对集合卡尔曼滤波在时变海洋环境下的声速剖面追踪性能进行了分析.将南海实验背景下普林斯顿海洋模型预报的声速剖面正交分解为3阶系数组成的状态-空间形式,其状态转移方程建模为3阶自回归过程;基于卡尔曼反馈理论,利用适合于水平非均匀模型RAM仿真的观测声压场对系统状态进行校正,实现声速剖面的动态追踪.在水平均匀、水平非均匀和海底参数失配环境下的仿真结果均能较好地实现对声速剖面的追踪,验证了算法的可行性.同时对不同信噪比、粒子数、阵元数和海底参数失配等情况下的分析表明,观测信息量的增加可以有效抑制观测误差和模型误差的影响,相关结论得到了实验数据的验证.

利用一次南海海山环境下的声传播实验数据,研究了负梯度水文环境下海底山对声传播的影响.针对实验数据中的传播损失异常,从射线声学角度给出了合理的解释,表明海底山的存在引起传播损失在距离上剧烈波动.在距离接收阵较近的7.6 km处,声源位于海山斜坡上,斜坡的反射使接收传播损失减小约8 dB,体现出斜坡增强特征.当声源位于海山后,海底山的遮蔽作用使23.8 km处的传播损失增加超过20 dB,不同位置处海山遮蔽效应的差异使传播损失随距离起伏.利用抛物模型对实验环境下的声传播进行了定量仿真,仿真传播损失同实验结果符合,验证了实验数据中海底山的反射和遮蔽作用.此外,对实验环境下海山的遮蔽损失进行分析,发现在不同声源位置处,海山遮蔽损失在特定频带上同频率对数具有线性关系.

受海面波浪起伏、降雨和内波等海洋动力学过程的影响,浅水声速剖面的时间演化具有高度非线性,针对该问题提出使用改进的粒子滤波方法进行声速剖面序贯反演.该方法通过建立声速剖面的经验正交模型(EOF)以及描述声速剖面时间演化特征的状态空间模型,将声速剖面反演问题建模为状态跟踪问题,利用不敏粒子滤波(UPF:Uncented Particle Filter)算法进行声速剖面序贯反演.仿真试验通过实测声速剖面数据和先验地声参数信息产生接收声场数据,再利用模拟声场数据估计声速剖面的时间变化.结果 表明,相比于集合卡尔曼滤波(EnKF:Ensemble Kalman Filter),在计算效率等同的情形下,该方法可以在状态参数的时间跳变点保持良好的跟踪性能,一定程度上克服了现有反演算法在跳变点发散的问题,可以有效提高声速剖面反演精度,尤其在声速剖面时变性较强时具有显著优势.

Environment uncertainties lead to difficulties for accurate underwater acoustic field predictions. This paper presents a synthetic test to track the time evolving sound speed profiles (SSPs) using acoustic pressure field, which is derived by Princeton Ocean Model (POM) outputs based on the representative environmental model of a sea trial. In the simulation, range independent SSPs are parameterized by Empirical Orthogonal Functions (EOFs) and their coefficients, which are placed into the state-space form. Their variations are modeled as a three-order Auto-Regress (AR) process, and tracked by an Ensemble Kalman Filter (EnKF) from observing the underlying sound fields as generated by a parabolic equation model. Promising tracking results are obtained from the synthetic data, especially for the first two orders coefficients, suggesting the feasibility of EnKF to assimilate the states with acoustic measurements. The performance of the tracking algorithm with respect to Signal to Noise Ratio (SNR) of measurements, the samples and the amount of observations as applied in EnKF are also discussed in this paper.

This paper presents a work of range-dependent geoacoustic inversion for two seamounts environment with negative gradient sound speed profiles based on the transmission losses (TLs), collected in an experiment in the South China Sea, 2016. Bombs of 200 m and the mooring vertical line array (VLA) is applied for recording. Typical characteristics of shadowing and reflecting by seamounts are confirmed by the fluctuations of TLs with respect to range, indicating the complexity of sound propagation within seamounts environment. In the framework of matched field inversion (MFI), the geoacoustic model of two layers and the range-dependent acoustic model (RAM) is applied to produce the replica TLs, which is used to compute the cost function in combination with the collected TLs in terms of the least mean variance. The simulated annealing (SA) is expected to augment the searching efficiency of geoacoustic parameters. Results of four models with different parameters within 120km are obtained, with which the simulated TLs are in good accordance with experiment results for several frequencies and receiving depths. Conclusion is drawn that the effects of range-dependence of geoacoustic parameters in seamounts environment are as important as those of bathymetry on sound propagation, which should be seriously considered especially with negative gradient sound speed profiles.

This paper presents characteristics study of internal wave in the Yellow Sea by analyzing nearly 40 h thermistor data obtained in 2007 experiment. Vertical displacements of isopycnel surfaces are derived from thermistor chain data, and its power spectrum is analyzed to qualitatively interpret the high-frequency characteristics of internal wave. The internal wave spectra of low modes are estimated with the method of mode decomposition, which shows a steeper slope in [13, 46] cph band than that of Modified GM model. A regional spectrum model based on the Modified GM model is proposed in this paper, which demonstrates can better fit the experiment data. Moreover, energy density of internal waves is also estimated in this paper.