On the use of joint time-frequency representations in SAR signal processing

The aim of this paper is to show that some of the open problems in Synthetic Aperture Radar signal processing can be seen in a new and advantageous perspective if the received signals are represented in the time-frequency domain. The joint time-frequency representation makes easier the extraction of the information necessary for the formation of the synthetic aperture, responsible for the high cross-range resolution. The proposed approach is applied to the imaging of moving objects and to the focusing of extended scenes, in presence of instabilities of the radar platform such that the conventional estimation techniques become insufficient. In particular, the time-frequency analysis allows the estimation of the useful signal parameters even in case of undersampling. This allows the use of relatively low Pulse Repetition Frequencies (PRF), avoiding then the shortcomings due to high PRFs, like the reduction of the sizes of the monitorable areas or the data rate increase.

[1]  Patrick Flandrin,et al.  A time-frequency formulation of optimum detection , 1988, IEEE Trans. Acoust. Speech Signal Process..

[2]  Leon Cohen,et al.  Instantaneous bandwidth for signals and spectrogram , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[3]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[4]  Boualem Boashash,et al.  A methodology for detection and classification of some underwater acoustic signals using time-frequency analysis techniques , 1990, IEEE Trans. Acoust. Speech Signal Process..

[5]  B. V. K. Vijaya Kumar,et al.  Performance Of Wigner Distribution Function Based Detection Methods , 1984 .

[6]  S. Barbarossa Detection and imaging of moving objects with synthetic aperture radar , 1992 .

[7]  John Kirk,et al.  Motion Compensation for Synthetic Aperture Radar , 1975, IEEE Transactions on Aerospace and Electronic Systems.

[8]  S.A.S. Werness,et al.  Moving target imaging algorithm for SAR data , 1990 .

[9]  Sergio Barbarossa Parameter estimation of undersampled signals by Wigner-Ville analysis , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[10]  Sergio Barbarossa,et al.  A novel procedure for detecting and focusing moving objects with SAR based on the Wigner-Ville distribution , 1990, IEEE International Conference on Radar.

[11]  Sergio Barbarossa New autofocusing technique for SAR images based on the Wigner-ville distribution , 1990 .

[12]  Sergio Barbarossa,et al.  Detection and imaging of moving objects with synthetic aperture radar. Part 2: Joint time-frequency analysis by Wigner-Ville distribution , 1992 .