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The problem of estimating a spectral representation of damped sinusoidal signals from a gapped data set is of considerable interest in several applications. In this paper, we propose a new iterative adaptive approach, named dIAA, that provides such an estimate also in the case of irregularly sampled data, a common scenario in, for instance, spectroscopical data measurements. Numerical examples illustrate...
Nuclear quadrupole resonance (NQR) is a radio frequency spectroscopic technique that can be used to detect solid-state compounds containing quadrupolar nuclei, a requirement fulfilled by most high explosives (and narcotics). In this paper, we present an overview of recent research in the detection of explosives using this technique. We also present mathematical models for the data for different acquisition...
We introduce a missing data recovery methodology based on a weighted least squares iterative adaptive approach (IAA). The proposed method is referred to as the missing-data IAA (MIAA) and it can be used for uniform or non-uniform sampling as well as for arbitrary data missing patterns. MIAA uses the IAA spectrum estimates to retrieve the missing data, based on a spectral least squares criterion similar...
Unimodular (i.e., constant modulus) sequences with good autocorrelation properties are useful in several areas, including communications, radar and sonar. The integrated sidelobe level (ISL) is often used to express the goodness of the autocorrelation properties of a given sequence. In this paper, we present several cyclic algorithms for the local minimization of ISL-related metrics. To illustrate...
We begin by revisiting the plain least-squares periodogram (LSP) for real-valued data. Then we introduce a new method for spectral analysis of non-uniformly sampled data by "iteratively weighting LSP", and we name the new method real-valued iterative adaptive approach (RIAA). LSP and RIAA are most suitable for data sequences with discrete spectra. For such type of data, we present a procedure...
In this paper, we propose optimal methods for preconditioning an ill-conditioned linear system of equations, obtained when interpolating missing data in a band-limited sequence. The optimal preconditioning weights are obtained by solving an eigenvalue optimization problem via semidefinite programming. The so-obtained optimal weights are compared with a commonly used set of heuristic weights in terms...
MIMO radar can achieve superior performance over the conventional phased-array radar through waveform diversity. Considerations in transmit waveform and receive filter design are central to attaining improved performance through a MIMO system. Moreover, adaptive array techniques are needed to improve accuracy, resolution and to further provide interference suppression. Recently, the weighted least-squares...
This paper addresses the problem of source localization and waveform estimation in array processing applications. We present two nonparametric user parameter free algorithms, namely the iterative adaptive approach (IAA) and the maximum likelihood based IAA (IAA-ML). Both IAA and IAA-ML can work with arbitrary array geometries and uncorrelated as well as coherent sources. We extend IAA and IAA-ML to...
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