TY -的A2 Marletta Vincenzo盟——赵,安邦AU - Bi Xuejie AU - Li Nansong盟——张,结果表明非盟-朴,Shengchun PY - 2019 DA - 2019/12/04 TI -目标深度分类算法的性能分析基于SP - 5928401六世海实验数据可以计算- 2019 AB -互谱信号的压力信号。信号的互谱分布活性成分可以有效地用于目标深度分类算法。该算法适用于深度分类的目标频率只能激发前两个正常模式。相应的研究成果主要是基于理论研究。很少有研究基于实验结果对算法性能。为了克服这项研究缺乏,基于有效深度模型,对各种接收的影响深度,源的频率,和接收信噪比算法性能研究。声速剖面的影响参数(负梯度、温跃层强度、温跃层厚度和河段深度)对算法性能也被研究。根据仿真结果,适当调整接收深度可以有效地提高算法的性能。源频率主要影响理想接收深度的位置可适当调整根据深度分类要求真实的海洋环境。该算法性能随信噪比的增加逐渐好转。 Moreover, the algorithm can also be applied under the conditions of negative gradient and thermocline. The comprehensive sound velocity profile parameters have a large impact on the depth classification performance of the algorithm. Even in the case of strong negative gradient or strong thermocline, the robustness of the algorithm is still high. The feasibility of our presented method has been verified by sea experiment. The practical application value of the ideal receiving depth has been researched and validated. The factors affecting the algorithm performance including line spectrum continuity and received signal-to-noise ratio have also been analyzed in our simulation and real sea experiments. SN - 1687-725X UR - https://doi.org/10.1155/2019/5928401 DO - 10.1155/2019/5928401 JF - Journal of Sensors PB - Hindawi KW - ER -