In recent years, researchers have tried to estimate the direction-of-arrival (DOA) of wideband sources and several novel techniques been proposed. this paper, we compare six algorithms for calculating DOA broadband signals, namely coherent subspace signal method (CSSM), two-sided correlation transformation (TCT), incoherent multiple classification (IMUSIC), test orthogonality frequency subspace...

In this paper, we present a method to estimate the signal subspace at all frequencies in given band, which is computed from usual set of frequency-bin sample covariance matrices wideband estimation. Fundamentally, exploits similarity between any two near-by produce an improved along band. Its key idea consists modeling by means projection matrix function approximated polynomial. The provides im...

This paper presents an overview of different types of wideband direction of Arrival (DOA) estimation methods. Direction-finding algorithms have straight forward applications in Sonar and Radar, and are also useful in advanced satellite and cellular communication systems for adaptive beamforming of smart antennas. Coherent Signal Subspace Processing (CSSM), one of the earliest wideband DOA estim...

We present an algorithm, dubbed Multi-Branch Matching Pursuit (MBMP), to solve the sparse recovery problem over redundant dictionaries. MBMP combines three different paradigms: being a greedy method, it performs iterative signal support estimation; as a rank-aware method, it is able to exploit signal subspace information when multiple snapshots are available; and, as its name foretells, it leve...

In this paper, we propose a novel direction of arrival (DOA) estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM...

Incoherent noise attenuation remains a challenging problem in seismic data processing. While many tools are successful at removing noise, this often comes at the expense of some signal. We seek the ideal noise attenuator– one that is effective, practical, and above all safe. Multichannel Singular Spectrum Analysis (MSSA) is a step in this direction. MSSA exploits the spatial redundancy of data ...

The paper contains several theoretical results related to the weighted nonlinear least-squares problem for low-rank signal estimation, which can be considered as a Hankel structured approximation problem. A parameterization of subspace time series connected with generalized linear recurrence relations (GLRRs) is described and its features are investigated. It shown how obtained help describe ta...