CS Radar Imaging via Adaptive CAMP
conference paper
In this paper we present results on application of Compressive Sensing (CS) to high resolution radar imaging and pro-
pose the adaptive Complex Approximate Message Passing (CAMP) algorithm for image reconstruction. CS provides
a theoretical framework that guarantees, under certain assumptions, reconstruction of sparse signals from many fewer
measurements than required by the Nyquist-Shannon sampling theorem. However, whereas most conventional imaging
techniques are based on linear filtering, in CS the image is obtained from a subsampled set of measurements by means
of a non-linear reconstruction algorithm. A variety of such algorithms have been proposed, and, for a given problem
instance, the solution will depend on a threshold that has either to be provided by the user or estimated from the com-
pressed measurements. In this paper, we present an adaptive version of CAMP, where the threshold is estimated from the
data itself to provide a solution with minimum reconstruction error. Our results show that the adaptive CAMP algorithm
can reconstruct the image with a Mean Squared Error (MSE) comparable to the reconstruction error achieved using an
optimally tuned algorithm.
pose the adaptive Complex Approximate Message Passing (CAMP) algorithm for image reconstruction. CS provides
a theoretical framework that guarantees, under certain assumptions, reconstruction of sparse signals from many fewer
measurements than required by the Nyquist-Shannon sampling theorem. However, whereas most conventional imaging
techniques are based on linear filtering, in CS the image is obtained from a subsampled set of measurements by means
of a non-linear reconstruction algorithm. A variety of such algorithms have been proposed, and, for a given problem
instance, the solution will depend on a threshold that has either to be provided by the user or estimated from the com-
pressed measurements. In this paper, we present an adaptive version of CAMP, where the threshold is estimated from the
data itself to provide a solution with minimum reconstruction error. Our results show that the adaptive CAMP algorithm
can reconstruct the image with a Mean Squared Error (MSE) comparable to the reconstruction error achieved using an
optimally tuned algorithm.
Topics
TNO Identifier
464116
Source title
EUSAR 2012 - 9th European Conference on Synthetic Aperture Radar, 23-26 April 2012, Nuremberg, Germany
Files
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