWO are considered. The approach that has less execution time is considered as most suitable for Amorphous. Amorphous‐ALO takes 67.76, 69.60 and 84.24 s for minimum, average and maximum execution whereas Amorphous‐GWO takes 65.17, 65.46 and 65.66 s for minimum, average and maximum execution respectively. As Amorphous‐GWO takes less execution time than Amorphous‐ALO; therefore, GWO is more suitable for optimization in Amorphous algorithm.

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Localization Techniques of Wireless Sensor Networks: A Review

Cited by 27 publications

References 9 publications

Survey of Collision Avoidance Systems for Underground Mines: Sensing Protocols

Survey of Collision Avoidance Systems for Underground Mines: Sensing Protocols

Research on improved localization algorithms RSSI-based in wireless sensor networks

Improvement of amorphous localization algorithm in WSN using ALO and GWO

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