Detection and Speed Estimation of Moving Target Based on Phase Compensation and Coherent Accumulation Using...

Area of Science:

• Radar systems engineering
• Signal processing
• Aerospace engineering

Background:

• Increasing use of unmanned aerial vehicles (UAVs) and small, low-flying aircraft necessitates advanced detection methods.
• Challenges in radar detection include weak echoes, low Doppler frequencies, and ground clutter interference.
• Existing radar detection methods struggle with the specific characteristics of small, slow-moving aerial targets.

Purpose of the Study:

• To propose a novel algorithm for the detection and speed estimation of small, low-flying aircraft using radar.
• To address the limitations of current methods in detecting targets with weak echoes and significant ground clutter.
• To enhance the signal-to-interference-plus-noise ratio (SINR) for improved target identification.

Main Methods:

• Development of a phase compensation and coherent accumulation algorithm based on the fractional Fourier transform (FRFT).
• Utilizing FRFT to converge target echo energy and analyze phase between echo peaks.
• Applying phase compensation and coherent accumulation in the fractional domain to mitigate ground clutter and improve SINR.
• Employing constant false alarm rate (CFAR) detection for target identification and radial speed estimation.

Main Results:

• The proposed FRFT-based algorithm effectively converges target echo energy.
• Phase compensation and coherent accumulation significantly reduce ground clutter interference.
• The algorithm demonstrates a marked improvement in signal-to-interference-plus-noise ratio (SINR).
• Successful validation through both data simulation and real-world data application.

Conclusions:

• The developed phase compensation and coherent accumulation algorithm based on FRFT is effective for detecting small, low-flying aircraft.
• The algorithm successfully overcomes challenges posed by weak echoes and ground clutter, enhancing radar detection performance.
• Radial speed estimation is accurately achieved directly from peak coordinates within the fractional domain.