Sabra Karim G
Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
J Acoust Soc Am. 2022 Aug;152(2):1201. doi: 10.1121/10.0013752.
Using a network of a few compact mobile underwater platforms, each equipped with a single acoustic sensor, as a distributed sensing array is attractive but requires precise positioning of each mobile sensor. However, traditional accurate underwater positioning tools rely on active acoustic sources (e.g., acoustic pingers), which implies additional hardware and operational complexity. Hence, self-localization (i.e., totally passive) methods using only acoustic sources of opportunity (such as surface vessels) for locating the mobile sensors of a distributed array appear as a simpler alternative. Existing underwater self-localization methods have mainly been developed for mobile platforms equipped with time-synchronized hydrophones and rely only on the time-differences of arrival between multiple pairwise combinations of the mobile hydrophones as inputs for a complex non-linear inversion procedure. Instead, this article introduces a self-localization method, which uses a linear least-square formulation, for two mobile time-synchronized vector sensor platforms based on their acoustic recordings of a distant surface vessel and their inertial navigation system (INS) measurements. This method can be generalized to multiple vector sensor pairs to provide additional robustness toward input parameter errors (e.g., due to a faulty INS) as demonstrated experimentally using drifting buoys with inertial vector sensors deployed ∼100 m apart in shallow water.
使用由几个紧凑的移动水下平台组成的网络，每个平台配备一个声学传感器，作为分布式传感阵列很有吸引力，但需要精确确定每个移动传感器的位置。然而，传统的精确水下定位工具依赖于有源声学源（例如，声学信标），这意味着额外的硬件和操作复杂性。因此，仅使用机会声学源（如水面船只）来定位分布式阵列中的移动传感器的自定位（即完全被动）方法似乎是一种更简单的选择。现有的水下自定位方法主要是为配备了时间同步水听器的移动平台开发的，并且仅依赖于移动水听器的多个成对组合之间的到达时间差，作为复杂非线性反演过程的输入。相反，本文介绍了一种自定位方法，该方法基于两个移动时间同步矢量传感器平台对远处水面船只的声学记录及其惯性导航系统（INS）测量，使用线性最小二乘公式。如在浅水中相隔约100米部署了惯性矢量传感器的漂流浮标实验所示，该方法可以推广到多个矢量传感器对，以提高对输入参数误差（例如，由于INS故障）的鲁棒性。
