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Objectives: Synthetic aperture sonar (SAS) is one kind of high resolution underwater imaging sonar. Its principle is to use small array to simulate large aperture array by uniforming linear motion along the direction of flight track, and realize coherent processing of echo signal to obtain high resolution two-dimensional sonar image, which is independent of imaging distance and acoustic wavelength. The back projection algorithm is an accurate point-by-point imaging algorithm, which is characterized by accurate focusing ability, suitable for wide beam and large scene imaging, and easy to realize motion compensation, but it has the disadvantages of low computational efficiency. In recent years, with the development of computer technology, especially the appearance of graphics processor unit, it has powerful computing power and provides a new way to accelerate the back projection algorithm. Methods: We propose a fast accurate back projection algorithm for multi-receiver SAS in heterogeneous environment. On the basis of analyzing the principle of accurate back-projection imaging algorithm, the pulse compression and time-consuming azi-muth accumulation are transformed into a single instruction multi-threaded mode, and the imaging process is accelerated by the powerful multi-core computing ability of graphics processor unit. Results: The validity and efficiency of the proposed fast imaging algorithm are verified by the imaging experiments performed on simulated and real SAS data. Compared with the serial imaging algorithm, its acceleration ratio is as high as 326.3 and 333.6. For large-scale data imaging processing, it shows excellent acceleration performance. Conclusions: The proposed back projection imaging algorithm greatly improves the imaging efficiency and meets the needs of real-time SAS imaging, which lays the foundation for subsequent motion compensation. [ABSTRACT FROM AUTHOR]

Objectives：Traditional echo simulator of synthetic aperture sonar (SAS) is based on the assumption that transmitter and receiver beam patterns are rectangle within mainlobe, which is determined by 3 dB beamwidth of beam pattern. This neglects the echo signal outside the mainlobe. Besides, the modulation of transmitter and receiver beam patterns is not considered. Methods：Depending on the instantaneous geometry relationship among transmitter, receiver and target, the echo simulation of SAS considering the modulation of transmitter and receiver beam patterns is carried out. Then, the influence of transmitter and receiver beam patterns on SAS imaging is discussed by the back projection algorithm. Results and Conslusions: Traditional array signal processing based on weighting is further conducted to show the influence of transmitter and receiver beam patterns on imaging results. The results are useful for the suppression of spectrum alias in the azimuth direction. Moreover, they are also helpful for the simulation verification and analysis of performance parameters of designed SAS systems. [ABSTRACT FROM AUTHOR]

This paper proposed an efficient range Doppler imaging algorithm for multi-array synthetic aperture sonar (SAS) in shared memory environment based on OpenMP, which solved the imaging problem of low efficiency by multi-core CPU resources. Considered the parallel characteristic of range Doppler algorithm for multi-array SAS, it parallelized the signal processing process such as preprocessing, range compression, phase compensation, range cell migration compensation and azimuth compression based on OpenMP, which greatly enhanced the reconstruction process of SAS image by multi-core CPU resources. The imaging test performed on real data shows that the speedup of the parallel imaging algorithm is up to 19. 86 times, which meets the demand for real-time processing of SAS imaging. [ABSTRACT FROM AUTHOR]

Aiming to solve the low efficiency imaging of multi-array synthetic aperture sonar, this paper proposed a fast imaging method for multi-array synthetic aperture sonar in heterogeneous environment. It considered the range Doppler algorithm characteristic for multi-array synthetic aperture sonar and different calculation features between CPU and GPU, the intensive calculation such as range compression, phase compensation, range cell migration compensation and azimuth compression was implemented on GPU, which greatly enhanced the imaging efficiency for multi-array synthetic aperture sonar. In the end, it verifies the validity and efficiency of the proposed method through the imaging experiment performed on real data and the speedup is up to 14.45 times compared to the serial algorithm. [ABSTRACT FROM AUTHOR]

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]