SATURN: A Double-Recursive Deconvolution Algorithm for Suppressing Sidelobe Effects in Non-Nyquist SAR and MIMO Imaging Radars

The angular resolution of an imaging radar system is limited by the aperture size and its associated cost and complexity. Relaxing the \lambda /2 element spacing condition for large arrays introduces sidelobe and grating lobe effects that severely degrade the image quality. In certain imaging appl...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2023, Vol.61, p.1-12
Main Authors: Muppala, Aditya Varma, Sarabandi, Kamal
Format: Article
Language:English
Subjects:
Algorithms
Angular resolution
Antenna arrays
Automotive radar
Automotive radars
CLEAN deconvolution
Complexity
Deconvolution
Image degradation
Image quality
Imaging
Imaging radar
imaging radars
Imaging techniques
Laser radar
MIMO communication
multiple-input multiple-output (MIMO) radars
Patch antennas
Radar
Radar equipment
Radar imaging
SAR (radar)
Segregation
Sidelobe reduction
sidelobe suppression
Sidelobes
sparse arrays
Superhigh frequencies
Synthetic aperture radar
synthetic aperture radars (SARs)
thinned arrays
Transmitters
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Description
Summary:The angular resolution of an imaging radar system is limited by the aperture size and its associated cost and complexity. Relaxing the \lambda /2 element spacing condition for large arrays introduces sidelobe and grating lobe effects that severely degrade the image quality. In certain imaging applications, such as automotive radars, the targets are sparsely located and the imaging domain can be approximated as a collection of point scatterers. In such cases, it is possible to "deconvolve" these sidelobe effects to recover a clean image. In this article, a double-recursive deconvolution algorithm titled Sparse Array Target-Segregation Using Recursive Nulling (SATURN) is proposed. It differs from existing CLEAN deconvolution algorithms in two steps: target response estimation and multiple target decorrelation. The target response is estimated using a Sweep and Extinguish step that removes the reliance on the complex image phase. Correlation between targets is suppressed using a Recursive Nulling step that prevents the breakup of point targets. The algorithm is applied to synthetic aperture radars (SARs) and multiple-input multiple-output (MIMO) radars in sparse 3-D imaging scenarios with canonical targets and real-world targets. Dynamic range improvement of 25 dB and thinning factors of over 200 are experimentally demonstrated using a 31-element circular array of X-band U-slot patch antennas with an array diameter of 30\lambda .
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2023.3328841