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.

Co-Sharing Waveform Design for Millimeter-Wave Radar Communication Systems

Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.

Efficient 2-D MUSIC algorithm for super-resolution moving target tracking based on an FMCW radar

Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution simultaneously.This paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW radar.Firstly,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching strategy.Secondly,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target tracking.These two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and resolution.Simulation experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.

Non-LOS target localization via millimeter-wave automotive radar

This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.

Millimeter-wave LFMCW radar water surface detection experiment and its imaging algorithm

A millimeter-wave linear frequency modulated continuous wave(LFM CW)radar is applied to water surface detection.This paper presents the experiment and imaging algorithm.In imaging processing,water surface texture can hardly be seen in the results obtained by traditional imaging algorithm.To solve this problem,we propose a millimeter-wave LFMCW radar imaging algorithm for water surface texture.Different from the traditional imaging algorithm,the proposed imaging algorithm includes two improvements as follows:Firstly,the interference from static targets is removed through a frequency domainfilter;Secondly,the multiplicative noises are reduced by the maximum likelihood estimation method,which is used to estimatethe azimuth spectrum parameters to calculate the energy of water surface echo.Final results show that the proposed algorithmcan obtain water surface texture,which means that the proposed algorithm is superior to the traditional imaging algorithm.

基于FMCW雷达的多目标生命体征检测与干扰抑制算法

应用雷达进行生命体征检测时,为解决传统算法无法区分相同距离的多个目标和多目标生命体征信号检测易受干扰的问题,本文提出一种新型的基于调频连续波(FMCW)雷达的多目标生命体征检测与干扰抑制算法。基于MIMO雷达回波数据进行距离-方位维快速傅里叶变换(FFT),完成距离和方位角的目标定位,解决同距离目标分辨问题,之后利用方差法滤除静态杂波和直流分量。针对生命体征信号易受干扰的问题,本文算法利用变分模态分解(VMD)进行呼吸和心跳信号的分离与重构,剔除无效的信号分量,然后对有效重构信号进行自相关和奇异值分解(SVD)去噪,得到干净的呼吸和心跳信号。通过多组实验测试,本算法相较于传统的FFT频谱分析法、VMD信号重构法和基于完全噪声辅助聚合经验模态分解联合独立成分分析算法(CEEMDAN-ICA),心率检测的平均误差分别降低了8.43%、5.66%和1.43%,验证了所提算法的有效性。此外,本文还进行了算法鲁棒性实验和工程应用边界条件分析。

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%。

Computationally efficient MUSIC based DOA estimation algorithm for FMCW radar

This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.

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。

Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Millimeter-wave cloud radar(MMCR)provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds.Therefore,MMCR has been widely applied in cloud observations.However,due to the influence of non-meteorological factors such as insects,the cloud observations are often contaminated by non-meteorological echoes in the clear air,known as clear-air echoes.It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background.The characteristics of clear-air echoes are studied here by combining data from four devices:an MMCR,a laser-ceilometer,an L-band radiosonde,and an all-sky camera.In addition,a new algorithm,which includes feature extraction,feature selection,and classification,is proposed to achieve the automatic identification of clear-air echoes.The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions.The recognition accuracy can reach up to 95.86%for the simple cases when cloud echoes and clear-air echoes are separate,and 88.38%for the complicated cases when low cloud echoes and clear-air echoes are mixed.

基于CNN-BiLSTM的FMCW雷达生命体征信号检测

针对FMCW雷达生命体征检测时存在呼吸谐波和杂波干扰,无法准确地提取生命体征信号,提出了一种基于CNN-BiLSTM神经网络的FMCW雷达生命体征信号检测算法。首先,根据FMCW雷达中频信号定位目标,然后根据目标位置获取目标距离门及其附近距离门的相位信号,并作为神经网络的输入,通过神经网络提取呼吸和心跳信号。实验结果表明,通过CNN-BiLSTM神经网络可以有效提取呼吸和心跳信号,并根据该提取到的呼吸和心跳信号可以准确估计呼吸频率和心率,估计误差分别为7.2%和8.1%。

基于FMCW毫米波雷达的测距值气象改正模型的建立

FMCW毫米波雷达具有低功耗、低成本、全天时全天候、精度高等优点,选择其作为监测设备,可以很大程度上满足监测需求,同时其操作便捷,携带方便。但是有研究表明,FMCW毫米波雷达在进行长时序观测时,雷达测距值会随着空气中的气象因素(温度、湿度、气压等)的改变而发生变化,导致测量精度降低。基于此,本文针对气象因素对毫米波雷达测距精度的影响而展开研究,提出基于调制载波折射率公式构建毫米波雷达的气象改正模型,改正后雷达测距值随时间的波动程度相较于改正前明显降低,测距值的标准差较改正之前降低了30%左右,与温度和湿度的相关系数均降低了50%及以下。结果表明,该模型在一定程度上削弱了气象因素对毫米波雷达测距值的影响,但是削弱效果有限,模型还有待优化。

Towards Converged Millimeter-Wave/Terahertz Wireless Communication and Radar Sensing

Converged communication and radar sensing systems have attained increasing attention in recent years.The development of converged radar-data systems is reviewed,with a special focus on millimeter/terahertz systems as a promising trend.Firstly,we present historical development and convergence technology concept for communication-radar systems,and highlight some emerging technologies in this area.We then provide an updated and comprehensive survey of several converged systems operating in different microwave and millimeter frequency bands,by providing some selective typical communication and radar sensing systems.In this part,we also summarize and compare the system performance in terms of maximum range/range resolution for radar mode and Bit Error Rate(BER)/wireless distance for communication mode.In the last section,the convergence of millimeter/terahertz communication-radar system is concluded by analyzing the prospect of millimeter-wave/terahertz technologies in providing ultrafast data rates and high resolution for our smart future.

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。

Comparison of Liquid Water Content Retrievals for Airborne Millimeter-Wave Radar with Different Particle Parameter Schemes

In the application of the physical iterative method to retrieve millimeter-wave radar liquid water content(LWC)and liquid water path(LWP),particle parameter scheme is the main factor affecting retrieval performance.In this paper,synchronous measurements of an airborne millimeter-wave radar and a hot-wire probe in stratus cloud are used to compare the LWC retrievals of the oceanic and continental particle parameter scheme with diameter less than 50μm and the particle parameter scheme with diameter less than 500μm and 1500μm(scheme 1,scheme 2,scheme 3,and scheme4,respectively).The results show that the particle parameter scheme needs to be selected according to the reflectivity factor when using the physical iterative method to retrieve the LWC and LWP.When the reflectivity factor is less than-30 d BZ,the retrieval error of scheme 1 is the minimum.When the reflectivity factor is greater than-30 d BZ,the retrieval error of scheme 4 is the minimum.Based on the reflectance factor value,the LWP retrievals of scheme 4 are closer to the measurements,the average relative bias is 5.2%,and the minimum relative bias is 4.4%.Compared with other schemes,scheme 4 seems to be more useful for the LWC and LWP retrieval of stratus cloud in China.

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FMCW雷达和ESP-EMSH网络的非接触健康监测系统

非接触式医疗健康监测系统能够有效地应对用户依从性问题,并消除传统监测方式带来的不适感,从而更好地融入日常生活。这种监测手段能够持续关注用户的健康状况,并具备在发生突发急性医疗事件时及时发出警示的潜力,可以满足新生儿、烧伤患者、传染病患者等特殊人群的监测需求。文中提出一种基于ESP32微控制器的创新型非接触式健康监测系统,用于监测独居老人的生命体征和跌倒情况。该系统通过非侵入方式实时监测老人的健康和跌倒状态,监测数据会实时显示在数据监测屏幕和监护人手机应用上。所设计系统具有显著的成本效益和出色的质量,在实验室测试中,该系统采用FMCW毫米波雷达技术,相比传统视频跌倒检测能够更好地保护用户隐私。ESP32微控制器支持ESP-EMSH组网和无线传输,可提供更广泛、更快速、更稳定的网络传输。所提出的健康监测系统显著减少了老人独居风险,有效地减少了危险时刻下未能及时获得帮助的情况。

A Survey of Gesture Recognition Using Frequency Modulated Continuous Wave Radar

With technology advances and human requirements increasing, human-computer interaction plays an important role in our daily lives. Among these interactions, gesture-based recognition offers a natural and intuitive user experience that does not require physical contact and is becoming increasingly prevalent across various fields. Gesture recognition systems based on Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar are receiving widespread attention due to their ability to operate without wearable sensors, their robustness to environmental factors, and the excellent penetrative ability of radar signals. This paper first reviews the current main gesture recognition applications. Subsequently, we introduce the system of gesture recognition based on FMCW radar and provide a general framework for gesture recognition, including gesture data acquisition, data preprocessing, and classification methods. We then discuss typical applications of gesture recognition systems and summarize the performance of these systems in terms of experimental environment, signal acquisition, signal processing, and classification methods. Specifically, we focus our study on four typical gesture recognition systems, including air-writing recognition, gesture command recognition, sign language recognition, and text input recognition. Finally, this paper addresses the challenges and unresolved problems in FMCW radar-based gesture recognition and provides insights into potential future research directions.

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。

应用于汽车FMCW雷达的超前进位锁相环研究

近年来汽车FMCW雷达广泛应用于新能源及智能网联领域,来测量外部目标的相对间距和速度。针对当前FMCW雷达系统灵敏度差、缺少灵活性、测量范围窄的问题,设计了一种应用于FMCW雷达领域的超前进位全数字锁相环。根据雷达对物体距离和速度的测量原理,采取集成电路芯片技术实现了对该环路结构的设计,利用Matlab软件搭建环路系统Z域模型并进行了稳定性分析对比,通过硬件描述语言(VHDL)编写环路程序,并联合调用Modelsim软件完成了仿真试验,最后结合仿真结果在硬件上验证设计的准确性。实验结果表明,基于超前进位的全数字锁相环有效提高了锁相频率,降低了系统延时,大幅度拓展了调频范围。