面向受扰时滞AUV集群系统的复杂海洋环境下协同导航方法研究

Cooperative navigation of Autonomous Underwater Vehicle (AUV) has been studied for many years, from the basic programs study and feasibility analysis to cluster cooperative navigation based on multi-load, multi-modal and multi-network. However, AUV has poor stability and robustness under complex marine environment. For example, the communication system of leader-follower AUV leads to a low sharing rate of navigation information between AUVs, and the unpredictability and variability of ocean currents lead to poor robustness of AUV cooperative navigation, and low-quality MIMU installed on AUVs leads to strong dependence on the collaborative navigation information chain. According to the problems above, a new method is studied in this project that can realize the adaptive adjustment of the network topology of the cooperative navigation and suppression and compensation of errors under the influence of the marine environment. Expanding the non-linear real-time filtering mechanism for low-quality MIMU payloads, and solve the key scientific problem of multi-AUVs cooperative navigation which has strong robustness, under complex ocean environment. Finally, a new anti-jamming cooperative navigation method for multi-AUVs under complex ocean environment is formed. This method has the capability of space-time adaptive adjustment. On the basis of improving the accuracy of AUV cooperative navigation, the stability and robustness are enhanced.

AUV协同导航经过近年来的发展，已经从最初的协同导航基本方案建立与可行性论证，深入到基于多载荷、多模态、多网络的集群协同导航研究工作。但面对复杂海洋环境，AUV协同导航仍然存在稳定性与鲁棒性等问题，如主-从AUV单一数据链通信体制导致AUV间导航信息共享率低、洋流的不可预知与随变性导致AUV协同导航鲁棒性差、AUV低品质MIMU载荷导致对协同导航信息依赖性强等。针对上述问题，本项目拟深入研究能实现协同导航网络拓扑结构自适应调整与海洋环境影响误差抑制补偿的AUV协同导航新方法，拓展面向低品质MIMU载荷的非线性实时滤波机理，解决面向复杂海洋环境下，具有强鲁棒性的多水下航行器协同导航关键科学问题。最终形成复杂海洋环境下具有空时自适应调整能力的新型AUV集群抗干扰协同导航方法，在提高AUV协同导航精度的基础上，增强协同导航系统的稳定性与鲁棒性。

本项目深入研究可实现协同导航网络拓扑结构自适应调整与海洋环境影响误差抑制补偿的AUV协同导航新方法：首先，针对编队中单节点系统噪声特性与量测噪声统计特性时变影响导航精度的问题，从频域角度分析噪声特性，提出了基于自适应系统噪声矩阵/Allan方差量测噪声矩阵卡尔曼滤波导航方法；其次，针对系统编队队形设计，完成可观测性与可观测度分析，得到主从式与平行式协同编队运动路径设计原则。此外，针对通信复杂环境观测噪声异常与声统计特性未知时变问题，提出了基于Huber鲁棒滤波/Myers-Tapley鲁棒自适应导航算法；最后，项目组开展了多节点协同导航技术验证性试验，初步验证了上述各项导航方法，超短基线定位/声学测速/惯性导航/水声测距/水声通信等多源异构导航数据融合能力、主从式编队协同导航定位能力。为项目研究成果的应用奠定基础。