VN-APIT: virtual nodes-based range-free APIT localization scheme for WSN

Jilong, Liu; Wang, Zhe; Yao, Mingwu; Qiu, Zhiliang

doi:10.1007/s11276-015-1007-z

Cited by 50 publications

(24 citation statements)

References 17 publications

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“…The broadcasting message includes its position information and ID. The nodes (includes other anchor nodes and all unknown nodes) collects the messages and exchange the message (including the value of RSSI) with their neighbor unknown nodes [20]. The format of the message is shown in Figure 3.…”

Section: Related Workmentioning

confidence: 99%

HTCRL: A Range-Free Location Algorithm Based on Homothetic Triangle Cyclic Refinement in Wireless Sensor Networks

et al. 2017

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Abstract:Wireless sensor networks (WSN) have become a significant technology in recent years. They can be widely used in many applications. WSNs consist of a large number of sensor nodes and each of them is energy-constrained and low-power dissipation. Most of the sensor nodes are tiny sensors with small memories and do not acquire their own locations. This means determining the locations of the unknown sensor nodes is one of the key issues in WSN. In this paper, an improved APIT algorithm HTCRL (Homothetic Triangle Cyclic Refinement Location) is proposed, which is based on the principle of the homothetic triangle. It adopts perpendicular median surface cutting to narrow down target area in order to decrease the average localization error rate. It reduces the probability of misjudgment by adding the conditions of judgment. It can get a relatively high accuracy compared with the typical APIT algorithm without any additional hardware equipment or increasing the communication overhead.

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Section: Related Workmentioning

confidence: 99%

HTCRL: A Range-Free Location Algorithm Based on Homothetic Triangle Cyclic Refinement in Wireless Sensor Networks

et al. 2017

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“…Range-free positioning is an indirect type of estimated positioning [9]. Typical algorithms include DV-hop [10] and APIT [11]. e advantage of range-free positioning is that there is no need to deploy auxiliary hardware, so it has a lower cost.…”

Section: Introductionmentioning

confidence: 99%

Range-Based Positioning with Self-Adapting Fireworks Algorithm for Wireless Sensor Networks

Huang

2020

Mathematical Problems in Engineering

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Positioning is the basic function of wireless sensor networks (WSN). At present, range-based positioning is a common method to obtain the position of a node, but its accuracy has encountered a bottleneck. The fundamental reason is that it ignores the ranging information between blind nodes. Therefore, based on the design of the positioning optimization factor to adjust the weight of the ranging information between the blind nodes, the positioning model of minimizing the error is established. On the basis of designing the blind node positioning matrix, the multiblind node localization problem is transformed into a single-objective optimization task, and the model also supports two-dimensional and three-dimensional positioning. In order to solve the model efficiently, we added a self-adaptive function that matches the positioning requirements for the explosion search mechanism of the fireworks algorithm (FWA) and then proposed a self-adaptive FWA (SA-FWA). The experimental results on the real ranging dataset show that the model has higher accuracy than other methods and achieves the current optimal positioning error, which is 1.88 m for received signal strength data and 1.02 m for time of arrival information, respectively.

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“…The region can be refined further using several complex algorithms. The unknown node is then estimated to be centroid [8,9] or chosen randomly inside this region [10]. Because range-free methods do not have any information about the network but the signal coverage, they need a denser network than the range-based methods in order to locate nodes.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

Nguyen

Tran

Safaei

et al. 2019

Sensors

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Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques.

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VN-APIT: virtual nodes-based range-free APIT localization scheme for WSN

Cited by 50 publications

References 17 publications

HTCRL: A Range-Free Location Algorithm Based on Homothetic Triangle Cyclic Refinement in Wireless Sensor Networks

HTCRL: A Range-Free Location Algorithm Based on Homothetic Triangle Cyclic Refinement in Wireless Sensor Networks

Range-Based Positioning with Self-Adapting Fireworks Algorithm for Wireless Sensor Networks

Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

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