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NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...

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Related Experiment Video

Updated: Jun 20, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

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Published on: February 12, 2014

Speckle processing method for synthetic-aperture-radar phase correction.

P H Eichel, D C Ghiglia, C V Jakowatz

    Optics Letters
    |September 15, 2009
    PubMed
    Summary
    This summary is machine-generated.

    A new iterative algorithm effectively corrects arbitrary phase errors in synthetic-aperture-radar data, significantly improving image quality in various conditions without user intervention.

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    Area of Science:

    • Remote Sensing
    • Image Processing
    • Signal Processing

    Background:

    • Uncompensated phase errors in synthetic-aperture-radar (SAR) data severely degrade reconstructed image quality.
    • Accurate phase error correction is crucial for reliable SAR image analysis.

    Purpose of the Study:

    • To introduce a novel iterative algorithm for robust estimation and correction of arbitrary phase errors in SAR data.
    • To demonstrate the algorithm's effectiveness across diverse phase error types and sources.

    Main Methods:

    • Development of a new iterative algorithm inspired by speckle processing techniques in optical astronomy.
    • Application of the algorithm to SAR datasets with varying phase error characteristics.

    Main Results:

    • The algorithm successfully focuses SAR scenes corrupted by significant phase errors.
    • Effective performance is demonstrated in both high and low signal-to-clutter conditions.
    • The method operates autonomously without requiring human intervention.

    Conclusions:

    • The presented iterative algorithm offers a robust solution for correcting phase errors in SAR imagery.
    • This technique has broad applicability for enhancing SAR image quality regardless of error source or scene conditions.