Steganography algorithm for adaptive multi-rate wideband speech based on algebraic codebook search

With the popularity of adaptive multi-rate wideband （AMR-WB） audio in mobile communication, many AMR- WB based techniques, such as a similar compression architecture to transmit secret information during the process of compression, were proposed to transmit covert messages. However, if a sender does not have the original waveform audio format （WAV） audio, the architecture cannot be used. In this paper, a new covert message method, which takes effect after WAV audio is compressed into AMR-WB speech, is proposed. This method takes advantage of algebraic codebook search. Aiming at improving speed and reducing search space, it does not perform algebraic codebook search using the optimal search algorithm, and it does not reach the positions of non-zero pulses via depth-first tree search that characterizes the energy of audio. According to the features of search methods and the codebook index construction, every track in each subframe is analyzed to find the proper positions for embedding secret information. Experimental results show that the proposed method has satisfactory capacity and simplicity regardless of compression process.

Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter （EKF）, the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.

AN ADAPTIVE MEASUREMENT SCHEME BASED ON COMPRESSED SENSING FOR WIDEBAND SPECTRUM DETECTION IN COGNITIVE WSN

An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS) theory in Cognitive Wireless Sensor Network (C-WSN). Local sensing information is collected via energy detection with Analog-to-Information Converter (AIC) at massive cognitive sensors, and sparse representation is considered with the exploration of spatial temporal correlation structure of detected signals. Adaptive measurement matrix is designed in AMS, which is based on maximum energy subset selection. Energy subset is calculated with sparse transformation of sensing information, and maximum energy subset is selected as the row vector of adaptive measurement matrix. In addition, the measurement matrix is constructed by orthogonalization of those selected row vectors, which also satisfies the Restricted Isometry Property (RIP) in CS theory. Orthogonal Matching Pursuit (OMP) reconstruction algorithm is implemented at sink node to recover original information. Simulation results are performed with the comparison of Random Measurement Scheme (RMS). It is revealed that, signal reconstruction effect based on AMS is superior to conventional RMS Gaussian measurement. Moreover, AMS has better detection performance than RMS at lower compression rate region, and it is suitable for large-scale C-WSN wideband spectrum sensing.

Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

Cyber-physical systems(CPSs)take on the characteristics of both multiple rates of information collection and processing and the dependency on information exchanges.The purpose of this paper is to develop a joint recursive filtering scheme that estimates both unknown inputs and system states for multi-rate CPSs with unknown inputs.In cyberspace,the information transmission between the local joint filter and the sensors is governed by an adaptive event-triggered strategy.Furthermore,the desired parameters of joint filters are determined by a set of algebraic matrix equations in a recursive way,and a sufficient condition verifying the boundedness of filtering error covariance is found by resorting to some algebraic operation.A state fusion estimation scheme that uses local state estimation is proposed based on the covariance intersection(CI)based fusion conception.Lastly,an illustrative example demonstrates the effectiveness of the proposed adaptive event-triggered recursive filtering algorithm.

Adaptive Digital Predistortion Schemes to Linearize RF Power Amplifiers with Memory Effects

To compensate for nonlinear distortion introduced by RF power amplifiers （PAs） with memory effects, two correlated models, namely an extended memory polynomial （EMP） model and a memory lookup table （LUT） model, are proposed for predistorter design. Two adaptive digital predistortion （ADPD） schemes with indirect learning architecture are presented. One adopts the EMP model and the recursive least square （RLS） algorithm, and the other utilizes the memory LUT model and the least mean square （LMS） algorithm. Simulation results demonstrate that the EMP-based ADPD yields the best linearization performance in terms of suppressing spectral regrowth. It is also shown that the ADPD based on memory LUT makes optimum tradeoff between performance and computational complexity.

A THROUGHPUT-EFFICIENT ADAPTIVE TRANSMIT-RECEIVE SCHEME FOR INDOOR DS-UWB SYSTEMS

In this paper, a novel adaptive transmit-receive scheme is presented for indoor Direct Se- quence Ultra-WideBand (DS-UWB) systems. In the proposed scheme, a simple switch module is in- troduced to improve the system throughput. Furthermore, adaptive detection is implemented via an improved Least Mean Squares (LMS) algorithm. The convergence behavior and the Bit Error Rate (BER) performance of the proposed scheme are examined under the realistic channel models. Simu- lation results show that, nearly without loss of the BER performance, the proposed scheme can obtain at least 2/3 improvement in training overhead compared with the conventional approach.

基于TOF和自适应抗差卡尔曼滤波的UWB室内定位算法

为提高超宽带(UWB)定位系统在室内复杂环境下的定位精度,提出一种基于飞行时间(TOF)和自适应抗差卡尔曼滤波(ARKF)的改进定位算法。针对超低功耗宽带设备在复杂室内环境状态下易受周围干扰而存在标准时间偏差的问题,提出一种改进的TOF算法,同时进行测距标定,拟合数据;对室内存在非视距(NLOS)干扰的情形,提出一种ARKF算法,通过比较残差与3倍信息的方差来判断视距(LOS)与NLOS情形。实验结果显示:该算法可以在静态与动态定位实验中有效提高系统定位精度,降低定位误差,取得较好的定位效果。

一种S波段超宽带能量选择表面设计

设计了一种工作在S波段的能量选择表面,可实现超宽带自适应强电磁防护。该结构由两层金属周期结构组成,顶层为两个对称分布的金属条和一个金属片,金属条与金属片间加载两个PIN二极管;底层为十字架结构。当入射电磁波场强低于阈值时,能量选择表面工作在透波状态,电磁波可以传播;当入射电磁波场强超过阈值时,金属条和金属片之间产生的感应电压使得PIN二极管导通,此时能量选择表面进入防护状态,电磁波被屏蔽。通过对能量选择表面在PIN二极管导通和截止状态下的表面电流和电场分布以及等效电路模型进行分析,解释了该结构的工作原理。采用PCB制作工艺加工了实物样板并对弱场入射下的插入损耗以及强场入射下的防护效能进行测试。实验和仿真结果匹配性良好,表明该能量选择表面在透波状态下的工作中心频率为2.7 GHz,插入损耗小于1 dB的工作频带为2.2~3.5 GHz;在防护状态下,工作频带的防护效能大于10 dB,达到了超宽带的要求。

超宽带脉冲作用下抗干扰器件的特性分析

基于高重频超宽带脉冲,研究了高重频超宽带脉冲对自适应调零天线和PIN限幅器的抗干扰性能的影响。基于Matlab和ADS仿真软件搭建模型,并通过实验平台对ADS的仿真结果进行验证。实验结果表明:对于导航接收机中的自适应调零天线,超宽带干扰脉冲会使其射频链路产生饱和效应,从而使功率倒置算法失效,进而无法在干扰方向形成零陷;对于PIN限幅器,超宽带干扰脉冲可以使其产生明显的尖峰泄露效应。相较于ns量级的窄谱高功率微波脉冲,超宽带脉冲对限幅器的干扰能力更强。

基于直扩超声波宽带人体通信多点接入的自适应速率调整

体域网是远程医疗和健康监护的重要环节,现有研究多采用电磁波传输。相比之下,人体软组织中超声波传播衰减小,产生的热量少,比电磁波传输距离远且致病风险低,利用超声波实现人体范围的通信和组网具有一定优势。现有的超声波宽带通信多采用超短脉冲减少多径交叠及其带来的干扰,结合直接序列扩频技术可以共享信道实现多点接入。但是,增加通信数量带来的干扰使目标通信链路接收节点的信噪比降低,采用固定帧长与码长无法保证通信可靠性。文中针对多点接入的场景,对节点的通信速率进行数学建模,研究竞争与合作两种场景下的自适应速率调整方法,利用凸优化理论的拉格朗日乘数法推导了帧长和码长的闭式解,在多点通信中动态改变帧长和码长实现速率调整。仿真结果表明,文中方法随着通信链路数及其干扰变化可实现自适应速率调整,其中,基于协商对策论的合作方案可以平衡不同节点的通信速率,获得更好的网络性能,基于速率最大的竞争方案有助于提高目标通信链路的有效通信速率,实际应用中需根据应用场景进行选择。

Blind Wideband Beamforming Algorithm Based on the Uncertainty Set

Without prior knowledge,the steering vector estimation error of the desired signal will deteriorate the beamforming performance to some extent.To solve this problem,a space-time blind wideband beamforming algorithm based on the uncertainty set is proposed.First of all,based on the space-time filtering model,the spherical constraint set is designed according to the uncertainty of the estimation error of the space-time steering vector.Then,the method of wideband beamforming under multiconstraints in the frequency domain is derived,and the calculation of parameters of steering vector estimation error and loading factor are given in detail.Finally,a blind broadband beamforming algorithm combined with the CAB algorithm is proposed.The improvement of the output signal-to-noise ratio is quantitatively analyzed by computer simulation to verify the correctness and robustness of the algorithm.

基于抗差估计的VIO/UWB自适应组合定位算法

在GNSS信号拒止的室内环境定位中,针对视觉惯性里程计(VIO)在长期运动或无回环等不利环境下产生误差累积偏移以及超宽带(UWB)受非视距影响定位精度难以保证的问题,提出了一种基于抗差估计的UWB辅助视觉惯性自适应组合定位算法。首先,构建UWB与VIO的优化框架,利用UWB定位结果对VIO进行全局约束。其次,在后端优化阶段加入抗差估计,实时调整传感器间的权重值,抑制UWB非视距的影响。最后,在EuRoc数据集和真实场景中进行了实验验证。真实场景实验结果表明,组合算法在非遮挡条件下定位精度相比于VINS_Mono提高75.05%,基于抗差估计的组合算法在遮挡条件下定位精度相比于不加抗差估计的组合算法提高37.53%。

基于变步长SOCP的宽带发射鲁棒唯相位ADBF算法

针对宽带自适应发射数字波束的权矢量非恒模、高动态环境下干扰抑制能力下降的问题,提出了一种基于变步长迭代二阶锥(Second-Order Cone Programming, SOCP)的宽带发射鲁棒唯相位自适应波束形成(Adaptive Digital Beam Forming, ADBF)算法。采用抽头延迟线结构(Tapped Delay Line, TDL)并结合多相滤波器(Polyphase Filter, PF)对宽带信号进行子带划分;在各子带内联合多线性约束最小方差(Multiple Linear Constrained Minimum Variance, MLCMV)准则与零陷展宽算法求解鲁棒权矢量;构建小相位扰动模型,引入变步长SOCP算法求解唯相位权矢量;最后通过综合滤波器进行子带综合,形成宽带发射波束。仿真结果表明,该算法可有效展宽干扰零陷,显著提高收敛性,且易于工程实施。

一种结合交互式多模型和自适应UKF的UWB/INS紧组合导航算法

超宽带技术在煤矿井下定位时,会受非视距、多径效应和电磁干扰等不利影响导致定位性能下降,该文提出了一种结合交互式多模型和自适应无迹卡尔曼滤波的超宽带/惯导紧组合导航算法。采用匀速与匀加速两个运动模型交叉耦合模拟井下目标的运动;采用无迹卡尔曼算法对两种传感器信息进行非线性滤波,得到较精确的定位信息;利用自适应模糊推理方法调整测量噪声协方差矩阵,提高定位精度和鲁棒性。仿真实验结果显示,提出的IMM-AUKF算法较传统算法跟踪精度提高了近10%。

A wideband LC-VCO with small VCO gain variation and adaptive power control

A wideband LC tank voltage-controlled-oscillator（VCO） is proposed.To solve the impacts of wideband operation on VCO gain（K_（VCO）） variation and start-up constraint,a binary-weighted varactor array and a binary-weighted negative resistance array all with optimal unit values are designed.Implemented in a 0.18μm CMOS process,the proposed VCO shows a frequency tuning range from 1.9 to 3.1 GHz,with a current consumption varying accordingly from 14.2 to 4 mA from a 1.8 V supply.With the proposed K_（VCO） suppression technique,the K_（VCO） varies from 50 to 60 MHz/V in the entire frequency range.The measured phase noise is -117 dBc/Hz at a 1 MHz offset from a 3 GHz carrier.

基于相关函数的低维度宽带波束形成算法

为了降低波束的旁瓣和主瓣宽度并提高抗干扰能力,本文提出了一种基于相关函数的低维度宽带波束形成算法。首先,对宽带信号进行FFT变换以将其转化为多个子带的窄带信号;其次,基于最小方差(MV)准则并利用相关函数将子带信号的干扰-噪声协方差矩阵重构为相关矩阵,以达到有效抑制噪声和干扰的目的;然后,利用降维算法以降低相关矩阵的复杂度,并利用拉格朗日乘数法来求解最优权矢量;最后,利用切比雪夫滤波器对最优权矢量进行静态加权调整,以期获得更高的阵列增益和更低的旁瓣电平。仿真结果表明:该算法的计算复杂度较小,主瓣宽度变窄1度左右,最佳输出信干噪比提高了约-1.3 d B,同时旁瓣幅度有效降低。

宽带自适应波束形成子带实现方法

提出一种基于通用参数滤波器组的宽带自适应波束形成子带实现方法.宽带接收信号经分析滤波器组分成若干子带信号,每个子带信号经各自的子带阵列处理器处理后由综合滤波器组恢复成宽带信号.因子带信号工作在更低的采样速率下,且每个子带信号处理器并行工作.有效降低了算法计算量.提高了阵列处理器效率.结果表明。与传统宽带处理方法相比,此子带方法除了输出信号均方误差略有增加外。能有效提高权值收敛速度。显著增强干扰抑制能力;与使用同样通道数目的正交镜像滤波器组的子带方法相比,该方法进一步提高了干扰抑制能力并可减小均方误差.

超宽带穿墙雷达对人体动目标探测的实验研究

分析超宽带穿墙雷达动目标检测原理,提出一种新的自适应背景相消方法用于抑制强杂波干扰。介绍了超宽带穿墙雷达实验系统,利用该系统对非金属墙壁后人体动目标进行探测实验,并分别针对处于不同运动状态目标的实验数据进行分析。实验结果表明,超宽带穿墙雷达对非金属墙体具有较强的穿透性,对墙后处于径向运动、原地静止、原地体动及切向运动等运动状态的人体目标均具有较好的探测能力,提出的动目标检测算法能够适应复杂环境的应用。

组合字典下超宽带穿墙雷达自适应稀疏成像方法

针对现有超宽带穿墙雷达稀疏成像算法大多只采用点目标稀疏基表示模型和稀疏优化的正则化参数不能被自适应调整以及目标位置不在划分网格上带来虚假像的问题,该文提出一种基于贝叶斯证据框架的自适应稀疏成像方法。该方法首先利用组合字典独立稀疏表示场景中的点目标和扩展目标,然后在建立的偏离网格稀疏表示模型的基础上分层最大化各参数的似然函数,用第1层推理结合共轭梯度算法估计组合字典的各稀疏表示系数,用第2层推理估计正则化参数和目标的偏离网格量,最终通过迭代优化参数的设置得到问题的求解。仿真和实验结果表明,该方法不仅同时自适应增强穿墙场景中的点目标和扩展目标,还消除了偏离网格目标引起的虚假像。

机载预警雷达技术及信号处理方法综述

机载预警雷达及其信号处理技术经历了巨大的发展,但也面临着隐身目标、非均匀杂波、复杂电磁环境、目标的识别和多种作战任务的严峻挑战。该文回顾了机载预警雷达及其信号处理技术的发展历程,分析了机载预警雷达面临的反隐身、反干扰、反杂波和目标识别方面的挑战,在此基础上提出了机载预警雷达体制正向数字化、宽带化、协同化、智能化和多功能一体化演变的趋势,最后分析了3D-STAP,MIMO-STAP、宽带检测、认知抗干扰等关键技术,有望对下一代机载预警雷达的研制发挥一定的指导意义。