A comparison of TCAR, CIR and LAMBDA GNSS ambiguity resolution

Abstract

With the envisioned introduction of three-carrier GNSS's (modernized GPS, Galileo), new methods of ambiguity resolution have been developed. In this contribution we will compare two important candidate methods for triple-frequency ambiguity resolution with the already existing LAMBDA (Least-squares Ambiguity Decorrelation Adjustment) method; the TCAR (Three-Carrier Ambiguity Resolution) method; and the CIR (Cascading Integer Resolution) method. It will be shown that for their estimation principle, both TCAR and CIR rely on integer bootstrapping, whereas LAMBDA is based on integer least-squares, of which optimality has been proven, that is, highest probability of success. In TCAR and CIR pre-defined ambiguity transformation are used, whereas LAMBDA exploits the information content of the full ambiguity variance-covariance matrix, with statistical decorrelation the objective in constructing the ambiguity transformation. For the aspect of resolving the ambiguities, TCAR and CIR are designed for use with the geometry-free model. LAMBDA can intrinsically handle any GNSS model with integer ambiguities and thereby utilize satellite geometry to its benefit in geometry-based models.