Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks

Area of Science:

• Radar Systems Engineering
• Aerospace Navigation
• Geophysics

Background:

• Secondary Surveillance Radar (SSR) systems are crucial for air traffic control.
• Existing methods for estimating SSR systematic errors (biases) often lack comprehensive physical modeling.
• Accurate bias estimation is vital for maintaining safe and efficient airspace operations.

Purpose of the Study:

• To develop a complete and rigorous mathematical model for secondary surveillance radar systematic errors.
• To incorporate physical effects systematically influencing SSR measurement processes into the model.
• To demonstrate improved accuracy in bias estimation using the developed model.

Main Methods:

• Developed a comprehensive mathematical model for SSR systematic errors (biases).
• Modeled azimuth biases based on antenna calibration and angle determination errors.
• Modeled distance bias considering atmospheric refractivity and clock errors.
• Modeled altitude bias incorporating atmospheric pressure and temperature effects.

Main Results:

• The developed model systematically accounts for physical effects impacting SSR measurements.
• Azimuth, distance, and altitude biases are parametrically modeled based on physical error sources.
• Adapting classical bias estimation with the complete model significantly improves accuracy, validated with simulated and real data.

Conclusions:

• The novel mathematical model provides a rigorous framework for understanding SSR biases.
• The model's physical parameterization leads to more accurate bias estimation compared to classical methods.
• This work contributes to enhancing the reliability and precision of secondary surveillance radar systems.