High resolution adaptive arrays based on random processing techniques: frequency hopping modulation

A new architecture for adaptive arrays using frequency hopping modulation is addressed. The resolution of the array and the interference rejection increase substantially applying random processing to the carrier frequency of the signals. The proposed framework is composed of two different stages. The anticipative stage, devoted to minimize the noise and fixed interferences contribution and the GSLC stage which provides cancellation of follower jammers and solves the multiuser collision problem. The developed system requires neither temporal nor spatial reference for its implementation, only the frequency sequence must be known. An adaptive approach has been implemented, allowing a fast convergence to the optimal behavior.Peer ReviewedPostprint (published version

The Maximal Eigengap Estimator for Acoustic Vector-Sensor Processing

This paper introduces the maximal eigengap estimator for finding the direction of arrival of a wideband acoustic signal using a single vector-sensor. We show that in this setting narrowband cross-spectral density matrices can be combined in an optimal weighting that approximately maximizes signal-to-noise ratio across a wide frequency band. The signal subspace resulting from this optimal combination of narrowband power matrices defines the maximal eigengap estimator. We discuss the advantages of the maximal eigengap estimator over competing methods, and demonstrate its utility in a real-data application using signals collected in 2019 from an acoustic vector-sensor deployed in the Monterey Bay

Complex wave propagation in the Campi Flegrei Caldera, Italy,from Source and receiver-array analysis of sea-shot recordings

We investigate wave propagation in the complex shallow crust of Campi Flegrei Volcanic Complex, Italy, using array recordings of air-guns. We apply source- and receiver-array analysis to define the independent variation of horizontal slowness at both the source and receiver regions. This method allows the identification of asymmetric ray-paths associated with near-source and near-observer velocity heterogeneities. P-wave wave-vectors at both the source and receiver arrays depict discrepancies as large as 50° with respect to the values expected for the 3D velocity structure of the Gulf. At the source region, these discrepancies may be associated with either un-modelled complexities in the geometry of the buried caldera rim, or with velocity variations beneath the source-array. At the receiver array, the inferred anomalies may be attributed to velocity variations marking the Solfatara crater rim, or to a near-receiver, low-velocity body whose position would coincide with negative gravimetric anomalies and a low Vp/Vs ratio region inferred by independent geophysical and seismological studies

Specific 2-D spectral estimation for wideband beamforming

Peer ReviewedPostprint (published version

Detection of Wideband Signal Number Based on Bootstrap Resampling

Knowing source number correctly is the precondition for most spatial spectrum estimation methods; however, many snapshots are needed when we determine number of wideband signals. Therefore, a new method based on Bootstrap resampling is proposed in this paper. First, signals are divided into some nonoverlapping subbands; apply coherent signal methods (CSM) to focus them on the single frequency. Then, fuse the eigenvalues with the corresponding eigenvectors of the focused covariance matrix. Subsequently, use Bootstrap to construct the new resampling matrix. Finally, the number of wideband signals can be calculated with obtained vector sequences according to clustering technique. The method has a high probability of success under low signal to noise ratio (SNR) and small number of snapshots

Estimation of the Number of Sources in Unbalanced Arrays via Information Theoretic Criteria

Estimating the number of sources impinging on an array of sensors is a well known and well investigated problem. A common approach for solving this problem is to use an information theoretic criterion, such as Minimum Description Length (MDL) or the Akaike Information Criterion (AIC). The MDL estimator is known to be a consistent estimator, robust against deviations from the Gaussian assumption, and non-robust against deviations from the point source and/or temporally or spatially white additive noise assumptions. Over the years several alternative estimation algorithms have been proposed and tested. Usually, these algorithms are shown, using computer simulations, to have improved performance over the MDL estimator, and to be robust against deviations from the assumed spatial model. Nevertheless, these robust algorithms have high computational complexity, requiring several multi-dimensional searches. In this paper, motivated by real life problems, a systematic approach toward the problem of robust estimation of the number of sources using information theoretic criteria is taken. An MDL type estimator that is robust against deviation from assumption of equal noise level across the array is studied. The consistency of this estimator, even when deviations from the equal noise level assumption occur, is proven. A novel low-complexity implementation method avoiding the need for multi-dimensional searches is presented as well, making this estimator a favorable choice for practical applications.Comment: To appear in the IEEE Transactions on Signal Processin