SAR Image Processing Device Sidelobe Suppression
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Solution Overview
Problem
Current radar image processing techniques face challenges in effectively suppressing both sidelobes and speckle noise in SAR images, as serial processing of these noise factors often degrades the performance of either sidelobe or speckle suppression, leading to image blur or reduced peak detection accuracy.
Innovation Solution
A radar image processing device and method that estimates pixel types as main lobe, sidelobe, or other pixels, performs pixel value interpolation to correct images, applies speckle suppression, and generates an output image with suppressed sidelobes and speckle, using a combination of pixel type estimation, replacement, and speckle suppression techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a window function is applied upon pulse compression to suppress sidelobes, then sidelobe suppression is improved, but the width of the main lobe is widened causing image resolution to be reduced
Solution Approach 1:
The patent segments the image processing into distinct stages: first performing pulse compression to generate the SAR image, then classifying pixels into main lobe and sidelobe regions, and finally applying speckle suppression only to sidelobe regions. This segmentation allows selective processing that suppresses sidelobes while preserving main lobe resolution.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image. Main lobe pixels receive minimal processing to preserve resolution, while sidelobe pixels undergo speckle suppression. This local differentiation resolves the contradiction by applying suppression only where needed without affecting main lobe sharpness.
2Object-affected harmful factors
If serial processing is performed for both sidelobe suppression and speckle suppression, then both noise factors can be addressed, but the performance of either sidelobe or speckle suppression is degraded leading to image blur or reduced peak detection accuracy
Solution Approach 1:
The patent performs preliminary classification of pixels into main lobe and sidelobe regions before applying speckle suppression. This preliminary action allows the system to protect main lobe pixels from suppression operations that would otherwise blur peaks and reduce detection accuracy.
Solution Approach 2:
The patent introduces pixel classification as an intermediary step between pulse compression and speckle suppression. This intermediary mechanism identifies which pixels should be suppressed and which should be preserved, enabling simultaneous handling of both sidelobe and speckle noise without degrading peak detection accuracy.
3Object-affected harmful factors
If pixel values are replaced through interpolation to correct sidelobes, then sidelobe suppression is improved, but image processing complexity increases
Solution Approach 1:
The patent extracts the problematic sidelobe pixels from the overall image processing flow by classifying them separately from main lobe pixels. This extraction allows targeted replacement of only sidelobe pixel values through interpolation, achieving suppression without unnecessarily complicating the processing of the entire image.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively suppresses sidelobes and speckle noise in SAR images, maintaining image resolution and accuracy by integrating pixel type estimation and interpolation with speckle suppression processing.
Implementation Method 1
based on the correlation between pixel values of a target pixel and each of pixels therearound in SLC data, it is determined whether the target pixel is a pixel caused by the main lobe, a pixel due to the sidelobe, or any other pixel
Implementation Method 2
pixel value replacement means for replacing a pixel value of the pixel caused by the main lobe and a pixel value of the pixel due to the sidelobe with pixel values generated in pixel value interpolation processing
Implementation Method 3
speckle suppression means for applying speckle suppression processing to the first corrected image to generate a second corrected image
Data Source
AI summary
A radar image processing device includes: an estimation unit 1 for setting, as a target pixel, each pixel of a two-dimensional map image, and estimating to which type each target pixel belongs among a pixel caused by the main lobe, a pixel due to the sidelobe, and any other pixel; a pixel value replacement unit 2 for replacing the pixel value of the pixel caused by the main lobe and the pixel value of the pixel due to the sidelobe with pixel values generated in pixel value interpolation processing based on the type of each pixel estimated by the estimation unit 1 to generate a first corrected image; a speckle noise suppression unit 3 for applying speckle noise suppression processing to the first corrected image to generate a second corrected image; and an output image generation unit 4 for generating an output image, in which speckle noise and sidelobes are suppressed, by using the two-dimensional map image, the second corrected image, and the type of each pixel.