Focusing Multireceiver SAS Data Based on the Fourth-Order Legendre Expansion

For the problem that the existing chirp scaling algorithm based on the method of series reversion (MSRCSA) needs to approximate the range cell migration (RCM) into a linear term of range and causes a larger range cell migration correction (RCMC) error, we propose an improved MSRCSA, which is able to focus azimuth‐variation bistatic SAR. Firstly, to avoid the linear approximation for RCM, this paper derives a new curvature factor varying with the azimuth frequency and range, utilizing to describe RCM without any approximation. Secondly, since the new curvature factor is different with the traditional curvature factor varying only with the azimuth frequency, a new scaling function is given to modulate the echo signal so that the required range‐variant RCMC shift can be implemented by using phase multiplies. Thirdly, the proposed MSRCSA is implemented by utilizing three phase multiplications and four fast Fourier transforms (FFTs). Finally, the good performance of the proposed MSRCSA is examined by comparing the imaging result of the proposed MSRCSA with that of the existing MSRCSA.

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“…where α(f η ; r ref ) has the form 0/0 according to (6). The solution for this form can be obtained by utilizing L'Hopital's rule.…”

Section: -D Spectrum Of a Bistatic Signalmentioning

confidence: 99%

“…The second challenge [5] is that the analytical solution for the bistatic 2-D spectrum is difficult to be obtained by directly utilizing the principle of stationary phase (POSP) [6][7][8], because the bistatic SAR has a range history with the double square roots (DSR). Currently, there are three approaches for the bistatic SAR to achieve the 2-D spectrum.…”

mentioning

confidence: 99%

A chirp scaling algorithm based on the method of series reversion for bistatic SAR

Cha

Ning

et al. 2022

Electronics Letters

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“…The geoacoustic parameters in each seabed layer, such as sound speeds, density and attenuations, all have significant effects on the underwater acoustic field prediction, the sonar performance prediction, the underwater acoustic detection and the underwater acoustic communication (Zhang et al, 2022;Zhao et al, 2022). Therefore, the acquisition of geoacoustic parameters is particularly important in shallow sea (Zhang et al, 2019;Yang et al, 2020). Although, the geoacoustic parameters can be obtained by direct core sample measurements, it is very time consuming and costly to obtain enough samples for a large area.…”

Section: Introductionmentioning

confidence: 99%

Inversion of shallow seabed structure and geoacoustic parameters with waveguide characteristic impedance based on Bayesian approach

Zhu

Xue²,

Ren³

et al. 2023

Front. Mar. Sci.

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Underwater acoustic technology is essential for ocean observation, exploration and exploitation, and its development is based on an accurate predication of underwater acoustic wave propagation. In shallow sea environments, the geoacoustic parameters, such as the seabed structure, the sound speeds, the densities, and the sound speed attenuations in seabed layers, would significantly affect the acoustic wave propagation characteristics. To obtain more accurate inversion results for these parameters, this study presents an inversion method using the waveguide characteristic impedance based on the Bayesian approach. In the inversion, the vertical waveguide characteristic impedance, which is the ratio of the pressure over the vertical particle velocity, is set as the matching object. The nonlinear Bayesian theory is used to invert the above geoacoustic parameters and analysis the uncertainty of the inversion results. The numerical studies and the sea experiment processing haven shown the validity of this inversion method. The numerical studies also proved that the vertical waveguide characteristic impedance is more sensitive to the geoacoustic parameters than that of single acoustic pressure or single vertical particle velocity, and the error of simulation inversion is within 3%. The sea experiment processing showed that the seabed layered structure and geoacoustic parameters can be accurately determined by this method. The root mean square between the vertical waveguide characteristic impedance and the measured impedance is 0.38dB, and the inversion results accurately represent the seabed characteristics in the experimental sea area.

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“…8,9 InSAS is a relatively new threedimensional imaging sonar technique. [10][11][12] Compared with SAS, [13][14][15][16][17][18][19] its advantage is that it has the ability of bathymetric. InSAS adds one or more receiver arrays based on SAS to obtain the height value of targets or the deformation of the seafloor by using the phase difference.…”

Section: Introductionmentioning

confidence: 99%

Review of interferometric synthetic aperture sonar interferometric phase filtering methods

Huang,

Ding,

Wang

et al. 2023

Advances in Mechanical Engineering

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Interferometric synthetic aperture sonar (InSAS) is a novel three dimensional underwater mapping system, which is widely used in various fields. Interferometric phase filtering is a crucial process in InSAS signal processing. The study of interferogram filtering method has great significance to improve the signal-to-noise ratio (SNR) of interferogram, reduce the difficulty of phase unwrapping, and improve the accuracy of digital elevation maps. Firstly, this article introduces the sources of interferometric phase noise. Secondly, it illustrates the difference between real domain filter and complex domain filter by simulation experiment. Thirdly, the various methods of InSAS interferogram filtering are systematically studied, which can be classified into spatial domain filtering and transform domain filtering. The transform domain filtering can be further divided into frequency domain and wavelet transform filtering. Moreover, the advantages and disadvantages of various methods are analyzed theoretically. Finally, numerical simulation and real-data processing experiments are performed, and the advantages and shortcomings of several methods are compared using residue numbers, root mean square error (RMSE), and CPU time as evaluation criteria.

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Focusing Multireceiver SAS Data Based on the Fourth-Order Legendre Expansion

Cited by 25 publications

References 26 publications

A chirp scaling algorithm based on the method of series reversion for bistatic SAR

A chirp scaling algorithm based on the method of series reversion for bistatic SAR

Inversion of shallow seabed structure and geoacoustic parameters with waveguide characteristic impedance based on Bayesian approach

Review of interferometric synthetic aperture sonar interferometric phase filtering methods

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