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In Big Data Processing we typically face very large data sets that are highly structured. To save the computation and storage cost, it is desirable to extract the essence of the data from a reduced number of observations. One example of such a structural constraint is sparsity. If the data possesses a sparse representation in a suitable domain, it can be recovered from a small number of linear projections...
Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. Arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. Array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure)...
It is impossible to enforce exact responses for each sensor involved in an antenna array. Important signal processing techniques such as Estimation of Signal Parameters via Rotational Invariance (ESPRIT), Forward Backward Average (FBA) and Spatial Smoothing (SPS) rely on sensor arrays with Vandermonde or centro-hermitian responses. To achieve such responses array interpolation is often necessary....
In the presence of colored noise, subspace based harmonic retrieval algorithms suffer a performance degradation due to the interference between signal and noise subspaces. In order to efficiently separate the signal and noise subspaces, prewhitening is applied to decorrelate the noise samples prior to harmonic retrieval. When noise-only observations are unavailable for estimating the noise statistics,...
Unmanned aerial vehicles (UAVs) are used in various applications such as civil and military surveillance, law enforcement, and support in natural disasters as well as in hazardous environments. Approaching and landing are necessary steps for all UAVs, indicating that radio altimeters are needed. In this paper, a radio altimeter based on an antenna array is proposed. Our solution allows some improvements...
Recently, the Sequential GSVD (S-GSVD) based prewhitening scheme has been proposed to improve R-dimensional subspace-based parameter estimation schemes in the presence of colored noise or interference with Kronecker structure. To apply the S-GSVD, second order statistics of the noise should be estimated, e.g., via samples captured in the absence of the desired signal components. In this contribution,...
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