National Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou 310000, China.
Sensors (Basel). 2022 Jul 26;22(15):5571. doi: 10.3390/s22155571.
The emergence of underwater acoustic networks has greatly improved the potential capabilities of marine environment detection. In underwater acoustic network applications, node location is a basic and important task, and node location information is the guarantee for the completion of various underwater tasks. Most of the current underwater positioning models do not consider the influence of the uneven underwater medium or the uncertainty of the position of the network beacon modem, which will reduce the accuracy of the positioning results. This paper proposes an underwater acoustic network positioning method based on spatial-temporal self-calibration. This method can automatically calibrate the space position of the beacon modem using only the GPS position and depth sensor information obtained in real-time. Under the asynchronous system, the influence of the inhomogeneity of the underwater medium is analyzed, and the unscented Kalman algorithm is used to estimate the position of underwater mobile nodes. Finally, the effectiveness of this method is verified by simulation and sea trials.
水下声纳网络的出现极大地提高了海洋环境检测的潜在能力。在水下声纳网络应用中,节点位置是一个基本而重要的任务,节点位置信息是完成各种水下任务的保证。目前大多数水下定位模型都没有考虑水下介质不均匀或网络信标调制解调器位置不确定性的影响,这将降低定位结果的准确性。本文提出了一种基于时空自校准的水下声纳网络定位方法。该方法仅使用实时获取的 GPS 位置和深度传感器信息,即可自动校准信标调制解调器的空间位置。在异步系统下,分析了水下介质不均匀性的影响,并使用扩展卡尔曼滤波算法估计水下移动节点的位置。最后,通过仿真和海上试验验证了该方法的有效性。