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Infrared search and track (IRST) systems based on 3-D velocity filters are quite sensitive to the random motion that remains after egomotion compensation has occurred (jitter). These systems are designed to detect small targets at long range and they often employ track-before-detect (TBD) strategies to integrate the target signal ahmg consecutive frames. Jitter causes frame misalignment and leads to a reduction of the detection performance. We analyze the effects of jitter on the false alarm and detection probabilities and on the detection range. The analytical expressions here derived are a valuable tool both in the analysis and synthesis of IRST systems based on 3-D velocity filters.

Use of the range instantaneous Doppler (RID) approach is proposed, for reconstructing very high resolution inverse synthetic aperture radar (ISAR) of maneuvering targets. It is shown that, for spatial resolutions, the RID approach is superior to the conventional range Doppler (RD) method.

The investigation of epitaxial molecular beam epitaxy growth of nanometric Germanium layers on silicon (001) 2 by 1, in situ, by X-ray silicon 2p photoelectron diffraction and Auger Ge LMM electron diffraction which consists primarily of preferential scattering of electrons in the direction of interatomic axes. The crystalline material quality and epitaxial perfection are affected by the residual pressure below a certain range, a decrease in the substrate temperature to room temperature, the deposition rate and the Ge overlayer thickness.

We investigate the statistical modeling of hyper-spectral data. The accurate modeling of experimental data is critical in target detection and classification applications. In fact, having a statistical model that is capable of properly describing data variability leads to the derivation of the best decision strategies together with a reliable assessment of algorithm performance. Most existing classification and target detection algorithms are based on the multivariate Gaussian model which, in many cases, deviates from the true statistical behavior of hyper-spectral data. This motivated us to investigate the capability of non-Gaussian models to represent data variability in each background class. In particular, we refer to models based on elliptically contoured (EC) distributions. We consider multivariate EC-t distribution and two distinct mixture models based on EC distributions. We describe the methodology adopted for the statistical analysis and we propose a technique to automatically estimate the unknown parameters of statistical models. Finally, we discuss the results obtained by analyzing data gathered by the multispectral infrared and visible imaging spectrometer (MIVIS) sensor.

Investigates the epitaxial molecular beam epitaxy growth of nanometric germanium layers on silicon (001) 2 X 1. Characterization methods used to control the growth of available germanium molecular beam epitaxy deposits; Details on the experiment; Results of the study.

Adaptive radar detection in non-Gaussian clutter is the subject of this work. The performance of two adaptive detection schemes developed in the literature, Kelly's generalized likelihood ratio test (GLRT) and the adaptive linear-quadratic (ALQ) detector, are tested on real sea clutter data recorded by the IPIX experimental radar (McMaster University, Canada) at the Osborne Head Gunnery Range (OHGR) in November 1993. The results of first- and second-order statistical analyses performed on two data sets are reported. Amplitude analysis has been carried out by checking the fitting to Weibull, log-normal, K, and generalized K models. The results show good agreement between performance prediction based on the generalized K model, with texture strongly correlated among primary and secondary data, and the performance obtained by processing the real sea clutter data.