Quadratic Frequency Modulation Signals Parameter Estimation Based on Two-Dimensional Product Modified Parameterized...

Area of Science:

• Signal Processing
• Radar Systems Engineering
• Computational Electromagnetics

Background:

• Inverse Synthetic Aperture Radar (ISAR) imaging systems often encounter complex target motion, necessitating accurate modeling of azimuth echo signals as multicomponent quadratic frequency modulation (QFM) signals.
• Effective estimation of chirp rate (CR) and quadratic chirp rate (QCR) is crucial for mitigating ISAR image defocusing issues, particularly for multicomponent QFM (multi-QFM) signals.
• Conventional CR and QCR estimation algorithms struggle with cross-term interference and limited anti-noise capabilities when applied to multi-QFM signals.

Purpose of the Study:

• To propose a novel estimation algorithm, the two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD), for accurate QFM signal parameter estimation.
• To enhance the performance of ISAR imaging by addressing the limitations of existing methods in handling multi-QFM signals.
• To achieve superior cross-term suppression and anti-noise performance compared to existing techniques.

Main Methods:

• The proposed 2D-PMPCRD algorithm utilizes a multi-scale parametric symmetric self-correlation function.
• It employs modified nonuniform fast Fourier transform-Fast Fourier transform (NUFFT-FFT) to map signals into the chirp rate-quadratic chirp rate (CR-QCR) domains.
• Signal processing involves multiplying different CR-QCR domains with varying scale factors to suppress cross-terms and enhance auto-terms.

Main Results:

• Simulation results demonstrate that the 2D-PMPCRD effectively suppresses cross-terms inherent in multi-QFM signals.
• The algorithm exhibits significantly improved anti-noise performance compared to conventional methods.
• The 2D-PMPCRD achieves better performance than the high order ambiguity function-integrated cubic phase function (HOAF-ICPF) and modified Lv's distribution.

Conclusions:

• The 2D-PMPCRD algorithm offers a robust solution for parameter estimation of QFM signals in ISAR imaging.
• It provides superior performance in terms of cross-term suppression and anti-noise capability for multi-QFM signals.
• The proposed method presents a viable and computationally efficient approach for enhancing ISAR imaging quality under complex target motion scenarios.