从侧面扫描声纳到高分辨率测深的进化优化

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI:10.1109/CEC.2002.1004421

E. Avgerinos, A. Zalzala, G. Zografos

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引用次数: 0

摘要

本文的主要目的是利用遗传算法来提高侧扫描原始数据的测深质量。优化序列从相位数据的逆建模开始，该模型独特地对应了侧扫描船和海底地形耦合系统的特征。然后将这些相位数据与声纳实际收集的相位数据进行比较，以产生相关系数作为目标函数。仿真结果表明，该算法对目标函数的最优值具有鲁棒收敛性。结果表明，这种新方法可以避免在相位数据正演处理中普遍遇到的困难。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Towards evolutionary optimisation for high resolution bathymetry from sidescan sonars

The main objective of this paper is to use genetic algorithms in order to improve the quality of the bathymetry derived from sidescan raw data. The optimisation sequence starts with inverse modelling of the phase data, which uniquely corresponds to the characteristics of the coupled system of the sidescan vehicle and the seafloor terrain. These phase data are then compared with phase data actually collected by the sonar, to produce a correlation coefficient as an objective function. Simulation results are reported for the algorithm showing robust convergence towards the optimum value of the objective function. The results indicate that this new approach can be used to avoid difficulties widely encountered during forward processing of phase data to derive bathymetry.

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Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

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