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

Zhiyu Qu1, Fuxin Qu2, Changbo Hou3

  • 1College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China. quzhiyu@hrbeu.edu.cn.

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|May 23, 2018
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Summary
This summary is machine-generated.

This study introduces a new method, the 2D-PMPCRD, to accurately estimate parameters for complex radar signals. This technique improves inverse synthetic aperture radar (ISAR) imaging by reducing noise and signal interference.

Keywords:
fast-Fourier transform (FFT)nonuniform fast-Fourier transform (NUFFT)parametric symmetric self-correlation function (PSSAF)quadratic frequency modulation (QFM) signal

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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.