A general theoretical approach to finding a minimum-mean-squared-error solution to a set of [ ] linear measurement equations involving unknown continuous and integer states was published in 1993 1 . This[ ] ( development was followed by the publication 2᎐4 of a practical method, known as the LAMBDA least-squares ) ambiguity decorrelation adjustment method, for efficiently implementing part of this approach, namely, the resolution of the integer states. This paper provides a method of implementing the general approach using a Kalman filter and some augmenting calculations. The result is an optimum filter in a recursive form. When the LAMBDA method is used to facilitate the integer-resolution calculations, the entire filter is computationally efficient, and has the potential for wide application. Extensions to prediction and smoothing are straightforward. An example of the application of this filter for relative navigation of space vehicles on the basis of GPS carrier and code measurements is described, and computer simulation results are provided.
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