Self-adaptive microwave photonics time-frequency signal processing for high-power interference suppression

Area of Science:

• Photonics and Radar Systems
• Signal Processing for Intelligent Transportation Systems

Background:

• Radar is crucial for intelligent transportation systems, but increasing radar complexity and dynamic traffic create operational challenges.
• High-power interference degrades radar performance, necessitating advanced suppression techniques.

Purpose of the Study:

• To propose a novel stimulated Brillouin scattering (SBS) based self-adaptive time-frequency signal processing (TFSP) method.
• To enhance radar operation performance by suppressing high-power interference in dynamic scenarios.

Main Methods:

• Exploiting the time-frequency characteristics of chirped optical signals during SBS for 2D adaptive suppression.
• Developing a wideband radar interference suppression method transparent to interference characteristics.
• Implementing real-time suppression and self-adaptability for various interferences.

Main Results:

• Demonstrated effective suppression of different interference types.
• Achieved significant performance improvement in radar detection, with up to 25.68 dB signal-to-noise enhancement.
• Verified the TFSP's self-adaptability to changing interference in dynamic scenarios.

Conclusions:

• The proposed SBS-based TFSP method effectively suppresses dynamic interference in radar systems.
• This technique enhances radar detection performance and offers real-time, self-adaptive interference management.
• The approach shows promise for improving the reliability of intelligent transportation systems.