652 research outputs found
Adaptive detection in nonhomogeneous environments using the generalized eigenrelation
This letter considers adaptive detection of a signal in a
nonhomogeneous environment, more precisely under a covariance mismatch between the test vector and the training samples, due to an interference that is not accounted for by the training samples, e.g., a sidelobe target or an undernulled interference. We assume that the covariance matrices of the test vector and the training samples verify the so-called generalized eigenrelation. Under this assumption, we derive the generalized likelihood ratio test and show that it coincides with Kelly’s detector
Adaptive Radar Detection of a Subspace Signal Embedded in Subspace Structured plus Gaussian Interference Via Invariance
This paper deals with adaptive radar detection of a subspace signal competing
with two sources of interference. The former is Gaussian with unknown
covariance matrix and accounts for the joint presence of clutter plus thermal
noise. The latter is structured as a subspace signal and models coherent pulsed
jammers impinging on the radar antenna. The problem is solved via the Principle
of Invariance which is based on the identification of a suitable group of
transformations leaving the considered hypothesis testing problem invariant. A
maximal invariant statistic, which completely characterizes the class of
invariant decision rules and significantly compresses the original data domain,
as well as its statistical characterization are determined. Thus, the existence
of the optimum invariant detector is addressed together with the design of
practically implementable invariant decision rules. At the analysis stage, the
performance of some receivers belonging to the new invariant class is
established through the use of analytic expressions
Enforcement of Regulation, Irregular Sector, and Firm Performance
In this paper we investigate how enforcement of regulation affects the size of irregular sector, firm perfomance and the exit rate to the market. Three kinds of enforcement policy will be tested in the model: control, punish and legitimacy. The first policy is based on the number of inspectors present in the economy; the second is defined by the magnitude of punish; the third is measured by the social legitimacy. Our results show the negligible influence of control to enforce irregularity; the strong effect of punish on irregular sector with a high exit rate; the good effect of legitimacy policy in promoting regularity with a low output performance.Irregular sector; enforcement policies; exit rate; firm perfomance
Adaptive Radar Detection of Dim Moving Targets in Presence of Range Migration
This paper addresses adaptive radar detection of dim moving targets. To
circumvent range migration, the detection problem is formulated as a multiple
hypothesis test and solved applying model order selection rules which allow to
estimate the "position" of the target within the CPI and eventually detect it.
The performance analysis proves the effectiveness of the proposed approach also
in comparison to existing alternatives.Comment: 5 pages, 2 figures, submitted to IEEE Signal Processing Letter
A Unifying Framework for Adaptive Radar Detection in Homogeneous plus Structured Interference-Part II: Detectors Design
This paper deals with the problem of adaptive multidimensional/multichannel
signal detection in homogeneous Gaussian disturbance with unknown covariance
matrix and structured (unknown) deterministic interference. The aforementioned
problem extends the well-known Generalized Multivariate Analysis of Variance
(GMANOVA) tackled in the open literature. In a companion paper, we have
obtained the Maximal Invariant Statistic (MIS) for the problem under
consideration, as an enabling tool for the design of suitable detectors which
possess the Constant False-Alarm Rate (CFAR) property. Herein, we focus on the
development of several theoretically-founded detectors for the problem under
consideration. First, all the considered detectors are shown to be function of
the MIS, thus proving their CFARness property. Secondly, coincidence or
statistical equivalence among some of them in such a general signal model is
proved. Thirdly, strong connections to well-known simpler scenarios found in
adaptive detection literature are established. Finally, simulation results are
provided for a comparison of the proposed receivers.Comment: Submitted for journal publicatio
An improved adaptive sidelobe blanker
We propose a two-stage detector consisting of a subspace
detector followed by the whitened adaptive beamformer orthogonal rejection test. The performance analysis shows that it possesses the constant false alarm rate property with respect to the unknown covariance matrix of the noise and that it can guarantee a wider range of directivity values with respect to previously proposed two-stage detectors. The probability of false alarm and the probability of detection (for both matched and mismatched signals) have been evaluated by means of numerical integration techniques
Theoretical performance analysis of the W-ABORT detector
In a recent paper we introduced a modification of the adaptive beaniformer orthogonal rejection test (ABORT) for adaptive detection of signals in unknown noise, by supposing under the null hypothesis the presence of signals orthogonal to the nominal steering vector in the whitened observation space. We will refer to this new receiver as the whitened adaptive beamformer orthogonal rejection test (W-ABORT). Through Monte Carlo simulations this new detector was shown to provide better rejection capabilities of mismatched (e.g., sidelobe) signals than existing ones, like ABORT or the adaptive coherence estimator (ACE), but at the price of a certain loss in terms of detection of matched (i.e., mainlobe) signals. The aim of this paper is to provide a theoretical validation of this fact. We consider both the case of distributed targets and point-like targets. We provide a statistical characterization of the W-ABORT test statistic, under the null hypothesis, and for matched and mismatched signals under the alternative hypothesis. For distributed targets, the probability of false alarm and the probability of detection can only be expressed in terms of multi-dimensional integrals, and are thus very complicated to obtain; in contrast, for point-like targets, such probabilities can be easily calculated by numerical integration techniques. The theoretical expressions derived herein corroborate the simulation results obtained previously
The classical Taub-Nut System: factorization, spectrum generating algebra and solution to the equations of motion
The formalism of SUSYQM (SUperSYmmetric Quantum Mechanics) is properly
modified in such a way to be suitable for the description and the solution of a
classical maximally superintegrable Hamiltonian System, the so-called Taub-Nut
system, associated with the Hamiltonian:
In full agreement with the results recently derived by A. Ballesteros et al.
for the quantum case, we show that the classical Taub-Nut system shares a
number of essential features with the Kepler system, that is just its Euclidean
version arising in the limit , and for which a SUSYQM approach has
been recently introduced by S. Kuru and J. Negro. In particular, for positive
and negative energy the motion is always periodic; it turns out that the
period depends upon and goes to the Euclidean value as .
Moreover, the maximal superintegrability is preserved by the
-deformation, due to the existence of a larger symmetry group related to
an -deformed Runge-Lenz vector, which ensures that in
closed orbits are again ellipses. In this context, a deformed version of the
third Kepler's law is also recovered. The closing section is devoted to a
discussion of the case, where new and partly unexpected features
arise.Comment: 11 pages, 6 figures. Version essentially extended: three new sections
added, some notations changed, typos corrected and four new figures include
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