LAMBDA 4.0: an advanced tool for integer estimation, validation and success rate simulation

Autor: Massarweh, L., Verhagen, S., Teunissen, P.
Jazyk: angličtina
Rok vydání: 2023
Zdroj: XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
DOI: 10.57757/iugg23-3087
Popis: The correct resolution of the carrier-phase integer ambiguity is a key aspect for centimetre-level precise positioning with Global Navigation Satellite Systems (GNSS). This integer ambiguity resolution (IAR) process enables the adoption of phase observations as ultra-precise pseudo-range measurements, thus leveraging their millimetre-level precision. An effective and rigorous approach to IAR problems has been given by the Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) method, described in Teunissen (1995). In addition to integer estimation and validation, implemented in the open source LAMBDA software, an evaluation of IAR success rate for different estimators has been made possible by the release of a Ps-LAMBDA toolbox.In this work, we describe the LAMBDA 4.0 toolbox, which has recently been developed by the GNSS research group at TU Delft. This toolbox merges the LAMBDA 3.0 (2012) and Ps-LAMBDA 1.0 (2013) functionalities into a single framework, where new different estimators are implemented, e.g. Vectorial Integer Bootstrapping (VIB), Integer Aperture Bootstrapping (IAB) and Best Integer Equivariant (BIE) solutions. Moreover, different algorithm modifications are introduced for enhanced performances, e.g. in the integer search process, so targeting high dimensional ambiguity resolution (HDAR) problems, which are foreseen to become more and more important in the future years. This high dimensionality challenge is expected in view of the possible deployment of new satellite mega-constellations in Low Earth Orbit (LEO), with hundreds of satellites being tracked by user receivers. This new LAMBDA 4.0 toolbox will officially be released to the public later this year.
The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)
Databáze: OpenAIRE