CLEAN technique in strip-map SAR for high-quality imaging

Abstract

Abstract-The maximum obtainable resolution of a stripmap synthetic aperture radar (SAR) system can be retained by simply avoiding weighting, or tapering, data samples in the along-track compression process. However, this will lead to hazardous artifacts caused by strong sidelobes of the corresponding adjacent scatterers whose interference might severely weaken the desired targets or even introduce false targets. On the other hand, some residual artifacts, even after tapering process, may still deteriorate the quality (contrast) of the SAR image. These issues can be remedied by applying the so-called CLEAN technique, which can mitigate these ill-effects in strip-map SAR imagery while maintaining the maximum resolution. This, indeed, is carried out as a post processing step, i.e., after the azimuth compression is accomplished, in the SAR system. The objective of this paper is to extend the CLEAN technique to strip-map SAR system to produce high-quality images with a very good along-track resolution. The algorithm is then applied to data from a ground-based circular SAR (CSAR) system to verify its implementation as well as this new application of the CLEAN technique.

Analysis of Low-Oversampled Staggered SAR Data

“…Although the proposed approach relies on the use of BLU and MIAA as the interpolators in the raw-data domain and rangecompressed domain, those can be replaced by other interpolators according to availability. For example, the use of SEs, which consider a certain spectral extent [45] or newly developed SEs for mixed spectra [46] could be evaluated as an alternative to MIAA, at the possible expense of computational complexity.…”

New imaging algorithm for range resolution improvement in passive Global Navigation Satellite System‐based synthetic aperture radar

“…At the meantime, the works [14, 17, 18] and [1] improved resolutions through SAR image processing and range signal processing, respectively. Specifically in [14, 17, 18], multi‐static image processing method [19, 20] is applied by fusion of the GNSS‐SAR images, which are acquired from different azimuth directions, where the spatial resolution is increased, compared to single bi‐static SAR. The work [1] proposed to use reflected GNSS intermediate frequency signal for imaging to reduce ambiguity level of the mainlobe of range compressed pulses.…”

A Novel Range Compression Algorithm for Resolution Enhancement in GNSS-SARs

“…Meanwhile, besides the aforementioned works, spatial resolution enhancement of the GNSS-SAR was studied in [ 3 , 4 , 5 ]. Typically, in works [ 4 , 5 ], the spatial resolution improvements were carried out based on multi-static image processing method with clean techniques [ 19 , 20 ] for extracting a scene-scattering center, in which both range and azimuth resolutions were improved. Based on GLONASS encrypted precision code (P code) signal and Beidou signal as source of opportunity as examples, spatial resolutions in [ 4 , 5 ] were improved to a level of 6–7 m.…”