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A sparse bayesian approach to multistatic radar imaging

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3 Author(s)
Raj, R.G. ; Radar Div., U.S. Naval Res. Lab., Washington, DC, USA ; Chance, Z. ; Love, D.J.

We tackle the problem of multistatic radar image formation by simultaneously exploiting the sparsity and covariance structure of radar images measured by a local GSM distribution of wavelet coefficients. Our aim is to gauge the extent to which such local statistical information can be leveraged in addition to the commonly used l1 sparsity constraint. Though we assume knowledge of the covariance structure of the source image, this provides a benchmark for subsequent relaxation of this assumption and its generalization to more complex probabilistic models of scene structure.

Published in:

Signals, Systems and Computers (ASILOMAR), 2011 Conference Record of the Forty Fifth Asilomar Conference on

Date of Conference:

6-9 Nov. 2011