Method for road vehicle localization based on magnetic landmarks, comprising: - an offline phase (1.0) configured to collect and store magnetic landmarks, each magnetic landmark comprising a magnetic anomaly; and - an online phase (2.0) adapted to match a current anomaly with a reference anomaly; wherein the offline phase (1.0) comprises an anomaly mapping stage (1.3) configured to associate to the magnetic anomaly of each magnetic landmark path location data, comprising at least two location data, creating a unique reference landmark to be stored in a reference landmark database; wherein the magnetic anomaly of each reference landmark is associated to a reference anomaly; and wherein the online phase (2.0) comprises an anomaly matching stage (2.3) followed by a localisation stage (2.4), wherein: - the anomaly matching stage (2.3) is configured to determine anomaly matching between a current anomaly and reference anomalies of the reference landmarks stored in the reference landmark database; and - the localisation stage (2.4) is configured to estimate the location of a vehicle, based on the path location data of the reference landmark resulting from the anomaly matching stage (2.3); the method being characterized by the offline phase (1.0) and the online phase (2.0) further comprising stages of pre-processing (1.1, 2.1) and anomaly detection (1.2, 2.2), wherein: - the pre-processing stage (1.1, 2.1) is configured to estimate the speed of the vehicle and to generate processed data streams (b), including a plurality of data parameters, from a received stream of raw inertial data (a); the processed data streams (b) being an input of: - the anomaly mapping stage (1.3) of the offline phase (1.0); and - the anomaly matching stage (2.3) of the online phase (2.0); and wherein - the anomaly detection stage (1.2, 2.2) is configured to define an interval of anomaly (d) from a processed data stream (b) generated by the pre-processing stage; the output of the anomaly detection stage (1.2, 2.2) being the input - the anomaly mapping stage (1.3) of the offline phase (1.0); and - the anomaly matching stage (2.3) of the online phase (2.0). - an offline phase (1.0) configured to collect and store magnetic landmarks, each magnetic landmark comprising a magnetic anomaly; and - an online phase (2.0) adapted to match a current anomaly with a reference anomaly; wherein the offline phase (1.0) comprises an anomaly mapping stage (1.3) configured to associate to the magnetic anomaly of each magnetic landmark path location data, comprising at least two location data, creating a unique reference landmark to be stored in a reference landmark database; wherein the magnetic anomaly of each reference landmark is associated to a reference anomaly; and wherein the online phase (2.0) comprises an anomaly matching stage (2.3) followed by a localisation stage (2.4), wherein: - the anomaly matching stage (2.3) is configured to determine anomaly matching between a current anomaly and reference anomalies of the reference landmarks stored in the reference landmark database; and - the localisation stage (2.4) is configured to estimate the location of a vehicle, based on the path location data of the reference landmark resulting from the anomaly matching stage (2.3); - the anomaly matching stage (2.3) is configured to determine anomaly matching between a current anomaly and reference anomalies of the reference landmarks stored in the reference landmark database; and - the localisation stage (2.4) is configured to estimate the location of a vehicle, based on the path location data of the reference landmark resulting from the anomaly matching stage (2.3); the method being characterized by the offline phase (1.0) and the online phase (2.0) further comprising stages of pre-processing (1.1, 2.1) and anomaly detection (1.2, 2.2), wherein: - the pre-processing stage (1.1, 2.1) is configured to estimate the speed of the vehicle and to generate processed data streams (b), including a plurality of data parameters, from a received stream of raw inertial data (a); - the pre-processing stage (1.1, 2.1) is configured to estimate the speed of the vehicle and to generate processed data streams (b), including a plurality of data parameters, from a received stream of raw inertial data (a); the processed data streams (b) being an input of: - the anomaly mapping stage (1.3) of the offline phase (1.0); and - the anomaly matching stage (2.3) of the online phase (2.0); - the anomaly mapping stage (1.3) of the offline phase (1.0); and - the anomaly matching stage (2.3) of the online phase (2.0); and wherein - the anomaly detection stage (1.2, 2.2) is configured to define an interval of anomaly (d) from a processed data stream (b) generated by the pre-processing stage; - the anomaly detection stage (1.2, 2.2) is configured to define an interval of anomaly (d) from a processed data stream (b) generated by the pre-processing stage; the output of the anomaly detection stage (1.2, 2.2) being the input - the anomaly mapping stage (1.3) of the offline phase (1.0); and - the anomaly matching stage (2.3) of the online phase (2.0). - the anomaly mapping stage (1.3) of the offline phase (1.0); and - the anomaly matching stage (2.3) of the online phase (2.0).