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An image contrast based algorithm for 2-D ISAR image autofocusing is proposed. The problem of ISAR image autofocusing is formulated analytically by defining geometry and dynamics of the radar-target system and by assuming a mathematical model for the received signal. The image focusing is then achieved by estimating the model parameters through the maximisation of the image contrast. The problem of the maximum search is solved numerically by means of an iterative search method. An algorithm able to produce an accurate initial guess is also developed by using the radon transform. The good accuracy of the initial guess guarantees the convergence of the optimisation problem solution to the global maximum. The performance of the proposed autofocusing technique is tested by comparing it to the point prominent processing (PPP) algorithm, the phase gradient algorithm (PGA) and the image entropy based technique (IEBT), through the use of real data. Results confirm the effectiveness of the proposed algorithm. 2 Mathematical aspects of signal modelling and ISAR processing Let the system geometry be represented by Fig. 1 where the radar is located at ð0; 0; h r Þ in the system of coordinates

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.

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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

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Passive bistatic radar or passive coherent location is gaining interest in the radar community, as it provides some advantages with respect to active radar. Passive radar does not aim to replace active radar; it provides a good complement to it. The computational effort that is required to implement the required signal processing is one of the drawbacks that affect passive radars. In this paper, a suboptimal but computationally affordable detection algorithm is investigated that is applicable to arbitrary waveforms (different types of illuminators of opportunity). First, a detailed mathematical formulation of the proposed suboptimum algorithm is derived. A theoretical performance analysis is then provided based on a comparison of the proposed with the optimum two-dimensional matched filter. Finally, simulated and real data are used to demonstrate the effectiveness of the proposed algorithm and to validate the theoretical performance analysis.

Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. However, television broadcast-transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating Manuscript lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.