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Superdirectivity is a very attractive option in array aperture constrained applications due to its high directivity and good angular discrimination. However, it is hardly applied in practice because of its extreme sensitivity to small random array errors. In this paper, we propose an online calibration method for superdirective arrays with gain-phase errors. Unlike the currently well-known robust...
An innovative technique for the synthesis of a nonuniform sonar array with as few elements as possible is proposed. This paper introduces a new method for linear array pattern synthesis based on continuous compressive sensing (CCS). Given a reference pattern subject to aperture constraints, the proposed approach allows the exact solution of the positions of sonar sensors, whose number is maximally...
In this paper, we consider joint estimation of the Direction-of-arrival (DOA) and channel parameters of fully correlated sources impinging on a linear array sensors in Underwater multipath environment. Amindavar et al.[1] proposed a blind techniques for simultaneous estimation of the DOA and the channel parameters based on the assumption that the source signal can be modeled by a sum of weighted complex...
Beamforming has been used in wireless sensor networks (WSNs) to increase the communication range of sensor nodes. These works investigate the beamforming performance using the theory of random arrays, and aims to achieve maximum transmitting power. Since the relative positions of sensor nodes and frequency/spatial response are generally unknown, it's also referred to as blind beamforming. In this...
Due to environment disturbance, interference between the normal modes, and the ambient noise, the spatial correlation between received signals is attenuated. In this paper, we consider the problem of detection performance degradation caused by spatial correlation attenuation, and a broadband correlation detection method based on the normal mode extraction is proposed accordingly. The method extracts...
Model-based passive source localization is known to be quite sensitive to model mismatch. In this paper, we present a new implementation based on matched-mode processing. Specifically we formulate mode filtering as a convex optimization problem, and ℓ1-regularized least squares is applied, which is robust in terms of the numerical implementation. Simulations with respective full-depth and partially-spanned...
In this paper, we consider the problem of direction of arrival (DOA) estimation with co-prime arrays via compressed sensing methods. A sparse signal recovery model based on the framework of co-prime array is presented. We propose to use OMP algorithm to efficiently implement the optimization procedure, which have a lower computational cost. The sparse recovery model of DOA estimation obeys the isotropy...
Traditional matched-field processing (MFP) techniques for underwater source localization such as Bartlett and Minimum variance Distortionless Response (MVDR) suffer from low resolution and sensitivity to environment/system mismatch respectively. This paper considers the problem of underwater source location estimation using a combination of sparsity imposed reconstruction method with newly proposed...
The Widely scalable Mobile Underwater Sonar Technology (WiMUST) project aims at developing a system of cooperative Autonomous Underwater Vehicles (AUVs) for geotechnical surveying and geophysical exploration. The paper reports about the first year activities and it gives an overview of the main objectives and methods. Results relative to distributed sensor array, cooperative control, mission planning,...
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