• ISAR
• SAR
• signal processing

This thesis reports on research into the field of Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) signal processing. The contributions of this thesis may be divided into two following parts:
* A new bistatic 3D near field circular SAR imaging algorithm was developed. High resolution radar imaging is typically obtained by combining wide bandwidth signals and synthetic aperture processing. High range resolution is obtained by using modulated signals whereas high cross range resolution is achieved by coherently processing the target echoes at different aspect angles of the target. Anyway, theoretical results have shown that when the aspect angle whereby the target is observed is sufficiently wide, high resolution target images can be obtained by using continuous wave (CW) radars [2], therefore allowing to reduce hardware costs. In a similar way, three dimensional radar imaging can be performed by coherently processing the backscattered field as a function of two rotation angles about two orthogonal axes [3].Three dimensional target radar imaging can be efficiently obtained by means of a 3D Fourier Transform, when the far-field (planar wave) approximation holds. Otherwise, the wavefront curvature has to be accounted for. For this reason, a new algorithm based on a near field spherical wave illumination that takes into account the wavefront curvature by adopting a planar piecewise approximation was designed. This means that the wavefront is assumed to be locally planar around a given point on the target. The operator that the algorithm uses for the focusing procedure is a space variant focusing function which aims at compensating the propagation losses and the wavefront curvature. The algorithm has been developed under the Microwave Electronic Imaging Security and Safety Access (MELISSA) project. The system MELISSA is a body scanner whose purpose is the detection of concealed objects. The added value of the system is the capability to provide an electromagnetic image of the concealed objects. The author would like to thank all people that worked at the project, all LabRass colleagues, all people who designed and acquired real data, all people that permitted the drafting of the first part of this thesis. The developed algorithm was presented in the chapter 1. The goal of this work was the system design concerning the imaging point of view, by simulating and therefore predicting the system performance by means of the developed algorithm. In the chapter 2 was shown how the design was achieved. Finally, in the chapter 3, the results on real data measured in anechoic chamber with a system with characteristics very close to the final system prototype MELISSA, was presented.
* A new way of ISAR processing has been defined, by applying the traditional ISAR processing to data acquired from passive radars. Purpose of the ISAR processing is to extract an electromagnetic bi-dimensional image of the target in order to determine the main geometric features of the target, allowing (when possible) recognition and classification. Passive radars are able to detect and track targets by exploiting illuminators of opportunity (IOs). In this work of thesis, it will be proven that the same concept can be extended to allow for Passive Inverse Synthetic Aperture Radar (P-ISAR) imaging. A suitable signal processing is detailed that is able to form P-ISAR images starting from range-Doppler maps, which represent the output of a passive radar signal processing. Multiple channels Digital Video Broadcasting - Terrestrial (DVB-T) signals are used to demonstrate the concept as they provide enough range resolution to form meaningful ISAR images. The problem of grating lobes, generated by DVB-T signal, is also addressed and solved by proposing an innovative P-ISAR technique. The second part of this thesis has been developed under the Array Passive ISAR adaptive processing (APIS) project. APIS is defined as a multichannel, bi-static single receiver for array passive radar, capable of detecting targets and generating ISAR images of the detected targets for classification purposes. The author would like to thank all people that worked at the project, all LabRass colleagues, all people who designed, built the prototype and acquired real data, all people that permitted the drafting of the second part of this thesis. In the chapter 4, the basics on Passive Bistatic Radar (PBR) was briefly recalled, the P-ISAR processor was detailed and the new algorithm per the Grating Lobes Cancellation was presented. In the chapter 5, some numerical results on simulated data was shown, in order to demonstrate the potentiality of the P-ISAR, for the imaging and classification purpose. In fact, by using more than three adjacent channels and by observing the signal for a long time, finer range and cross-range resolutions, respectively, could be achieved. Finally, the obtained results on real data was discussed in the chapter 6.