通信学报2025，Vol.46Issue(1)：67-78,12.DOI:10.11959/j.issn.1000-436x.2025017
基于阵列的神经网络水声通信信号多参数联合估计算法
Array-based neural network algorithm for multi-parameter joint estimation of underwater acoustic communication signals
摘要
Abstract
To address the challenges posed by complex and highly variable underwater acoustic channel(UWAC)with severe attenuation,a novel neural network algorithm was proposed for multi-parameter joint estimation.Multi-channel spectrograms derived from array signals were utilized by the algorithm to improve the detection probability of UWAC signals under non-cooperative conditions and extend the sensing range.A carrier frequency label assignment strategy was designed,in which carrier frequency served as the key physical feature to distinguish different signals,thereby effec-tively mitigating interference from out-of-band signals and noise.End-to-end multi-task learning was adopted to simulta-neously perform signal detection,modulation recognition,and joint estimation of the number of signal sources,carrier frequency,bandwidth,and direction of arrival,eliminating the complex beamforming process typically required in tradi-tional methods before detection and recognition.Simulation results confirm that accurate signal estimation is reliably achieved even in the presence of array element position mismatches and when signals are obscured by noise.Lake ex-periments further demonstrate the practicality and generalization capability of the proposed algorithm.关键词
多参数联合估计/波达方向估计/调制模式识别/阵列信号处理/神经网络Key words
multi-parameter joint estimation/direction of arrival estimation/modulation recognition/array signal process-ing/neural network分类
电子信息工程引用本文复制引用
成乐,刘悦,胡正良,朱宏娜,罗斌..基于阵列的神经网络水声通信信号多参数联合估计算法[J].通信学报,2025,46(1):67-78,12.基金项目
国家重点研发计划基金资助项目(No.2021YFC3101402,No.SQ2021YFF0500035) The National Key Research and Development Program of China(No.2021YFC3101402,No.SQ2021YFF0500035) （No.2021YFC3101402,No.SQ2021YFF0500035）
