基于自组织UWSNs水下目标跟踪关键问题研究

This project aims to conduct the research in exploring the crucial technologies in target tracking fields that are based on self-organized Underwater Wireless Sensor Networks (UWSNs). The research’s outcome will meet our nation’s needs of the ocean explorations and homeland security. The proposed research also considers the chracteristic of UWSNs and the particularity of acoustic communication channel. First, the research will study the problem of node's position uncertainty caused by node shaking in UWSNs, investigate the method of modeling node’s position uncertainty and its relation with Posterior Cramer-Rao Lower Bound (PCRLB). Second, the proposed research will develop the model of underwater acoustic channels as well as the related PCRLB problems in order to being aware of the effects of the unideal underwater acoustic communication channel parameters on the performance of target tracking. Third, this research will study the relations between PCRLB and parameters of the clutter under the conditions of the measurement origin uncertainty. According to target movement and PCRLB criterion designed in this project, nodes in UWSNs will alternatively wake up and sleep to self-organize the local networks, which aims to implement underwater target tracking tasks. Finally, these achievements will be extended to tracking underwater multi-targets based on self-organized UWSNs. This research will target at increasing tracking performance and extending the lifetime of UWSNs by finding out the partition strategy for tracking underwater multi-targets. The results of this project will advance the fundamental theory of underwater target tracking and facilitate the industrial applications of UWSNs.

结合海洋开发和海洋国土安全的需求，针对水下无线传感器网络（UWSNs）的特点和水声信道特殊性，本项目重点研究基于自组织UWSNs的目标跟踪关键技术。首先针对UWSNs中的节点晃动造成的节点位置不确定问题，研究节点位置不确定建模和后验克拉美罗下界（PCRLB）问题；接着针对非理想通信信道问题，研究水声信道的建模问题，并给出相应的PCRLB，研究信道参数对目标跟踪性能的影响；然后，针对量测来源不确定问题，着重研究PCRLB与杂波参数的关系；UWSNs中的水下节点根据目标的位置变化和PCRLB准则交替睡眠和唤醒，自动组成局部网络，完成水下目标跟踪任务。最后，在以上单目标跟踪的基础上，研究基于划分策略的水下多目标跟踪，以提高跟踪性能和UWSNs网络寿命。针对上述研究问题取得的进展和突破，必将完善水下目标跟踪理论，同时也促进了UWSNs的工程实用化。

为满足水下目标跟踪在军事和民用方面的需要，结合海洋开发和海洋国土安全的需求，针对水下无线传感器网络（UWSNs）的特点和水声信道特殊性，本项目重点研究基于自组织UWSNs的目标跟踪关键技术。本项目组在前期量化量测条件下节点拓扑结构对跟踪性能的影响的研究基础上，继续开展非理想条件下基于自组织UWSNs跟踪算法的设计。首先，本项目组提出了基于节点移动预测和同时定位跟踪的算法HLMP-SLAT，研究了移动节点下的跟踪问题；在非理想信道条件下，提出了一种基于失序量测的GM-PHD滤波器，实现异步量测下的融合跟踪。然后，在考虑量测模型不确定和目标模型不确定的基础上，设计了基于最优量化界的量化方法，实现了低比特量测下的水下目标高精度跟踪。在目标跟踪过程中，通过推导节点深度和Fisher信息矩阵之间的关系，研究了节点深度最优问题，并设计了合适的权值评估方法，提出了多传感器加权粒子滤波算法和基于动态簇的水下多传感器协作被动跟踪策略，保证了水下目标被动跟踪精度的收敛性，也有效降低了跟踪过程中网络的能量消耗，完善了基于自组织UWSNs的水下目标跟踪理论。本项目组已经完成了计划书中的全部研究内容，并取得超过预期的成果。发表标注资助号的论文13篇（SCI收录8篇，EI收录4篇）；参加学术会议11人次；申请国家发明专利9项（其中授权5项）；项目负责人获得3项科研奖励。在本项目研究工作的基础上获得后续国家、省部级资助项目8项。项目负责人入选江苏省“双创人才计划”，教育部长江特聘教授，国家“万人计划”科技创新领军人才和科技部创新人才推进计划中青年科技创新领军人才。