The main function of GP-Cloud is to detect the anomaly in the GNSS signals and classify them. GP-Cloud supports anomaly/interference/event classification into the following classes:

Spoofing

This alarm is raised when the system detects a signature of false GNSS signals in data coming from GP-Probe TGE2. 

Interference with certain types of modulation and signal structure can cause significant degradation in the positioning/time accuracy of GNSS receivers. Such interference may be classified as spoofing. Our general approach is as follows:

• If the interference reduces the reception quality of GNSS signals, it is jamming. 
• If the interference causes significant errors in pseudorange, Doppler, etc, it can be classified as spoofing. As it may cause a GNSS receiver to output incorrect coordinates and time.

Jamming

Interference causes a decrease in SNR and the number of visible satellites. GNSS receiver either fails to produce a navigation solution at all or produces it with minor errors.

Interference

Interference is detected by analyzing the RF spectrum and power in the GNSS bands. But it does not affect the reception quality of GNSS signals.

Anomaly

The system detects abnormal behavior of GNSS signals that are not typical for a particular data source. Classification of anomalies is not possible due to insufficient data

Low Position Accuracy

This status is displayed when the accuracy of coordinates generated by a receiver surpasses the defined limits. Coordinate accuracy is calculated as the difference between the GNSS receiver coordinates and a reference position set in GP-Cloud.

PPS Offset

Certain modifications of the GP-Probe come with a built-in module for measuring PPS phase errors. By connecting the PPS output of your time server to the PPS input of the GP-Probe, you can continuously monitor the accuracy of your time synchronization system. In GP-Cloud, you can define PPS accuracy limits. If these boundaries are surpassed, a "PPS Offset" event will be detected and you will receive a notification in real-time.

Hardware Error

All GPSPATRON equipment is designed with an automatic hardware error detection system.
If a problem occurs, GP-Cloud displays the "Hardware Error" status with the error code and description of the reason behind the error.

Offline

Event Classification Support by Devices

Detected when the data source is disconnected for more than 10 seconds.

DIN L1 | Post-Analysis for Identifying Spoofing and Jamming Events

While the GP-Probe DIN L1 can detect anomalies and interference, it does not explicitly classify an event as spoofing or jamming in real time. However, by analyzing recorded data, users can differentiate between these types of interference using a systematic approach.

It is important to note that real-world GNSS interference scenarios can be significantly more complex than the examples provided here. The classification methods in this guide are based on common patterns observed during controlled testing. However, in practical applications, multiple overlapping factors—such as environmental conditions, receiver-specific behavior, and multi-source interference—may complicate analysis.

This section provides general guidelines for post-analysis, but it is not an absolute classification method. There may be cases where additional investigation, expert interpretation, or advanced analytics are required to determine the exact cause of interference.

Key Parameters for Classification

The following parameters are crucial for analyzing GNSS anomalies and determining whether they are caused by spoofing or jamming:

• Spectrum Waterfall
• Anomaly Probability
• Peak Power
• Signal-to-Noise Ratio (SNR)
• Number of Tracked Satellites
• Horizontal Position Accuracy
• PPS Phase Offset
• Satellite Bar Chart

Classification Table for Spoofing and Jamming

The table below summarizes how different parameters behave during spoofing and jamming, allowing users to classify the event through post-analysis.

Step-by-Step Post-Analysis Guide

To analyze an event recorded in GP-Cloud or onboard logs from DIN L1, follow these steps:

1. Check the Spectrum Waterfall

• Jamming: A wideband signal (>10 MHz bandwidth) is visible.
• Spoofing:
  • Coherent (low power): No visible spectrum change.
  • Non-coherent (high power): A narrowband signal (~2 MHz bandwidth) is visible.

✅ If a strong wideband signal is observed → Jamming.
✅ If no spectrum anomaly or a 2 MHz peak is detected → Possible Spoofing.

2. Examine Anomaly Probability & SNR Trends

• Jamming:100% anomaly probability combined with a falling SNR.
• Spoofing:100% anomaly probability combined with a rising SNR.

✅ If anomaly probability is high but SNR is dropping → Jamming.
✅ If anomaly probability is high but SNR is rising → Spoofing.

3. Evaluate Peak Power

• Jamming: Peak power is significantly increased (>20 dB above noise).
• Spoofing:
  • Coherent: No change in peak power.
  • Non-coherent: Moderate power increase.

✅ If peak power increases significantly → Jamming.
✅ If peak power remains unchanged or moderately increases → Spoofing.

5. Analyze Signal-to-Noise Ratio (SNR) Behavior

• Jamming: SNR decreases due to excessive noise.
• Spoofing:
  • Coherent: SNR increases (~10–15 dB jump).
  • Non-coherent: SNR decreases initially (blocking real GNSS), then increases.

✅ If SNR drops sharply → Jamming.
✅ If SNR first drops, then rises → Non-coherent Spoofing.
✅ If SNR jumps by 10–15 dB → Coherent Spoofing.

6. Assess the Number of Tracked Satellites

• Jamming: Sudden loss of satellites due to interference.
• Spoofing: Number of satellites remains the same or increases (mix of real and fake).

✅ If satellites disappear abruptly → Jamming.
✅ If satellites remain or increase (fake ones added) → Spoofing.

7. Examine Horizontal Position Accuracy

• Jamming:
  • No position effect OR
  • Minor degradation (~50 m) OR
  • Loss of position solution.
• Spoofing:
  • Coherent:Gradual position shift.
  • Non-coherent:
    • Step 1:Loss of solution (initial interference).
    • Step 2:Sudden position jump (fake coordinates takeover).

✅ If GNSS position is lost suddenly → Jamming or Non-coherent Spoofing Step 1.
✅ If GNSS position shifts gradually → Coherent Spoofing.
✅ If position jumps → Non-coherent Spoofing Step 2.

8. Check PPS Phase Offset (If Available)

• Jamming: No effect unless GNSS reception is lost.
• Spoofing:
  • Coherent: Gradual PPS phase drift.
  • Non-coherent:
    • Step 1:Loss of PPS signal.
    • Step 2:Sudden PPS phase jump.

✅ If PPS signal is lost → Non-coherent Spoofing Step 1.
✅ If PPS phase drifts gradually → Coherent Spoofing.
✅ If PPS phase jumps suddenly → Non-coherent Spoofing Step 2.

9. Inspect the Satellite Bar Chart

• Jamming: Random drop in satellite visibility.
• Spoofing: Mix of real and spoofed satellites.

✅ If satellites disappear randomly → Jamming.
✅ If both real and fake satellites are present → Spoofing.

Examples of Post-Analysis Scenarios

1. Coherent Spoofing (Difficult to Detect)

• No spectrum anomalies.
• SNR increases from 30 dB → 40 dB.
• No satellites lost, but position starts shifting.
• PPS offset gradually increases.

✅ Conclusion: This is a synchronous spoofing attack.

2. Non-Coherent Spoofing

• Fake signals appear in the spectrum.
• Peak power exceeds threshold.
• SNR remains stable initially but increases with power.
• The receiver sees a mix of real and fake satellites.

✅ Conclusion: This is a non-coherent spoofing attack.

3. Jamming

• Strong power peak in the spectrum.
• Anomaly probability reaches 100%.
• SNR drops significantly.
• Satellites disappear from tracking.

✅ Conclusion: This is a jamming attack.