access icon free BP algorithm for the multireceiver SAS

The imaging performance and efficiency are two important issues for the multireceiver synthetic aperture sonar (SAS). Back projection (BP) algorithm is characterised by the high performance and low efficiency. In this study, the authors first recall the standard BP algorithm based on the interpolation for the multireceiver SAS. Then, two improved BP algorithms based on the range Fourier transformation (FT) are presented. Considering the fact that the time delay in the time domain can be carried out by the phase shifting in the frequency domain, an FT shifting based BP algorithm avoiding the interpolation error is presented. Although this method produces the focusing result with high performance, it is very time consuming. In order to improve the imaging efficiency without loss of imaging performance, the authors propose an oversampling-based BP algorithm, which is based on the fact that the zero-padding in the frequency domain is equivalent to the interpolation in the time domain. After that, the computation complexity of three BP algorithms is analysed in detail. Finally, simulations and real data are exploited to validate the presented methods.

Inspec keywords: Fourier transforms; radar computing; synthetic aperture sonar; computational complexity; interpolation; sonar imaging; neural nets; image sampling; backpropagation

Other keywords: computation complexity; multireceiver synthetic aperture sonar; time domain; imaging performance; FT shifting based BP algorithm; multireceiver SAS; imaging efficiency; standard BP algorithm; frequency domain; high performance; back projection algorithm; oversampling-based BP algorithm; range Fourier transformation

Subjects: Computer vision and image processing techniques; Neural computing techniques; Oceanographic and hydrological techniques and equipment; Sonar and acoustic radar; Integral transforms in numerical analysis; Integral transforms in numerical analysis; Electrical engineering computing; Interpolation and function approximation (numerical analysis); Optical, image and video signal processing

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