A Comparison of the Least Squares with Kalman Filter Methods Used in Algorithms of Fusion with Dead Reckoning Navigation Data

Abstract

Different calculation methods and configurations of navigation systems can be used in algorithms of navigational parameter fusion and estimation. The article presents a comparison of two methods of fusion of dead reckoning position with that from a positioning system. These are the least squares method and the Kalman filter. In both methods the minimization of the sum of squared measurement deviations is the optimization criterion. Both methods of navigation position parameter measurements fusion are illustrated using the data recorded during actual sea trials. With the same probabilistic model of dead reckoning navigation, the fusion of DR results with positioning data gives similar outcome.

Authors and Affiliations

Andrzej Banachowicz, Adam Wolski

Keywords

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  • EP ID EP246973
  • DOI 10.12716/1001.11.04.16
  • Views 103
  • Downloads 0

How To Cite

Andrzej Banachowicz, Adam Wolski (2017). A Comparison of the Least Squares with Kalman Filter Methods Used in Algorithms of Fusion with Dead Reckoning Navigation Data. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 11(4), 691-695. https://europub.co.uk/articles/-A-246973