Mixed Integer-Real Valued Adjustment (IRA) Problems: GPS Initial Cycle Ambiguity Resolution by Means of the LLL Algorithm

Abstract In order to achieve to GPS solutions of first-order accuracy and integrity, carrier phase observations as well as pseudorange observations have to be adjusted with respect to a linear/linearized model. Here the problem of mixed integer-real valued parameter adjustment (IRA) is met. Indeed,...
Ausführliche Beschreibung

Abstract In order to achieve to GPS solutions of first-order accuracy and integrity, carrier phase observations as well as pseudorange observations have to be adjusted with respect to a linear/linearized model. Here the problem of mixed integer-real valued parameter adjustment (IRA) is met. Indeed, integer cycle ambiguity unknowns have to be estimated and tested. At first we review the three concepts to deal with IRA: (i) DDD or triple difference observations are produced by a properly chosen difference operator and choice of basis, namely being free of integer-valued unknowns (ii) The real-valued unknown parameters are eliminated by a Gauss elimination step while the remaining integer-valued unknown parameters (initial cycle ambiguities) are determined by Quadratic Programming and (iii) a RA substitute model is firstly implemented (real-valued estimates of initial cycle ambiguities) and secondly a minimum distance map is designed which operates on the real-valued approximation of integers with respect to the integer data in a lattice. This is the place where the integer Gram-Schmidt orthogonalization by means of the LLL algorithm (modified LLL algorithm) is applied being illustrated by four examples. In particular, we prove that in general it is impossible to transform an oblique base of a lattice to an orthogonal base by Gram-Schmidt orthogonalization where its matrix enties are integer. The volume preserving Gram-Schmidt orthogonalization operator constraint to integer entries produces “almost orthogonal” bases which, in turn, can be used to produce the integer-valued unknown parameters (initial cycle ambiguities) from the LLL algorithm (modified LLL algorithm). Systematic errors generated by “almost orthogonal” lattice bases are quantified by A. K. Lenstra et al. (1982) as well as M. Pohst (1987). The solution point %$\bf{\hat z}%$ of Integer Least Squares generated by the LLL algorithm is %$\bf{\hat z}=(L')^{-1}[L'{\hat x}]%$ ∈ $ ℤ^{m} $ where L is the lower triangular Gram-Schmidt matrix rounded to nearest integers, [L], and %$\bf{\hat z}=[L'{\hat x}]%$ are the nearest integers of L'◯, ◯ being the real valued approximation of z ∈ $ ℤ^{m} $, the m-dimensional lattice space Λ. Indeed due to “almost orthogonality” of the integer Gram-Schmidt procedure, the solution point %$\bf{\hat z}%$ is only suboptimal, only close to “least squares.” © 2000 John Wiley & Sons, Inc. Ausführliche Beschreibung

Autor*in:	Grafarend, Erik W. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2000

Schlagwörter:	Carrier Phase Ambiguity Resolution Solution Point Carrier Phase Observation Triple Difference

Übergeordnetes Werk:	Enthalten in: GPS solutions - Berlin : Springer, 1995, 4(2000), 2 vom: Okt., Seite 31-44
Übergeordnetes Werk:	volume:4 ; year:2000 ; number:2 ; month:10 ; pages:31-44

Links:	Volltext

DOI / URN:	10.1007/PL00012840

Katalog-ID:	SPR009761675