Non-linear, non-Gaussian estimation for improving position and orientation determination in mobile mapping system

Thanh Trung Duong, Kai-Wei Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In a mobile mapping system, the integration of Inertial Navigation System (INS) and Global Positioning System (GPS) is widely applied for determining position and orientation. The Kalman filter or Extended Kalman Filter (EKF) is popularly used for data fusion estimation. In such those estimation strategies, linearization and assuming Gaussian distribution are utilized. However, the fact that the system model and measurement model in INS/GPS integration are originally non-linear and the noise arising during operation may be non-Gaussian distribution. These characteristics may leads to the low performance of the system utilizing KF or EKF in case of highly non-linear model and non-Gaussian noises. This paper investigates on some of non-linear, non-Gaussian estimation strategies in order to improve the performance of the system.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages698-703
Number of pages6
Publication statusPublished - 2011 Dec 1
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
Duration: 2011 Oct 32011 Oct 7

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume1

Other

Other32nd Asian Conference on Remote Sensing 2011, ACRS 2011
CountryTaiwan
CityTapei
Period11-10-0311-10-07

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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