This article handles the topic of cognitive radar (CR) architecture design in the framework of multifunction radar operating in a resource-constrained and spectrum-constrained environment. Despite the advances in this field of research and its relative technologies, the way humans and echolocation mammals are able to interact with the external environment goes beyond the capability of any available man-made system. A CR can be thought as a system in which the transmitter, receiver, and software parameters can be changed over time in response to the observed scene with the aim to optimize radar performances given limited resources and environment constraints. The radar, therefore, has to reason about what is being observed and has to take decisions about how to use its limited resources to improve its performance. Rules may represent the way the system reasons, while performance encodes the information contained into the received echoes, and can be used to control next actions and system memory. A rule-based cognitive architecture is proposed in this article as a way to design a CR that has to manage its resources dynamically while handling several tasks, such as target detection, imaging, and recognition in a complex and changing scenario.

This chapter presents an overview of radar systems and their main applications that have pushed radar toward new paradigms and system concepts. In particular, the chapter discusses the basic theory and concepts behind a classical radar system. The basic radar nomenclature and architecture are summarized in brief, and a summary of the main radar functionalities and applications is given. This is followed by the new challenges that modern radar systems are facing, with special emphasis on a high degree of adaptability to the environment and the capacity to cooperate in a network. Such new features are meant to enhance the radar performance in terms of detection, tracking, and automatic target recognition in a dynamic environment and to enable a radar system to be able to handle several tasks by managing its resources autonomously and intelligently.

This paper presents the results of the Software-defined Multiband Array Passive Radar (SMARP) project. The objective of the project was to design and realize a multiband passive radar demonstrator based on a software-defined solution and oriented to coastal surveillance applications. This work has been conceived in the framework of the Italian National Plan for Military Research. The project overall duration was 36 months and it was composed by three phases. The system concept and the results of each phase are presented in this paper.

Clutter heterogeneity caused by cultivation variation of the terrain properties degrades STAP detection performance. In recent years, a priori knowledge sources has been used directly and indirectly for STAP performance improvement. Monostatic radar systems are typically considered, but in the bistatic case, strong clutter non-stationarity introduced by the geometry makes convetional STAP not possible. In this case it is also very difficult to exploit a priori knowledge either directly or indirectly. In this paper an original processing chain that combines a priori knowledge with STAP filtering for detection performance improvement is proposed for bistatic geometries. Finally, ISAR processing is jointly combined with the knowledge-aided bistatic STAP to obtain focused images of non-cooperative moving targets.

The European Commission initiative CleanSky launched several project activities aimed at improving flight route planning in the presence of unforeseen events, such as rapidly evolving thunderstorms occurring along the route, both to increase the safety and comfort of flight and to keep emissions as low as possible. Improving meteorological instrumentation onboard and supporting the pilot in interpreting such goals are important to achieve this goal. Potential improvements to aircraft weather radar related to the use of dual opalization technology were investigated along several CleanSky projects. Two experimental campaigns, were carried out in 2016 within the X-WALD project with a prototypal radar using a low-power X-band dual-polarization radar mounted in the nose of two different aircrafts in the Netherlands and in Italy. Results from these campaigns and comparison of data collected on board with ground based instrumentation are presented.

The applicability of interferometric inverse synthetic aperture radar (InISAR) techniques to images reconstructed via compressive sensing (CS)-based algorithms is investigated. Specifically, the three-dimensional (3D) reconstruction algorithm is applied after exploiting CS for data compression and image reconstruction. The InISAR signal model is derived and formalised in a CS framework. A comparison between conventional CS reconstruction and global sparsity constrained reconstruction techniques is performed for different compression rates and different signal-to-noise ratio conditions. Performances on the 2D and 3D reconstructions are evaluated. Results obtained on real data acquired during the NATO-SET 196 trial are shown.

Based on the experiences of the Department of Information Engineering of the University of Pisa and the Radar and Surveillance System (RaSS) national laboratory of the National Interuniversity Consortium of Telecommunication (CNIT), Radar Imaging for Maritime Observation presents the most recent results in radar imaging for maritime observation. The book explores both the areas of sea surface remote sensing and maritime surveillance providing key theoretical concepts of SAR and ISAR imaging and more advanced and ad-hoc techniques for applications in maritime scenarios. The book is organized in two sections. The first section discusses the fundamentals of standard SAR/ISAR processing and novel imaging techniques, such as Bistatic, Passive, and, 3D Interferometric ISAR. The second section focuses on the applications and results obtained by processing real data from maritime observations like SAR image processing for oil spill, detection in SAR images and fractal analysis. Useful to both beginners and experts in maritime observation, this book provides several examples of (mainly space-borne) radar imaging of maritime targets. Nevertheless, the same principles and techniques apply to the case of manned or unmanned carriers and to ground and air moving targets.

In the framework of developments of 3D forest Tomography, the issue of extensive and detailed characterizations of temporal decorrelation phenomena has recently emerged, especially for the future spaceborne missions. In particular, height-varying (stratified) behaviour of long-term temporal decorrelation mechanisms has been analyzed by advanced 4D (3D+Time) Differential SAR Tomography processing applied to airborne data, and dedicated radar-tower campaigns have been conducted or are running. In this work, new Differential Tomography analyses exploiting a very quick acquisition ground-based miniradar are presented, aiming to open investigation of both height- and time-varying characteristics of the short-term decorrelation processes of the complex moving and non-stationary (dynamic) volumetric scatterers of windblown forests. This innovative characterization methodology and the first reported findings can be useful especially for the development of advanced spaceborne Tomography systems based on formation-flying and 3D correlative track-pair only processing.

This paper presents a recently built passive radar demonstrator, called the Software-defined Multiband Array Passive Radar (SMARP). This work has been conceived in the framework of the Italian National Plan for Military Research. The system is able to detect and track targets by exploiting DVB-T and UMTS transmitters. The system concept and the results are presented in this paper.

Multiple-input–multiple-output (MIMO) technology has been suggested as an effective tool in overcoming some of the issues that are typically relate to conventional over the horizon radars. Notwithstanding, effects, such as fading and multipath propagations are ever present and cannot be avoided even when using a MIMO configuration. For this reason, a study on the impact of such effects on high frequency (HF) skywave MIMO radars is fundamental for an effective design of such systems. This study aims to study the effects of ionospheric propagation on the performance of the HF MIMO skywave radar. In particular, the relationship between the transmitted signal parameters and the ionospheric variations because of perturbations is highlighted in a suitable signal model. The performance analysis is performed in terms of estimated direction of arrival and loss of virtual array elements.

The improvement of the essential aircraft equipment used by pilots has a very important role in safety enhancement. In this context polarimetric weather Doppler radars could offer a valuable aid in improving detection and classification of hydrometeors, helping pilots to take the more efficient trajectory, balancing risk level and unnecessary detours. In this work an analysis of a polarimetric radar signal simulator developed by the RaSS team is presented.

In this paper, the potential of an avionic polarimetric weather radar is shown. The simulator used for such a purpose is a statistical simulator capable of reproducing complex signals as those gathered by an onboard radar, along with polarimetric and Doppler observables. The simulator, developed in the framework of the CleanSky European program, can be an useful tool to evaluate the radar prototypes that in a near future will be mounted on real aircrafts to enhance pilots' environmental awareness, which is declared as a major CleanSky objective.

Passive bistatic radar or passive coherent location is gaining interest in the radar community, as it provides some advantages with respect to active radar. Passive radar does not aim to replace active radar; it provides a good complement to it. The computational effort that is required to implement the required signal processing is one of the drawbacks that affect passive radars. In this paper, a suboptimal but computationally affordable detection algorithm is investigated that is applicable to arbitrary waveforms (different types of illuminators of opportunity). First, a detailed mathematical formulation of the proposed suboptimum algorithm is derived. A theoretical performance analysis is then provided based on a comparison of the proposed with the optimum two-dimensional matched filter. Finally, simulated and real data are used to demonstrate the effectiveness of the proposed algorithm and to validate the theoretical performance analysis.

Moving targets appear defocused within SAR images and their detection is a challenging especially in the case of targets embedded in strong clutter. Moreover, in bistatic geometries, the clutter echo returns are range dependent. This situation degrades significantly STAP performance. In this paper, an adaptive compensation to homogenize data is performed first. This operation allow the proposed Space Doppler Adaptive Processing to be used to suppress bistatic ground clutter improving detection capabilities. Then, ISAR technique is used to obtain well focused images of extended non-cooperative moving targets. Two principal issues will be addressed. First combination of bistatic adaptive clutter suppression in the space-Doppler domain and ISAR technique is presented. Then a suboptimal approach is proposed to overcome computational issue. Result using simulated data are shown.

A soft 3D reconstruction algorithm for non cooperative moving targets is proposed in this paper. This method exploits a dual interferometric ISAR system (InISAR) to estimate the heights of the dominant scatterers with respect to the Image Projection Plane (IPP). In particular, the interferometric phases measured from two orthogonal baselines are used to reconstruct both the third dimension from 2D-ISAR images and the IPP. A Cross-Channel Coherence-based detection is used in order to take into account only the areas of the target with meaningful interferometric phase. In order to verify the effectiveness and the reliability of this technique, a Multi-Channel ground-based radar has been used.

The problem of interferometric 3D ISAR imaging exploiting data compressed and reconstructed via Compressive Sensing technique is discussed in this paper. The ISAR signal model is provided as well as its CS formulation. Then, the interferometric 3D imaging technique is recalled and applied to CS reconstructed data proving the effectiveness of the proposed method and the capability of CS ISAR algorithm to preserve both the amplitude and the phase information.

HF Skywave radars exploit the refractive properties of the ionosphere to reach distances beyond the horizon allowing for the surveillance of very large areas. The instability of the ionospheric channel on wide temporal and spatial scales is one of the most important issue to be addressed in the design of such systems, especially when considering a MIMO configuration. In fact, large scale ionospheric disturbances and multipath can affect the propagating signals and degrade the radar performance. The main objective of this paper is to derive a suitable signal model that accounts for ionospheric multipath and fading. ROC curves are then simulated and compared to the case in which multipath is not considered.

Non-cooperative moving targets appear defocussed within SAR images. Moreover, in the case of ground targets, the blurring effect due to the uncompensated target motion decreases detection capabilities. In this work, clutter suppression by means of Space Doppler Adaptive Processing and ISAR imaging are combined to obtain high resolution images of non-cooperative moving targets within SAR images. Results obtained by processing a real dataset prove the effectiveness of the proposed processing chain.

Advanced satellite synthetic aperture radar (SAR) systems, such as Cosmo-SkyMed (CSK), provide high-resolution images with reasonably short revisiting time, allowing for a number of applications in areas such as homeland security and maritime surveillance. Especially in the case of maritime surveillance, moving targets imaging represents a challenge for SAR systems as the complex target motions produce evident image defocusing. In this paper, we propose a complete processing chain that aims at detecting and imaging ship targets moving inside the imaged scene. In the proposed technique, moving targets are focused by using inverse SAR (ISAR) processing, which proves effective also in the case of target's complex motions. The implemented processing chain can be considered an innovative combination of well-established detection and ISAR imaging approaches. It is important to state that the proposed maritime ISAR mode for the CSK SAR system acts as an add-on system and, therefore, does not require any modification to the original CSK design. The effectiveness of the proposed approach is demonstrated by processing archive images acquired by CSK in spotlight mode; moreover results obtained by using CSK images acquired ad hoc against a cooperative target are also provided in order to prove the validity of the overall chain also in presence of targets with small size. As additional option of the proposed maritime ISAR it will also be shown that super-resolution techniques are applicable to targets affected by complex motions after ISAR processing is used.

The next generation of radar (radio detection and ranging) systems needs to be based on software-defined radio to adapt to variable environments, with higher carrier frequencies for smaller antennas and broadened bandwidth for increased resolution. Today's digital microwave components (synthesizers and analogue-to-digital converters) suffer from limited bandwidth with high noise at increasing frequencies, so that fully digital radar systems can work up to only a few gigahertz, and noisy analogue up- and downconversions are necessary for higher frequencies. In contrast, photonics provide high precision and ultrawide bandwidth, allowing both the flexible generation of extremely stable radio-frequency signals with arbitrary waveforms up to millimetre waves, and the detection of such signals and their precise direct digitization without downconversion. Until now, the photonics-based generation and detection of radio-frequency signals have been studied separately and have not been tested in a radar system. Here we present the development and the field trial results of a fully photonics-based coherent radar demonstrator carried out within the project PHODIR. The proposed architecture exploits a single pulsed laser for generating tunable radar signals and receiving their echoes, avoiding radio-frequency up- and downconversion and guaranteeing both the software-defined approach and high resolution. Its performance exceeds state-of-the-art electronics at carrier frequencies above two gigahertz, and the detection of non-cooperating aeroplanes confirms the effectiveness and expected precision of the system.