2016
DOI: 10.1515/arsa-2016-0011
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Optimal Estimation of a Subset of Integers with Application to GNSS

Abstract: ABSTRACT. The problem of integer or mixed integer/real valued parameter estimation in linear models is considered. It is a well-known result that for zero-mean additive Gaussian measurement noise the integer least-squares estimator is optimal in the sense of maximizing the probability of correctly estimating the full vector of integer parameters. In applications such as global navigation satellite system ambiguity resolution, it can be beneficial to resolve only a subset of all integer parameters. We derive th… Show more

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Cited by 8 publications
(6 citation statements)
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“…Alternatively, the framework of Generalized Integer Aperture (GIA) estimation, introduced by Brack in his series of works [15][16][17]40], extends the concepts on IAR and PAR to describe selective pull-in regions and their aperture. Thus, GIA estimators procure a joint subset selection, integer estimation, and test validation upon the aperture of the decision regions.…”
Section: Partial Ambiguity Resolution Strategiesmentioning
confidence: 99%
“…Alternatively, the framework of Generalized Integer Aperture (GIA) estimation, introduced by Brack in his series of works [15][16][17]40], extends the concepts on IAR and PAR to describe selective pull-in regions and their aperture. Thus, GIA estimators procure a joint subset selection, integer estimation, and test validation upon the aperture of the decision regions.…”
Section: Partial Ambiguity Resolution Strategiesmentioning
confidence: 99%
“…Depending on the index set I and the covariance matrix Qâ either of the two above introduced integer least-squares based estimators may be the better choice in terms of the probability of correct integer estimates. It is, however, possible to formulate the optimal estimator, which resolves a given subset I of the integer parameters a with the highest possible probability of correct integer estimates P (ǎ = a I ) within the class of partial integer estimators as defined in (4.2), see Brack (2016a). Let the integer estimatesǎ opt of a I be given by…”
Section: Optimal Partial Integer Estimationmentioning
confidence: 99%
“…For PAR, the index set I can assume any of the 2 n possibilities that result from either including each of the n ambiguities in I or not. The optimal estimator for a given subset I leading to the highest possible probability of correct estimates is discussed in [20] and given byž = argmax…”
Section: Reliable Model-driven Ambiguity Resolutionmentioning
confidence: 99%