Optimization and Performance Enhancement of Gesture Recognition Algorithm Based on FMCW Millimeter-Wave Radar

Gesture recognition plays an increasingly important role as the requirements of intelligent systems for human-computer interaction methods increase.To improve the accuracy of the millimeter-wave radar gesture detection algorithm with limited computational resources,this study improves the detection performance in terms of optimized features and interference filtering.The accuracy of the algorithm is improved by refining the combination of gesture features using a self-constructed dataset,and biometric filtering is introduced to reduce the interference of inanimate object motion.Finally,experiments demonstrate the effectiveness of the proposed algorithm in both mitigating interference from inanimate objects and accurately recognizing gestures.Results show a notable 93.29%average reduction in false detections achieved through the integration of biometric filtering into the algorithm’s interpretation of target movements.Additionally,the algorithm adeptly identifies the six gestures with an average accuracy of 96.84%on embedded systems.

基于双注意力机制的FMCW雷达人体行为识别

为了提高调频连续波(frequency modulated continuous wave,FMCW)雷达人体行为识别的分类精度和泛化性能,提出了一种基于双注意力机制的特征融合方法。通过设置阈值,对距离-时间谱图和微多普勒谱图中的有效频谱进行提取、拼接后送入AlexNet和VGG16神经网络来提取特征;加入空间注意力和改进的通道注意力模块,丢弃冗余信息,以增强对重要信息的关注,获取更感兴趣的特征进行特征融合分类。实验结果表明,该方法对6种日常人体行为的平均识别准确率高达97.0%。

多波段FMCW雷达低慢小探测数据集(LSS-FMCWR-1.0)及高分辨微动特征提取方法

无人机等低慢小目标探测对雷达目标检测和识别技术提出了很高的挑战,迫切需要构建相关数据集,支撑低慢小探测技术的发展和应用。该文公开了一个多波段调频连续波(FMCW)雷达低慢小目标探测数据集,基于Ku波段和L波段的FMCW雷达采集6种类型的无人机回波数据,通过雷达调制周期和调制带宽,具备不同时域和频域分辨和测量能力,构建了多波段FMCW雷达低慢小探测数据集(LSS-FMCWR-1.0)。为了进一步提升无人机微动特征提取能力,该文提出基于局部极大值同步提取变换的无人机微动提取和参数估计方法,在短时傅里叶变换的基础上提取时频能量最大值,保留有用信号分量,实现精细化时频表示。基于LSS-FMCWR-1.0进行验证分析,结果表明该方法相较于传统时频方法,熵值平均降低了5.3 dB,旋翼叶长估计误差降低了27.7%,所提方法兼顾高时频分辨率和较高的参数估计精度,为后续目标识别奠定了基础。

Modified Omega-K algorithm for processing helicopter-borne frequency modulated continuous waveform rotating synthetic aperture radar data

With appropriate geometry configuration, helicopter- borne rotating synthetic aperture radar （ROSAR） can break through the limitations of monostatic synthetic aperture radar （SAR） on forward-looking imaging. With this capability, ROSAR has extensive potential applications, such as self-navigation and self-landing. Moreover, it has many advantages if combined with the frequency modulated continuous wave （FMCW） technology. A novel geometric configuration and an imaging algorithm for helicopter-borne FMCW-ROSAR are proposed. Firstly, by per- forming the equivalent phase center principle, the separated trans- mitting and receiving antenna system is equalized to the case of system configuration with antenna for both transmitting and receiving signals. Based on this, the accurate two-dimensional spectrum is obtained and the Doppler frequency shift effect in- duced by the continuous motion of the platform during the long pulse duration is compensated. Next, the impacts of the velocity approximation error on the imaging algorithm are analyzed in de- tail, and the system parameters selection and resolution analysis are presented. The well-focused SAR image is then obtained by using the improved Omega-K algorithm incorporating the accurate compensation method for the velocity approximation error. FJnally, correctness of the analysis and effectiveness of the proposed al- gorithm are demonstrated through simulation results.

基于FMCW毫米波雷达的人体生命体征检测实验设计

利用线性调频连续(FMCW)毫米波雷达设计人体生命体征检测教学实验。基于FMCW毫米波雷达采集多个人体目标回波数据;采用快时间维快速傅里叶变换和Capon算法生成距离角度图;利用线性约束最小方差准则进行数字波束形成,提取各个目标所对应的慢时间维信号,使用改进的微分交叉相乘算法完成相位信号的提取;结合差分增强处理和带通滤波器实现对呼吸和心跳频率的估计,完成对多目标生命体征检测。有助于学生对雷达系统工作基本原理和信号处理方法的理解,提高雷达原理课程的教学效果。

基于光电锁相环的高线性FMCW激光雷达频率调谐技术

搭建了可调谐半导体激光器扫频非线性校正系统,研究了锯齿波调制下半导体激光器的扫频非线性特性,将光电锁相环技术引入调频连续波光源系统中,提出在预失真校正电流基础上采用光电锁相环的方法来克服扫频非线性,以防止大范围扫频非线性频差导致的失锁现象。基于调频连续波激光测距实验,验证光频线性化的效果,并分析了扫频非线性对精确距离测量的影响。实验结果表明,经过非线性校正后,激光器输出光频与理想线性光频差的均方根误差缩小到23.7 MHz(减小为校正前的1/219),残余非线性仅余0.0339%,1-r2的数量级达到10-7,测距实验中得到的目标厚度误差在不同测量距离下在0.05 mm~0.15 mm之间变化,表明非线性校正取得了良好的效果。

微小型无人机载FMCW SAR宽波束运动补偿算法

调频连续波(frequency modulated continuous wave,FMCW)体制的合成孔径雷达(synthetic aperture radar,SAR)具有较宽的方位向波束,运动误差在成像处理时会产生较为严重的方位空变性。对此,建立了具有三轴运动误差的信号模型;对宽波束情况下的距离和方位的耦合性以及由运动误差导致的方位空变性进行了分析;在视线向(line of sight,LOS)引入传统的频率分割算法来补偿方位空变误差,在航向将运动误差建模为包络误差与相位误差;提出了“逐方位块补偿法”来消除相位误差中的空变性。最后,通过仿真实验验证了所提算法的有效性。

基于MIMO-FMCW雷达的多人生命体征检测

针对多输入多输出(MIMO)体制调频连续波(FMCW)雷达难于对室内环境多人生命体征进行准确检测的问题,本文提出一种基于MIMO-FMCW雷达的多人生命体征检测方法。首先对中频信号做距离维快速傅里叶变换(FFT)和Capon角度估计得到对应的距离角度图,利用二维恒虚警检测技术(2D-CFAR)和基于密度的聚类(DBSCAN)算法确定每个目标的距离角度信息,通过线性约束最小方差(LCMV)准则进行数字波束形成得到目标对应的慢时间维信号,并使用反正切函数完成相位信号的提取,最后利用谐波判别准则实现对呼吸和心跳信号频率的估计继而完成对多目标生命体征检测。实验结果表明,谐波判别准则实现了平均相对误差小于10%的呼吸率和心率检测精度,证明了该方法的有效性。

IMAGING ANALYSIS OF FREQUENCY MODULATION CONTINUOUS WAVE SYNTHETIC APERTURE RADAR IN NEAR RANGE MODE

Frequency-Modulation Continuous-Wave Synthetic Aperture Radar(FMCW SAR)has shown great potential in the applications of civil and military fields because of its easy deployment and low cost.However,most of these work and analysis are concentrated on airborne FMCW SAR,where the characteristics of the imaging geometry and signal are much similar to that of traditional pulsed-SAR.As a result,a series of test campaigns of automobile-based FMCW SAR were sponsored by Institute of Electronics,Chinese Academy of Sciences(IECAS)in the autumn of 2012.In this paper,we analyze the imaging issues of FMCW SAR in automobile mode(named as near range mode),where a vehicle is used as moving platform and a large looking angle is configured.The imaging geometry and signal properties are analyzed in detail.We emphasize the difference of the near range mode from the traditional airborne SAR mode.Based on the analysis,a focusing approach is proposed in the paper to handle the data focusing in the case.Simulation experiment and real data of automobile FMCW SAR are used to validate the analysis.

基于FMCW的10kV配电电缆故障定位及类型识别方法

为了解决电缆输入阻抗谱法对高阻故障定位距离较短、遮蔽区域大等不足,该文提出一种基于频域反射法的调频连续波(frequency modulated continuous wave,FMCW)电缆故障定位及类型识别方法。首先,依据FMCW电缆故障定位的原理结合电缆分布参数模型进行电缆故障定位仿真,获取电缆的FMCW幅值谱、相位谱。仿真结果表明,幅值谱可用于故障定位,相位谱可用于故障类型识别。根据仿真结果获取不同类型电缆故障(开路、短路、高阻、低阻故障)的相位谱特征。最后,在300m的射频同轴电缆和194m的10k V-XLPE电缆上进行测试,验证所提方法的有效性。实验结果表明,FMCW幅值谱能有效定位电缆的故障;FMCW相位谱的相位特征可以区分开路、短路、高阻、低阻故障。相较于电缆输入阻抗谱法,FMCW方法将高阻故障的检测距离从20 m提高至200m,将输入阻抗法40%的遮蔽区域降至18.2%以内,且对高阻故障的灵敏度从2 kΩ(40Z0)提高至10 kΩ(200Z0)。

A TECHNIQUE FOR MEASURING THE LINEARITY OF A LINEARLY FREQUENCY-MODULATED SIGNAL

A technique for measuring the linearity of a linearly frequency-modulated continuous wave (LFM-CW) signal is presented. It uses a delay-line and a mixer to sense the slope of the output of a sweep oscillator, so that the original form of frequency function deviated from idealized linear slope is retrieved by means of spectrum analysis. Consequently,the linearity of the LFM signal is determined. The formulation is performed based on the principle that an angle-modulated signal can be approximated by an amplitude-modulated signal if the modulation coefficient is sufficiently small. To examine the validity of the procedure and to study the effect of each parameter on the accuracy of measurement, a number of computer simulations has been made. The results of simulation show that the error of the measurement is less than 2%.

基于FMCW雷达的多通道特征融合人体动作识别方法

针对采用单一特征进行人体动作识别准确率不高的问题,提出了一种基于调频连续波(Frequency Modulated Continuous Wave,FMCW)雷达的多通道特征融合人体动作识别方法。通过对FMCW雷达回波数据进行预处理,得到人体动作的距离参数与多普勒参数,构建出距离-时间特征谱图和多普勒-时间特征谱图数据集。为了进行人体动作特征的充分提取与精确识别,改进了单通道输入的传统卷积神经网络结构,把部分残差连接结构和跨阶段部分连接结构进行了优化应用至雷达人体动作识别领域,设计出端到端的CSP-FCNN(Cross Stage Partial-Fusion Convolutional Neural Network)多通道融合卷积神经网络。采用公开数据集进行实验,结果表明所提方法有效解决了单一特征动作识别信息量欠缺以及网络提取特征不充分的问题,识别准确率较单一特征识别方法提高了5%以上。

基于FMCW雷达的多人生命体征检测算法

为实现无感化和长时间的多人生命体征检测,提出一种基于调频连续波(FMCW)雷达的体征检测方法。使用单元平均恒虚警率(CA-CFAR)算法实现多个目标的定位和区分;针对呼吸谐波对心率信号的干扰现象,采用最小均方(LMS)算法对呼吸谐波进行自适应噪声抵消,提高心率信号信噪比;使用高分辨率的MUSIC算法实现呼吸和心率频率的估计。实验表明,该算法能够对多个目标准确地估计呼吸率和心率,且准确率优于快速傅里叶变换(FFT)和自相关等算法。

多普勒模糊下的FMCWMIMO雷达目标参数估计方法

近年来,随着智能驾驶技术的不断发展,毫米波雷达作为汽车安全控制系统的核心组件受到了广泛关注。时分复用(TDM)多输入多输出(MIMO)调频连续波(FMCW)雷达因具有低硬件成本和高角度分辨率的优势而被广泛应用于汽车雷达,但TDMMIMO在实际应用中还存在对运动目标检测易出现速度模糊和角度模糊问题,导致检测误差变大,对于自动驾驶场景存在一定的安全隐患。为解决上述TDM MIMO FMCW雷达存在检测误差高的问题,提出了在多普勒模糊下的FMCW MIMO雷达目标参数估计方法,在不增加额外硬件开销的前提下,可确保算法在低复杂度下提升监测的时效性,解决了速度模糊和相位偏移问题;利用加Kaiser窗FFT波束形成方法对目标角度进行测量,从而得到更精准的目标信息。仿真和实验结果验证了所提方法的有效性。

基于二阶Keystone变换的FMCWSAR动目标成像与参数估计

本文研究了一种适用于调频连续波(Frequency Modulated Continuous Wave,FMCW)合成孔径雷达(Synthetic Aperture Radar,SAR)的地面动目标成像与参数估计的方法。首先,建立FMCW SAR系统下的动目标回波模型,通过多普勒频移补偿和时频代换,提出了一种基于二阶Keystone变换校正动目标回波距离弯曲的方法。其次,用Hough变换去估计动目标距离向速度,并据此进行距离走动校正。最后,采用Wigner-Hough变换估计动目标的多普勒调频率,通过补偿二次和三次多普勒相位实现动目标的精确聚焦。仿真结果表明:该方法对参数估计有较高的准确性,同时估计的参数对动目标成像有较好的聚焦效果。

基于多域融合的FMCW雷达手势识别方法

为了提高对动态手势动作的识别性能,文中提出一种基于多域融合的调频连续波(Frequency Modulated Continuous Wave,FMCW)雷达手势识别方法。首先,利用FMCW雷达对不同手势动作进行探测并收集回波数据;然后,对接收的回波数据进行预处理得到目标的距离-时间矩阵、多普勒-时间矩阵和固定帧时间长度的距离-多普勒-帧三维矩阵,将每个手势动作对应的三种数据矩阵输入到三通道卷积神经网络(Convolutional Neural Networks,CNN)中进行手势特征提取;最后,采用可训练的权值矩阵对各个数据域提取的特征向量进行融合得到手势动作分类结果。实测数据处理结果表明所提基于加权融合的三通道CNN手势识别方法对八种手势动作的分类平均准确率达到98.45%,与传统的平均融合和拼接融合方式相比有效提高了对手势动作的分类能力。

Frequency-modulated continuous-wave dual-frequency LIDAR based on a monolithic integrated two-section DFB laser

We demonstrate a high-resolution frequency-modulated continuous-wave dual-frequency LIDAR system based on a monolithic integrated two-section(TS) distributed feedback(DFB) laser. In order to achieve phase locking of the two lasers in the TS-DFB laser, the sideband optical injection locking technique is employed. A high-quality linear frequency-modulated signal is achieved from the TS-DFB laser. Utilizing the proposed LIDAR system, the distance and velocity of a target can be measured accurately. The maximum relative errors of distance and velocity measurement are 1.6% and 3.18%, respectively.

小波阈值去噪在FMCW雷达信号处理中的应用

针对调频连续波(FMCW)雷达回波信号中存在噪声的问题,采用小波阈值法进行去噪。详细讨论了小波阈值去噪过程中各参数的选取原则,构造了一种优于典型阈值函数(如:软、硬阈值函数,软硬阈值改良折衷法和半软阈值函数)的新阈值函数。利用典型阈值函数和构造的阈值函数,对实际雷达回波信号进行处理,证明了构造的阈值函数去噪效果更佳。

24 GHz FMCW车载测距雷达系统设计

为了研制汽车防撞系统,设计了一款24 GHz FMCW雷达系统。该系统包括雷达射频模块、中频信号处理模块和数字基带处理模块。雷达射频模块采用基于异质结场效应晶体管NE3514研制的雷达射频模块传感器实现;中频信号处理模块由高通滤波器、可变增益放大器、低通滤波器构成。采用TLV2374运算放大器设计实现高通滤波器,TLV2374运算放大器与数字电位器MCP42100设计实现可变增益放大器,AD8532运算放大器设计实现低通滤波器;数字基带处理模块采用STM32F407微处理器完成数据采集与信号特征提取以及系统控制。该车载测距雷达能够实现90 m的距离测量。

基于级数反演的斜视FMCW SAR成像算法研究

在斜视调频连续波(FMCW)合成孔径雷达(SAR)成像中,斜距的三次项不仅会对相位产生影响,同时对包络也会有影响.如果不进行有效校正,将会影响到SAR图像的聚焦效果.针对这个问题,本文利用级数反演的方法推导出斜距展开到三次项时回波信号的距离多普勒频谱表达式,并在距离多普勒域上对三次项进行包络和相位滤波处理.此外,考虑到时域走动校正带来方位空变性问题,本文利用方位非线性变标算法(NCS)解决其沿方位空变性问题并给出结合运动补偿的实测数据处理的算法流程图.最后通过对多个点目标的场景进行仿真实验以及实测数据处理来验证本文成像算法的可行性和有效性.