Underwater acoustic localization (UWAL) is a useful technique, and is applied in finding the acoustical sources, such as the black box. The existing UWAL methods are mainly based on the time of arrival (TOA), the time difference of arrival (TDOA), and the direction of arrival (DOA), which need the time synchronization, the knowledge of signal period, and the high precision angular measurement, respectively. However, these conditions are difficult to be satisfied in the scene of locating the black box utilizing single autonomous underwater vehicle. In this article, we propose the definition of second-order time difference of arrival (STDOA) and establish the localization model based on the STDOA. The proposed STDOA-based method eliminates the unknown signal period and overcomes the restriction of the traditional TDOA-based method. Combined with the particle filter, target tracking algorithm based on the STDOA is also presented. Precision analysis and the simulation results validate the effectiveness of the STDOA-based method and prove that the proposed method achieves a comparable localization precision compared with the TOA-based method and the TDOA-based method, and a higher precision compared to the DOA-based method.

Single-beacon navigation for group autonomous underwater vehicles (AUVs) suffers from long navigation period and asynchronization. This paper addresses the problem by introducing the single-input-multiple-output (SIMO) model, where, a single AUV transmits the signal and other AUVs receive the signal. Utilizing the time-delay of signals from the beacon and the sender, the navigation for all AUVs is achieved simultaneously, and the navigation period is dramatically decreased. Moreover, based on the new SIMO model, a tracking method utilizing extended Kalman filter is also put forward to increase the navigation precision and reduce the computational burden. Finally, a coordinate fusion algorithm based on the location, error, and time-delay is presented, which fuses the independent AUV coordinates to be a higher precision holistic coordinate system for group AUVs. Simulation results show the effectiveness of the proposed method.

基于浅海射线声学多途结构，提出了一种具有高稳健性、高精度的单水听器目标运动参估计方法. 针对匀速直线运动目标，综合多途时延差和运动学几何关系，构建了目标三维多途时延模型，进而获得目标运动参数与多途时延差的非线性时间映射. 研究了典型水声信道的倒谱表达式，提出了利用倒谱提取多途时延差的策略. 采用差分进化综合优化手段估计目标运动参数，提高了算法的稳健性. 理论及仿真结果表明，倒谱的时间分辨率不受信号带宽的限制，而主要取决于信号类型和信噪比；CW信号的倒谱对多普勒不敏感；参数估计精度主要取决于时延差估计精度和参与差分进化运算的信息量，当包含有最近点信息时参数估计性能较好. 水池实验结果进一步验证了方法的正确性和有效性.

Underwater acoustic navigation is extensively utilized across many industries due to its exceptional dependability and continuous real-time functionality. Due to the swift advancement of technology in recent years, the velocity of autonomous underwater vehicles (AUVs) has progressively increased. A high frame rate is required for the underwater acoustic navigation system in order to precisely obtain the trajectory of the AUV. Nevertheless, the discrepancy lies in the fact that the high frame rate and the unambiguous measurement could be seen as contradictory. Higher frame rates greatly raise the probability of range ambiguity, leading to various potential pseudo solutions that exacerbate the difficulty of accurate positioning and noticeably impact navigation performance. To address the aforementioned issue, a high frame rate acoustic navigation technique that relies on the suppression of range ambiguity has been studied in this paper. Initially, the relationship between measurements were investigated, specifically the time delay and Doppler shift, and the confusing periodic leap. Subsequently, the coupling model was employed to develop a high-precision acoustic navigation model, taking into account the statistical characteristics of measurements. We also examined a high-precision solving approach. Ultimately, the proposed method was validated through both simulation analysis and field testing to confirm its practicality and efficiency. The results demonstrate that it can attain a high level of accuracy in resolving the ambiguous problem and achieve high-precise acoustic navigation.

Considering the requirement of the near-field calibration under strong underwater multipath condition, a high-precision geometric calibration method based on maximum likelihood estimation is proposed. It can be used as both auxiliary-calibration and self-calibration. According to the near-field geometry error model, the objective function of nonlinear optimization problem is constructed by using the unconditional maximum likelihood estimator. The influence of multipath on geometric calibration is studied. The strong reflections are considered as the coherent sources, and the compensation strategy for auxiliary-calibration is realized. The optimization method (differential evolution, DE) is used to solve the geometry errors and sources’ position. The method in this paper is compared with the eigenvector method. The simulation results show that the method in this paper is more accurate than the eigenvector method especially under high signal-to-noise ratio (SNR) and multipath environment. Experiment results further verify the effectiveness.