Multi-beam sonar submarine topography measurement quality real-time evaluation method based on phase method

Abstract

The invention provides a multi-beam sonar submarine topography measurement quality real-time evaluation method based on a phase method, which is characterized in that the quality factor of the multi-beam sonar phase method is shown in the description, wherein, QFphi represents the quality factor, tp is the arrival time under the phase detection, the units s and T0 are the transmitting pulse widthof the signal, the units s and k are the slopes after the linear fitting of the phase difference, delta phi 2 is the estimated phase standard deviation. According to the evaluation method, the computational complexity is low and easy to obtain, and the calculation only involves some simple characteristic quantities of the echo signal; the judgment criterion is simple and clear, and the higher thequality factor value is, the more accurate the depth estimation is; real-time quality monitoring of the sounding values can be achieved because the quality factor itself is obtained with the TOA and is immediately available; as an objective indicator of the quality level of the sounding value, the multi-beam sonar submarine topography measurement quality real-time evaluation method based on the phase method can be used in later more advanced post-processing algorithms, such as CUBE algorithm.

Description

technical field [0001] The invention relates to a quality real-time evaluation method, in particular to a phase method-based multi-beam sonar seabed topographic measurement quality real-time evaluation method. Background technique [0002] In the process of multi-beam sonar seabed topographic survey, it is necessary to objectively estimate the error of each calculated depth value. In fact, since the acoustic scattering signal is fluctuating in nature, the estimation of the arrival time or angle is also random, and the fluctuation level is related to the signal-to-noise ratio (SNR) of the received echo signal. In the process of data collection, the error of the detection value in an environment that is too noisy is relatively large, which is not reliable, so the device should have the ability to identify and eliminate these data. And for those parts that have reached the preset threshold and are regarded as reliable detection values, objective indicators representing their q...

AI Technical Summary

Problems solved by technology

The processing effect of this method is very good, but it also has very obvious limitations. Since it is usually very difficult to estimate the actual signal-to-noise ratio, this method is more suitable for performance prediction analysis or system design, not suitable for Quality monitoring of field data in a routine operating environment

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