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LAP Lambert Academic Publishing Integration of Space Born and Ground Based Navigation Systems: An application of kalaman filter

Name: Integration of Space Born and Ground Based Navigation Systems: An application of kalaman filter
Brand: LAP Lambert Academic Publishing
Price: 53.0 GBP
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Electronics Engineering

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Description

The main driving force to integrate these two navigation systems as an integrated GPS/INS system in different architectural forms to provide robust positioning. The complementary advantages of GPS and INS have been extracted. The loosely coupled and tightly coupled GPS/INS systems have been in existence for more than two decades and performed reasonably well, nevertheless, the tracking performance was still a problem to be addressed in non-benign environments such as dynamic scenarios, indoor environments, urban areas, under foliages etc., where the GPS tracking loops lose lock due to the weak signals, subjected to excessive dynamics or completely blocked. The strong force for this research, therefore, was to address these limitations with ultra-tight integration architecture of GPS/ Pseudolite /INS system using Kalman filter. Since the theory on ultra-tight integrated system was still at its infancy at the commencement of this study, resources available are very less. The existing literature did not provide adequate design or implementation details. All these shortcomings have motivated this study

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 3659125458
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Electronics & Communications Engineering > Electronics Engineering
Domain: Amazon UK
Release Date: 28 July 2012
Listed Since: 31 July 2012

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LAP Lambert Academic Publishing Integration of Space Born and Ground Based Navigation Systems: An application of kalaman filter

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It has never been this cheap. We have no record of a lower price.

LAP Lambert Academic Publishing Integration of Space Born and Ground Based Navigation Systems: An application of kalaman filter

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