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.

A Contrast Maximization Based Technique for 2D ISAR Autofocusing

MARTORELLA, MARCO;BERIZZI, FABRIZIO;
2005

Abstract

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.
Martorella, Marco; Berizzi, Fabrizio; B., Haywood
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/202073
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