As rail transport moves toward higher degrees of automation under initiatives like the R2DATO project [1], accurate and reliable train localization has become essential. Global Satellite Navigation System (GNSS) is considered as a main technology in enabling operational advancements including Automatic Train Operation (ATO), moving block signaling, and virtual coupling, which are the core components of the Horizon Europe 2024 rail digitalization agenda. However, GNSS signal integrity is increasingly threatened by intentional and unintentional radio frequency interference (RFI). This include jamming and spoofing, which are particularly concerning as the broadcasted signal can deliberately disrupt or manipulate the GNSS signal. - Jamming refers to an intentional form of interference that induces disturbances in the GNSS band, causing performance degradation or can even entirely block the receiver from acquiring the satellite signals. - Spoofing involves broadcasting counterfeit satellite signals to deceive the GNSS receiver, leading to inaccurate estimation of position, navigation and timing information. This concern about interference is not unique to rail applications. The aeronautical sector has long recognized the risks posed by GNSS interference, with extensive documentation on its impact on navigation, landing procedures, and surveillance systems. In recent years, awareness of these risks has expanded to other transport sectors. Within the automotive industry, particularly in Intelligent Transport Systems (ITS), several studies [2][3][4] have addressed the vulnerability of GNSS against interference. Similar concerns are now emerging in the rail domain [5][6][7], especially as GNSS is increasingly adopted in safety-critical applications. In literature, several levels of actions have been explored, ranging from merely the detection of a malicious signal at the initial phase to the application of advanced signal processing methods aimed at suppressing the effects of interference [8]. In alignment with the goal of the R2DATO project, we evaluated the impact of various classes of interference signals such as amplitude modulation (AM), frequency modulation (FM), pulsed, frequency hopping and chirp signals on the GNSS observables including Automatic Gain Control (AGC) and Carrier to Noise Ratio (CNO) as measured by a Commercial Off-The-Shelf (COTS). However, in this work, the analysis is only limited to impact of chirp interference on GPS L1 receiver observables and detection performance.