The Italian Space Agency (ASI) has recently entrusted CO.RI.S.T.A. with the development of a radar system that can be mounted onboard small airplanes or helicopters and may operate, at different frequencies belonging to the P-Band, either as Synthetic Aperture Radar (SAR) or as Sounder. In this work, we present preliminary results of the helicopter-borne desert campaign carried out with this system in 2018 over the Erfoud area, Morocco, in the frame of a project that has involved different public Italian Research Institutes and Universities.

We establish the fundamental limits of lossless analog compression by considering the recovery of arbitrary random vectors x ∈ Rmfrom the noiseless linear measurements y = Ax with measurement matrix A ∈ Rn×m. Our theory is inspired by the groundbreaking work of Wu and Verdú (2010) on almost lossless analog compression but applies to the nonasymptotic, i.e., fixed-m case, and considers zero error probability. Specifically, our achievability result states that, for Lebesgue-almost all A, the random vector x can be recovered with zero error probability provided that n > K(x), where K(x) is given by the infimum of the lower modified Minkowski dimension over all support sets U of x (i.e., sets U ⊆ Rmwith P[x ∈ U] = 1). We then particularize this achievability result to the class of s-rectifiable random vectors as introduced in Koliander et al. (2016); these are random vectors of absolutely continuous distribution-with respect to the s-dimensional Hausdorff measure-supported on countable unions of s-dimensional C1-submanifolds of Rm. Countable unions of C1-submanifolds include essentially all signal models used in the compressed sensing literature such as the standard union of subspaces model underlying much of compressed sensing theory and spectrum-blind sampling, smooth submanifolds, block-sparsity, and low-rank matrices as considered in the matrix completion problem. Specifically, we prove that, for Lebesgue-almost all A, s-rectifiable random vectors x can be recovered with zero error probability from n > s linear measurements. This threshold is, however, found not to be tight as exemplified by the construction of an s-rectifiable random vector that can be recovered with zero error probability from n <; s linear measurements. Motivated by this observation, we introduce the new class of s-analytic random vectors, which admit a strong converse in the sense of n ≥ s being necessary for recovery with probability of error smaller than one. The central conceptual tools in the development of our theory are geometric measure theory and the theory of real analytic functions.

This work aims to describe the characteristics and the status of development, including the results of a first preliminary testing campaign, of a low frequency airborne imaging radar developed in Italy for the Italian Space Agency.

We establish the fundamental limits of lossless linear analog compression by considering the recovery of random vectors x ∈ ℝmfrom the noiseless linear measurements y = Ax with measurement matrix A ∈ ℝn×m. Specifically, for a random vector x ∈ ℝmof arbitrary distribution we show that x can be recovered with zero error probability from n > inf dimMB(U) linear measurements, where dimMB(·) denotes the lower modified Minkowski dimension and the infimum is over all sets U ⊆ ℝmwith P[x ∈ U] = 1. This achievability statement holds for Lebesgue almost all measurement matrices A. We then show that s-rectifiable random vectors-a stochastic generalization of s-sparse vectors-can be recovered with zero error probability from n > s linear measurements. From classical compressed sensing theory we would expect n ≥ s to be necessary for successful recovery of x. Surprisingly, certain classes of s-rectifiable random vectors can be recovered from fewer than s measurements. Imposing an additional regularity condition on the distribution of s-rectifiable random vectors x, we do get the expected converse result of s measurements being necessary. The resulting class of random vectors appears to be new and will be referred to as s-analytic random vectors.

This paper presents the Radar for Icy Moon Exploration (RIME) that is a fundamental payload in the Jupiter Icy Moon Explorer (JUICE) mission of the European Space Agency (ESA). RIME is a radar sounder aimed to study the subsurface of Jupiter's icy moons Ganymede, Europa and Callisto. The paper illustrates the main goals of RIME, its architecture and parameters and some recent advances in its design.

This letter deals with the design, realization, and validation of a multimode/multifrequency airborne radar designed for both surface and subsurface prospections. The system operates in the frequency band from very high frequency (VHF) to ultrahigh frequency (UHF) and works in two different modes: 1) a nadir-looking sounder in the VHF band (carrier frequency of 163 MHz); and 2) a side-looking imager (i.e., synthetic aperture radar) in the UHF band with two channels at 450 and 860 MHz, respectively. The system validation has been carried out for the “sounder” mode due to helicopter-borne surveys carried out over an area in the Campania region, Southern Italy. The surveys have provided a first proof of system capability in obtaining useful information about the surface and shallower subsurface layers over a large scale and in a relatively short time. In particular, the data collected by the sounder have been processed by means of a microwave tomographic reconstruction approach, and features consistent with tunnels buried at a depth of 15 m have been identified.

This paper presents the Radar for Icy Moons Exploration (RIME) instrument, which has been selected as payload for the JUpiter Icy moons Explorer (JUICE) mission. JUICE is the first Large-class mission chosen as part of the ESA's Cosmic Vision 2015-2025 programme, and is aimed to study Jupiter and to investigate the potentially habitable zones in the Galilean icy satellites. RIME is a radar sounder optimized for the penetration of Ganymede, Europa and Callisto up to a depth of 9 km in order to allow the study of the subsurface geology and geophysics of the icy moons and detect possible subsurface water. In this paper we present the main science goals of RIME, the main technical challenges for its development and for its operations, as well as the expected scientific returns.

A key aspect of a previously proposed undersampled digitally heterodyned stepped frequency GPR is the capability to generate and acquire a large band of frequencies. This is obtained by moving most of the analog domain functionalities of the SFGPR into the digital one. The necessity to generate a large bandwidth is to achieve high resolution. In this paper a procedure faster than the "brute force" one presented in [1] allows to choose and to analyze the best set of values of the parameters characterizing the SFGPR. The analysis was performed with the aid of different software tools developed ad hoc in a high level language. The key aspects of the analysis and its main results are discussed and illustrated.

This paper provides an overview of the Europa Jupiter System Mission (EJSM) and of its scientific objectives, focusing the attention on the subsurface radar (SSR) instrument included in the model payload of the Jupiter Ganymede Orbiter (JGO). The SSR instrument is a radar sounder system at low frequency (HF/VHF band) designed to penetrate the surface of Ganymede icy moon of Jupiter for performing a subsurface analysis with a relatively high range resolution. This active instrument is aimed at acquiring information on the Ganymede (and partially on the Callisto during flybys) shallow subsurface. The paper addresses the main issues related to SSR, presenting its scientific goals, describing the concept and the design procedure of the instrument, and illustrating the signal processing techniques. Despite the fact that SSR can be defined on the basis of the heritage of the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) and SHAllow RADar (SHARAD) instruments currently operating at Mars, the EJSM mission poses additional scientific and technical challenges for its design: 1) the presence of a relevant Jupiter radio emission (which is very critical because it has a significant power spectral density in proximity of the expected SSR central frequency); 2) the properties of the subsurface targets, which are different from those of the Mars subsurface; 3) the different orbit conditions; and 4) the limited available resources (in terms of mass, power, and downlink data rate). These challenges are analyzed and discussed in relation to the design of the instrument in terms of: 1) choice of the central frequency and the bandwidth; 2) signal-to-noise ratio (SNR); 3) signal-to-clutter ratio (SCR); and 4) definition of the synthetic aperture processing. Finally, the procedure defined for SSR performance assessment is described and illustrated with some numerical examples.

The radar altimeter of the Cassini mission to Titan operates in a transition region between pulse- and beam-limited conditions. Due to the specific observation geometry, low values of mispointing angle have been found to significantly affect altimeter impulse response (IR). This involves a nonconventional formulation of the system response which is the main goal of this paper. An analytical model of the average return power waveform, valid for near-nadir altimetry measurements, has been developed in order to cope with the particular operating conditions of Cassini mission. The model used to approximate the altimeter waveform is based on the same general assumptions of the classical Brown's model (1977) but exploits a flat surface response approximation by Prony's methods. Both theoretical considerations and simulated data have been taken into account to support the accuracy of the proposed model. To infer the main geophysical parameters describing surface topography from altimetry data, a parametric estimation procedure has been used. The maximum likelihood estimator procedure has been chosen since, in principle, it can assure optimal performance as a consequence of the analytical model we used to describe the system IR. Performances of the implemented method have been numerically evaluated through simulation of data received by CASSINI in high-resolution altimeter mode.

MARSIS (Mars advanced Radar for subsurface and ionosphere sounding) is a low frequency nadir looking sounding radar selected by ESA as a payload of the Mars Express mission, whose primary Scientific Objective is to map the distribution of water both solid and liquid, at global scale on the Martin crust. MARSIS is the first instrument to be able to detect what lies beneath the surface of Mars (up to about 5 km). MARSIS operates with a very high fractional bandwidth: 1 MHz bandwidth allows a vertical resolution of 150 m in vacuum which corresponds to 50-100 m in the subsurface, depending on the electromagnetic wave propagation speed in the crust. The center frequency of the pulses transmitted by MARSIS can be set to 1.8 MHz, 3 MHz, 4 MHz and 5 MHz. On day side operations, it operates only in 4 MHz and 5 MHz due to the ionosphere plasma frequencies of Mars cutting of all frequencies lower than 3 MHz. All the four carrier frequencies are available for subsurface sounding on night side. The Mars Shallow Radar Sounder (SHARAD), a facility instrument provided by the Italian Space Agency (ASI), is embarked on board the NASA Mars Reconnaissance Orbiter spacecraft. SHARAD began science operations on October 3rd 2006 : it has been collected data from surface and subsurface. This instrument penetrates to roughly half a kilometer below Mars' to search for information about underground layers of ice, rock and, perhaps, melted water. SHARAD operates with a center frequency of 20 MHz and 10 MHz bandwidth. These parameters allow vertical resolution on the order of 10-20 m. The carrier frequency of 20 MHz guarantees the capability of SHARAD to operate in day side as well as in night side. Both MARSIS and SHARAD use the principle of a Synthetic Aperture Radar (SAR) to achieve a fine along-track resolution. In particular,MARSIS is an un-focused SAR with best along-track resolution of 2 km; data coming from SHARAD can be processed with focusing algorithm (Chirp Scaling Algorithm), rising a best horizontal resolution of 300 m. This paper provides a comparison between MARSIS and SHARAD images in different zones of the Mars' surface. From the preliminary analysis it has been evident that MARSIS detects signals from subsurface interfaces at 3 km of depth, while the signals received by SHARAD in the same zone and at the same depth are much weaker compared with the background noise. However,SHARAD radar-grams show subsurface interfaces at 100-200 m of depth: these interesting targets can not be discriminated by MARSIS because of its coarse vertical resolution. At the same time,SHARAD data add to MARSIS data scientific information about the upper portions of the crust of Mars.

In the frame of the study "Innovative radar altimeter concepts", founded by the European Space Agency (ESA), the authors analyzed potential advanced measurement concepts for radar altimeters of future generation, studied the feasibility of the identified techniques and proposed a design for an instrument based on the most promising system concept. This paper summarizes the major results of the study.

This paper summarizes scientific rationale and technical approach for a bistatic synthetic aperture radar (SAR) mission (BISSAT). The study has been funded by the Italian Space Agency for a competitive Phase-A study along with other five missions. Its concept consists in flying a passive SAR on board a small satellite, which observes the area illuminated by an active SAR, operating on an already existing large platform.

The authors have augmented the NASA DC-8 AIRSAR instrument with a pair of C-band antennas displaced across track to form an interferometer sensitive to topographic variations of the Earth's surface. During the 1991 DC-8 flight campaign, data were acquired over several sites in the US and Europe, and topographic maps were produced from several of these flight lines. Analysis of the results indicate that statistical errors are in the 2-4-m range, while systematic effects due to aircraft motion are in the 10-20-m range. The initial results from development of a second-generation processor show that aircraft motion compensation algorithms reduce the systematic variations to 2 m, while the statistical errors are reduced to 2-3 m.>