基于FPGA的跳频通信系统开发

为了提高通信的抗干扰和保密性,对跳频通信进行了研究,通过分析跳频通信的实现方式,提出基于FPGA的跳频通信系统实现方案。该方案中发端信号采用QPSK调制,接收端采用超外差接收以达到减少噪声和提高接收灵敏度的效果,接收端跳频同步采用等待自同步的跳频捕获和基于延迟锁相环的跳频跟踪。测试结果表明所设计的跳频通信系统可以正确实现跳频通信。与传统跳频通信实现方案相比,该方案具有灵活性强、开发周期短、开发费用低等优点。     

混沌的可加性

从理论上推导了由几个混沌时间序列构成的新序列的动力学特性，提出了可加性的概念.计 算机仿真结果说明，新的时间序列具有分维吸引子，对初始值很敏感，两条邻近轨道随着时 间的增加呈现指数分离，具有短期可预测性，因此新序列也是混沌序列，即混沌具有可加性 .混沌时间序列的可加性理论不仅具有重要的理论意义，而且具有重要的应用价值，它是研 究多跳频电台的跳频码的理论基础. 关键词： 混沌时间序列 吸引子 分维 可加性     

一种异步非正交跳频网台盲分选方法

提出了一种新体制跳频网台盲分选方法,针对跳频通信异步非正交组网方式,将基于最大信噪比算法的盲源分离技术应用于跳频网台分选。建立了跳频网台盲分选仿真数学模型并进行了多跳频网台分选仿真。仿真结果验证了盲源分离技术应用在跳频网台分选中的可行性和有效性,得出了跳频网台盲分选方法对异步非正交组网方式的分选性能。     

基于光纤布拉格光栅编解码器的直接序列扩频跳频光码分多址系统

提出了一种混合直扩跳频光纤码分多址（DS／FH－OCDMA）系统的实现方法，该系统采用跳频素数码作为扩频码，运用了光纤布拉格光栅序列作为编解码器，并在解码器两端安置了双硬限幅器以提高系统的性能，理论分析和仿真结果表明，该系统具有大用户容量，高功率效率和低误码率等方面的优点。     

一种基于扩展素数码和单重合序列的二维光正交码EPC/OCS

以扩展素数码(EPC)作为时间扩频伪随机序列,单重合序列(OCS)作为波长跳频伪随机序列,构造了一种新的二维光正交码EPC/OCS,并分析了码字的互相关性能.与修正素数跳频码MPHC相比,EPC/OCS的波长数并不局限于素数,可以是任意整数,不仅构造灵活,而且可充分利用MW OCDMA系统的有效波长数.当系统的有效波长数大于某个素数时,EPC/OCS不仅码字容量大于MPHC,而且互相关性能也有所改善.理论分析表明,EPC/OCS可降低MW OCDMA系统误码率.     

面向信号的仪器控制模型研究

在复杂电磁场的背景下,捕获良好短波电台的信号是人们研究的重要议题。在研究短波跳频电台的的干扰特点的基础上,利用最小均方误差（Least Mean Squares,LMS）算法对干扰进行抵消。基于LMS算法的研究提出的变步长LMS算法函数建模;基于短波跳频电台的研究对,在Simulink环境下进行电台仿真建模。将新算法嵌入自定义模块中并与加干扰的电台模型联合仿真。仿真结果表明,新算法模块的加入可以有效对短波跳频电台的干扰进行抑制。自定义的LMS算法模型的建立对新算法的开发应用打下了基础、在复杂战场环境下有效保障短波跳频电台正常工作提出了新思路。     

脉内跳频信号研究

以频率跳变方式逼近任意的信号频率调制规律是设计复杂信号的有效方法。本文研究了在声信号检测中应用这种“脉内跳频信号”的一些基本问题。 首先,本文对脉内跳频信号的检测模糊度函数作了计算和分析,说明了信号频率量化所引起的检测模糊度函数的量化效应。接着指出,为了消除信号相位起伏对检测性能的影响,脉内跳频信号适宜于用“检波后匹配处理器”实现“最佳”处理。这种信号处理器的检测响应函数已经导出,并通过分析和“全相干检测器”的性能作了对比。最后,本文给出了一个“数控跳频信号源”的原理方案。其中,信号的跳频规律由指令装置按预定的数码控制,并且便于同“检波后匹配处理器”直接配合而组成完整的信号检测系统。     

跳频通信系统脉冲同步干扰仿真研究

跳频技术是目前通信领域应用非常广泛的一种通信方式。当跳速足够高、跳频带宽足够宽时,常规的干扰方法往往难以奏效。提出利用脉冲干扰信号对跳频信号的同步部分进行干扰的方法,并在MATLAB中建立典型跳频通信系统的信号级干扰仿真系统,采用脉冲信号进行干扰仿真研究。结果表明,脉冲干扰信号是一种对抗跳频通信的可行方式,针对跳频通信系统的同步部分进行干扰可以有效降低对脉冲信号源的综合指标要求。     

基于跳频通信的移动机械遥控系统

为解决在同一个工作区域多个无线通信网络容易彼此干扰无法协同工作的问题,以移动机械工程车辆为控制对象,设计JRCJ500无线遥控系统,由用户手持终端接收用户操作指令,现场控制器驱动远程设备动作,实现对车辆的远程操作控制与状态信息反馈;采用STM32L低功耗处理器设计无线通信模块,选择公用通信频段,基于跳频扩频通信技术,约定无线通信数据格式与跳频频点,通过简单高效的跳频图案生成算法,在每一帧数据中添加同步字头,实现了无线通信网络的快速同步组网,保证了通信的稳定性,实现了在限定工作区域多台无线通信设备同时工作的应用需求。由于采用模块化设计,系统具有良好的通用性和可移植性,能够在多种复杂恶劣工作场合实现远程控制功能。     

二维旋转谐振子势中单粒子的跳频压缩及演化

本文主要研究二维旋转谐振子势中单粒子的动力学行为,通过跳频的方式分析该粒子的压缩演化过程,并分析了相应的物理机制.一方面,研究跳频过程对回旋半径模式的压缩演化,通过选择适当的跳频时刻,分析跳频过程对压缩的影响.研究表明,回旋半径坐标的压缩程度并未在跳频时刻发生改变,但可在后续的演化中出现更强的压缩现象.另一方面,主要研究跳频过程中心导向模式的压缩演化.通过参数的选择,分析了两种压缩模式,即发散模式和振荡模式的压缩及演化.有趣的是,在中心导向模式压缩中,外势存在一个由旋转角速度决定的临界势阱纵横比.压缩模式在此处发生突变,且在振荡模式中,势阱纵横比趋于该临界值时,将出现明显的压缩.     

A residual-based message passing algorithm for constraint satisfaction problems

Message passing algorithms, whose iterative nature captures complicated interactions among interconnected variables in complex systems and extracts information from the fixed point of iterated messages, provide a powerful toolkit in tackling hard computational tasks in optimization, inference, and learning problems. In the context of constraint satisfaction problems (CSPs), when a control parameter (such as constraint density) is tuned, multiple threshold phenomena emerge, signaling fundamental structural transitions in their solution space. Finding solutions around these transition points is exceedingly challenging for algorithm design, where message passing algorithms suffer from a large message fluctuation far from convergence. Here we introduce a residual-based updating step into message passing algorithms, in which messages with large variation between consecutive steps are given high priority in the updating process. For the specific example of model RB (revised B), a typical prototype of random CSPs with growing domains, we show that our algorithm improves the convergence of message updating and increases the success probability in finding solutions around the satisfiability threshold with a low computational cost. Our approach to message passing algorithms should be of value for exploring their power in developing algorithms to find ground-state solutions and understand the detailed structure of solution space of hard optimization problems.     

Methods of estimation of equilibrium charge distribution of ions in solid and gaseous media

The new version of theoretical estimation of equilibrium charge distribution of ions passing through the matter is proposed. This estimation is based on the correction of charge exchange cross sections for gases taking into account the density effect. The results of calculations are compared with experimental data and with empirical estimation based on the averaging of experimental data for charge distributions of ions in gases and solids. The theoretical method describes the experimental oscillations of width of the charge distribution in contrast to the empirical method.     

Variational Message Passing and Local Constraint Manipulation in Factor Graphs

Accurate evaluation of Bayesian model evidence for a given data set is a fundamental problem in model development. Since evidence evaluations are usually intractable, in practice variational free energy (VFE) minimization provides an attractive alternative, as the VFE is an upper bound on negative model log-evidence (NLE). In order to improve tractability of the VFE, it is common to manipulate the constraints in the search space for the posterior distribution of the latent variables. Unfortunately, constraint manipulation may also lead to a less accurate estimate of the NLE. Thus, constraint manipulation implies an engineering trade-off between tractability and accuracy of model evidence estimation. In this paper, we develop a unifying account of constraint manipulation for variational inference in models that can be represented by a (Forney-style) factor graph, for which we identify the Bethe Free Energy as an approximation to the VFE. We derive well-known message passing algorithms from first principles, as the result of minimizing the constrained Bethe Free Energy (BFE). The proposed method supports evaluation of the BFE in factor graphs for model scoring and development of new message passing-based inference algorithms that potentially improve evidence estimation accuracy.     

稀疏贝叶斯学习水声信道估计与脉冲噪声抑制方法

水声信道具有显著的稀疏特性,利用稀疏贝叶斯学习(SBL)算法能够实现稀疏水声信道的有效估计。针对SBL计算复杂度较高的问题,将广义近似消息传递-稀疏贝叶斯学习(GAMP-SBL)引入水声信道估计。该方法在SBL的框架下结合GAMP以消息传递的方式计算信道冲激响应,能够有效降低SBL的计算复杂度。针对假设背景噪声服从高斯分布的信道估计方法在脉冲噪声环境下性能下降问题,提出了基于GAMP-SBL的脉冲噪声抑制水声信道估计方法:首先利用脉冲噪声时域稀疏特性,采用GAMP-SBL估计脉冲噪声并进行抑制,然后再次利用GAMP-SBL实现水声信道估计.基于第九次北极科考冰下脉冲噪声的两次仿真结果表明,所提出的方法在归一化均方误差上相对于未进行脉冲噪声抑制的GAMP-SBL最大分别降低了18.71%,6.61%,在信道解码前误码率上最大分别降低了1.66%,4.05%,并且相对于Clipping方法更加稳健。在信噪比为20 dB时,误码率可低于10-2。      

非定常输运问题适应于消息传递并行编程环境的香农熵计算方法

在多计算步的非定常输运问题的蒙特卡罗模拟中,为自动调整每一步的样本数以获得较高的计算效率,可以有多种准则.一种可选的方法是在每一步每隔若干样本监测一次系统中未死亡粒子属性分布对应的香农熵的收敛情况以决定何时停止追加样本,此种方法需要在每一步频繁计算香农熵值.由于在MPI消息传递并行编程环境下香农熵的经典计算方法必须广播大量的数据,导致每一步的计算时间随香农熵计算频率的提高而快速增大,这显然是不能满足实际需求的.本文提出了一种适应于消息传递并行编程环境的香农熵计算新方法,该方法计算得到的香农熵值并不等价于经典方法,但二者之间的差别会随着样本数的增加而趋于零.新方法的最大优势是高频计算香农熵值的时间代价大为降低,为最终实现基于香农熵收敛判断的每步样本数的自动调整奠定了必要的基础.     

一种基于warping变换的浅海脉冲声源被动测距方法

针对浅海波导中脉冲声源被动测距问题, 提出了一种利用接收信号的能量密度函数进行warping变换的声源被动测距方法. 对于浅海波导, 接收信号的能量密度函数中不同号简正波相干部分, 经warping变换后输出结果的频谱中包含与声源和接收器位置无关的不变性频率特征. 这些特征频率在数值上等于理想波导中相干的两号简正波的截止频率差, 与海底参数无关, 因此仅需已知海水中的平均声速和海水深度便可计算出特征频率值. 当声源距离未知时, 利用特征频率的提取值与真实特征频率之间的关系可以实现快速测距, 极大地提高了计算速度. 为了验证方法的有效性, 对2011年11月黄海海域水声实验的接收脉冲数据进行了处理, 测距结果与实测距离符合良好, 平均测距误差在8%以内.     

基于生成函数方法的现实网络座键渗流建模

基于生成函数方法针对现实网络构建座键渗流模型, 并应用于4种有代表性的具体网络, 检验其对关键渗流指标估计的精确程度, 讨论模型估计误差成因, 同时给出其简单应用。所得现实网络渗流模型可应用于估计各类现实网络承受点边打击之后的连通状态, 也可以用来评估现实网络的整体抗毁程度。该模型处理过程简单, 预测结果精度与信息传播算法的结果精度相比可以被接受, 其计算用时则远低于信息传播算法, 具备很好的应用潜力。     

The Network Source Location Problem: Ground State Energy,Entropy and Effects of Freezing

Ground state entropy of the network source location problem is evaluated at both the replica symmetric level and one-step replica symmetry breaking level using the entropic cavity method. The regime that is a focus of this study, is closely related to the vertex cover problem with randomly quenched covered nodes. The resulting entropic message passing inspired decimation and reinforcement algorithms are used to identify the optimal location of sources in single instances of transportation networks. The conventional belief propagation without taking the entropic effect into account is also compared. We find that in the glassy phase the entropic message passing inspired decimation yields a lower ground state energy compared to the belief propagation without taking the entropic effect. Using the extremal optimization algorithm, we study the ground state energy and the fraction of frozen hubs, and extend the algorithm to collect statistics of the entropy. The theoretical results are compared with the extremal optimization results.     

A single current density component imaging by MRCDI without subject rotations

Magnetic resonance current density imaging (MRCDI) is a useful method for measuring electrical current density distribution inside a subject. Due to the requirement of subject rotations in MRCDI, MRCDI has not been widely applied to in vivo studies. In this paper, we propose a new current density image (CDI) reconstruction method by which a single component of the current density can be imaged by MRCDI without subject rotations. After measuring one of the two magnetic field components, produced by the current density component passing through the measurement plane, we have reconstructed the current density component images in the spatial frequency domain. Even though the proposed method has a limitation that the area of magnetic field measurement should be much larger than that of the current density, the proposed method is expected to expedite MRCDI applications to in vivo studies.     

Decentralized detection for B5G massive MIMO: When local computation meets iterative algorithm

Massive multiple-input multiple-output (MIMO) is a key enabler for 5G and beyond. For signal detection of massive MIMO, computing resources available at the network edge were underexplored in most existing algorithms. For this reason, the paper proposes a new detection algorithm, termed inner-looping decentralized generalized expectation consistent for signal recovery (iDeGEC-SR), which leverages an extra (inner) loop of message passing added to the DeGEC-SR and makes better exploration of the local computing resources. As demonstrated by theoretical analysis and Monte Carlo simulations, the algorithm outperforms state-of-the-art techniques like GEC-SR (in terms of computational complexity), GAMP and DeGEC-SR (in terms of estimation accuracy), considerably.