Passive RF Tomography: Signal Processing and Experimental Validation

Radio frequency (RF) tomography is an imaging technique based upon a set of distributed transmitters and receivers surrounding the area under observation. This method requires prior knowledge of the transmitters\u27 and receivers\u27 locations. In some circumstances the transmitters may be uncooperative, while in other cases extrinsic emitters may be used as source of opportunity. In these scenarios, RF tomography should operate in a passive modality. A previous work postulated the principles and feasibility of passive RF tomography. This research further develops the underlying theory through concise and ad-hoc signal processing. Experimental verification and validation corroborate the effectiveness of passive RF tomography for object detection and imaging

Bistatic SAR along track interferometry with multiple fixed receivers

This paper presents an along-track interferometry (ATI)study for a bistatic or multiestatic SAR configuration with fixed ground receivers. This technique can be useful for sea current estimation or for any problem of Ground Motion Target Indicator (GMTI). The proximity of the ground receivers to the scene allows to be very sensitivite to velocities with small baselines. This paper also proposes a multibaseline approach for ATI able to diferenciate among different velocity contributions in the same resolution cell. At the end of this paper, some results over real acquired bistatic data will be presented and discussed. The data have been acquired using the C-band SAR Bistatic Receiver for INterferometric Applications (SABRINA) and ESA’s ENVISAT satellite, as a transmitter of opportunity.Peer ReviewedPostprint (published version

Cooperative Coherent Multistatic Imaging and Phase Synchronization in Networked Sensing

Coherent multistatic radio imaging represents a pivotal opportunity for forthcoming wireless networks, which involves distributed nodes cooperating to achieve accurate sensing resolution and robustness. This paper delves into cooperative coherent imaging for vehicular radar networks. Herein, multiple radar-equipped vehicles cooperate to improve collective sensing capabilities and address the fundamental issue of distinguishing weak targets in close proximity to strong ones, a critical challenge for vulnerable road users protection. We prove the significant benefits of cooperative coherent imaging in the considered automotive scenario in terms of both probability of correct detection, evaluated considering several system parameters, as well as resolution capabilities, showcased by a dedicated experimental campaign wherein the collaboration between two vehicles enables the detection of the legs of a pedestrian close to a parked car. Moreover, as \textit{coherent} processing of several sensors' data requires very tight accuracy on clock synchronization and sensor's positioning -- referred to as \textit{phase synchronization} -- (such that to predict sensor-target distances up to a fraction of the carrier wavelength), we present a general three-step cooperative multistatic phase synchronization procedure, detailing the required information exchange among vehicles in the specific automotive radar context and assessing its feasibility and performance by hybrid Cram\'er-Rao bound.Comment: 13 page

Implementation and Performance of Factorized Backprojection on Low-cost Commercial-Off-The-Shelf Hardware

Traditional Synthetic Aperture Radar (SAR) systems are large, complex, and expensive platforms that require significant resources to operate. The size and cost of the platforms limits the potential uses of SAR to strategic level intelligence gathering or large budget research efforts. The purpose of this thesis is to implement the factorized backprojection SAR image processing algorithm in the C++ programming language and test the code\u27s performance on a low cost, low size, weight, and power (SWAP) computer: a Raspberry Pi Model B. For a comparison of performance, a baseline implementation of filtered backprojection is adapted to C++ from pre-existing MATLAB® code. The factorized backprojection algorithm shows a computational improvement factor of 2-3 compared to filtered backprojection. Execution on a single Raspberry Pi is too slow for real-time imaging. However, factorized backprojection is easily parallelized, and we include a discussion of parallel implementation across multiple Pis

Passive Multistatic Radar Imaging using an OFDM based Signal of Opportunity

This paper demonstrates a proof of concept in using an OFDM-based signal of opportunity for SAR imaging purposes within a passive, multistatic radar construct. Two signal processing methods have been proposed to create phase history data. The same methods are applied in both a simulated software model and an experimental data collection environment to produce simulated SAR images using the CBP imaging algorithm. The images generated from both the experimental and simulated data were observed to be consistent with each other and with expectations in terms of resolution. Coherent addition of the images results in improved image resolution due to the geometric and frequency diversity of the multistatic scenario compared to the individual bistatic pairs

Multistatic and Multiple Frequency Imaging Resolution Analysis-Application to GPS-Based Multistatic Radar

International audienceThis paper focuses on the computation of the generalized ambiguity function (GAF) of a multiple antennas multiple frequencies radar system (MAMF). This study provides some insights into the definition of resolution parameters of a MAMF radar system. It turns out that the range and azimuth resolutions are not the most suitable criteria to specify the MAMF radar resolution. Therefore a new set of resolution parameters is introduced like the resolution ellipse which expresses the resolution anywhere in the image plane or δ→max, (δ→min) which expresses the highest (lowest) bound of the spatial radar resolution. To point out the pertinence of our study, we illustrate it with a MAMF radar system built around GPS satellites. The effect of the radar system geometry on resolution is investigated. For several scenarios, the GAF and its numerical form, the point spread function (PSF), are computed and their results are compared

DISCUS - The Deep Interior Scanning CubeSat mission to a rubble pile near-Earth asteroid

We have performed an initial stage conceptual design study for the Deep Interior Scanning CubeSat (DISCUS), a tandem 6U CubeSat carrying a bistatic radar as main payload. DISCUS will be operated either as an independent mission or accompanying a larger one. It is designed to determine the internal macroporosity of a 260-600 m diameter Near Earth Asteroid (NEA) from a few kilometers distance. The main goal will be to achieve a global penetration with a low-frequency signal as well as to analyze the scattering strength for various different penetration depths and measurement positions. Moreover, the measurements will be inverted through a computed radar tomography (CRT) approach. The scientific data provided by DISCUS would bring more knowledge of the internal configuration of rubble pile asteroids and their collisional evolution in the Solar System. It would also advance the design of future asteroid deflection concepts. We aim at a single-unit (1U) radar design equipped with a half-wavelength dipole antenna. The radar will utilize a stepped-frequency modulation technique the baseline of which was developed for ESA's technology projects GINGER and PIRA. The radar measurements will be used for CRT and shape reconstruction. The CubeSat will also be equipped with an optical camera system and laser altimeter to sup- port navigation and shape reconstruction. We provide the details of the measurement methods to be applied along with the requirements derived of the known characteristics of rubble pile asteroids.Comment: Submitted to Advances in Space Researc

GNSS Reflectometry and Remote Sensing: New Objectives and Results

The Global Navigation Satellite System (GNSS) has been a very powerful and important contributor to all scientific questions related to precise positioning on Earth's surface, particularly as a mature technique in geodesy and geosciences. With the development of GNSS as a satellite microwave (L-band) technique, more and wider applications and new potentials are explored and utilized. The versatile and available GNSS signals can image the Earth's surface environments as a new, highly precise, continuous, all-weather and near-real-time remote sensing tool. The refracted signals from GNSS Radio Occultation satellites together with ground GNSS observations can provide the high-resolution tropospheric water vapor, temperature and pressure, tropopause parameters and ionospheric total electron content (TEC) and electron density profile as well. The GNSS reflected signals from the ocean and land surface could determine the ocean height, wind speed and wind direction of ocean surface, soil moisture, ice and snow thickness. In this paper, GNSS remote sensing applications in the atmosphere, oceans, land and hydrology are presented as well as new objectives and results discussed.Comment: Advances in Space Research, 46(2), 111-117, 201