Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering

Muthukrishnan, Kavitha; Hazas, Mike

doi:10.1007/978-3-642-01721-6_14

Cited by 21 publications

(17 citation statements)

References 9 publications

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“…This approximation can introduce errors that in general lead to a non-optimal performance of this filter and in some cases to diverge from the true solution. To solve these problems, there are in the literature a wide range of methods that try to minimize the error [4,39,41,44].…”

Section: Position Estimatormentioning

confidence: 99%

Advanced Train Location Simulator (ATLAS) for developing, testing and validating on-board railway location systems

Goya

Zamora-Cadenas

Arrizabalaga

et al. 2015

Eur. Transp. Res. Rev.

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Purpose This article focuses on a novel Advanced Train LocAtion Simulator (ATLAS) for on-board railway location using wireless communication technologies, such as satellite navigation and location based systems. ATLAS allows the creation of multiple simulation environments providing a versatile tool for testing and assessing new train location services. This enhancement reduces the number of tests performed in real scenarios and trains, reducing the cost and development time of new location systems as well as assessing the performance level for given tracks. Methods The simulation platform is based on modular blocks, where each block can be replaced or improved. The

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Section: Position Estimatormentioning

confidence: 99%

Advanced Train Location Simulator (ATLAS) for developing, testing and validating on-board railway location systems

Goya

Zamora-Cadenas

Arrizabalaga

et al. 2015

Eur. Transp. Res. Rev.

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“…The positions of the deployed nodes were surveyed a priori using a tape measure with reference to the walls. Eleven nodes were deployed in a lab that was relatively empty except for some desks in the corners of the room; three were placed in rooms along the other side of the corridor representing typical office spaces; and the remaining seven were placed in the corridor connecting the rooms and the lab (refer to [22] for the deployment area). In all the experiments the inertial sensor and an ultrasound node which was transmitting ultrasonic pulses were firmly attached to the user's foot ( Fig.1(b)).…”

Section: Data Collectionmentioning

confidence: 99%

“…We use the results of the Ubisense Location Engine [35] (refer to our previous work [22] reporting the Ubisense performance for the same deployment area) to report the groundtruth measurements. In addition to the IMU and ultrasound node, the users also carried an Ubisense compact tag to gather the groundtruth for validation purposes.…”

Section: A Groundtruth or Reference Systemmentioning

confidence: 99%

“…Although the Ubisense estimates will have some error, they are close enough for the purposes of judging the validity of the tracking performance (especially to see the shape of the trail). Additionally, since we enabled extra filtering [36] as opposed to the default Ubisense location algorithm, with no filtering, the estimates we use for comparison are likely more accurate than the results reported in [22]. For static beacon localisation, the manually surveyed points are used to validate the results of MDS.…”

Section: A Groundtruth or Reference Systemmentioning

confidence: 99%

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Towards a Rapidly Deployable Positioning System for Emergency Responders

Muthukrishnan¹,

Dulman²,

Langendoen³

2011

jgps

Self Cite

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Abstract-Providing ad-hoc solutions for positioning and tracking of emergency response teams is an important and safety-critical challenge. Although solutions based on inertial sensing systems are promising, they are subject to drift. We address the problem of positional drift by having the responders themselves deploy beacons, specifically ultrasound beacons, as they progress into an unknown environment. Our research focuses on a sensor network approach that does not require any pre-deployment of infrastructure. This paper targets two important aspects within the context of providing positioning service for emergency responders namely on how to locate the deployed static beacons, and on how to track the responders by using a combination of ultrasound and inertial measurements. The main contributions of this paper are: (i) characterisation of the errors encountered in an inertial-based pedestrian dead reckoning solution and ultrasound range measurements in a mobile setting, (ii) an algorithm for ultrasound beacon localisation (using multidimensional scaling), (iii) formulation of a Kalman filtering based algorithm for tracking the responder using a combination of ultrasound range and inertial measurements, and (iv) the presented algorithms are evaluated using data collected from real deployments and are compared against an ultra-wideband (UWB) precision location system. Our approach of preventing the drift in inertial estimates by combining with ultrasound measurements are promising and offers a viable solution to providing positioning and tracking support to emergency responders.

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“…While localization is done by knowing the probability density function of the noise in parametric methods, in methods that are not parametric, localization is done without any information about the noise [5]. In the literature, in addition to these methods, there are some others that use these methods for different environments [6,[14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Horizontal dilution of precision-based ultra-wideband positioning technique for indoor environments

Küçük¹

2014

Turk J Elec Eng & Comp Sci

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Ultra-wideband (UWB) technology provides considerable performance in many indoor localization problems thanks to its very wide spectrum and high-resolution characteristics. In this paper, we propose using the horizontal dilution of precision (HDOP) to decrease the localization error in indoor environments for UWB localization systems.To achieve this aim, first we determine the positioning accuracy of a commercially available UWB positioning system using laboratory experiments. Next, the results of the position estimations obtained by the HDOP are compared with the experimental results acquired by the UWB positioning system. Finally, we investigate a detailed comparison with the least squares (LS), nonlinear regression (NLR), and iterative nonlinear regression (INR) techniques. In terms of the mean position estimation error, the proposed HDOP technique increases the performance of the UWB positioning system and the LS algorithm by approximately 10% and 3%, respectively. In addition, while the proposed HDOP technique provides localization for all of the test points, both the NLR and INR algorithms perform below the expected levels at the same points.

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Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering

Cited by 21 publications

References 9 publications

Advanced Train Location Simulator (ATLAS) for developing, testing and validating on-board railway location systems

Advanced Train Location Simulator (ATLAS) for developing, testing and validating on-board railway location systems

Towards a Rapidly Deployable Positioning System for Emergency Responders

Horizontal dilution of precision-based ultra-wideband positioning technique for indoor environments

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