Dolphins whistle contour automatic extraction and recovery

海豚是一种高智商的水生哺乳动物，它们使用自己独特的“语言”——哨声来进行互相交流。要想理解海豚的语言，就必须要对海豚哨声进行分析研究。当前对海豚哨声的分析研究大多是基于哨声语谱图进行的，但语谱图中哨声轮廓与背景噪声混合在一起，不仅导致目前对哨声的分割、提取等预处理都是用人工方式进行，同时也给后续的实验造增加了难度。如果对语谱图中的哨声轮廓进行去噪、特征提取和修复等自动化预处理，就能实时进行海豚哨声与背景噪声的分离，获得一个完整的海豚哨声轮廓。这不仅节约了人工提取花费的时间，也有利于海豚哨声的个体识别、行为分类、通讯机制等后续研究。 基于以上原因，本文构建了一套完整的海豚哨声轮廓自动提取与修复...Dolphin is one kind of intelligent aquatic mammals, they use their own ways to communicate with each other, which are called whistles. To understand their language, it is necessary to analyze the whistles. Currently, most researches on whistles is based on spectrogram. However, the whistle contour is mixed with background noise in the spectrogram, which causes the manual segmentation and extractio...学位：工学硕士院系专业：信息科学与技术学院_计算机科学与技术学号：3152012115301

Simulation Research on Obstacle Avoidance of Autonomous Underwater Vehicle Based on Single Beam Ranging Sonar

针对多波束声纳体积大,成本高的局限,利用单波束声呐的探测波束依次旋转,依次获取自主式水下航行器(AuTOnOMOuS undErWATEr VEHIClE,AuV)前方的左、中、右3个区域的障碍物距离信息.通过设计合适的环境障碍状态与有效的避障行为集合,并利用强化学习选择适合AuV自主避障的障碍状态-行为组合.仿真实验表明,根据单波束传感器提供的障碍物信息,通过强化学习获得的状态-动作组合,可以保证AuV躲避前方90°开角的障碍物,达到安全航行的要求.On one hand,the single-beam sonar acquires the obstacle distance information,which includes three areas(left,center and right)in front of autonomous underwater vehicle by rotating its ranging beam,for the large volume and high cost limitations of the multi-beam sonar.On the other hand,appropriate environmental states and effective obstacles avoidance behaviors are designed,and the proper state-action combinations for obstacle avoidance are selected by the reinforcement learning.Simulation results show that,according to the obstacle information provided by the single-beam sonar and the state-action combination obtained through reinforcement learning,AUV can guarantee to avoid obstacles in front of the opening angle of 90degrees and meet requirements safe navigation.国家自然科学基金(60975084;61165016