Moreno Monge, BeatrizRodríguez Caderot, GraciaLacy de, M.C.2023-06-192023-06-192014-071080-537010.1007/s10291-013-0335-7https://hdl.handle.net/20.500.14352/33641We present the new MAP3 algorithms to perform static precise point positioning (PPP) from multifrequency and multisystem GNSS observations. MAP3 represents a two-step strategy in which the least squares theory is applied twice to estimate smoothed pseudo-distances, initial phase ambiguities, and slant ionospheric delay first, and the absolute receiver position and its clock offset in a second adjustment. Unlike the classic PPP technique, in our new approach, the ionospheric-free linear combination is not used. The combination of signals from different satellite systems is accomplished by taking into account the receiver inter-system bias. MAP3 has been implemented in MATLAB and integrated within a complete PPP software developed on site and named PCube. We test the MAP3 performance numerically and contrast it with other external PPP programs. In general, MAP3 positioning accuracy with low-noise GPS dual-frequency observations is about 2.5 cm in 2-h observation periods, 1 cm in 10 h, and 7 mm after 1 day. This means an improvement in the accuracy in short observation periods of at least 7 mm with respect to the other PPP programs. The MAP3 convergence time is also analyzed and some results obtained from real triple-frequency GPS and GIOVE observations are presented.engjournal articlehttp://link.springer.com/article/10.1007/s10291-013-0335-7http://www.springer.com/restricted access52Precise point positioningGNSSMultifrequency algorithmsComplete covariance matrixLeast squaresGeodesia2504 Geodesia