Optimality analysis of sensor-target localization geometries

Bishop, Adrian N.; Fi̇dan, Barış; Anderson, Brian D. O.; Doğançay, Kutluyıl; Pathirana, Pubudu N.

doi:10.1016/j.automatica.2009.12.003

Cited by 392 publications

(314 citation statements)

References 20 publications

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“…Moreover, we can even consider cases in which the standard deviation is multiplied by a percentage of the true range value between the target and individual sensors. In both these cases the Fisher information matrix for velocity estimation becomes very similar to the Fisher information matrix for bearing-only localization and we point to [26] for the details.…”

Section: On the Fisher Information For Velocity Estimationmentioning

confidence: 89%

“…Firstly, we note that optimal sensor placement for velocity estimation is equivalent to the optimal sensor placement for range-based localization as outlined in [26]. However, importantly, the optimal sensor placement for estimating the target velocity does not depend on the velocity itself.…”

Section: On the Fisher Information For Velocity Estimationmentioning

confidence: 98%

“…2 illustrates two optimal sensor placement scenarios obtained from each other by reflecting a particular sensor about the emitter position. For more information on the proof of Proposition 8 and further details the reader may refer to [26].…”

Section: On the Fisher Information For Velocity Estimationmentioning

confidence: 99%

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Doppler Shift Target Localization

Shames

Bishop

Smith³

et al. 2013

IEEE Trans. Aerosp. Electron. Syst.

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This is an author produced version of a paper published in IEEE Transactions on Aerospace and Electronic Systems.This paper has been peer-reviewed but does not include the final publisher proofcorrections or proceedings pagination.© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Abstract-This paper outlines the problem of doppler-based target position and velocity estimation using a sensor network. The minimum number of doppler shift measurements at distinct generic sensor positions to have a finite number of solutions, and later, a unique solution for the unknown target position and velocity is stated analytically. Furthermore, we study the same problem where not only doppler shift measurements are collected, but also other types of measurements are available, e.g. bearing or distance to the target from each of the sensors. Later, we study the Cramer-Rao inequality associated with the doppler-shift measurements to a target in a sensor network, and use the Cramer-Rao bound to illustrate some results on optimal placements of the sensors when the goal is to estimate the velocity of the target. Some simulation results are presented in the end.

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Section: On the Fisher Information For Velocity Estimationmentioning

confidence: 89%

Section: On the Fisher Information For Velocity Estimationmentioning

confidence: 98%

See 1 more Smart Citation

Doppler Shift Target Localization

Shames

Bishop

Smith³

et al. 2013

IEEE Trans. Aerosp. Electron. Syst.

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“…This problem has overcome incorporating a priori information about the approximate position of the target (Fang, 1990). Placement of receivers affects substantially the performance of the localization algorithm (Bishop et al, 2010), who found that the optimal placement of two receivers in range-based localization is when they form an angle with the target of π 2 . For three receivers, there are two optimal placement possibilities according to corollary 1 in Bishop et al (2010), π 3 , and 2π 3 .…”

Section: Introductionmentioning

confidence: 99%

“…Placement of receivers affects substantially the performance of the localization algorithm (Bishop et al, 2010), who found that the optimal placement of two receivers in range-based localization is when they form an angle with the target of π 2 . For three receivers, there are two optimal placement possibilities according to corollary 1 in Bishop et al (2010), π 3 , and 2π 3 . Han et al (2007) proposed improving localization accuracy, placing the receivers on vertices of equilateral triangles.…”

Section: Introductionmentioning

confidence: 99%

Indoor localization: novel RSSI approach based on analytical solution and two receivers

Ahmad

Petković

Toepfer

2017

J. Sens. Sens. Syst.

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Abstract. Indoor localization based on trilateration method uses at least three receivers for an accurate localization in 2-D. We performed indoor localization in 2-D using only two receivers, combining algebraic equations for signal strengths into one quadratic equation with transmitter position as unknown and using a specific receiver placement at the two adjacent corners of the room. This receiver arrangement assures unique coordinates of the transmitter position inside a room, rejecting automatically the other solution which appears outside the room volume. The accuracy of the method is numerically tested in a room with dimensions of 9.7 m × 4.7 m × 3 m and shows a mean reconstruction error of 3.4 cm.

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Human Motion Capture and Identification for Assistive Systems Design in Rehabilitation

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3 Jointtype enumeration. https://msdn.microsoft.com/en-us/library/microsoft.kinect .jointtype.aspx. Accessed: 2015-05-22. 4 Kinect for windows features. https://www.microsoft.com/en-us/kinectforwindows/ meetkinect/features.aspx. Accessed: 2015-05-22. 5 Rokoko smartsuit pro. https://www.rokoko.com/en?gclid=CjwKCAjw_47YBRBxEiwAYu KdwynSSU8rlweQF-R8QBmqMjHq_aEzrUOffS7E0CYpc2pRCkeV9LAZ-xoCrT4QAvD_ BwE. Accessed: 2018-05-20. 6 Tracking users with kinect skeletal tracking. https://msdn.microsoft.com/en-us/library/ jj131025.aspx. Accessed: 2015-05-22.

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Optimality analysis of sensor-target localization geometries

Cited by 392 publications

References 20 publications

Doppler Shift Target Localization

Doppler Shift Target Localization

Indoor localization: novel RSSI approach based on analytical solution and two receivers

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