For two-dimensional (2-D) spectral analysis, the adaptive filtering based technologies, such as CAPON and APES (Amplitude and Phase EStimation), are developed under the implicit assumption that the data sets are rectangular. However, in real SAR applications, especially for the wide-angle cases, the collected data sets are always non-rectangular. This raises the problem of how to extend the original adaptive filtering based algorithms for such kind of scenarios. In this paper, we propose an extended adaptive filtering (EAF) approach, which includes Extended APES (E-APES) and Extended CAPON (E-CAPON), for arbitrarily shaped 2-D data. The EAF algorithms adopt a missing-data approach where the unavailable data samples close to the collected data set are assumed missing. Using a group of filter-banks with varying sizes, these algorithms are non-iterative and do not require the estimation of the unavailable samples. The improved imaging results of the proposed algorithms are demonstrated by applying them to two different SAR data sets.
We consider nonparametric complex spectral estimation using an adaptive filtering based approach where the finite impulse response (FIR) filter-bank is obtained via a rank-deficient robust Capon beamformer. We show that by allowing the sample covariance matrix to be rank-deficient, we can achieve much higher resolution than existing approaches, which is useful in many applications including radar target detection and feature extraction. Numerical examples are provided to demonstrate the performance of the new approach as compared to existing data-adaptive and data-independent FIR filtering based spectral estimation methods.
We investigate both two-dimensional (2-D) and three-dimensional (3-D) synthetic aperture radar (SAR) imaging techniques for a forward-looking ground penetrating radar (FLGPR) system. In particular, we consider SAR imaging using the delay-and-sum (DAS), phase-shift migration, and spectral estimation (joint APES (Amplitude and Phase EStimation) and RCB (Robust Capon Beamforming)) approaches with the PSI (Planning Systems Inc.) FLGPR Phase II system. For the DAS and phase-shift migration approaches, we use shading in both frequency and cross-track aperture dimensions to reduce sidelobe leakages and clutter. We perform both coherent and non-coherent multi-look processing as well as smoothing to improve the SAR imaging quality and landmine detection capability of the system. The effectiveness of the approaches are demonstrated with an experimental data set collected by the PSI FLGPR Phase II system.