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Data from: Spatially sparse emitters localization with QVBEM algorithm

Citation

Sabahi, Mohamad Farzan; Ramezani, Esmaeil; Saberali, Seyyed Mohammad (2020), Data from: Spatially sparse emitters localization with QVBEM algorithm, Dryad, Dataset, https://doi.org/10.5061/dryad.3r2280gbx

Abstract

We study the estimation of the spatially sparse radio emitter locations from space, via the proposed Quad-tree variational Bayesian expectation maximization (QVBEM) algorithm. Firstly, we assume that the emitters are approximately lie on a uniform grid points in the region under surveillance. The VBEM algorithm is applied and the points exceeding the threshold level are considered as potential targets. Then, the grids are refined around the potential targets via the Quad-tree algorithm and the process is iterated. It allows us to find the location of sparse emitters with much less computational complexity due to the use of fewer grid points.