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.

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.

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.

FM interference suppression for PRC-CW radar based on adaptive STFT and time-varying filtering

The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.

Adaptive digital self-interference cancellation based on fractional order LMS in LFMCW radar

Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.

Range Ambiguity Elimination in a Short-Range FMCW Radar System

Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from the estimated phase of the received signal which is wrapped into （0, 2π]. By integrating Doppler frequency shifts, the variation of range can be estimated and used as an auxiliary information to help eliminating the corresponding range ambiguity. The performance of the new technique is evaluated by simulations. The results show that this technique is robust to sever phase noise and can be used effectively for ambiguity elimination of the modified sinusoidal frequency modulated continuous wave radar.

Parameters of Exterior Ballistic Feature Points Extraction in Radar Measurement Data by EMD

The problem of measuring exterior ballistic feature points is always difficult to solve and it is essentiale on exterior ballistic measurement.By analysis of radar reflection characteristics and non-stationary echo signals of exterior ballistic feature points,the echo data of exterior ballistic feature points is measured by using the continuous wave radar.The parameters of feature points are extracted by the empirical mode decomposition method(EMD)of Hilbert-Huang transform(HHT)spectrum analysis technique.The radar echo signal model and EMD extraction model are established to analyze the exterior ballistic mutation point detection and EMD extraction method of aliasing echo signal.Typical feature point parameters of exterior ballistic in rocket flight tests are carried out and the effectiveness of the method is verified.A new method of measuring the parameters of exterior ballistic feature point is therefore presented.

基于时频域分析的车载毫米波雷达干扰抑制方法

文中针对车载调频连续波雷达之间相互干扰导致虚警和漏警的问题,提出一种在时频域基于改进经验模式分解和自回归模型相结合的干扰抑制方法。该方法首先使用经验模式分解区分出拍频信号中干扰分量主导的低阶本征模态函数,将其转换到短时傅里叶变换域后通过全局阈值方法进行干扰分量定位;其次,在时频域根据定位信息将拍频信号包含干扰的数据置零;最后,使用自回归模型对拍频信号中缺失的有用信号进行估计并插值。通过仿真和实测结果显示,该方法在精确地去除干扰分量的同时可以减少有用信号的功率损失,干扰抑制后的信号与参考信号的相关系数达到0.9697。与现有干扰抑制技术相比文中方法也体现出更优的干扰抑制性能。

基于可解释网络解耦表征的低成本雷达定位解算方法

为降低调频连续波(FMCW)雷达成本,同时提高定位精度,设计可解释解耦表征模型。该模型由网络解算器、虚假信号生成器以及可解释潜变量三部分组成。首先处理雷达信号获得中频频谱;然后输入到网络解算器中生成位置潜变量;再通过物理机制对潜变量进行转换,生成虚假中频信号频谱;最后,设计局部光滑损失函数对模型进行自监督训练,实现潜变量的解耦物理表征。实验结果表明:所提算法能对雷达系统频谱信号的粗粒度进行超分辨率细化,其机理能有效应对雷达系统的硬件公差、环境噪声、安装误差等问题,并可自动地训练出雷达的解算网络,从而具有大规模室内、机载联网定位的应用潜力。

连续波生物雷达生命体征检测平台与实验研究

为全面提高实践教学质量,基于当前生物雷达生命体征检测的研究热点,开发了一个低成本的连续波生物雷达生命体征检测平台,用于开展呼吸、心率的非接触式检测实验研究。该实验平台以人体为被测对象,搭载了生物雷达传感器,以MSP430F5529 LaunchPad为硬件基础,设计了雷达基带信号调理电路板,并利用MATLAB/LabVIEW进行体动信号的数据处理和分析,提取呼吸、心跳信号。实验内容涵盖模拟电路、单片机与嵌入式系统、信号与系统、数字信号处理等多门课程内容。基于该实验平台进一步开展非接触式呼吸、心跳检测在医疗诊断、家庭监护领域的应用研究和创新开发,培养学生的创新精神和综合能力。

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%。

一种面向低成本轻量级雷达的单比特复用阵列信号收发框架

面向低成本轻量级雷达的应用需求,该文提出了一种联合单比特采样量化和时分复用接收机的雷达信号收发框架。首先,通过介绍该框架的工作原理,阐述其在节省接收机数量方面的优势。从雷达资源配置的角度,分析了单比特采样量化在该框架中的重要性,并提出了该框架可利用时间换空间,获得比经典线性调频连续波雷达更好的探测性能。接着,推导了雷达测距、测速和测角公式,以及目标参数估计的克拉美罗界。在此基础上,验证了该框架的性能优势,同时也给出了其稳定工作的信噪比条件。最后,利用一种基于单比特二维多重信号分类的速度维配对算法,验证了该框架获取目标原理的正确性,以及性能分析的可靠性。

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。

基于延迟断点映射FMCW的双功能雷达通信系统设计

基于调频连续波(Frequency Modulated Continuous Wave, FMCW)的双功能雷达通信(Dual-Functional RadarCommunication, DFRC)系统具有时频利用率高、抗多普勒性能强、距离旁瓣低的特点。现有的FMCW-DFRC波形系统产生双功能性能恶化,并增加通信接收机的链路复杂度。设计了一种基于延迟断点映射(Delayed Breakpoint Mapping, DBM)FMCW的DFRC系统,通过啁啾周期内延迟断点位置的映射和被分割的簇间的相位进行数据调制。通信接收端在载波混频和欠采样后,在数字域实现去啁啾、码片对齐和数据解调,极大降低了接收端生成相干信号和ADC性能的需求。在雷达处理链路中,设计了断点区域删除与拼接(Breakpoint Area Deletion and Splicing, BADS)方案,使DFRC的雷达性能与无调制的FMCW一致。仿真结果表明,与无补偿的方案相比,BADS方案距离图像的副瓣幅度减小约37 dB,且不受调制数据的影响。与现有基于啁啾波形的DFRC方案的通信性能相比,DBM-FMCW降低了约3 dB误符号率。

基于多核DSP的星载双基FMCW SAR成像算法实现

调频连续波(frequency modulated continuous wave,FMCW)合成孔径雷达(synthetic aperture radar,SAR)降低了传感器的峰值传输功率,使系统的重量和成本最小化,被广泛应用于机载平台。将双基地构型与FMCW技术相结合,应用于星载平台,即构成星载双基地FMCW SAR。本文对距离多普勒(range-Doppler,RD)算法进行改进,建立起一种高性能的适宜星载双基地平台的FMCW SAR成像频域算法,这种算法的处理精度明显提高,成像效果更好。基于多核数字信号处理器(digital signal processor,DSP)构建适用于星载双基SAR成像算法的并行处理架构,完成软硬件设计实现。验证了所提软件架构可以满足实时成像需求,以及算法工程化实现的可行性。

基于24 GHz连续波多普勒雷达能量密度分布的非接触式睡眠动作检测

睡眠动作是反映睡眠质量的重要生理指标。现有基于雷达的睡眠动作检测方法主要根据雷达信号原始能量的变化检测睡眠动作。由于不同目标动作幅度的不同会导致能量变化的差异,这些方法在检测不同目标的睡眠动作时准确率受限。为提高睡眠动作检测的准确率,提出了一种基于雷达能量密度分布的睡眠动作检测方法。首先,提出基于连续波多普勒雷达能量密度分布的检验统计量特征和显著性水平特征;随后基于上述特征引入XGBoost模型实现睡眠动作检测;最后,通过多种环境下的真实实验验证算法的有效性与鲁棒性。实验结果表明,所提出的检验统计量特征和显著性水平特征可以在降低训练样本需求的同时有效提高准确率,在多种环境下均能达到95%以上的检测准确率。

强干扰下基于三阶互累积量的FMCW雷达信号DOA估计算法

针对车载调频连续波雷达存在相互干扰的实际情况,本文提出了一种基于三阶互累积量的多目标波达方向超分辨估计方法.该方法利用同步采集的阵列信号并根据回波信号和干扰信号的非相关特性,构造三阶互累积量矩阵,随后根据子空间方法获得二维空间谱,实现距离和方位的联合估计.计算机仿真结果表明,本文所提方法能够在抑制强干扰影响的同时实现3°以内多目标识别,与现有超分辨法和重构法相比,具有更高的角度分辨率和估计精度.

利用调频连续波雷达测距讲解频谱分析

分析模拟信号的频谱是离散傅里叶变换(DFT)的一个重要应用,也是本科“数字信号处理”课程的重要知识点。以调频连续波雷达测距为例,结合具体参数讲解“数字信号处理”课程中频率估计、频率分辨率和栅栏效应等知识点,探索如何结合工程案例提升专业课程的教学效果,不仅促进了学生对相关知识的理解,还让学生深刻体会到理论结合实际的重要性。

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。