Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing

Image contrast maximization and entropy minimization are two commonly used techniques for ISAR image autofocusing. When the signal phase history due to the target radial motion has to be approximated with high order polynomial models, classic optimization techniques fail when attempting to either maximize the image contrast or minimize the image entropy. In this paper a solution of this problem is proposed by using genetic algorithms. The performances of the new algorithms that make use of genetic algorithms overcome the problem with previous implementations based on deterministic approaches. Tests on real data of airplanes and ships confirm the insight

Virtual multichannel SAR for ground moving target imaging

Slow moving ground targets are invisible within synthetic aperture radar (SAR) images since they appear defocused and their backscattered signal completely overlap the focused ground return. In order for this targets to be detected and refocused the availability of some spatial degrees of freedom is required. This allows for space/slow time processing to be applied to mitigate the ground clutter. However, multichannel SAR (M-SAR) systems are very expensive and the requirements in terms of baseline length can be very restrictive. In this study a processing scheme that exploits high PRF single channel SAR system to emulate a multichannel SAR is presented. The signal model for both target and clutter components are presented and the difference with respect to an actual M-SAR are highlighted. The effectiveness of the proposed processing is then demonstrated on simulated a measured dataset

Compressive sensing for interferometric inverse synthetic aperture radar applications

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

Image Based Robust Target Classification For Passive ISAR

This paper presents an automatic and robust, image feature-based target extraction, and classification method for multistatic passive inverse synthetic aperture radar range/cross-range images. The method can be used as a standalone solution or for augmenting classical signal processing approaches. By extracting textural, directional, and edge information as low-level features, a fused saliency map is calculated for the images and used for target detection. The proposed method uses the contour and the size of the detected targets for classification, is lightweight, fast, and easy to extend. The performance of the approach is compared with machine learning methods and extensively evaluated on real target images

A fully photonics-based coherent radar system

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

Distributed physical sensors network for the protection of critical infrastractures against physical attacks

The SCOUT project is based on the use of multiple innovative and low impact technologies for the protection of space control ground stations and the satellite links against physical and cyber-attacks, and for intelligent reconfiguration of the ground station network (including the ground node of the satellite link) in the case that one or more nodes fail. The SCOUT sub-system devoted to physical attacks protection, SENSNET, is presented. It is designed as a network of sensor networks that combines DAB and DVB-T based passive radar, noise radar, Ku-band radar, infrared cameras, and RFID technologies. The problem of data link architecture is addressed and the proposed solution described

4D quick Diff-Tomo analyses of short-term decorrelation of distributed scatterers

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

Realization of a flexible technological demonstrator for hf sky-wave data links

Radio frequency range between 3–30 MHz is called high frequency or shortwave radio. For a long time, the high frequency band has been considered as the most important means for communications over long distance. The advent of new technologies, such as satellite and terrestrial communications, made the high frequency systems obsolete. Despite that, a new interest for these systems is growing due to the need of having a relatively cheap and simple system for data and voice exchange, which could be a real alternative to existing system in case of their failure. This paper aims to present an effective and flexible HF digital transceiver demonstrator based on the software defined radio paradigma. The purpose of this demonstrator is to maintain the “essential” information among the authorities in case of the failure of both satellite and Internet communications for critical scenarios (e.g., terroristic attacks, natural disasters)