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On algorithms for attitude estimation using GPS

Authors: Assaf Nadler; Itzhack Y. Bar-Itzhack; Haim Weiss;

On algorithms for attitude estimation using GPS

Abstract

This paper discusses algorithms for attitude determination using GPS differential phase measurements, assuming that the cycle integer ambiguities are known. The problem of attitude determination is posed as a parameter optimization problem where a new quaternion-based cost function is used. Since the new cost function is not a simple quadratic form and therefore Davenport's q-Method is not applicable in this case. Three algorithms for finding the optimal quaternion are derived, two of which are discrete. The third one is a continuous version of the Newton-Raphson algorithm. This continuous version is new and has a guaranteed exponential convergence to the closest local minimum located on the gradient direction in regions where the associated Hessian matrix is positive definite. The algorithms presented in this paper can handle cases of planar antenna arrays and thus cover a deficiency in earlier algorithms. The efficiency of the new algorithms is demonstrated through numerical examples.

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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!
7
Average
Top 10%
Average
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