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arXiv · 1702.05411

Block- and Rank-Sparse Recovery for Direction Finding in Partly Calibrated Arrays

Christian Steffens·Marius Pesavento
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Abstract

A sparse recovery approach for direction finding in partly calibrated arrays composed of subarrays with unknown displacements is introduced. The proposed method is based on mixed nuclear norm and 1 norm minimization and exploits block-sparsity and low-rank structure in the signal model. For efficient implementation a compact equivalent problem reformulation is presented. The new technique is applicable to subarrays of arbitrary topologies and grid-based sampling of the subarray manifolds. In the special case of subarrays with a common baseline our new technique admits extension to a gridless implementation. As shown by simulations, our new block- and rank-sparse direction finding technique for partly calibrated arrays outperforms the state of the art method RARE in difficult scenarios of low sample numbers, low signal-to-noise ratio or correlated signals.

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Christian Steffens, Marius Pesavento. 2017-02-17. Block- and Rank-Sparse Recovery for Direction Finding in Partly Calibrated Arrays. https://doi.org/10.1109/tsp.2017.2770104

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