Spoofing events are increasingly affecting the performance of devices and operations relying on Global Navigation Satellite Systems (GNSSs). Developing powerful and robust GNSS spoofing detection and mitigation algorithms is an important endeavor in the GNSS community nowadays; some of the challenges in this field are limited access to spoofing measurement data, as spoofing over wireless channels is not legally allowed and in-lab spoofing emulators are not necessarily able to precisely capture the effects of radio channels, and the fact that classical Receiver Autonomous Integrity Monitoring approaches are typically quite complex, especially when dealing with complex or targeted spoofers. Our paper addresses these two challenges, first, by proposing a targeted spoofing model with a variable number of spoofed satellites, starting from Android raw pseudorange measurements, and second, by introducing a consistency-check-based iterative approach for spoofing detection and mitigation. We test our solution in various dynamic scenarios (bus, walk, ferry, car, flight, and bike), and we show that the positioning error correction rates depend on the number of spoofing pseudorandom (PRN) codes, as well as on the spoofing error introduced by our model. We also show that a large part of the spoofing errors can be mitigated with the proposed algorithms if the number of spoofed satellites (or pseudoranges) is sufficiently low with respect to the total number of visible satellites.