基于正交时频空间调制的移动无人平台水声通信算法OA
Underwater Acoustic Communication Algorithm for Mobile Unmanned Platform Based on Orthogonal Time Frequency Space Modulation
水下平台快速移动时会给水声通信系统带来严重的多普勒频移影响,传统通信系统及信道估计方法无法有效应对此类问题.本文从移动环境水声信道特征出发,通过理论与仿真实验研究移动环境下正交时频空间(OTFS)调制水声通信技术.首先,搭建了模拟水声信道与通信框架,对比分析了正交频分复用(OFDM)技术与OTFS技术在移动水下环境中的性能表现,从而验证了 OTFS技术在快速移动的水下无人平台(AUV)通信系统中应用的必要性和可行性;其次,将一种基于变分推断和稀疏贝叶斯学习的信道估计方法与传统信道估计方法进行对比,综合评估其在OTFS技术中的性能优势;最后,在OTFS实际水声通信系统中应用优化的变分稀疏贝叶斯(OVSB)信道估计方法,验证了仿真结果的准确性.
Traditional communication systems and conventional channel estimation methods are often inadequate for ef-fectively mitigating the severe Doppler frequency shifts caused by the rapid movement of underwater platforms in acoustic communication scenarios.Starting from the characteristics of underwater acoustic channels in mobile environments,this paper investigates OTFS(orthogonal time frequency space)modulation for underwater acoustic communication through the-oretical analysis and simulation studies.A simulated underwater acoustic channel and communication framework is devel-oped to compare the performance of OFDM(orthogonal frequency division multiplexing)and OTFS in dynamic underwater conditions,thereby demonstrating the necessity and feasibility of deploying OTFS in communication systems for high-speed AUVs(autonomous underwater vehicles).To further enhance the system performance,a channel estimation method based on variational inference and sparse Bayesian learning is evaluated against conventional approaches,highlighting its advantages within the OTFS framework.Moreover,the proposed OVSB(optimized variational sparse Bayesian)estimation method is integrated into a practical OTFS-based underwater acoustic communication system,and experimental results confirm the accuracy of simulation predictions.
吕志超;王刚;于菲;李虎明;王相宇
山东科技大学海洋科学与工程学院,山东青岛 266590山东科技大学海洋科学与工程学院,山东青岛 266590山东科技大学海洋科学与工程学院,山东青岛 266590山东科技大学海洋科学与工程学院,山东青岛 266590山东科技大学海洋科学与工程学院,山东青岛 266590
OTFS(正交时频空间)调制移动水声通信变分推断稀疏贝叶斯水下无人平台
OTFS(orthogonal time frequency space)modulationmobile underwater acoustic communicationvariational inferencesparse BayesianAUV(autonomous underwater vehicle)
《机器人》 2026 (3)
452-460,9
国家重点研发计划(2023YFB390720202)水声通信与海洋信息技术教育部重点实验室基金(UAC202305)青岛市自然科学基金(23-2-1-100-zyyd-jch).
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