A Novel Speed Compensation Method for ISAR Imaging with Low SNR

Area of Science:

• Radar Systems Engineering
• Signal Processing
• Image Reconstruction

Background:

• Inverse Synthetic Aperture Radar (ISAR) imaging is crucial for target identification.
• Low signal-to-noise ratio (SNR) conditions significantly degrade ISAR image quality.
• Accurate target speed estimation is essential for effective ISAR image compensation.

Purpose of the Study:

• To propose novel speed compensation algorithms for ISAR imaging under low SNR.
• To enable direct estimation of target speed from wideband radar echoes.
• To enhance the robustness and efficiency of ISAR speed compensation techniques.

Main Methods:

• Development of two algorithms: Cubic Phase Function (CPF) and Integrated Cubic Phase Function (ICPF).
• Direct speed estimation from wideband radar echo data.
• Utilization of non-coherent accumulation for noise robustness in the ICPF algorithm.
• Implementation of a fast searching strategy (coarse and precise search) to reduce computational load.

Main Results:

• The proposed CPF and ICPF algorithms effectively compensate for target speed in ISAR imaging.
• The ICPF-based algorithm demonstrates significant robustness against noise in low SNR environments.
• The fast searching strategy successfully reduces the computational burden of the speed compensation algorithms.
• Experimental validation confirms the effectiveness of both proposed algorithms.

Conclusions:

• The novel CPF and ICPF algorithms provide effective solutions for ISAR speed compensation, particularly under low SNR conditions.
• The ICPF algorithm's noise resilience makes it suitable for challenging radar environments.
• The optimized implementation strategy enhances the practical applicability of these advanced ISAR imaging techniques.