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In order to solve the unwrapping problem of low efficiency for large interferogram, we propose a new phase unwrapping algorithm in shared memory environment, which is designed based on quality-guided and minimum discontinuity optimization strategies. The three processes, phase quality map computing, high and low quality area’s partition and low quality area’s optimization, are parallelized in shared memory environment. In order to fully use the multi-core computing ability, a dynamic allocation method for computing task is designed for the optimization process of low quality are- as. Unwrapping tests performed on simulated and InSAR interferogram show that the proposed algo rithm improves the high quality of unwrapped result and greatly optimizes the efficiency. [ABSTRACT FROM AUTHOR]

We propose a non-recursive minimum discontinuity phase unwrapping algorithm for im­proved efficiency. After analyzing the principles of minimum discontinuity phase unwrapping algo­rithm* a stack is used to store the intermediate results during edge spreading and circle canceling processes and thena non-recursive algorithm for phase unwrapping is implemented. The new algorithm was combined with the quantized quality-guided phase unwrapping algorithm, which enhances the un­wrapping efficiency by restricting the optimization area. Unwrapping tests performed on InSAR and InSAS interferograms show that the proposed method maintains high quality unwrapping results and greatly improves efficiency. [ABSTRACT FROM AUTHOR]

We proposed a parallel quality-guided phase unwrapping algorithm in shared memory environment. The intrinsic relationship between the neighboring phase points about quality value computing is analyzed firstly, and then the row and column arrays are used to store the intermediate results in order to eliminate the repeated computation of gradient. The computing task is allocated by row, which can simplify the computing of row and column gradient mean values. Finally, the allocation of computing task is realized using OpenMP instructions, and the quality map is computed in parallel. The inherent parallelism of quality guided process is also analyzed in-depth, but subject to the repetitive thread startup and exit overhead, it is difficult to reflect the advantage of speed. Unwrapping tests performed on InSAR and InSAS interferogram show that the proposed method greatly improves the efficiency of phase unwrapping, and provides a foundation for improving the solution precision under real-time conditions. [ABSTRACT FROM AUTHOR]

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]

Complex image registration is one of the most important steps during the process of interferometric signal processing, and its efficiency directly affects the performance of interferometric signal processing system. In order to improve the efficiency of complex image registration algorithm, we propose an opti⁃ mized complex image registration algorithm for interferometric synthetic aperture sonar (InSAS) in shared memory environment. Firstly, after analyzing the characteristic of calculation and parallelism of each pro⁃ cessing step for complex image registration, an optimized computation method for coarse registration and refine registration is proposed for the massive sliding operation based on the coherence of data in adjacent windows. Then, in order to make full use of multi-core computing resource to accelerate the process of complex image registration, OpenMP instructions are used to parallel design and task allocation for coarse and refine registration, complex image interpolation and wrapped phase extraction. Finally, the correctness and efficiency of the proposed method are verified by the parallel complex image registration for InSAS. [ABSTRACT FROM AUTHOR]