Marco Martorella

High-resolution ISAR imaging of maneuvering targets by means of the range instantaneous Doppler technique: modeling and performance analysis

Very high resolution inverse synthetic aperture radar (ISAR) imaging of maneuvering targets is a complicated task. In fact, the conventional range Doppler (RD) ISAR technique does not work properly when target motions generate terms higher than the first order in the phase of the received signal relative to each scatterer. This effect typically happens when at least one of these situations occur: (1) very high resolution images are required; (2) the target maneuvers; and (3) the target undergoes significant angular motions (roll, pitch, and yaw). A novel ISAR technique, named range instantaneous Doppler (RID), has been proposed for the reconstruction of very high resolution images of maneuvering targets. In this paper, we analytically show that the RID technique works properly when high-resolution ISAR images are required of maneuvering and/or rolling, pitching, and yawing targets; we also quantify the performance improvement of the RID technique with respect to the RD technique. The problem is tackled from an analytical point of view. First, we define a new model of the ISAR received signal that is valid for maneuvering targets, then we derive and compare the analytical expression of the point spread function (PSF) for the two techniques. Furthermore, we perform a statistical analysis to evaluate the improvement of the RID technique versus the RD technique in terms of spatial resolution. Finally, we prove the effectiveness of the RID technique by simulating the imaging process for two different targets: (1) a ship that undergoes roll, pitch and yaw motions and (2) a fast maneuvering airplane.

Novel approach for ISAR image cross-range scaling

Inverse synthetic aperture radar (ISAR) imaging systems produce electromagnetic images of targets in the range-Doppler domain. In order to rescale the image in a homogeneous range-cross range domain (meters by meters), the modulus of the target effective rotation vector must be known. Although in some cases it can be retrieved by means of ancillary data, in most cases the modulus of the target effective rotation vector must be estimated. A blind technique is proposed for estimating the modulus of the target effective rotation vector that exploits information carried by the chirp rate of scattering centres. A technique based on image segmentation, local polynomial Fourier transform (LPFT), and image contrast (IC) maximisation is used in order to extract the scattering centres and estimate their chirp rate. Simulated and real data analyses are provided to confirm the effectiveness of the proposed algorithm.

On Bistatic Inverse Synthetic Aperture Radar

The use of multiple radar configurations can overcome some of the geometrical limitations that exist when obtaining radar images of a target using inverse synthetic aperture radar (ISAR) techniques. It is shown here how a particular bistatic configuration can produce three view angles and three ISAR images simultaneously. A new ISAR signal model is proposed and the applicability of employing existing monostatic ISAR techniques to bistatic configurations is analytically demonstrated. An analysis of the distortion introduced by the bistatic geometry to the ISAR image point spread function (PSF) is then carried out and the limits of the applicability of ISAR techniques (without the introduction of additional signal processing) are found and discussed. Simulations and proof of concept experimental data are also provided that support the theory.

Statistical CLEAN Technique for ISAR Imaging

Inverse synthetic aperture radar (ISAR) images are frequently used in target classification and recognition applications. Some classifiers often require features that can be more easily obtained by extracting scattering centers from ISAR data rather than by reconstructing ISAR images. An available method for scattering center extraction, namely, the CLEAN technique, was proposed in a recent paper by Yang et al. In this paper, an improvement of this CLEAN technique is proposed that introduces a new method for detecting scattering centers. The proposed technique is based on a Gaussianity test, and its effectiveness is first theoretically proven and then tested on real data. Moreover, a comparison with the technique proposed by Yang et al. is shown.

Time windowing for highly focused ISAR image reconstruction

In several applications long recorded live inverse synthetic aperture radar (ISAR) data are used to obtain one or more ISAR images. In order to reconstruct a well-focused ISAR image, a suitable selection of the echoes to be coherently processed must be provided. Such a selection can be made by defining a time window. We propose a technique for the automatic selection of the position and length of the time window that provides the ISAR image with the highest focus. The technique, namely the maximum contrast based automatic time window selection (MC-ATWS), is based on the definition of image contrast (IC). Due to the fact that the IC is a measure of the image focus, the time window is selected by maximizing the IC. The technique effectiveness is tested by using simulated and real data.

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.

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.

Target Recognition by Means of Polarimetric ISAR Images

Automatic target recognition (ATR) is generally the reason why inverse synthetic aperture radar (ISAR) imaging systems are employed. Moreover, the use of fully polarimetric radar systems in radar imaging applications such as SAR and ISAR has enhanced both image quality and classification capabilities. The authors propose a novel technique for ATR using polarimetric ISAR (Pol-ISAR) images. The proposed method is based on a model matching approach. Results are obtained that show the effectiveness of such a technique.

On the fractal dimension of sea surface backscattered signal at low grazing angle

Fractal analysis of sea surface backscattering signal (sea clutter in radar terminology) represents a novel technique for the study of sea surface roughness. When Kirchhoffs assumption is satisfied, the fractal dimension of the signal is linearly related to the fractal dimension of the sea surface. Moreover, such a relationship is independent of transmitted frequency, polarization, time, space, sea wave propagation direction, incident angle (within the constraint of Kirchoffs assumption) and significant wave height. Nevertheless, for a low grazing angle, the Kirchhoff approximation does not hold and the behavior of the sea clutter fractal dimension cannot be theoretically predicted. The purpose of this paper is to investigate the fractal dimension of the sea clutter at low grazing angle, in order to extend the theoretical results. Moreover, the effects of the presence of a target on the sea surface are analyzed by means of the fractal dimension. Such an analysis is performed by using live recorded clutter data. In detail, the fractal dimensions dependence on space, time, sea wave propagation direction, sea wave height, transmitted polarization and presence of targets is investigated. A discussion on the use of the sea clutter fractal dimension for sea surface monitoring is addressed.

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.