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Aliasing01:18

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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
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Robust SAR Waveform Design for Extended Target in Spectrally Dense Environments.

Rui Zhang1, Fuwei Wu1, Bing Gao1

  • 1Nanjing Research Institute of Electronics Technology, Nanjing 210039, China.

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|June 27, 2025
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Summary
This summary is machine-generated.

This study introduces a robust waveform design for Synthetic Aperture Radar (SAR) to improve extended target signatures in cluttered environments. The method optimizes signal-to-clutter ratio (SCR) under uncertainty, enhancing SAR imaging performance.

Keywords:
SARSCRextended targetsrobust waveformspectral constraint

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Remote Sensing

Background:

  • Synthetic Aperture Radar (SAR) imaging requires robust methods for detecting extended targets, especially in spectrally dense environments.
  • Existing waveform design techniques may not adequately address uncertainties in target and background scattering characteristics.

Purpose of the Study:

  • To develop a robust waveform design method for enhancing extended target signatures in SAR images.
  • To maximize the worst-case signal-to-clutter ratio (SCR) under statistical uncertainties.

Main Methods:

  • Formulated the problem as maximizing worst-case SCR over uncertainty sets for target and background statistics.
  • Derived closed-form solutions for uncertain statistics.
  • Transformed the problem into a nonconvex fractional quadratically constrained quadratic problem (QCQP).
  • Utilized Dinkelbach's algorithm and Lagrange duality to solve the QCQP via semidefinite programming.

Main Results:

  • Developed a robust waveform design scheme for SAR imaging.
  • Demonstrated the ability to handle uncertainties in scattering characteristics.
  • Achieved a sufficient condition for global convergence of the proposed algorithm.

Conclusions:

  • The proposed robust waveform design method effectively enhances extended target signatures in SAR images.
  • The method provides a significant improvement in signal-to-clutter ratio (SCR) under uncertain conditions.
  • The approach is validated through numerical examples, showing its practical applicability.