Liu Yang, He Long, Fan Gang, Wang Xue, Zhang Ya
College of Mechatronics Engineering, North University of China, Taiyuan 030051, China.
School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.
Sensors (Basel). 2024 May 14;24(10):3127. doi: 10.3390/s24103127.
Underwater mobile acoustic source target localization encounters several challenges, including the unknown propagation speed of the source signal, uncertainty in the observation platform's position and velocity (i.e., platform systematic errors), and economic costs. This paper proposes a new two-step closed-form localization algorithm that jointly estimates the angle of arrival (AOA), time difference of arrival (TDOA), and frequency difference of arrival (FDOA) to address these challenges. The algorithm initially introduces auxiliary variables to construct pseudo-linear equations to obtain the initial solution. It then exploits the relationship between the unknown and auxiliary variables to derive the exact solution comprising solely the unknown variables. Both theoretical analyses and simulation experiments demonstrate that the proposed method accurately estimates the position, velocity, and speed of the sound source even with an unknown sound speed and platform systematic errors. It achieves asymptotic optimality within a reasonable error range to approach the Cramér-Rao lower bound (CRLB). Furthermore, the algorithm exhibits low complexity, reduces the number of required localization platforms, and decreases the economic costs. Additionally, the simulation experiments validate the effectiveness of the proposed localization method across various scenarios, outperforming other comparative algorithms.
水下移动声源目标定位面临若干挑战，包括源信号传播速度未知、观测平台位置和速度的不确定性（即平台系统误差）以及经济成本。本文提出一种新的两步闭式定位算法，该算法联合估计到达角（AOA）、到达时间差（TDOA）和到达频率差（FDOA），以应对这些挑战。该算法首先引入辅助变量来构建伪线性方程以获得初始解。然后利用未知变量与辅助变量之间的关系推导出仅包含未知变量的精确解。理论分析和仿真实验均表明，即使在声速未知和平台存在系统误差的情况下，所提方法仍能准确估计声源的位置、速度和声速。它在合理的误差范围内实现渐近最优，以逼近克拉美罗下界（CRLB）。此外，该算法具有低复杂度，减少了所需定位平台的数量，并降低了经济成本。此外，仿真实验验证了所提定位方法在各种场景下的有效性，优于其他对比算法。
