196,312 research outputs found
Polarimetric ISAR autofocusing
No full textM. Martorella, J. Palmer, F. Berizzi, B. Haywood, and B. Bate
Space-Doppler processing for multichannel ISAR imaging of non-cooperative targets embedded in strong clutter
No full textNon-cooperative moving targets appear defocussed in SAR images and the blurring effect due to the unknown motion leads to low detection capabilities. In this work, clutter suppression and ISAR processing are combined to obtain well focused images of extended non-cooperative moving targets embedded in strong clutter, by exploiting Multichannel SAR (M-SAR) systems. Clutter mitigation and radar motion compensation are performed by means of the proposed Space Doppler Adaptive Processing. Then ISAR processing is used to compensate the unknown target motion. Two principal issues will be addressed. First, a technique to apply ISAR processing after clutter mitigation is presented, and then a suboptimal approach for clutter mitigation is proposed to overcome computational and statistical issues associated with estimation of clutter cross-power spectral matrix. Results of the processing applied to simulated data are provided in order to show the effectiveness of the proposed techniques.Alessio Bacci, Douglas Gray, Marco Martorella, Fabrizio Berizz
Statistical CLEAN technique for ISAR imaging
No full text© Copyright 2009 IEEE – All Rights ReservedAbstract
Inverse synthetic aperture radar (ISAR) images are frequently used in target classification and recognition applications. Some classifiers often require features that can be more easily obtained by extracting scattering centers from ISAR data rather than by reconstructing ISAR images. An available method for scattering center extraction, namely, the CLEAN technique, was proposed in a recent paper by Yang et al. In this paper, an improvement of this CLEAN technique is proposed that introduces a new method for detecting scattering centers. The proposed technique is based on a Gaussianity test, and its effectiveness is first theoretically proven and then tested on real data. Moreover, a comparison with the technique proposed by Yang et al. is shown.Marco Martorella, Nicola Acito, and Fabrizio Berizz
Montsant. Racó de la Martorella
No full textBoItinerari: Collet del Pla Gran o de l’Hort – Grau de l’Escletxa –Punta alta del Boter – Racó de la Martorella – Mas de l’Extrem – Sant Salvador del Montsant (750 m.) – Mas del Serrador – Portell de Boca d’Infern – Ermita de la Foia (600 m.) – Mas de Forçans – Monestir d’Escaladei – La Cartoixa d’Escalade
Target recognition by means of polarimetric ISAR images
No full textAutomatic target recognition (ATR) is generally the reason why inverse synthetic aperture radar (ISAR) imaging systems are employed. Moreover, the use of fully polarimetric radar systems in radar imaging applications such as SAR and ISAR has enhanced both image quality and classification capabilities. The authors propose a novel technique for ATR using polarimetric ISAR (Pol-ISAR) images. The proposed method is based on a model matching approach. Results are obtained that show the effectiveness of such a technique.M. Martorella, E. Giusti, L. Demi, Z. Zhou, A. Cacciamano, F. Berizzi, B. Bate
Analysis of the Robustness of Bistatic Inverse Synthetic Aperture Radar in the Presence of Phase Synchronisation Errors
No full textBistatic inverse synthetic aperture radar (B-ISAR) has the potential to become the radar imaging tool for obtaining noncooperative target images in arbitrary bistatic configurations. A monostatic ISAR processor is used here to form B-ISAR images and its robustness is tested with respect to phase synchronisation errors and rapidly time-varying bistatic configurations. Specifically, the B-ISAR point spread function (PSF) is analytically derived and the problem of B-ISAR image autofocusing is reformulated in such conditions. It is shown that, in most bistatic scenarios, the range-Doppler (RD) based monostatic ISAR processor is able to form focussed B-ISAR images. Simulation results are used to support the theoretical results
Multi-bistatic radar for resident space objects feature estimation
No full textThe amount of space debris orbiting the Earth has seen a dramatic grow through the recent years. Its rising population increases the potential danger to space missions. At present time, it is urgent to gain as much information as possible in order to characterize this environment. The classification in term of size and angular speed plays an important role in the process of assessing space debris threat and improving the overall knowledge of the objects that occupy the space around the Earth. This paper proposes an innovative technique for Resident Space Objects (RSOs) feature estimation by using multi-bistatic radar
A cognitive architecture for space time adaptive processing
No full textA cognitive radar can be conceived as a system that is able to autonomously and continuously change the parameters of both the transmitter and the receiver to optimise its performances in changing complex and changing environment with the available resources. In this paper, we implement a simple rule-based form of cognitive radar to optimise ground moving target imaging. The system architecture is presented that highlights the how cognition is implemented into STAP processing to optimise STAP filtering performances. Some preliminary results are shown based on recently acquired real airborne radar data
Size estimation of space debris models from their RCS measured in anechoic chamber
No full textSpace debris characterization is becoming increasingly important in the framework of Space Situational Awarenees (SSA). In fact, the uncontrolled multiplication of orbital debris has been statistically quantified around 130 million objects. It is therefore instrumental to take actions to protect operational spacecraft and human activities in space. Since years, NASA has been working to this end and has developed an RCS-to-size mapping function, known as Size Estimation Model (SEM). In this paper, RCS data acquired during a measurement campaign in an anechoic chamber has been used to derive a similar function. A comparison of the size estimated by using both models is shown in this paper
Inverse Radon transform scaling via spin rate estimation for resident space object size assessment
No full textThe population of resident space objects (RSOs) has increased drastically during the past years. These objects became a great threat for active satellites. The consequences of a collision with orbital debris strictly depend on the size and velocity of the debris. Typical collision velocities range from seven to fifteen kilometres per second, depending on the collision angle. Such debris must be detected, tracked, and catalogued in order to avoid collisions. Here, object size-related parameters will be estimated by making use of a scaled inverse Radon transform (IRT). The scaled IRT is obtained by estimating the object spin rate
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