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An Adaptive Filter for INS/GPS Integrated Navigation System

Authors: Hang Shi; Zhou Wu; Baosheng Liu;

An Adaptive Filter for INS/GPS Integrated Navigation System

Abstract

The integrated navigation system, specially the system based on GPS and INS, is a leading trend of navigation technology, and some of typical integrated navigation systems have been developed and tested in the past few years (Farrell, 1998). But due to the complex application circumstance, it is difficult to describe the noise statistical property accurately. In this paper, a modified adaptive filter algorithm is presented for INS/GPS integrated navigation system. At first, an improved Kalman filter and Hinfin robust filter are explicitly represented for INS/GPS integrated navigation system. Meanwhile, a standard for judging that whether the filter trends to divergence is proposed to combine the two methods. Aiming at the detail position/velocity integrated mode, the computer simulation result of INS/GPS integrated navigation show that this method can restrain the divergence effectively and has better adaptive ability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
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