Cooperative method for wireless sensor network localization

Stanoev, Angel; Filiposka, Sonja; In, Visarath; Kocarev, Ljupčo

doi:10.1016/j.adhoc.2016.01.003

Cited by 47 publications

(26 citation statements)

References 27 publications

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“…Among wireless technologies supporting localization, the wireless sensor network (WSN) has become popular in recent years. (5)(6)(7)(8)(9)(10) It is supported by the advancement of micro-mechanical systems and the development of digital electronic technology. The ZigBee module, which is the IEEE 802.15.4 standard, (11) is widely used because of its various advantages, i.e., cost effectiveness, low power consumption, security, robustness, and reliability.…”

Section: Introductionmentioning

confidence: 99%

Soft-clustering Technique for Fingerprint-based Localization

Cherntanomwong¹,

Sooraksa²

2018

Sensors and Materials

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In this paper, the soft-clustering algorithm for the fingerprint-based localization technique is proposed. In an indoor environment, the fingerprint-based localization technique is usually employed since it can deal with signal fluctuation. Its basic principle is to find the target location by comparing its signal parameters with a previously recorded database of knownlocation-signal parameters. Here, the received signal strength indicator (RSSI) provided by the wireless sensor network (WSN) is used as the signal parameter. The high accuracy of location estimation requires a very fine spatial resolution of the database, corresponding to the time consumed for pattern matching. To reduce the calculation time, clustering can be applied because it can reduce the database size by grouping similar data in the same cluster. The accuracy of the algorithm to cluster the target location and fingerprint locations is the main concern. The result shows that the clustering technique used can successfully cluster the target sensing node into an appropriate cluster. This implies that, by using soft clustering with the fingerprint technique, the target location can be estimated faster than by using classical fingerprint techniques since the target location can be estimated within a small set of fingerprints in the cluster, not with all fingerprints in the database.

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Section: Introductionmentioning

confidence: 99%

Soft-clustering Technique for Fingerprint-based Localization

Cherntanomwong¹,

Sooraksa²

2018

Sensors and Materials

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“…Acknowledging that the cost of hardware required by range-based solutions may be inappropriate in relation to the required location precision, researchers have sought alternate range-free solutions to localization problems in sensor networks. The typical range-free algorithms [6] include Centroid [7], CPE (Convex Position Estimation) [8], APIT (Approximate Point in Triangle) [9] and DVhop [10]. Centroid scheme was firstly proposed by Bulusu et al in [11], which is a localization scheme based on network connectivity.…”

Section: Introductionmentioning

confidence: 99%

An Improved Localization Scheme Based on DV-Hop for Large-Scale Wireless Sensor Networks

Zhu¹,

Lv²,

Tao³

2016

JCM

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Wireless Sensor Networks (WSNs) have revolutionized the world of distributed systems and enabled many new applications. And, measurement data or information exchanges happened in WSNs without location information are meaningless. It is extremely urgent to establish and maintain low cost and high efficient localization schemes for real-time large-scale surveillance systems. In this work, an improved DVhop (Distance Vector-hop) based localization scheme IDV-hop (improved DV-hop) embedded in WLS (weighted least square) method is proposed for the purpose of surrounding surveillance, object localization for early warning, rescue operations and restructuring plan et al. Two critical parameters, correction coefficient k c and weighted coefficient w s,i , are introduced into IDV-hop scheme to improve location performance. And then, NS-2 simulations demonstrate that analysis results match well with simulation results. Besides, performance comparisons of IDV-hop scheme with other DV-hop based schemes are also proposed. Analysis and comparison results show that localization delay and accuracy of IDV-hop is improved largely relative to other schemes, especially for higher node density.

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“…The ultrasonic ranging error is caused by several main factors of temperature, humidity, atmospheric pressure, NLOS, ultrasonic transmitter and receiver direction, ultrasonic receiver error, software processing delay and so on [7]. Next, we make a specific analysis of these main factors one by one.…”

Section: Solving Algorithm Of Positioning Equationmentioning

confidence: 99%

Application of Wireless Sensor in Automatic Device

2018

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Abstract-To improve the cost and accuracy in the positioning method of wireless sensor network in automatic devices, we proposed an improved distance based positioning method. We analyzed the positioning algorithm based on RSSI, TOA, TDOA, AOA distance measure. Due to different geographic shape, the right trajectory is important to the algorithm. We replaced hyperbola curve with asymptote in this study because the hyperbola positioning algorithm is not energy efficiency. We designed the positioning process of asymptote line algorithm. For the computational complexity, the hyperbola asymptotes are judged by the intersection point, which has an additional step compared to the maximum likelihood method. However, the maximum likelihood method must calculate the quadratic equations. The simulation results show that the algorithm proposed in this study is better than maximum likelihood method in positioning accuracy and the two algorithms have the same computational complexcity. The process of positioning presented in this study is simple and has a low cost.

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Cooperative method for wireless sensor network localization

Cited by 47 publications

References 27 publications

Soft-clustering Technique for Fingerprint-based Localization

Soft-clustering Technique for Fingerprint-based Localization

An Improved Localization Scheme Based on DV-Hop for Large-Scale Wireless Sensor Networks

Application of Wireless Sensor in Automatic Device

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