测距优化与能量有效覆盖的三维水声传感器网络目标定位跟踪技术研究

项目名称： 测距优化与能量有效覆盖的三维水声传感器网络目标定位跟踪技术研究

项目编号： No.61501168

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 刘志华

作者单位： 河北师范大学

项目金额： 20万元

中文摘要： 针对三维水声传感器网络(UASNs)目标定位跟踪技术中的定位不精和能耗过高问题，本项目拟基于水声信号传播的视线(LOS)与非视线(NLOS)法定义比例因子，并设计精确的基于优化策略的水声传播时延估计方案以提高测距精度。引入概率能量有效覆盖理论，对目标进行概率探测，提出格栅式测量优化预测区域，降低网络能耗。提出颜色序列定位法，在三维分层投影模型下，推导目标的移动方向与速度，同时将信号值存储为目标序列，通过比较样本的颜色序列与目标序列的差值过滤样本点，提出新的加权方法，提高样本状态估计的准确性；并设计新的导航策略，动态跟踪水下目标的运动轨迹。同时研究统一、合理的评价体系，采用软件仿真和硬件平台测试相结合的方式对提出的定位跟踪算法进行跟踪概率、跟踪误差、跟踪延迟和跟踪开销等验证。

中文关键词： 三维水声传感器网络；定位跟踪；能量有效覆盖；格栅式测量；颜色序列

英文摘要： For the problem of low precision and high energy consumption in the technology of target localization and tracking in 3D underwater acoustic sensor networks (UASNs), we consider defining the scale factor based on the classification of line-of-sight (LOS) propagation and none-line-of-sight (NLOS) propagation for underwater acoustic signals. And on the basis of optimization, accurate sound travel time solution is designed to improve the ranging accuracy. To detect targets by high probability, the theory of probability and energy effective coverage are introduced. Further to reduce energy consumption of UASNs and optimize the prediction area, grid type measure is proposed. We present the color sequence localization, where we deduce the sailing direction and velocity of the targets based on the model of 3D hierarchical projection. The signal values are stored as the sequence of a target, and by comparing the difference between samples’ sequences and targets’ sequences, samples can be filtered out. The new weighted approach is studied as well to improve the accuracy of sample state estimates. New navigation strategy will be studied for tracking underwater targets dynamically. Meanwhile, based on the combination of software simulation and hardware test bed, the unified and reasonable evaluation system will be studied to verify the tracking probability, tracking error, tracking delay and tracking cost of the proposed algorithms.

英文关键词： Underwater acoustic sensor networks (UASNs);Localization and tracking;Energy efficient coverage;Grid type measure;Color sequences