Distributed TOA-Based Positioning in Wireless Sensor Networks: A Potential Game Approach

Ke, Mingxing; Xu, Yuhua; Anpalagan, Alagan; Liu, Dianxiong; Zhang, Yuli

doi:10.1109/lcomm.2017.2765642

Cited by 30 publications

(22 citation statements)

References 13 publications

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“…The following proof follows the lines for proof in [ 28 ]. The potential function is formulated as follows:

…”

Section: Potential Game For Power Allocationmentioning

confidence: 98%

“…(ii) Distributed power allocation for agent nodes in cooperative localization scenarios was considered in [ 27 ], while we consider distributed power allocation for anchor nodes in this work. Also, a potential game based distributed ToA (time of arrival) localization approach was presented in [ 28 ], which is interesting and constructive.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach

Tian

et al. 2018

Sensors

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The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ-equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

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“…The following proof follows the lines for proof in [ 28 ]. The potential function is formulated as follows:

…”

Section: Potential Game For Power Allocationmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach

Tian

et al. 2018

Sensors

Self Cite

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“…Different types of measurements such as time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA or DOA), and signal power are used for localization and tracking in WSNs. Some mixed measurements are also proposed in previous studies .…”

Section: Introductionmentioning

confidence: 99%

Dual‐mode multiple‐target tracking in wireless sensor networks based on sensor grouping and maximum likelihood estimation

Adhami

Ghazizade

Majidi

2020

Int J Communication

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Summary The problem of tracking multiple mobile targets, using a wireless sensor network, is investigated in this paper. We propose a new sensor grouping algorithm, based on the maximum sensor separation distances (G‐MSSD), for estimating the location of multiple indistinguishable targets, either jointly or individually, depending on the distances between the generated groups. The joint tracking algorithm is formulated as a maximum likelihood (ML) estimator and solved through a modified version of the well‐known Gauss‐Newton (MGN) iterative method. We propose two candidate initial guesses for MGN based on G‐MSSD in joint tracking mode, while for the individual mode, the information of each group is used to estimate the location of only the corresponding target. The Cramer‐Rao lower bound (CRLB) for the variance of the proposed ML estimator is derived, and the potential conditions for reducing the CRLB are presented. Since tracking efficiency is affected by poor estimates, we present two criteria to evaluate the quality of estimates and detect the poor ones. An approach is also proposed for correcting the poor estimates, based on additional initial guesses. We demonstrate the effectiveness and accuracy of our proposed dual‐mode algorithm via simulation results and compare our results with the Multi‐Resolution search algorithm.

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“…Many kinds of measurements can be used as the positioning characteristic parameters, such as time of arrival (ToA) [4], time difference of arrival (TDoA) [5], frequency different of arrival (FDoA) [6], received signal strength (RSS) [7], angle of arrival (AoA) [8,9], and their combination [10][11][12]. Conventional positioning techniques rely on these measurements, and each has its own merits and drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Detection of an unknown radio transmitter using an enhanced K-nearest neighbor algorithm based on virtual reference point and RSSD information

Zhang

Jiang

2019

J Wireless Com Network

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Accurate detection of the unknown radio transmitter (URT) is crucial to combat illegal occupation of radio signal resources and protect communication system from harmful signal interference. The fingerprint positioning technique based on received signal strength (RSS) is famous for requiring no extra equipment, antenna arrays, and time synchronization. However, conventional RSS-based fingerprint positioning techniques that utilize K-nearest neighbor (KNN) method are confronted with problems when the positioning target is radio transmitter with unknown emission strength and frequency. Moreover, they not only cannot realize the precise localization of the URT but also only rely on pre-set reference points in the fingerprint database. In this paper, a new KNN-based geo-location approach using received signal strength difference (RSSD) information and virtual reference point is proposed to estimate an URT location. To obtain more accurate RSSD measurements, a RSSD-based filtering method by calculating the Euclidean distance between each sampling RSSD and the average value is devised to establish the fingerprint database. To achieve higher positioning accuracy, we combine KNN technique with the virtual reference (VR) point to propose RSSD-VRKNN algorithm. The simulation results show that the proposed scheme can obtain the best positioning performance compared with the conventional KNN and weighted K-nearest neighbor (WKNN) techniques. The performance and feasibility of our proposed algorithm are verified through extensive experiments.

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Distributed TOA-Based Positioning in Wireless Sensor Networks: A Potential Game Approach

Cited by 30 publications

References 13 publications

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach

Dual‐mode multiple‐target tracking in wireless sensor networks based on sensor grouping and maximum likelihood estimation

Detection of an unknown radio transmitter using an enhanced K-nearest neighbor algorithm based on virtual reference point and RSSD information

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