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Improving optimality of ultra tightl...

Sivananthan, Sivaloganathan.

Improving optimality of ultra tightly coupled GPS and INS integrated receiver prefilter using particle filters.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Improving optimality of ultra tightly coupled GPS and INS integrated receiver prefilter using particle filters.
Author:	Sivananthan, Sivaloganathan.
Description:	128 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .
Notes:	Adviser: Jay A. Weitzen.
Contained By:	Dissertation Abstracts International72-06B.
Subject:	Engineering, Electronics and Electrical.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3451822
ISBN:	9781124572666

Improving optimality of ultra tightly coupled GPS and INS integrated receiver prefilter using particle filters.
Sivananthan, Sivaloganathan.

Improving optimality of ultra tightly coupled GPS and INS integrated receiver prefilter using particle filters. - 128 p.

Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .

Thesis (Ph.D.)--University of Massachusetts Lowell, 2011.

A robust integrated receiver that integrates an Inertial Navigation System and a Global Positioning System and uses a Kalman Filter to close the phase lock loops has been proposed recently in the form of an Ultra Tightly Coupled (UTC) receiver. One of the complexities of the UTC receiver is establishing the mathematical relationship between the states from the INS, and measurements from the GPS. Many forms of ultra tight coupling method have been proposed by linearizing these relationships to realize these highly non-linear relationships in the integrated system. This thesis describes two approaches that have not been tried so far: first, it tries to measure the loss in optimality due to linearization by comparing UTC receiver's prefilter performance (the RMS errors of estimated quantities) to the performance limit given by the Posterior Cramer Rao Bound (PCRB); second, it implements a nonlinear filter involving Particle Filter to eliminate the linearization and measures the performance improvement. The prefilter that models the relationship between the GPS signal quantities early, punctual and late in-phase and quadrature phase amplitudes and receiver measurements pseudo range and range rate are presented and their PCRBs are derived. A particular implementation of particle filter known as Regularized Particle Filter (RPF) is implemented. Simulation results are presented to show how much accuracy is lost due to the linearized suboptimal implementation and the improvement achievable by employing a nonlinear filter. It is shown that RMS errors of the estimated parameters are an order of magnitude higher than their lower bounds. It is also shown that the RPF can achieve about 21% improvement in the pseudo range estimation and 33% improvement in the range rate estimation.

ISBN: 9781124572666Subjects--Topical Terms:

226981
Engineering, Electronics and Electrical.

Improving optimality of ultra tightly coupled GPS and INS integrated receiver prefilter using particle filters.
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245 1 0 $a Improving optimality of ultra tightly coupled GPS and INS integrated receiver prefilter using particle filters.
300 $a 128 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .
500 $a Adviser: Jay A. Weitzen.
502 $a Thesis (Ph.D.)--University of Massachusetts Lowell, 2011.
520 $a A robust integrated receiver that integrates an Inertial Navigation System and a Global Positioning System and uses a Kalman Filter to close the phase lock loops has been proposed recently in the form of an Ultra Tightly Coupled (UTC) receiver. One of the complexities of the UTC receiver is establishing the mathematical relationship between the states from the INS, and measurements from the GPS. Many forms of ultra tight coupling method have been proposed by linearizing these relationships to realize these highly non-linear relationships in the integrated system. This thesis describes two approaches that have not been tried so far: first, it tries to measure the loss in optimality due to linearization by comparing UTC receiver's prefilter performance (the RMS errors of estimated quantities) to the performance limit given by the Posterior Cramer Rao Bound (PCRB); second, it implements a nonlinear filter involving Particle Filter to eliminate the linearization and measures the performance improvement. The prefilter that models the relationship between the GPS signal quantities early, punctual and late in-phase and quadrature phase amplitudes and receiver measurements pseudo range and range rate are presented and their PCRBs are derived. A particular implementation of particle filter known as Regularized Particle Filter (RPF) is implemented. Simulation results are presented to show how much accuracy is lost due to the linearized suboptimal implementation and the improvement achievable by employing a nonlinear filter. It is shown that RMS errors of the estimated parameters are an order of magnitude higher than their lower bounds. It is also shown that the RPF can achieve about 21% improvement in the pseudo range estimation and 33% improvement in the range rate estimation.
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