Sub-aperture sidelobe and alias mitigation techniques
View Patent ↗Methods for mitigating sidelobes and aliases, providing levels of suppression in excess of 20 dB. The methods may include 1) a version of the CLEAN algorithm developed in radio astronomy, modified to work on sub-aperture images; 2) weighting functions based on the phase and amplitude statistics of the sub-aperture image pixels to select points in the CLEAN algorithm; and 3) weighting functions based on the phase and amplitude statistics of the sub-aperture image pixels to mitigate sidelobes and aliases, in conjunction with CLEAN or separately. The methods may be used with all synthetic aperture techniques and are not limited to SAR.
1. A method of enhancing a CLEAN algorithm comprising:
breaking an aperture used to create an image into a plurality of sub-apertures,
selecting image pixels for which sidelobes or aliases are to be removed,
storing amplitudes of pixels that have not been worked on before,
modeling and subtracting scaled impulses from the selected pixels in each individual sub-aperture,
repeating the selecting, storing and subtracting steps until a stop condition is met, and
substituting the stored pixel amplitudes into the image.
2. The method of claim 1 comprising selecting points in a CLEAN algorithm.
3. A method of enhancing a CLEAN algorithm comprising:
breaking an aperture used to create an image into a plurality of sub-apertures,
modeling and subtracting impulses for each individual sub-aperture, and
selecting points in a CLEAN algorithm, wherein the method of selecting points in a CLEAN algorithm comprises:
calculating sub-aperture statistics,
generating at least one weighting function based on the calculated sub-aperture statistics, and combining and weighting sub-aperture images using the weighting function.
4. A method of enhancing a CLEAN algorithm comprising:
breaking an aperture used to create an image into a plurality of sub-apertures,
selecting image pixels for which sidelobes or aliases are to be removed,
wherein the step of selecting image pixels comprises:
calculating sub-aperture statistics,
generating at least one weighting function based on the calculated sub aperture statistics, and
combining and weighting sub-aperture images using the weighting function,
storing amplitudes of pixels that have not been worked on before,
modeling and subtracting scaled impulses from the selected pixels in each individual sub-aperture,
repeating the selecting, storing and subtracting steps until a stop condition is met, and
substituting the stored pixel amplitudes into the image.
5. A method of enhancing a CLEAN algorithm comprising:
breaking an aperture used to create an image into a plurality of sub-apertures,
selecting image pixels for which sidelobes or aliases are to be removed,
storing amplitudes of pixels that have not been worked on before,
modeling and subtracting scaled impulses from the selected pixels in each individual sub-aperture,
repeating the selecting, storing and subtracting steps until a stop condition is met,
substituting the stored pixel amplitudes into the image,
calculating sub-aperture statistics,
generating at least one weighting function based on the calculated sub-aperture statistics, and weighting the image with the at least one weighting function.