1,721,266 research outputs found
Compatibility Assessment of Multistatic/Polarimetric Clutter Data with the SIRP Model
No full textThis article deals with the statistical inference of simultaneously recorded co- and cross-polarized bistatic coherent sea-clutter returns at S-band. This study is conducted employing appropriate statistical learning tools, involving the complex envelope of data, to assess the compliance of the available measurements with the spherically invariant random process (SIRP) representation, as well as to analyze possible texture correlations among the diverse polarimetric channels. Moreover, the spatial heterogeneity of the sea-clutter data is studied. The results highlight that the SIRP model is a good candidate for the representation of bistatic coherent clutter and usually the coherence time of the SIRP texture at the bistatic nodes is longer than that in the monostatic sensing. Notably, at bistatic angles in order of 60°, the quadrature components of the cross-polarized bistatic measurements substantially exhibit a Gaussian behavior. These achievements further shed light on the bistatic sea-clutter diversity from the geometric and polarimetric point of view.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
A MAXIMUM ENTROPY FRAMEWORK FOR SPACE-TIME ADAPTIVE PROCESSING" INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY
No full text
Rao test for adaptive detection in Gaussian interference with unknown covariance matrix
No full textThis paper deals with the problem of detecting a signal known up to a scaling factor in the presence of Gaussian disturbance with unknown covariance matrix. A new detector based on the Rao test criterion is introduced and its invariance properties and constant false alarm rate (CFAR) behavior are studied. At the analysis stage, the performance of the new receiver is assessed, also in comparison with some classical adaptive radar detectors, both in the matched as well as in the mismatched signal case. Remarkably, the Rao test may achieve a matched detection performance which is commensurate with that of the generalized likelihood ratio test (GLRT)-based detectors if a sufficient number of training data is available. Moreover, it also exhibits better rejection capabilities of mismatched signals than the counterparts. In the last part of the work, a two-stage detector whose second stage coincides with the Rao test is devised. It represents a suitable means to restore the detection performance of the plain Rao test in the presence of a small number of training data. Finally, the performance of the aforementioned two-stage processor is analyzed in closed form and the CFAR behavior is proved
Blind adaptive detection of distributed targets in compound-Gaussian clutter
No full textThis paper considers the problem of detecting distributed targets in the presence of compound-Gaussian noise with unknown statistics. At the design stage, in order to cope with the a priori uncertainty, we model clutter return as Gaussian vectors with the same structure of the covariance matrix, but possibly different power levels. Hence, resorting to the method of sieves, we devise a fully blind detector which ensures the Constant False Alarm Rate (CFAR) property with respect to the disturbance power levels. Moreover the performance analysis confirms the capability of the novel receiver to operate in scenarios of practical interest for radar systems. Finally the comparison with the plain Modified Generalized Likelihood Ratio Test (MGLRT), devised assuming Gaussian disturbance, shows, that even in the presence of Gaussian clutter, the newly proposed detector achieves satisfactory performance
Fast converging adaptive matched filter and adaptive cosine/coherence estimator
No full textThis paper deals with the problem of detecting a signal known up to a scaling factor in the presence of Gaussian disturbance with unknown covariance matrix. We focus on scenarios where the number of secondary data which share the same covariance of the data under test is very limited. Thus, we propose a modified version of the adaptive matched filter (AMF) and of the adaptive cosine/coherence estimator (ACE) which can be applied even if the sample covariance matrix is rank deficient. Even though these detectors do not ensure the constant false alarm rate (CFAR) property with respect to the covariance matrix of the disturbance, a sensitivity analysis has shown that the threshold setting is very robust with respect to possible discrepancies between the design and the operating conditions. Finally, numerical results highlight that the proposed receivers outperform the conventional AMF and ACE in low sample situations. (C) 2002 Elsevier Science B.V. All rights reserved
Maximum likelihood estimation of structured persymmetric covariance matrices
No full textIn this paper we address estimation of the structured covariance matrix of a Gaussian process. To this end we assume that the aforementioned quantity is the sum of a positive semidefinite hermitian and persymmetric term, which accounts for the interference, plus a matrix proportional to the identity and representative of the internal noise covariance. Under these constraints we devise the maximum likelihood estimator of the overall disturbance covariance matrix and remarkably show that exploiting persymmetry, in conjunction with the others structural covariance informations, can lead to a significant reduction in the number of training data required for ensuring satisfactory performances. (C) 2002 Elsevier Science B.V. All rights reserved
A new derivation of the adaptive matched filter
No full textThis paper deals with the problem of detecting a signal known up to a scaling factor in the presence of Gaussian disturbance with unknown covariance matrix. We propose a novel derivation of the adaptive matched filter (AMF) previously designed in a previous paper by Robey et al.. Precisely, we show that the Wald test for the problem at hand coincides with the AMF
ROBUST ADAPTIVE RADAR DETECTION IN THE PRESENCE OF STEERING VECTOR MISMATCHES
No full textIn this paper we consider the problem of robust radar detection in the presence of Gaussian disturbance with unknown covariance matrix. We design and assess three new robust adaptive detectors, capable of operating in the presence of unknown discrepancies between the nominal and the actual steering vector. Remarkably the new decision rules exhibit a bounded constant false alarm rate (CFAR) behavior and allow, through the regulation of a design parameter, to trade off target sensitivity with sidelobes energy rejection. Finally computer simulations show that the proposed detectors achieve a visible performance improvement, in many situations of practical interest, over the traditional adaptive detection algorithms, especially in the presence of severe steering vector mismatches
Polarimetric adaptive detection of range-distributed targets
No full textIn this paper, we address the problem of polarimetric adaptive detection of range-spread targets in Gaussian noise with unknown covariance matrix. At the design stage, we model the target echo from each polarimetric channel as a deterministic signal known up to a scaling factor (possibly varying from cell to cell), which accounts for the polarimetric scattering properties of the target. We first show the failure of the generalized likelihood ratio test (GLRT) procedure to deal with this kind of problem, and thus, we propose a fully adaptive detector based on the method of sieves. We also derive the analytical expression for the probability of false alarm and show that the newly introduced receiver can be made bounded constant false alarm rate (CFAR). Finally, we present simulation results highlighting the performance gain that can be achieved by resorting to polarization diversity in conjunction with high resolution
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