Title
CS Radar Imaging via Adaptive CAMP
Author
Anitori, L.
Otten, M.P.G.
Hoogeboom, P.
Publication year
2012
Abstract
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.
Subject
Physics & Electronics
RT - Radar Technology
TS - Technical Sciences
Defence Research
Radar
Defence, Safety and Security
Compressive Sensing
Radar Images
High Resolution
Signal Processing
Image Reconstruction
Algorithms
Complex Approximate Message Passing
To reference this document use:
http://resolver.tudelft.nl/uuid:456c24f0-34fb-4e2d-a88b-b48664d72839
TNO identifier
464116
Source
EUSAR 2012 - 9th European Conference on Synthetic Aperture Radar, 23-26 April 2012, Nuremberg, Germany
Document type
conference paper