Amerigo Capria

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.

A Contrast-Based Algorithm For Synthetic Range-Profile Motion Compensation

In stepped-frequency radar, target motions produce range-profile distortions. Range shift, signal-to-noise ratio loss, and symmetric spreading are produced by target radial velocity, whereas target radial acceleration is mainly responsible for asymmetric smearing. Acceleration-distortion effects are usually negligible when a high Pulse Repetition Frequency (PRF) is used, although this is not the case for low-PRF radars. In this paper, a new motion-compensation technique based on contrast optimization is proposed. The innovative contributions of this paper are as follows: (1) A theoretical analysis of the distortions produced by target motions on the reconstruction of synthetic aperture radar is provided; (2) the proposed technique compensates both phase terms, which are due to target radial velocity and acceleration; therefore, synthetic range profiles can be focused by processing low-PRF radar returns; (3) a new cost function for the synthetic range profiles (namely, contrast) is defined and used for motion compensation; (4) the proposed technique can be applied to any kind of stepped-frequency waveforms; and (5) an estimation error analysis is performed, first theoretically and then by means of both simulations and real data.

Passive ISAR With DVB-T Signals

As recently demonstrated, passive radars are able to detect and track targets by exploiting illuminators of opportunity. In this paper, it will be proven that the same concept can be extended to passive inverse synthetic aperture radar (P-ISAR) imaging. A suitable type of signal processing is proposed that is able to form P-ISAR images starting from range-Doppler maps, which represent the output of passive-radar signal processing. Multiple-channel digital television broadcasting (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, which are generated by the DVB-T signal, is also addressed and solved.

Automatic Target Recognition by Means of Polarimetric ISAR Images and Neural Networks

Inverse synthetic aperture radar (ISAR) images are often used for classifying and recognizing targets. Moreover, the use of fully polarimetric ISAR (Pol-ISAR) images enhances classification capabilities. In this paper, the authors propose a novel automatic target recognition (ATR) technique based on the use of fully Pol-ISAR images and neural networks (NNs). In order to reduce the amount of data processed by the classifier, the brightest scattering centers are first extracted by means of the Pol-CLEAN technique, and then, their scattering matrices are decomposed using Camerons decomposition. A classifier based on the use of multilayer perceptron NN that makes use of the features extracted from the Pol-ISAR images is then implemented. A proof-of-concept test is performed on real data acquired during a controlled experiment in an anechoic chamber.

Polarimetrically-Persistent-Scatterer-Based Automatic Target Recognition

Reliable automatic target recognition (ATR) systems based on inverse synthetic aperture radar (ISAR) images require a robust feature selection. An ATR system based on polarimetric ISAR images has been recently proposed that extracts bright scatterers and uses their polarimetric signatures to define classification features. Since bright scatterers could be the results of multiple scattering, the concept of polarimetrically persistent scatterers (PPSs) has been introduced in a recent work. PPS is usually associated with single scattering mechanism and, therefore, may prove to be more robust for classification purposes. In this paper, an ATR system is defined that makes use of PPS. Furthermore, a detailed analysis is carried out to emphasize the meaning of PPSs when used for ATR.

Contrast-Optimization-Based Range-Profile Autofocus for Polarimetric Stepped-Frequency Radar

One of the main benefits brought by the use of fully polarimetric radars is the ability to identify scattering mechanisms, which are related to the target physical properties. One of the most critical problems in synthetic range-profile reconstruction is the distortion induced by the target motion. Radial target velocity and acceleration generate second- and third-order phase terms in the received signal, which produce range shift and point-spread-function smearing. The distortions induced by the target motion produce, as a consequence, a signal-to-noise ratio loss. Recently, a method based on contrast maximization has been proposed in order to compensate target radial motions using single-polarization data. In this paper, an extension of such an algorithm is proposed that exploits fully polarimetric data in order to improve the target radial motion compensation.

Passive Bistatic Radar (PBR) for harbour protection applications

In this paper we investigate the feasibility of using Passive Bistatic Radar, PBR, to provide security for a harbour area. There have been numerous publications on the suitability of passive radar for air surveillance applications. However, this paper focuses predominantly on maritime applications. We investigate the ability of passive radar to detect, track, and eventually manage, marine vessels (boats). The paper includes a case-study of the Livorno Harbour in Italy. Livorno has been chosen as it represents a busy maritime hub. Simulations are provided to determine the theoretical radar performance, which are then compared with experimental results from a DVB-T-based passive radar. It will be shown that passive radars represent a viable solution for harbour protection applications.

DVB-T passive radar for vehicles detection in urban environment

Passive radar systems exploit non-cooperative transmitter to detect targets in areas of interest. Some of the main advantages of such systems with respect to conventional radars include low cost architectures, low energy requirements and potentially null probability of intercept. In this paper a low-cost solution for vehicles detection making use of passive radar concept is presented. A Software Defined Radio (SDR) solution and commercial antennas have been used to realize a DVB-T passive radar demonstrator. An analysis of the DVB-T signal is firstly presented together with a study of its capability as radar waveform. Afterwards an experimental setup is presented and analysed and finally some results of targets detection are shown.

A FARIMA based analysis for wind falls and oil slicks discrimination in sea SAR imagery

The aim of this paper is to define an analysis technique, which uses the fractionally integrated autoregressive-moving average (FARIMA) model, for discriminating wind falls from oil slick areas in sea SAR imagery. The method deals with the estimation of the fractional differencing and ARMA parameters for the sea SAR images mean radial PSD and is applied to some ERS-1 and ERS-2 images of the Mediterranean sea, North sea and Atlantic (Galicia) ocean containing only oil slick or only wind falls, or wind falls and oil slick anomalies

Spatial Adaptive Processing for Passive Bistatic Radar

This paper presents work done on the application of Spatial Adaptive Processing (SAP) to Passive Bistatic Radar (PBR) systems. Specifically, the main goal is to analyse SAP performances in terms of interference spatial filtering and the estimation of the targets Direction of Arrival (DoA) when using PBR systems. Multiple solutions are provided and compared in order to identify the best multichannel processing architecture. Results are shown by using real multichannel PBR data.