A linear combination-based weighted least square approach for target localization with noisy range measurements

Wang, Chang; Qi, Fei; Shi, Guangming; Ren, Jingbo

doi:10.1016/j.sigpro.2013.06.005

Cited by 12 publications

(11 citation statements)

References 18 publications

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“…Most of the previous methods [5,6,8,11,23,25] are based on the least square procedure. Thus, the source position is computed by…”

Section: Problem Formulationmentioning

confidence: 99%

“…There are algebraic method and matrix method for the multistation localization system [5]. Algebraic methods mainly include the TOA method [19] which uses the circles produced by range measurements at other sensors to find the position of the transmitter at the intersection of circles in two dimensions or spheres in three dimensions and the AOA method [10] which calculates the target position from the point of intersection of bearing lines.…”

Section: Introductionmentioning

confidence: 99%

“…It should be noted that algebraic methods are designed for the minimum location system, such as the TOA method with three anchor sensors, and the AOA method with two anchor sensors. The main advantage of algebraic methods is that they can provide a simple algebraic solution without the computation of matrix inversion which makes those methods can be applied in a low-cost location system especially for wireless sensor networks (WSNs) [5,20]. Since the algebraic methods are based on local information of a minimum system, the direct extension for those methods to a multistation redundancy system may not obtain optimal performance since those solutions cannot make use of extra measurements to improve position accuracy [8].…”

Section: Introductionmentioning

confidence: 99%

“…To improve the localization accuracy, matrix methods [5,6,8,11,[21][22][23][24][25] based on global information of measurements from all sensors were developed for a multistation redundancy system. The closed-form solution which requires solving a set of linear equations including all the measurements was given by Friedlander [21].…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Estimator for Target Localization in a Multistation Redundancy System without Matrix Inversion

et al. 2018

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This paper focuses on target localization problem in a multistation redundancy system which finds broad applications in sonar, radar, and location-based service. Previous solutions can only be applied to the minimum system, such as the TOA method with three sensors and the AOA method with two sensors or need matrix inversion. To solve this problem, we propose a simple closed-form solution for a multistation redundancy localization system by using the estimation variance as the weighting coefficient to compute an average of each group's localization result. The proposed method, with simple algebraic solution, requires no matrix inversion and can be used for low-cost hardware devices. We derive the method in TOA solution and AOA solution, respectively. The proposed method can also be extended to other locating technologies. Numerical examples are provided to illustrate the performance of the proposed method in root-mean-square error. The positioning accuracy of the proposed method is close to Cramér-Rao low bound both in TOA solution and AOA solution.

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“…Most of the previous methods [5,6,8,11,23,25] are based on the least square procedure. Thus, the source position is computed by…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Efficient Estimator for Target Localization in a Multistation Redundancy System without Matrix Inversion

et al. 2018

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“…For different mounting target, digital aircraft assembly tooling need to adapt to dynamic assembly environments, digital measuring device for measuring a benchmark during assembly gradually moving generally [2,3]. Digital measuring instruments relied upon in the traditional sense, the calculation method of measurement results also tend to use the least squares method and weighted least squares method [4,5]. These methods can be used for general reference solving, but it is difficult to meet the positioning error criterion in assembly areas.…”

Section: Introductionmentioning

confidence: 99%

Locating Datum Modeling for Minimum Normal Error in Aircraft Digital Assembly System

Hu¹,

Wang²,

Ren³

et al. 2015

Advances in Intelligent Systems Research

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Abstract. This paper analyzes the status of aircraft digital assembly process locating datum modeling methods, study the localization process of the aircraft digital assembly. By analyzing the error evaluation criteria for assembly positioning, proposed a locating datum modeling method for the minimum normal error, and the locating datum model can get the targeting points of aircraft digital assembly process. Finally, through the digital assembly locating datum modeling of one aircraft to verify, and get a better results.

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A hybrid RSSI and AoA indoor positioning approach with adapted confidence evaluator

Wu,

Wang,

2024

Ad Hoc Networks

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A linear combination-based weighted least square approach for target localization with noisy range measurements

Cited by 12 publications

References 18 publications

An Efficient Estimator for Target Localization in a Multistation Redundancy System without Matrix Inversion

An Efficient Estimator for Target Localization in a Multistation Redundancy System without Matrix Inversion

Locating Datum Modeling for Minimum Normal Error in Aircraft Digital Assembly System

A hybrid RSSI and AoA indoor positioning approach with adapted confidence evaluator

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