<p>A reliable navigation solution is increasingly critical as Global Navigation Satellite System (GNSS) technology underpins applications such as transportation. However, spoofing attacks remain a significant threat by injecting misleading position, velocity, and time (PVT) estimates into GNSS receivers. Although various detection techniques have been proposed, many rely on hardware modifications, additional sensors, or computationally intensive algorithms, which may limit their practicality for low-cost devices. This gap highlights the need for lightweight, receiver-based detection methods that exploit existing measurements without requiring additional resources. This paper proposes a spoofing detection approach that operates solely on standard receiver outputs, specifically Doppler frequency, and monitors the Doppler rate feature under attacks. The core principle is to compare the measured Doppler frequency shift rate from receiver tracking outputs with the predicted Doppler frequency shift rate derived from receiver navigation results, where a statistically significant inconsistency indicates a potential spoofing attack. We analyze detection performance under various user dynamics and spoofer antenna configurations, covering 16 representative attack scenarios, and demonstrate effectiveness in 11 out of them. To distinguish spoofing from noise and unintentional interference, we design an adaptive threshold and adopt the Neyman-Pearson decision rule to maximise the probability of detection for a prescribed false-alarm rate. The method is validated in simulation and on public spoofing-attack datasets. In the TEXBAT validation, the proposed method achieves a detection delay of less than 5 s while maintaining a false alarm rate of approximately 2%, demonstrating its reliability under representative spoofing attacks.</p>