Multisensor Integration and Data Fusion for Positioning

Author:

Li Yong1,Jiang Wei2,Yang Ling3,Rizos Chris4

Affiliation:

1. Navextech Technology Ltd, Australia

2. Beijing Jiaotong University, China

3. Tongji University, China

4. University of New South Wales, Australia

Abstract

This chapter presents an alternative framework to the traditional centralised Kalman filtering (CKF) approach for implementing the optimal state estimation algorithm in support of multisensor integration. The data fusion algorithm is implemented via a series of transformations of vectors in the so-called information space (iSpace). This chapter describes how the conventional decentralised Kalman filtering (DKF) algorithm can be derived using a unified approach. A new global optimal fusion (GOF) algorithm is derived using the iSpace approach. Two case studies are presented to illustrate applications of the multisensor algorithms for GNSS/Locata/INS and GNSS/WiFi/INS integration.

Publisher

IGI Global

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4. Applanix Corporation. (2009). POS MV V4 User guide. Author.

5. Error equations of inertial navigation

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