Verification of Robustified Kalman Filters for the Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) Data,

Abstract

The purpose of this research is to compare the effects of two filtering routines which may be used to integrate Inertial Navigation System (INS) and Global Positioning System (GPS) data to determine certain state vector elements. The two filtering routines are: 1) the ordinary Kalman Filter, and 2) a Two-Stage Least- Squares Procedure, which will be referred to as the 2-Stage Filter. Using the Kalman Filter to determine state vector elements, the vector quantities can be affected when system error is introduced into the model. Theoretically, the 2-Stage Filter is more robust, that is, it should be able to determine accurately the state vector elements despite the presence of errors (Schaffrin 1991) This research will attempt to verify the 2-Stage Filter is, in fact, a more robust filter than the Kalman Filter.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1994
Accession Number
ADA288609

Entities

People

  • Jeffrey W. Haak

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Coordinate Systems
  • Covariance
  • Data Sets
  • Differential Equations
  • Equations
  • Equations Of State
  • Filters
  • Filtration
  • Global Positioning Systems
  • Inertial Navigation
  • Inertial Navigation Systems
  • Kalman Filters
  • Navigation
  • New York
  • Observation
  • Observers
  • Statistical Analysis

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Positioning, Navigation, and Timing (PNT) Technology.

Technology Areas

  • Space