E. Dalle Mese

A survey on ISAR autofocusing techniques

Over many years of research, several ISAR autofocusing techniques have been proposed. Today, we can divide them into two main categories: parametric and non-parametric techniques. The prominent point processing and the phase gradient algorithm are two classical examples of non-parametric techniques, whereas the more recent image contrast and entropy based techniques represent a new generation of parametric techniques. In this paper, the advantages and disadvantages of each technique are highlighted and a performance analysis is carried out by means of ISAR image reconstruction of real data.

Performance analysis of a contrast-based ISAR autofocusing algorithm

The ISAR imaging technique is a well consolidated method for target image reconstruction. One of the main critical steps of the technique is motion compensation. This operation consists of removing from the received signal a phase term due to the translational motion of the target. As the target motion is not a priori known, motion parameters are typically estimated from the received data by means of autofocusing techniques. Different techniques are proposed in the literature. Their effectiveness is demonstrated by showing the results obtained by applying the algorithms to real and simulated data, without giving a quantitative analysis of their performance. The goal of this work is to analyze the performance of an image contrast-based ISAR autofocusing technique developed by the authors. The results are provided in terms of the statistics of the focusing parameter estimation errors.

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

Optimal Recursive Processing in Phase-Coded Waveform Radars

A recursive algorithm is proposed for target detection in pulse-compression radars. This method performs a least square estimate of the radar-channel impulse response, yielding range-sidelobe elimination The algorithm considered becomes particularly simple when pseudorandom binary sequences are employed. In such a case, the losses of signal-to-noise ratio, with respect to the matched filter, are evaluated and the performance degradations due to a Doppler residual, for an imperfect frequency tuning, are computed.

Improving the total rotation vector estimation via a bistatic isar system

In hybrid SAR/ISAR systems full knowledge of the radar-target geometry is often not available. In such cases, both the cross-range scaling factor and the image plane are not known a-priori and they have to be estimated in order to classify the target. The modulus of the effective rotation vector can be estimated from the data and cross-range scaling can be achieved. Nevertheless, the orientation of such a vector, which is orthogonal to the image plane, can only be estimated in particular cases and from a long sequence of images. In this paper a novel technique, based on the use of bistatic radar imaging systems, for estimating the total rotation vector is proposed.

Automatic Target Recognition of terrestrial vehicles based on polarimetric ISAR image and model matching

An Automatic Target Recognition (ATR) algorithm has recently been proposed that makes use of Polarimetric ISAR images and a Model Matching approach. In this paper, the authors propose a variation of such an approach that is suitable for ATR of terrestrial vehicles. The effectiveness of the proposed implementation is tested by means of real data acquired during a controlled turn-table experiment.

Plume effect on radar cross section of missiles at HF band

The radar cross section of missiles at HF band is affected by the presence of the missile plume. In fact, although the plume is transparent at microwave frequencies, it reflects almost the totality of the energy at the HF band. In this paper, we evaluate the effect of the missile plume on its radar cross section (RCS) at HF band. In order to achieve this goal we: (1) verify that the missile plume can be physically represented by a plasma through a chemical analysis of the combustion; (2) define the time-varying non-linear differential equation that rules the electron density equilibrium in the plume; (3) solve the time-varying non-linear differential equation in order to evaluate the length of the plume that contributes to the RCS calculation; (4) evaluate the RCS of the missile+plume by means of the method of moments (MoM). As a numerical case, the application of both a surface and sky wave over the horizon (OTH) radar has been considered. Specifically, the RCS (as a function of the incidence angle) of the missile during the boost phase trajectory has been evaluated.

Cognitive adaptive waveform technique for HF skywave radar

In High-Frequency (HF) Over The Horizon (OTH) radar, the space-time variation of the ionospheric channel, external noise as well as transmission channel limitations, is one of the most critical and challenging aspects of the system design and control. Waveforms parameters must be adaptively tuned to the actual external conditions. The purpose of this paper is to define and analyse a technique to set the waveform parameters in a cognitive way as a function of the operating conditions. Measurements of the external ionospheric channel and noise as well as a priori knowledge of the national frequency allocation plan will be the support of the waveform adaptive algorithm.

Isotropic and Anisotropic FEXP-Fractal Spectral Models for High Resolution Sea SAR Images

The aim of this paper is the definition of an anisotropic self-similar spectral model for high-resolution sea synthetic aperture radar (SAR) imagery. The assumption of spatial isotropy for sea SAR images is valid when the sea is calm, as the sea wave energy is spread in all directions and the SAR image PSD shows a circular symmetry. However, if the surface wind speed exceeds 7 m/s the anisotropy of sea SAR images starts to be perceptible. In this work we define an anisotropic spectral model by adding a 2-D isotropic fractionally exponential model (FEXP) to an anisotropic term defined starting from the fractal model of sea surface spectra. For this FEXP-Fractal (FEXPF) model we define a new class of spreading functions to characterize the anisotropic component. FEXPF models allow the spectra of sea SAR images to be simulated in different sea states and wind conditions - and with oil slicks -at low computational costs. FEXPF demonstrated reliable results when applied to European Remote Sensing (ERS) SAR Precision Images (PRI) of the Mediterranean Sea and the AtlanticOcean.

Radar imaging of noncooperating maneuvering aircraft

The problem of performing automatic high resolution radar imaging of noncooperating maneuvering aircraft is investigated. In order to define the main features of the radar processor, a numerical model of the system which makes use of an electromagnetic model of the moving aircraft so that the actual, complete operating conditions can be simulated has been developed. The availability of such a numerical tool avoids the need to carry out long and onerous experimental tests. In this framework an automatic high-resolution radar imaging technique has been developed. The imaging algorithm provides parameters useful for target classification.<<ETX>>