1. An adaptive method for estimating the electron content of the ionosphere, comprising the following steps performed in succession: a collection of a set of measurements carried out by a plurality of fixed receiving beacons on the ground receiving radio frequency signals transmitted by a plurality of transmitting navigation satellites situated in orbit, a computation, for each of the signals of the set of measurements (MSS), of the spatial coordinates of the point of intersection (IPP) between a transmission axis of the signal and a surface (ITL) surrounding the Earth, and a vertical total electron content (VTEC) determined at this point of intersection (IPP); a cloud of points, made up of the spatial coordinates of the point of intersection (IPP) and of a vertical total electron content (VTEC) being thus defined, a computation, by means of a statistical estimator (ESC), of a vertical total electron content (VTEC i ), for each of the nodes (N i ) of an initial mesh (IPM) of the surface (ITL), a statistical dispersion analysis (ASD) of the vertical total electron content (VTEC i ) at each of the nodes (N i ) of the initial mesh (IPM), making it possible to select between two predetermined disturbance levels, a weak disturbance (P 1 ) or a strong disturbance (P 2 ), of the ionosphere, a step comprising: in the case of a weak disturbance (P 1 ), a computation making it possible to define a suitable statistical estimator (ESCA), from the initial statistical estimator (ESC), in the case of a strong disturbance (P 2 ), a computation making it possible to generate a new suitable mesh (IPMA) of the surface (ITL), from the initial mesh (IPM), a statistical error analysis (ASE) of the vertical total electron content (VTEC i ) determined, by means of the suitable statistical estimator (ESCA) and of the initial mesh (IPM) in the case of a weak disturbance (P 1 ), or by means of the initial statistical estimator (ESC) and the suitable mesh (IPMA) in the case of a strong disturbance (P 2 ); the statistical error analysis (ASE) making it possible to select between two predetermined error levels, a weak error (E 1 ) which implies a validation of the adaptation of the method, or a strong error (E 2 ) which implies the stopping of the method.