A Novel Localization Scheme Based on RSS Data for Wireless Sensor Networks

Abstract. Node localization is a fundamental and important technology in wireless sensor networks. In this paper, a localization algorithm in wireless sensor networks based on PSO is proposed. Unlike most of the existing location algorithm, the proposed algorithm figures out the rectangular estimation range of unknown node by bounding box algorithm and takes one value as the estimated coordinates of this node, then it has been optimized by PSO, so got the more precise location of unknown nodes. Simulation results show that this optimized algorithm outperforms traditional bounding box on the positioning accuracy and localization error.

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“…In this paper, RSS (Received Signal Strength) [7] is used to measure distance between two nodes. The radio range is a circle in this model.…”

Section: Communication Modelmentioning

confidence: 99%

A Localization Algorithm in Wireless Sensor Networks Based on PSO

Xiong

Liu

et al. 2011

Lecture Notes in Computer Science

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“…This scheme requires the path-loss model parameters, such as sensor node transmitting power and pathloss exponent, which generally assumed as a priori by means of calibration operation. Since RSS hardware with measured signal power technique is now becoming a regular feature of wireless devices and can be used to estimate the distance between target node and anchor [14], which can be used as an initial approximation of the input of the free space path loss model [15]. In literature [16], localization algorithm using weighted least square (WLS) criteria has been proposed, which considerably improves the location estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

A Computationally Efficient Received Signal Strength Based Localization Algorithm in Closed-Form for Wireless Sensor Network

Zhang

Xiong

Bao-guo

2017

Neural Process Lett

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Ranging error is known to degrade significantly the target node localization accuracy. This paper investigates the use of computationally efficient positioning solution of least square (LS) in closed-form, to reduce localization accuracy loss caused by ranging error. For range-based node localization, the LS solution based on least square criterion has been confirmed to exhibit capability of optimum estimation but extensively achieve at a very complex calculation. In this paper we consider the problem how to acquire such LS solution provided with estimation performance at low complex calculation. In this paper, we use the Gauss noise model and use the weighted least squares criterion and the effective calculation method to solve the linearized equation derived from the RSS measurement, and put forward a new approach to estimate the performance of the target node location estimation. Based on the Fisher information matrix, the Cramér-Rao lower bound of target position estimation is derived based on received signal strength. We obviously indicate that the proposed algorithm can approximately achieve the LS solution in estimation performance at a markedly low complex calculation. Simulations are performed to show the improvement of the proposed algorithm.

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“…The received signal strength indicator (RSSI) is one of the simplest methods that has been used for estimation of distances between nodes [7], [8], [9], [10], [11], [12]. The distance estimates are based on the strength of the signal received by another node.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Impact of the Physical Environment on a Wireless Sensor Network

Smolau

Beaubrun

2011

2011 IEEE International Conference on Communications (ICC)

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In this paper, we elaborate a set of scenarios and experiments for evaluating the impact of physical environment on a Wireless Sensor Network (WSN). More specifically, a WSN application is implemented for collecting received signal strength indicator (RSSI) measurements in two different environments. The main contributions are twofold: boxplot diagrams are used for graphical comparison of RSSI measurements, and statistical analysis of variance (ANOVA) is performed for evaluating the impact of physical environment on a WSN. Results analysis shows the conditions under which the impact of physical environment on a WSN is significant.

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A Novel Localization Scheme Based on RSS Data for Wireless Sensor Networks

Cited by 22 publications

References 2 publications

A Localization Algorithm in Wireless Sensor Networks Based on PSO

A Localization Algorithm in Wireless Sensor Networks Based on PSO

A Computationally Efficient Received Signal Strength Based Localization Algorithm in Closed-Form for Wireless Sensor Network

Analysis of the Impact of the Physical Environment on a Wireless Sensor Network

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