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中文摘要：
介绍基于回波强度的海底底质分类软件的框架,并从多波束声呐原理入手解析ALL格式多波束声呐数据的存储结构和内容,通过软件开发可实现ALL格式多波束声呐数据的解码,提取各种数据包,并且通过一系列的数据预处理形成基于波束脚印包络栅格的高分辨率声呐图像。最后,利用改进的BP神经网络对生成的声呐图像进行海底底质分类。实验证明,本系统对底质全图分类效果很好,并为海底微地貌识别提供精确可靠的依据。
英文摘要：
First of all,the framework of sediment classification system based on echo intensity is introduced,The paper then analyzes storage structure and content of ALL format multibeam sonic data with multibeam sonar principles.It can decode ALL format data,and extract all kinds of data packets from ALL raw file by means of software developing.By means of a series of data preprocessing,it can create high-resolution sonic images based on a footprint envelope grid from these sonic data.In the end,the sediment classification is implemented with improved BP neural network in the sonic image.The experiment proves that it can obtain good effects for sediment classification with sonic image,and provide an accurate and reliable basis for submarine microgeomorphology recognition.
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