主动声呐恒包络波形设计及其性能分析

为主动声呐设计恒包络的伪随机编码MSK调制波形。通过分析MSK信号表达式,得到波形的复包络信号。使用遗传算法优化伪随机序列,降低波形的自相关旁瓣,可减小声呐的虚警概率。通过优化复包络信号的自相关函数旁瓣值和互相关函数值,得到自相关性能和正交性能优良的恒包络波形,可以缓解多部声呐间的同频干扰。通过仿真分析波形的模糊度图,波形具有良好的频率分辨率和距离分辨率,可以取代峰均比过高的编码调相信号,满足主动声呐对运动目标的探测需求。     

主动声纳恒包络波形设计及其性能分析

为了解决伪随机编码调相信号峰均比过高问题,为主动声纳设计恒包络的伪随机编码MSK调制波形。通过分析MSK信号表达式,得到波形的复包络信号。使用遗传算法优化伪随机序列,降低波形的自相关旁瓣,可减小声纳的虚警概率。通过优化复包络信号的自相关函数旁瓣值和互相关函数值,得到自相关性能和正交性能优良的恒包络波形,可以缓解多部声纳间的同频干扰。通过仿真分析波形的模糊度图可知,波形具有良好的频率分辨率和距离分辨率。该波形设计可以取代峰均比过高的编码调相信号,满足主动声纳对运动目标的探测需求。     

海豚Whistles为信息载体的正交频分复用循环移位键控扩频伪装水声通信

提出一种伪装水声通信调制方法,将原始海豚whistles信号表示为以自身DFT系数为数据符号的正交频分复用(OFDM)块,采用m序列对OFDM块中的子载波幅度进行指数调制实现正交频分复用循环移位键控(OFDM-CSK)扩频调制,分别采用PEAQ算法与相关系数计算听觉与波形相似度,作为两个客观评价结果约束OFDM子载波幅度的修改程度,保证伪装的效果。提出匹配滤波与正交匹配追踪结合的自同步算法,使伪装通信信号帧结构的设计保持原始whistles叫声的模式,提高了伪装的效果。通过CSK扩频技术很大程度地提高系统的频带利用率且通过垂直阵虚拟时间反转信道均衡技术提高了通信系统的稳健性。海上试验验证了伪装通信方法的可行性。      

基于循环前缀相关性的水声OFDM信号调制识别

为解决非合作通信系统中水声OFDM信号的类型识别,本文研究水声OFDM通信信号与常见单载波水声数字通信信号(MPSK,MFSK)之间的调制识别问题。考虑到水声信道复杂传播特性对循环前缀相关性的影响,本文通过截取信号前后片段并迭代搜索双相关峰进行无需先验知识的水声OFDM通信信号特征参数提取,在此基础上设计了一种基于模糊系统的水声OFDM通信信号识别器。对不同信道条件下海上实录信号数据的识别实验结果表明了本文方法的有效性。     

基于循环前缀相关性的水声OFDM信号调制识别方法*

本文研究水声OFDM通信信号与常见单载波水声数字通信信号(MPSK,MFSK)之间的调制识别问题。考虑到水声信道复杂传播特性对循环前缀相关性的影响,本文通过截取信号前后片段并迭代搜索双相关峰进行无需先验知识的水声OFDM通信信号特征参数提取,在此基础上设计了一种基于模糊系统的水声OFDM通信信号识别器。对不同信道条件下海上实录信号数据的识别实验结果表明了本文方法的有效性。     

二进制偏移载波调制的零相关窗水声同步技术研究

针对线性调频信号同步相关的旁瓣、m序列扩频同步的序列自噪声和二进制相移键控调制信号在主瓣周围一个码片范围内存在较强烈的旁瓣三个问题,提出了一种基于二进制偏移载波(BOC)调制信号的无干扰窗水声同步方式.利用互补序列的非周期自相关函数之和为零的特殊性质,实现了在主瓣周围一个码片范围外,零相关窗范围内的无干扰窗.使用BOC(1,1)方式对信号进行亚载波调制,以减少主瓣周围一个码片范围内的旁瓣.对单通道信号和双通道信号的零相关窗形式都进行了设计,通过仿真和实验验证了BOC零相关窗方法在水声系统的同步、信道测量和估计中的有效性.     

基于一体化波形的W波段光子辅助通信感知系统

提出并演示了一个光子辅助的集成雷达和通信系统,该系统利用光子辅助拍频在W波段产生毫米波信号。通过将正交相移键控（QPSK）信号编码到线性调频连续波（LFMCW）雷达信号上,实现了传感和通信波形的集成。一体化波形可以通过去啁啾分离通信信号与雷达感知信号,并通过脉冲压缩实现高分辨率感知。实验结果表明,在91 GHz频段内可实现单目标和双目标检测,感知精度约为2.0 cm。此外,成功实现了W波段下2 m、10 m和50 m传输距离的20 Gbit/s高质量无线通信。该系统还适用于各种成分的一体化波形,为高速通信和高分辨率雷达感知融合提供了有效参考。     

猝发混合扩频水声隐蔽通信技术

针对常规的连续载波调制扩频通信方式容易通过能量检测的方法被截获的问题,提出了一种猝发的混合扩频水声隐蔽通信方式,该方法通过在时间上随机的发送脉冲混合调制扩频信号来降低截获概率,而且可以比较灵活的通过调整平均占空比来满足不同隐蔽性的要求,但是该隐蔽性是以牺牲通信速率为代价的。猝发信号中混合了二进制相位键控(BPSK)、循环移位键控(CSK)和多进制频移键控(MFSK)扩频调制方式,采用自同步和时频二维搜索算法实现码元和载波同步。通过仿真分析了猝发通信系统的隐蔽性能和多途信道下的误码性能,并且通过了南海海试验证了算法的性能,在5 km的通信距离上,4 kHz的带宽内,单个脉冲信号的通信速率可以达到317 bps,误码率达到10-3以下。      

任意复包络信号的匀速运动目标回波脉间补偿及相干积累

现代声呐、水下制导等水声探测系统常常使用窄带脉冲、调制、编码、伪随机等种类繁多的发射信号波形来满足低信噪比检测、高分辨估计、抗干扰、主动隐蔽探测的应用需求.针对这一情况,本文研究了任意信号的长时间积累问题,给出了一种任意复包络信号的匀速运动目标回波脉间补偿及相干积累检测方法.通过构建任意发射信号波形的广义模糊函数,将匹配滤波器输出表示为所构造的广义模糊函数,使得任意复包络信号的脉压波形不仅能够用统一的数学模型来表述和计算,而且能够提供多脉冲回波的距离走动信息和多普勒频移信息,为多脉冲距离位置对齐和Fourier变换(FFT)积累提供了依据.对于用广义模糊函数表示的匹配滤波器输出,采用Keystone变换将复包络对齐,消除了距离走动,采用FFT补偿多普勒频移项,实现了任意复包络信号的长时间相干积累.对于水下探测中使用的连续波信号、线性调频信号以及复杂的m序列编码信号、Costas跳频编码信号波形进行了信号积累及检测的计算机仿真,验证了任意复包络信号的匀速运动目标回波脉间补偿及相干积累的正确性.消声水池实验验证了该方法的有效性.     

余弦BOC信号伪相关函数无模糊跟踪方法

二进制偏移载波 (binary offset carrier,BOC) 调制方式实现了频谱分离和频段共享,被应用于全球导航卫星系统中;但由于BOC信号自相关函数的主峰和副峰幅度差异较小,容易引起捕获和跟踪模糊,导致较大的测距误差;余弦相位BOC(Cosine-phased BOC,CosBOC)信号自相关函数形式相对复杂,给其无模糊处理带来了挑战;基于伪相关函数法(pseudo correlation function, PCF)思想,针对CosBOC信号设计本地参考信号的特殊码片波形,与接收信号相关后经过非线性组合可获得单峰无模糊相关函数,消除了跟踪模糊性;仿真结果表明:参数取值合适时该方法的跟踪和抗多径性能均优于同等条件下的BPSK-like方法。     

扩频原理在聚合物光纤性能测量中的应用

提出了一种将扩频通信原理用于聚合物光纤性能测量的新方法,使用伪随机序列对注入测量系统的光信号进行调制,实现输入光信号的扩展频带,输出光信号经光电转换后,用伪随机序列对信号进行解扩处理,根据扩频原理,解扩后的信号的信噪比会有较大提高.对测量系统的性能进行了仿真分析并与实验结果进行了比较,结果表明该方法可以精确地测量信噪比低于-20 dB的有用信号波形.     

大气激光通信非对称限幅光正交频分复用技术

将一种新的正交频分复用调制技术运用到大气激光通信系统中,分析了采用这种非对称限幅光正交频分复用调制技术的大气激光通信系统在大气湍流信道下的性能.在此基础上,把非对称限幅光正交频分复用调制方案与传统的开关键控及直流偏置光正交频分复用调制方案进行了比较,并在大气湍流信道中进行了仿真.仿真结果表明:非对称限幅光正交频分复用调...     

Multi-task learning approach for modulation and wireless signal classification for 5G and beyond: Edge deployment via model compression

Future communication networks must address the scarce spectrum to accommodate extensive growth of heterogeneous wireless devices. Efforts are underway to address spectrum coexistence, enhance spectrum awareness, and bolster authentication schemes. Wireless signal recognition is becoming increasingly more significant for spectrum monitoring, spectrum management, secure communications, among others. Consequently, comprehensive spectrum awareness on the edge has the potential to serve as a key enabler for the emerging beyond 5G (fifth generation) networks. State-of-the-art studies in this domain have (i) only focused on a single task – modulation or signal (protocol) classification – which in many cases is insufficient information for a system to act on, (ii) consider either radar or communication waveforms (homogeneous waveform category), and (iii) does not address edge deployment during neural network design phase. In this work, for the first time in the wireless communication domain, we exploit the potential of deep neural networks based multi-task learning (MTL) framework to simultaneously learn modulation and signal classification tasks while considering heterogeneous wireless signals such as radar and communication waveforms in the electromagnetic spectrum. The proposed MTL architecture benefits from the mutual relation between the two tasks in improving the classification accuracy as well as the learning efficiency with a lightweight neural network model. We additionally include experimental evaluations of the model with over-the-air collected samples and demonstrate first-hand insight on model compression along with deep learning pipeline for deployment on resource-constrained edge devices. We demonstrate significant computational, memory, and accuracy improvement of the proposed model over two reference architectures. In addition to modeling a lightweight MTL model suitable for resource-constrained embedded radio platforms, we provide a comprehensive heterogeneous wireless signals dataset for public use.     

A Signal processing method of OFDM communication receiver based on CNN

Orthogonal frequency division multiplexing (OFDM) the signal processing is a key issue in wireless communication research. The multipath effect and Doppler shift of wireless communication channels can lead to distortion of the transmitted signal, which poses a considerable challenge to the information recovery of communication receivers. This paper presents the signal processing method of OFDM communication based on convolutional neural network (CNN). The method replaces all signal processing modules of the OFDM communication receiver with CNN, and the information is recovered by the CNN. In order to adapt to the processing of communication signals, we designed a one-dimensional convolutional neural network (1D-CONV-CNN) model as the neural network structures by this method. Simulation results indicate that the signal processing method effectively reduces the bit error rate (BER) and improves its performance compared with the conventional reception method under different channel conditions.     

Resource block Filtered-OFDM for future spectrally agile and power efficient systems

Spectrum sharing is a common paradigm in future communication systems and a spectrally agile baseband waveform with minimal out-of-band emissions is a critical component. In this paper, we propose a new multicarrier modulation technique, called resource block Filtered-OFDM (RB-F-OFDM) and present the transceiver design. This waveform can be used over channels with non-contiguous spectrum fragments and exhibits very low adjacent channel interference, which is required for cognitive radio systems with multi channel carrier aggregation capabilities. As such, regulatory based very stringent adjacent channel leakage ratio (ACLR) and adjacent channel selectivity (ACS) requirements can be met. We show that the transceiver complexity may be reduced by utilizing an efficient polyphase implementation that is commonly used in the filter bank multicarrier (FBMC) modulation. In addition, some efficient peak-to-average power ratio (PAPR) reduction techniques can be naturally applied. The new design is backwards compatible with legacy OFDM based systems. Simulation results to evaluate the performance, including measured bit error rate (BER) in multipath channels, are provided.     

Spread spectrum communication system with chaotic frequency modulation

A new spread spectrum communication system utilizing chaotic frequency modulation of sinusoidal signals is discussed. A single phase lock loop (PLL) system in the receiver is used both to synchronize the local chaotic oscillator and to recover the information signal. We study the dynamics of the synchronization process, stability of the PLL system, and evaluate the bit-error-rate performance of this chaos-based communication system.     

Optical orthogonal frequency division multiplexed transmission using all‐optical discrete Fourier transform

Orthogonal frequency division multiplexing (OFDM) can provide spectrally efficient communication channels because it can utilize carrier orthogonality and various impairment mitigation methods. An optical OFDM signal can be generated electronically to multiplex lower‐rate carriers. In recent advancements, OFDM signals are also shown to be generated and demultiplexed by all‐optical discrete Fourier transform (DFT), overcoming the speed limit of electronics for >Tbps capacity. High‐performance DFT devices, such as arrayed waveguide grating (AWG) or planar lightwave circuit (PLC), are critically required to obtain strong orthogonality for scalable all‐optical OFDM (AO‐OFDM) system implementations. Advanced techniques such as coherent modulation and detection with digital impairment mitigation are also important for long‐reach AO‐OFDM transmissions. More recently, optical superchannel schemes have been introduced utilizing coherent detection for multi‐Tbps AO‐OFDM transmissions. This paper reviews the device and system aspects for the AO‐OFDM technology, including a generalized theoretical model to provide an indepth understanding.     

Constrained radar waveform optimization for a cooperative radar-communication system

The coexistence of radar-sensing and communication systems research has received a surge of interest in recent times to tackle the issue of spectrum inadequacy. Designing an optimized radar waveform for a coexistence scenario has been a challenging task for accomplishing the convergence of radar-sensing and communication functionalities, without degrading the performance at either end. This paper proposes a novel global optimization-based Spatial Branch and Bound (SBnB) approach to optimize the phase coefficients of a Non-Linear Frequency Modulated (NLFM) waveform in a CRCS framework. In addition, the Modified-Power Ratio Constraint-Cramér–Rao Lower Bound (M-PRC-CRLB), a local optimization-based approach is proposed to optimize the phase coefficients of an NLFM waveform. The spectral energy distribution and auto-correlation characteristics of an NLFM waveform are comprehensively investigated for various values of polynomial order (N) and at different threshold Signal-to-Noise-Ratio (SNR) values. To compare the proposed waveform design approaches (M-PRC-CRLB, SBnB) with the existing waveform design approaches namely, Minimum Estimation Error Variance (MEEV) and PRC- CRLB, a Peak-to-Side-Lobe-Ratio (PSLR), and Integrated-Side-Lobe-Ratio (ISLR) are evaluated at various polynomial orders and threshold SNR values. Furthermore, the performance of a CRCS is assessed using the radar estimation rate and communication data rate. The simulation results reveal that the proposed optimized radar waveform design approaches provide improved performance compared to the existing radar waveform design approaches in terms of radar estimation rate. Further, the proposed global optimization-based SBnB approach achieves a comparable performance of the communication data rate. In addition, the proposed approaches accomplish enhanced spectral utilization, controlled side-lobe energy levels, reduced range-domain ambiguities, and a higher information rate in a CRCS.