Moving Target High Resolution Imaging of Foliage Penetrate Ultra-Wide Band Synthetic Aperture Radar (FOPEN UWB SAR) is of great significance for battlefield awareness of concealed target. Great range migration and strong clutter make moving target detection and imaging difficult, especially the Signal to Clutter Ration(SCR) some times is so low that the moving targets is invisible in FOPEN UWB SAR imagery. To improve SCR, the clean technique is used in range compressed data domain. The clean technique and data reconstruction help single channel of FOPEN UWB SAR suppress strong tree clutter and stationary target signal from region of interest. A new definition called General Key-Stone Transform is given, which can correct any order of range migration. FOPEN UWB SAR has long integrated time. The plane and target moving in long time lead to complex range migration. To obtain high resolution imagery of moving target, General Key-Stone transform are applied to remove the range migration and realize multiple moving target data segment. Both General Key-Stone Transform and Clean Technique are applied in real data processing of FOPEN UWB SAR. The result shows that multiple moving targets in the trees are clearly detected and high resolution imagery is formed.
Wave number Domain Imaging algorithm can deal with the problem of foliage-penetrating ultra-wide band synthesis aperture radar (FOPEN UWB SAR) imaging. Stolt interpolation is a key role in Imaging Algorithm and is unevenly interpolation problem. There is no fast computation algorithm on Stolt interpolation. In this paper, A novel 4-4 tap of integer wavelet filters is used as Stolt interpolation base function. A fast interpolation algorithm is put forwards to. There is only plus and shift operation in wavelet interpolation that is easy to realize by hardware. The real data are processed to prove the wavelet interpolation valid for FOPEN UWB SAR imaging.
A new concept is defined as General Key-Stone Transform, which can remove any order of range migration. Two new imaging algorithms are obtained according to two order of General Key-Stone Transform concept. One imaging algorithm based on two order of General Key-Stone Transform fits for broadside SAR, the other imaging algorithm based on two orders General Key-Stone Transform fits for side-look SAR. Practice data processing shows that both of them are good SAR imaging algorithms.
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