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A time-variant curve (TVC) model-based automatic equalization method is proposed for the intensity variation problem of synthetic aperture sonar (SAS) images. A theoretical expression of TVC is deduced based on sound transmission model, underwater backscattering strength model and SAS image model. A method to calculate the TVC observations is established based on the statistical model of SAS images. An estimation method based on non-linear least square fitting model (NL-LSFM) is used to acquire the optimized parameter of TVC. At last, the SAS images are automatically equalized and enhanced based on the optimized TVC. The method proposed has been validated by lake and sea trials. The test results show that the result calculated by the TVC expression is consistent with the experimental data, and the automatic equalization method can remove the intensity variation of SAS images properly. [ABSTRACT FROM AUTHOR]

Drew lesson from the synthetic aperture radar, and made the further processing to the fictitious wave-field data, that was correlation and synthesizing processing. Specifically, developed the traditional mode of processing that mainly based on profiles into a new method,in which, several apertures synthesis with the measure point as the center, lapse point-by-point, finally, multiple coverage was adopted. In hopes to improves the signal-to-noise ratio, highlight the abnormal, improves the resolution and increases the exploration depth. Through the processing of theoretical model data, verified the effectiveness of this method. The different theoretical model processing suggests that related to enhanced synthesis of useful signal, to improve the signal to noise ratio, resolution enhancement effect. The feasibility and validity of synthetic aperture of transient electromagnetic imaging numerical calculation was demonstrated. [ABSTRACT FROM AUTHOR]