Performance analysis of diverse environment based on RSSI localization algorithms in wsns

Livinsa, Z. Mary; Jayashri, S.

doi:10.1109/cict.2013.6558160

Cited by 13 publications

(8 citation statements)

References 6 publications

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“…The trilateration measurement method [17][18][19][20] is widely used for positioning the calculation of sensor nodes in WSNs. This method can be used to determine the sensor node position if the distance between the three anchor nodes and target sensor node are known [7].…”

Section: Related Workmentioning

confidence: 99%

Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling

et al. 2016

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This study aims to determine the distance between the mobile sensor node (i.e., bicycle) and the anchor node (i.e., coach) in outdoor and indoor environments. Two approaches were considered to estimate such a distance. The first approach was based on the traditional channel propagation model that used the log-normal shadowing model (LNSM), while the second approach was based on a proposed hybrid particle swarm optimizationartificial neural network (PSO-ANN) algorithm to improve the distance estimation accuracy of the mobile node. The first method estimated the distance according to the LNSM and the measured received signal strength indicator (RSSI) of the anchor node, which in turn used the ZigBee wireless protocol. The LNSM parameters were measured based on the RSSI measurements in both outdoor and indoor environments. A feed-forward neural network type and the Levenberg-Marquardt training algorithm were used to estimate the distance between the mobile node and the coach. The hybrid PSO-ANN algorithm significantly improved the distance estimation accuracy more than the traditional LNSM method without additional components. The hybrid PSO-ANN algorithm achieved a mean absolute error of 0.022 m and 0.208 m for outdoor and indoor environments, respectively. The effect of anchor node density on localization accuracy was also investigated in the indoor environment.

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Section: Related Workmentioning

confidence: 99%

Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling

et al. 2016

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“…Xu et al [28] proposed an RSSI-based distance measurement model using log-normal shadowing model with dynamic variance propagation model and found that the proposed propagation model owns strong self-adaptability to various environments. Livinsa and Jayashri [29] proposed an RSSI-based location algorithm for distance estimation and location estimation under outdoor environment and indoor environment. They discovered that the performance of distance estimation in outdoor environment is better than that in indoor environment.…”

Section: Related Workmentioning

confidence: 99%

The Accurate Location Estimation of Sensor Node Using Received Signal Strength Measurements in Large-Scale Farmland

Miao

Zhang

2018

Journal of Sensors

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The range measurement is the premise for location, and the precise range measurement is the assurance of accurate location. Hence, it is essential to know the accurate internode distance. It is noted that the path loss model plays an important role in improving the quality and reliability of ranging accuracy. Therefore, it is necessary to investigate the path loss model in actual propagation environment. Through the analysis of experiments performed at the wheat field, we find that the best fitted parametric exponential decay model (OFPEDM) can achieve a higher distance estimation accuracy and adaptability to environment variations in comparison to the traditional path loss models. Based on the proposed OFPEDM, we perform the RSSI-based location experiments in wheat field. Through simulating the location characteristics in MATLAB, we find that for all the unknown nodes, the location errors range from 0.0004 m to 5.1739 m. The location error in this RSSI-based location algorithm is acceptable in the wide areas such as wheat field. The findings in this research may provide reference for location estimation in large-scale farmland.

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“…Localization is motivated by military applications such as battlefield surveillance. In localization, there are various algorithms and techniques that have been proposed for a localize node [11]. Mainly localization uses two types of nodes namely anchor node or beacon node and target node or unknown node [9] [10].…”

Section: Background Of Localizationmentioning

confidence: 99%

“…Z.Mary Livinsa el at [11] proposed the RSSI based localization algorithm for distance estimation and position estimation for reduce the localization error. In distance estimation, path loss model is used for the received signal strength power and 3 anchor nodes are used for the position estimation with trilateration method to reduce the localization error by using linear equation.…”

Section: Multilaterationmentioning

confidence: 99%

RSSI Based Localization Scheme in Wireless Sensor Networks: A Survey

Mistry¹,

Mistry²

2015

2015 Fifth International Conference on Advanced Computing &Amp; Communication Technologies

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Now a days, Wireless Sensor Networks (WSNs) are most growing research area because of its low cost, infrastructure less, increase capabilities of nodes, real time and accurate. Localization is a major issue in the wireless sensor networks because it has a number of sensor nodes which are deployed at positions and they may not be fixed at their own position. In localization different techniques are used for distance and position estimation. In this paper we will focus on RSSI based localization in WSN which will show how to reduce location errors and improve accuracy by using various models and techniques. After that we will focus on how to make an algorithm scalable and improve the energy efficiency by providing authentication and key management.

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Performance analysis of diverse environment based on RSSI localization algorithms in wsns

Cited by 13 publications

References 6 publications

Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling

Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling

The Accurate Location Estimation of Sensor Node Using Received Signal Strength Measurements in Large-Scale Farmland

RSSI Based Localization Scheme in Wireless Sensor Networks: A Survey

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