A new method for improving the inductively coupled data transmission rate of mooring buoy based on carrier signal frequency selection

In the inductively coupled data transmission system of the mooring buoy, the carrier signal frequency of the transmission channel is limited due to the inherent characteristics of the system, resulting in limited channel bandwidth. The limited channel bandwidth limits the increase in inductively coupled data transmission rate.In order to improve the inductively coupled data transmission rate of mooring buoy as much as possible without damaging the data transmission performance, a new method was proposed in this paper. The method is proposed to improve the data transmission rate by selecting the appropriate carrier signal frequencies based on the principle of maximizing the amplitude value of amplitude-frequency characteristic curve of the system. Research has been done according to this method as follows. Firstly, according to the inductively coupled transmission mooring buoy structure, the inductively coupled data transmission circuit model was established. The binary frequency shift keying(2FSK) digital signal modulation mode was selected. Through theoretical analysis, the relation between the carrier signal frequency and the data transmission performance, the relation between the carrier signal frequency and the 2FSK signal bandwidth were obtained. Secondly, the performance and the bandwidth of the signal transmission were studied for the inherent characteristics of the actual inductively coupled data transmission system. The amplitude-frequency characteristic of the system was analyzed by experiments. By selecting the appropriate carrier signal frequency parameters, an excellent data transmission performance was guaranteed and a large 2FSK signal bandwidth was obtained. Finally, an inductively coupled data transmission rate optimization experiment and a bit error rate analysis experiment were designed and carried out. The results show that the high-speed and reliable data transmission of the system was realized and the rate can reach 100 kbps.

Carrier frequency and symbol rate estimation based on cyclic spectrum

Carrier frequency and symbol rate estimation are the main contents of parameter estimation,which is the basis of modulation recognition and further processing of signals especially in non-cooperative communication.With the development of wireless communication,the signal transmission environment has become increasingly bad,causing more difficulties in parameter estimation.It is well known that the signal cycle spectrum is robust to noises and signal parameters are closely related.In practice,it is impossible to calculate the cyclic spectrum of infinite length data signals.When using finite length data to obtain a cycle spectrum,the truncation noise is induced,resulting in interference.It is necessary to overcome the influence of noises in order to improve the detection ability of discrete spectral lines.An improved method of the discrete spectral line extraction algorithm is proposed by reflecting the amplitude advantage of discrete spectral lines through salient features of continuous noises in discrete spectral line neighborhood.

基于多载波调制技术的无线短波通信多频段信号增强研究

在现代无线通信系统中,多载波调制技术由于其高效的频谱利用和强大的信号处理能力,成为实现可靠通信的关键技术之一。这项技术特别适用于复杂的短波通信环境,其中信号容易受到多路径效应和频率选择性衰落的影响。文章综合研究了多载波调制技术在无线短波通信中的应用,并提出了一系列信号增强措施,包括多载波调制参数的优化、多频段信号的同步与校准、功率控制与信号优化的集成技术以及针对频段拥堵的动态频率分配策略。此外,文章还通过技术应用测试验证了这些策略的有效性,结果显示这些策略能显著提升短波通信系统的性能和可靠性。

基于窄带频谱分析的电力线载波通信干扰过滤技术

电力线路载波通信受到背景噪声、脉冲噪声等方面干扰因素影响,导致通信信号质量下降,为此提出一种基于窄带频谱分析的通信干扰过滤技术。首先构建近似模型分析通信信号特征,利用马尔可夫链模拟信道上脉冲噪声状态。然后基于窄带频谱分析算法,在信号频谱周期图下,利用正交数据窗分离直接频谱,筛选估计方差以避免频谱泄漏事件的发生。利用傅里叶变换计算特征频谱,估计信号能量的集中特性,分析通信信号,平衡信号振幅和干扰抑制。最后通过时频峰值实施干扰滤波,有效保证电力线载波通信信号质量。经过实验数据分析证明,所提技术的载波干扰幅值最小值为1.1 dB,载波通信信号误码率平均值为1.9%,方法耗时平均值为3.8 s。

Quality monitoring and biases estimation of BOC navigation signals

Many safety-critical applications that utilize the global navigation satellite system (GNSS) demand highly accurate positioning information, as well as highly integrity and reliability. Due to GNSS signals are easily distorted by the interferences or disturbances, the signal quality monitoring (SQM) is necessary to detect the presence of dangerous signal distortions. In this paper, we developed an SQM software for binary offset carrier (BOC) modulated navigation signals. Firstly, the models of BOC signal with ideal and distortion are presented respectively. Then the architecture of SQM software is proposed. Moreover, the effect of the white gaussian noise (WGN) and the front-end filter on the correlation peak of the receiver is analyzed. Finally, the biases induced by the signal distortion are evaluated. The experiments simulate the relationships between the code phase shift and the normalized correlation value in the case of the signal digital distortion and the analog distortion. The simulation results demonstrate that the proposed SQM method can effectively monitor the signal distortion and accurately estimate the correlation peak deviation caused by the distortion.

基于可微分架构搜索的多载波信号自动调制识别

针对城市多径信道下缺乏多载波信号通用数据集,以及传统信号特征与网络模型难以有效识别低信噪比下失真信号调制类型的问题,提出一种基于可微分架构搜索的多载波信号自动调制识别算法。首先,产生了常见OFDM、FBMC与OTFS多载波信号经过典型城市多径信道的接收信号数据集,选取对调制参数不敏感的信号时频图作为特征向量来训练神经网络;其次,采用可微分架构搜索方法自动搜索最佳网络结构,避免了网络结构设计的反复验证工作;最后,在特征学习过程中引入联合注意力机制,将失真信号特征进行空间转换以降低多径干扰影响,同时计算特征图各通道信息权重并排序,以提升相关特征图通道的分类效果。仿真结果表明,所提算法不仅能提升在城市多径信道环境下尤其是低信噪比时的识别正确率,而且对调制参数变化和小样本场景具有更好的鲁棒性。

Carrier Synchronization for Very Low SNR

The Turbo decoding performance will suffer serious degradation under low signal-to-noise ratios （SNR） conditions for the reason of residual frequency and phase offset in the carrier. In this paper, an improved residual carrier frequency offset estimation algorithm based on a priori probability aided （APPA） phase estimation is proposed. A carrier synchronization loop that combines the iterative turbo decoder and the phase estimator together is constructed, where the extrinsic information obtained from the Turbo decoder is used to aid an iterative phase estimation process. The simulation results show that the algorithm performs successfully under very low SNR conditions （for example, less than -7.4 dB） with large frequency offset and phase error and the performance of this algorithm is very close to the optimally synchronized system.

Continuous-Wave Interference Mitigation for Acquisition Method in Unified Carrier TT&C Systems

An interference mitigation for acquisition method,based on both energy center and spectrum symmetry detection,has been proposed as a possible solution to the problem of signal acquisition susceptibility to continuous-wave interference(CWI)in unified carrier telemetry,tracking,and command(TT&C)systems.With subcarrier modulation index as a priori condition,the existence of CWI is determined by comparing the energy center with the symmetric center.In the presence of interference,the interference frequency point is assumed and culled;sequentially,the spectral symmetry is used to verify whether the signal acquisition is realized.Theoretical analysis,simulations,and experimental results demonstrate that the method can realize the acquisition of the main carrier target signal with an interference-to-signal ratio of 31 dB,which represents an improvement over the existing continuous-wave interference mitigation for acquisition methods.

高速低载频比传感信号下的逆变器有源阻尼自适应控制

逆变器工作在高频运行和控制载波比低的情况下,存在谐振尖峰抑制,提出了高速低载频比传感信号下的逆变器有源阻尼自适应控制技术。在高速低载频比传感信号下,构建逆变器数学模型。输出电流到电容电压与定子电流之间的传递函数,将逆变器的有源阻尼等效成一个控制电压环。调整有源阻尼自适应控制回路的参数,制定逆变器有源阻尼自适应控制策略。实验结果表明:文中技术的稳定裕度由2.46 dB下降至1.18 dB,可以保证逆变器的稳定运行;在不同采样频率下,可以控制逆变器输出与电网电压相同相位和频率的并网电流,其中在采样频率为5.9f时,输出并网电流和电压均表现为正弦状态,波动范围分别为[35 A,58 A]和[185 V,225 V],具有较好的控制效果。

适用于任意阶数的BOC信号无模糊度捕获算法

针对二进制偏移载波(binary offset carrier, BOC)调制信号在捕获过程中的模糊度问题,提出了一种基于自相关函数加减互补的BOC(m,n)信号无模糊度捕获算法。根据副载波脉冲周期延拓的特性,通过拆分副载波,进而分离自相关函数,将关于码相位对称的第一个子相关函数和最后一个子相关函数做加减法运算后求差值,最后通过取模求和运算将旁峰完全消除。理论和仿真实验结果表明,该算法的适应性良好,适用于任意阶数的BOC调制信号,并且可以完全消除旁峰,保留窄相关峰特性。相比于SCPC、ASPeCT和BPSK-Like三种传统BOC信号无模糊度捕获算法,该算法的载噪比性能有约1.5~4.5 dBHz提高。

基于高动态环境下B2a信号的双通道跟踪算法

在北斗三号B2a信号中,针对在高动态环境下信号多普勒变化较大,导致导航接收机跟踪环路收敛速度较慢、稳定性差等问题,基于北斗B2a信号传统跟踪环路算法设计出基于三阶锁频辅助四阶锁相的双通道联合跟踪载波跟踪环,并对此跟踪算法进行仿真分析。实验结果表明双通道联合跟踪算法对信号的利用率明显提升且环路收敛速度快,在信号较差的情况下也能实现稳定跟踪,并且稳定性和准确度明显提升。

微波宽带超高精度双向时间比对技术研究

当前微波双向时间比对技术广泛应用于视距区域站间时间同步领域,能够达到纳秒站间时间同步水平,对于时间同步指标更高的应用场景还有待进一步提升。本文利用大带宽扩频信号和载波相位在时间测量性能方面的潜在优异性能,提出了基于宽带信号调制解调技术的微波双向载波相位时间比对方法,设计了原型试验系统,利用氢原子钟和相位微跃计验证了实验室条件下系统的测量不确定度(A类)0.27 ps和分辨力4 ps,达到了预期效果,为后续远距离试验和应用推广奠定了坚实的技术和试验基础。

基于北斗导航系统的三频载波相位高精度时间长距离传递方法研究

全球导航卫星系统(GNSS)是高精度时间长距离传递技术重要应用手段。针对高精度时间长距离传递受限于全球定位系统(GPS)载波信号组合的问题,该文提出一种基于北斗导航系统(BDS)的三频载波相位高精度时间长距离传递方法。分别对BDS不同载波信号B1、B2、B3进行两两组合,通过二次叠加无电离层,消弱各种全链路误差影响,验证了B12和B13组合时间传递精度最低,B13和B23组合时间传递精度最高,3种组合的时间传递均方根(RMS)误差差异不超过0.03 ns。与国际精密钟差产品比较,结果表明在2600 km的时间链上,基于BDS的三频载波相位的时间传递均方根误差小于0.244 ns,基于BDS的三频载波相位长距离时间传递可以实现亚纳秒级,可为全球导航卫星系统应用提供技术支撑。

一种无线电信号的模拟调制参数测量系统设计

无线电信号的模拟调制参数测量在无线电检测定位、通信发射机测试校准,民用船舶的导航通信等领域都有广泛应用。设计实现了一种基于超外差结构的无线电信号模拟调制参数的测量系统,以STM32F4系列单片机作为控制核心,包括的主要硬件电路模块有本振信号源、混频器、LC无源滤波器、锁相环、低噪声放大器、包络检波电路、鉴频电路等。系统可自动识别普通调幅波、调频波、未调制的单频载波等模拟调制类型,完成无线电信号解调输出的同时自动测量出载波频率、调制信号频率、调幅指数、调频指数等主要调制参数。实测结果表明,系统对调制类型识别正确,调幅或调频信号的解调波形信噪比高、无明显失真,载波频率测量的相对误差小于10-5,主要调制参数测量的相对误差均小于5%。

基于无人机平台的电磁信号探测系统设计

针对战场电磁环境机动监测需求,运用电磁信号感知与可视化分析技术,设计了一种基于无人机平台的战场电磁信号探测系统,构建了基于改进的FFT Pruning算法和Welch功率谱估计算法的频率中心计算模型,可实现复杂电磁环境下目标信号的频率、带宽、功率等参数检测,为部(分)队提供了机动、轻型、便捷的电磁信号监测手段。

基于卡尔曼和扩展卡尔曼滤波的耦合载波跟踪方法

鉴于低信噪比高动态环境下的载波跟踪过程中,接收信号存在显著的各阶频偏变化率,故提出了一种基于卡尔曼和扩展卡尔曼滤波的耦合载波跟踪方法。载波跟踪通过基于卡尔曼滤波的锁频环辅助基于扩展卡尔曼滤波的锁相环来实现,对频率斜升信号和频率加速信号分别进行了载波跟踪环路结构的分析,得到系统方程,并进行了载波跟踪系统性能仿真。经仿真验证,在信噪比为-20 dB条件下,该方法跟踪频率斜升信号收敛时间小于60 ms,跟踪频率加速信号收敛时间小于90 ms,对两种信号的频率跟踪残差均小于5 Hz,相位跟踪残差均小于0.25rad,跟踪性能显著优于传统环路。

基于BP神经网络的雷达信号载波频率测量

现代电子战争中常通过电子侦察的方式获取敌方雷达的各种信息,雷达信号的载波频率是后续进行辐射源识别、干扰和抗干扰的一个重要参数。鉴于神经网络对数据优异的多维函数表征能力,设计了一种架构简单的基于神经网络的雷达信号载波频率快速测量方法。首先对含有噪声的雷达信号进行采样,对采样得到的每个信号的频率进行标注,预处理获得信号样本数据集。然后将数据集划分为训练集和测试集合,输入到BP神经网络中进行频率拟合。最后,向训练所得的网络模型输入射频采样得到的时域信号,网络输出信号瞬时频率值。在输入信号频率范围为0.2~2.6 GHz,信噪比为30 dB的条件下,对该网络进行多次随机重复测试,实验结果显示输入信号频率估计值均方根误差优于5 MHz。

基于多参数识别的电力载波通信信号监测系统设计

电力载波通信信号在传输过程中存在衰减,为降低电力载波通信传输误码率,实时监测信号传输行为,设计了基于多参数识别的电力载波通信信号监测系统。根据动态遗忘因子取值范围,建立多参数识别机制,再联合相关载波通信数据,求解信号衰减参数,完成对电力载波通信的可行性分析。按照载波通信体系整体架构的布局形式,确定滤波器、耦合器元件所属连接位置,完成电力载波通信信号监测系统设计。对比实验结果表明,在多参数识别机制作用下,电力载波通信传输误码率最大值仅为23.5%,在实时监测信号传输行为方面具有突出应用价值。

电力机房巡检机器人载波通信异常信号识别研究

电力机房机器人载波通信中,受到电力机房设备干扰,产生隐蔽式异常信号。设计基于卡尔曼滤波的电力机房巡检机器人载波信号异常信号识别方法。首先引入卡尔曼滤波模型,滤除机器人载波通信中存在的噪声,计算平均频率偏差,结合小波连续变换对信号码元幅值分解,锁定异常信号突变的范围,实现异常信号的识别。通过测试结果表明,所设计的异常信号识别方法,能够有效检测出电力机房巡检机器人两个时间段的隐蔽异常信号,验证了设计方法的识别效果。

极端数据辅助的RSSE-PSP盲分离算法

针对逐幸存路径处理(PSP)算法在处理成对载波多址(PCMA)信号盲分离问题时复杂度过高的问题,提出一种基于极端数据辅助的减状态序列估计逐幸存路径处理(RSSE-PSP)盲分离算法。该算法基于PCMA信号中存在部分极端数据,按照单路源信号的参数估计结果去除频偏、相偏后能够凸显出极端数据,充分利用这部分极端数据,可以直接解调出源信号相应位置的传输符号,继而在PSP算法进行序列估计的过程中减少需要遍历的状态数,有效降低了PSP算法的复杂度,同时避免了极端符号位置的误码。仿真实验表明,在较高信噪比条件下,RSSE-PSP算法在分离复杂度和分离性能方面均优于传统的PSP算法。