Weighted Linear Least Square Localization Algorithms for Received Signal Strength

Wu, Shixun; Xu, Dengyuan; Liu, Shouyin

doi:10.1007/s11277-013-1040-0

Cited by 15 publications

(9 citation statements)

References 10 publications

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“…distance between the source and the receiver that can be exploited to locate the source by converting the received power into distance [12]. Multiple locations can be added by using multiple receiver nodes that allow trilateration or even multilateration.…”

Section: Proceedings Of the 23rd International Conference On Automatimentioning

confidence: 99%

“…Multiple locations can be added by using multiple receiver nodes that allow trilateration or even multilateration. The main issue is the accuracy of the estimated location because of the heterogeneous nature of the radio propagation environment [12]. The major challenge that is faced in PD localization is the anonymity of the propagation parameters i.e.…”

Section: Proceedings Of the 23rd International Conference On Automatimentioning

confidence: 99%

“…The major challenge that is faced in PD localization is the anonymity of the propagation parameters i.e. the source transmitted power is unknown as well as the path loss index is environment dependent and can vary from node to node due to the heterogeneous nature of the propagation enviromemnt [12] [13]. The following equation describes the RSS model that is based on the common path loss model:…”

Section: Proceedings Of the 23rd International Conference On Automatimentioning

confidence: 99%

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Partial discharge localization based on received signal strength

Mohamed

Lazaridis

Upton

et al. 2017

2017 23rd International Conference on Automation and Computing (ICAC)

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Abstract-Partial Discharge (PD) occurs when insulation containing defects or voids is subject to high voltages. If left untreated PD can degrade insulation until, eventually, catastrophic insulation failure occurs. The detection of PD current pulses, however, can allow incipient insulation faults to be identified, located and repaired prior to plant failure. Wireless technology has paved the path for PD detection and monitoring. Software Defined Radio (SDR) is a promising technology. Signals from two PD sources are received at six outdoors locations using an SDR USRP N200 which is connected to a laptop. PD sources, thereafter, are localized based on received signal strengths.

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Section: Proceedings Of the 23rd International Conference On Automatimentioning

confidence: 99%

Section: Proceedings Of the 23rd International Conference On Automatimentioning

confidence: 99%

Section: Proceedings Of the 23rd International Conference On Automatimentioning

confidence: 99%

See 1 more Smart Citation

Partial discharge localization based on received signal strength

Mohamed

Lazaridis

Upton

et al. 2017

2017 23rd International Conference on Automation and Computing (ICAC)

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“…The cumulative error is caused by the accumulation of the preceding round of localization errors, so effectively eliminating the preceding round of localization errors can avoid the accumulation of errors. Inspired by this, the researchers [22] proposed that the weighted least squares method with the inverse of the variance of the errors as weight could eliminate the impact of the previous round of errors. There have been many discussions about the weight matrix W, however, it is difficult to know the size of errors in the actual environment.…”

Section: Improved Localization Algorithmmentioning

confidence: 99%

Incremental Localization Algorithm Based on Regularized Iteratively Reweighted Least Square

Yan

Song

Liu

et al. 2016

Foundations of Computing and Decision Sciences

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Abstract.Incremental localization algorithm is a distributed localization method with excellent characteristics for wireless network. However, its estimated result is generally influenced by the heteroscedasticity arising from cumulative errors and the collineation among anchor nodes. We have proposed a novel incremental localization algorithm with consideration to cumulative errors and collinearity among anchors. Using iteratively reweighted and regularized method, the algorithm reduces the influences of errors accumulation and avoids collinearity problem between anchors. Simulation experiment results show that compared with the previous incremental localization algorithms, the proposed algorithm obtains a localization solution which not only has high accuracy but also high stability. Therefore, the proposed algorithm is suitable for different deployment environments and has high adaptability.

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“…The most popular means of wireless location involve the measurement of time of arrival (TOA), time difference of arrival (TDOA), received signal strength (RSS) and angle of arrival (AOA) [1][2][3][4][5] of radio signals transmitted by the mobile station (MS) and received at a number of fixed base stations (BSs) or vice versa.…”

Section: Introductionmentioning

confidence: 99%

Adaptive NLOS Mitigation Location Algorithm in Wireless Cellular Network

Wang

2015

Wireless Pers Commun

Self Cite

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In a cellular network, a location scenario is considered in this paper, which the home base station (BS) measures the range and angle while neighboring BSs measure the ranges. Based on the range and angle measurements, two adaptive non-line-of-sight (NLOS) identification and mitigation location algorithms with low complexity are proposed. The main idea of our proposed algorithms is to search the optimal subset of range and angle measurements by utilizing the hybrid lines of position algorithm and comparing the normalized residual error to perform the NLOS identification and location. Compared with the existing algorithms, the proposed algorithms have three advantages: one is different to the existing algorithms that require at least three BSs, the proposed algorithms can be suitable for two BSs scenario. Second is the low complexity of our proposed algorithms compared with the existing algorithms. The last is simulation results show that the proposed algorithms outperform the existing algorithms in bad urban and urban environments.

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Weighted Linear Least Square Localization Algorithms for Received Signal Strength

Cited by 15 publications

References 10 publications

Partial discharge localization based on received signal strength

Partial discharge localization based on received signal strength

Incremental Localization Algorithm Based on Regularized Iteratively Reweighted Least Square

Adaptive NLOS Mitigation Location Algorithm in Wireless Cellular Network

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