基于AUV载移动声源的海洋环境参数序贯反演方法研究

Sound propagation is main means of perception, identification and communication of underwater information. It is closely related to ocean environment. Sound Propagation is greatly disturbed by a variety of physical processes in ocean which cause the variety temperature and salt. On the other hand, sound propagation in turn contains a full of marine environment parameters such as temperature field. Underwater acoustic inversion is a method of parameters estimation, which usually uses a sound source and a received array. In recent years, with the development of autonomous underwater vehicles (AUVs), the combination of acoustic inversion and AUVs has become one of the developing directions of marine environmental monitoring. In this proposal, we will study sequential inversion of ocean environmental parameters with an AUV carrying sound source. By solving mobile acoustic inversion of spatial-temporal coupling modeling, sequential inversion of environmental parameters with high degrees of freedom, and performance analysis of parameter estimation errors and path planning for mobile sources, we will develop new theory and methods for sequential inversion. The estimated results have a wide coverage and high spatial-temporal resolution. The project provides new ideas, theories and technologies for dynamic monitoring of the regional marine environment.

声传播是水下信息感知、辨识和通讯的主要手段，它与海洋环境有着紧密的联系：一方面声传播受多种物理过程引起的海洋温盐场扰动影响很大，另一方面声传播又包含了丰富的海洋温度场等环境参数信息。海洋声学反演是一种采用布设的声发射/接收节点对声传播路径上的水文特性/地声参数进行估计的方法。近年来，随着水下移动平台的发展，将环境参数声学反演技术与移动平台结合起来，并对有限的观测资源进行优化部署，成为动态海洋环境监测的发展方向之一。项目开展基于自主水下航行器（AUV）平台的移动声源海洋环境参数序贯反演方法研究，突破移动声学反演空-时状态耦合建模、水体动态环境参数及沉积层静态地声参数高自由度序贯反演、参数估计误差性能分析及移动源路径规划三大难点问题，发展既具有较宽覆盖范围，又具有较高空-时分辨率的海洋环境参数移动声源序贯反演方法，为区域动态海洋环境监测提供新思路、新理论和新技术。

项目组针对计划书移动声源海洋环境参数序贯反演方法研究这一任务，按年度计划开展了各项研究内容的理论推导、仿真分析及实验验证工作，取得的主要成果如下：（1）开展了移动声学反演空-时状态耦合建模研究，构建了移动源环境参数时间独立、移动源环境参数时间依赖、基于动力模式的状态空间建模等适合于多种实际应用的状态空间模型；（2）在建立状态空间模型基础上，提出了适用于移动源高维非线性声学反演的3种序贯滤波算法，并利用海试数据分析和比较了算法的有效性；（3）研究了基于动力模式温度场输出的两维及三维移动平台自适应采样路径规划方法，并利用仿真和部分实测数据验证了算法的可行性；（4）发表标注基金资助的SCI/EI期刊/国际会议论文8篇，其中第一标注5篇，第二标注3篇，授权发明专利2项，培养博士后1名，博士研究生1名，硕士研究生6名。