Application of the Kalman filter to spherical discrete track smoothing and prediction
Demetry, James S.
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This paper investigates the effectiveness of a method for circumventing the problem of nonlinear observation of a linear system's state variables in the Kalman filter discrete estimation scheme. The method employs a linearization of the nonlinear coordinate transformation, in this case cartesian to spherical. The performance of a filter designed by this method is observed as a function of measurement error, accuracy of filter initialization, and the relevance of the estimated initial error covariance, P subscript 2| subscript 1. The investigation reveals that the most critical factor in filter performance and stability is filter state initialization.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
NPS Report NumberTechnical Report/ Reserach Paper No. 70
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