QIAO Fei1， JIANG Jiajia1， LI Yao2， LI Chunyue1， LI Zhuochen1， DUAN Fajie1， FU Xiao1
（1. State Key Lab of Precision Measuring Technology and Instruments， Tianjin University， Tianjin 300072, China； 2. Systems Engineering Research Institute, China State Shipbuilding Corporation, Beijing 100036, China）
Abstract： Bionic covert camouflage underwater acoustic communication has recently attracted great attention. However, we have not found relevant methods or literatures to recognize these bionic camouflage communication signals (BCCS) in the area of anti-reconnaissance. Focused on recognizing the BCCS, we propose a recognition method based on the statistics of multi-features of the cetacean whistle time-frequency contour (TFC) to recognize the camouflaged whistle communication train (CWCT) which is modulated by abrupt linear frequency modulation (LFM) signals. Firstly, by analyzing the characteristics of distributions of real and bionic TFCs, we know that the real whistle is a sweep signal whose TFC is continuously distributed. According to the coding principle, the CWCTs use piecewise LFM signals with different time lengths to imitate whistle TFC to transmit information. Considering the multi-features of non-cooperative signal through screening for the abrupt shifts in frequency, the detection results of linear correlation of instantaneous frequency curves (IFCs) and the statistics of time lengths of piecewise LFM, we can recognize the CWCTs. The simulation results show that the proposed recognition method can achieve excellent accuracy up to 80% under different conditions, including SNRs, coding times, coding quantities and underwater acoustic channels. It achieves simple and effective extraction of whistle sound and its TFC, which is of reference significance to recognize the BCCSs modulated by other coding methods.
Key words： bionic camouflage communication signal (BCCS)； linear frequency modulation (LFM) signal； signal recognition； extraction of time-frequency feature； multi-feature recognition
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基于线性突变调频信号调制的仿鲸声伪装通信信号的识别方法
乔飞1， 蒋佳佳1， 李遥2， 李春月1， 李卓尘1， 段发阶1， 傅骁1
（1. 天津大学 精密测量技术与仪器国家重点实验室， 天津 300072； 2. 中国船舶工业 系统工程研究院， 北京 100036）
摘要:近年来， 仿生伪装水声通信技术引起了广泛的关注。 然而， 在反侦察技术中， 目前还没有发现相关的方法和文献来识别仿生伪装水声通信信号。 为实现对这类仿生伪装水声通信信号准确识别， 提出了一种基于鲸类哨声时频轮廓多种特征统计的识别方法来识别基于线性调频信号调制的仿鲸类哨声伪装水声通信信号。 首先， 分析真实时频轮廓与仿生时频轮廓的分布特征可知， 真实哨声信号为扫频信号， 其时频轮廓连续分布。 根据编码原理， 仿哨声通信信号使用不同时长的分段线性调频信号模拟真实时频轮廓传递信息。 通过对接收非合作信号的频率突变点筛选， 短时频率曲线线性相关性检测及时宽数据分组统计， 综合分析多种特征， 实现仿鲸类哨声伪装水声通信信号的识别。 仿真实验结果表明， 该识别方法在不同信噪比、 编码时间、 编码量和水声信道条件下均可实现80%的识别正确率。 因而， 该方法可实现哨声信号及其时频轮廓的简单快速提取， 对识别其他编码方式的仿鲸声伪装通信信号具有参考意义。
关键词:仿生伪装通信； 线性调频信号； 信号识别； 时频特征提取； 多特征识别
引用格式：QIAO Fei, JIANG Jiajia, LI Yao, et al． Recognition method for bionic camouflage cetacean whistle communication trains modulated by abrupt LFM signals． Journal of Measurement Science and Instrumentation， 2023， 14（1）： 25-34. DOI： 10．3969／j．issn．1674-8042．2023．01．004
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