For impulse radio ultra-wideband (IR-UWB) ranging systems,effects of the settings of transmitter-related parameters, which include the pulse shape, the bandwidth and the pulse repetition interval (PRI), on ranging acc...For impulse radio ultra-wideband (IR-UWB) ranging systems,effects of the settings of transmitter-related parameters, which include the pulse shape, the bandwidth and the pulse repetition interval (PRI), on ranging accuracy were studied through theoretical analysis and simulations. Both the match-filtering based coherent TOA estimation algorithm and the energy-detection based non-coherent algorithm were used during simulations. Results show that the pulse shape has the least effect on the ranging accuracy. Increasing the pulse bandwidth can improve the ranging performance, but the performance is hardly improved any more when the bandwidth is increased beyond a certain level. PRI should be set long enough to guarantee the accurate ranging, because when PRI is shorter than the maximum excess delay of the channel, the ranging accuracy will be deteriorated by inter-pulse interference.展开更多
人体呼吸系统相关疾病常常伴随着呼吸深度和节律的异常,因此呼吸信号监测和呼吸模式识别在医疗健康领域中尤其是对于睡眠监测、疾病预断具有重要意义。其中,非接触式的脉冲式超宽带雷达(Impulse Radio Ultra-Wideband,IR-UWB)因具有良...人体呼吸系统相关疾病常常伴随着呼吸深度和节律的异常,因此呼吸信号监测和呼吸模式识别在医疗健康领域中尤其是对于睡眠监测、疾病预断具有重要意义。其中,非接触式的脉冲式超宽带雷达(Impulse Radio Ultra-Wideband,IR-UWB)因具有良好的距离分辨率和穿透能力以及全天候全天时、安全无创的检测优势,正逐步成为睡眠健康监护领域中最关键的感知技术之一。然而受睡眠监测特定的室内场景影响,复杂的测量环境给呼吸模式特征的准确提取带来了限制和挑战,传统的雷达呼吸模式识别算法主要关注一维呼吸时、频域特征,而IR-UWB雷达目标回波信息分散在多个距离门内,使用一维特征识别准确率较低。为此,本文针对IR-UWB雷达中人体呼吸在时间上慢速起伏运动、在距离上是扩展目标的信号模型特点,提出了一种引入时距信息的IR-UWB雷达多域特征融合呼吸模式识别方法。算法在提取一维呼吸信号波形时、频域特征的基础上更进一步挖掘雷达二维时距图像中潜在的呼吸模式形态特征,通过多域特征融合实现呼吸模式的非接触式检测和识别。在图像处理上,针对图像受呼吸异常节律影响呈现局部粘连特性导致呼吸周期提取难的问题,提出一种通过相位矩阵图像处理来检测雷达图像中的呼吸时距条带从而获取图像特征的方法。实验结果表明,利用该算法提取的多域特征对六种呼吸模式进行机器学习的分类识别,可以实现96.3%的识别准确率。展开更多
研究了一种基于时域射线追踪技术(Time Domain Ray Tracing)适用于大尺度室内环境传播建模的IR-UWB信号传播模型。该模型综合考虑室内传播存在的多径效应、阴影效应和穿墙效应等物理现象,引入墙体内部的时域传输系数和墙体至空气的时域...研究了一种基于时域射线追踪技术(Time Domain Ray Tracing)适用于大尺度室内环境传播建模的IR-UWB信号传播模型。该模型综合考虑室内传播存在的多径效应、阴影效应和穿墙效应等物理现象,引入墙体内部的时域传输系数和墙体至空气的时域透射系数,分析并解释了时域传播系数的物理意义。模型利用了IR-UWB信号时域极窄的特点,与传统的FDTD方法相比,能够显著提高大尺度环境下的计算效率。最后通过与实测结果的对比,验证了该模型的有效性,详细研究了模型的计算精度及误差成因。展开更多
Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the ...Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.展开更多
目的:为解决穿透条件下多人体目标识别定位问题,提出一种基于多基地脉冲超宽谱(impluse radio ultra wideband,IR-UWB)生物雷达系统的多人体目标识别定位方法。方法:基于多基地IR-UWB生物雷达系统,采用回波二次拐点和相关系数相结合的方...目的:为解决穿透条件下多人体目标识别定位问题,提出一种基于多基地脉冲超宽谱(impluse radio ultra wideband,IR-UWB)生物雷达系统的多人体目标识别定位方法。方法:基于多基地IR-UWB生物雷达系统,采用回波二次拐点和相关系数相结合的方法,对穿墙条件下采集的多目标雷达回波信号进行处理和目标识别,再根据计算出的各目标在3个通道中的径向距离和获得的方位信息对目标进行定位。为验证方法的有效性,在实验室条件下进行多人体目标识别定位实验。结果:该方法可以对多人体目标进行正确识别和定位,3个目标的径向距离定位结果与实测距离误差均小于0.1 m。结论:基于多基地IR-UWB生物雷达系统的多人体目标识别定位方法可在穿墙条件下实现3个人体目标的探测定位,大大提高了非接触生命探测的效率。展开更多
This paper introduces a human gesture recognition algorithm using an impulse radio ultra-wide- band (IR-UWB) radar sensor. Human gesture recognition has been one of the hottest research topics for quite a long time. M...This paper introduces a human gesture recognition algorithm using an impulse radio ultra-wide- band (IR-UWB) radar sensor. Human gesture recognition has been one of the hottest research topics for quite a long time. Many gesture recognition algorithms or systems using other sensors have been proposed such as using cameras, RFID tags and so on. Among which gesture recognition systems using cameras have been extensively studied in past years and widely used in practical. While it might show some deficiencies in some cases. For example, the users might not like to be filmed by cameras considering their privacies. Besides, it might not work well in very dark environments. While RFID tags could be inconvenient to many people and are likely to be lost. Our gesture recognition algorithm uses IR-UWB radar sensor which has pretty high resolution in ranging and adjustable gesture recognition range, meanwhile, does not have problems in privacy issues or darkness. In this paper, the gesture recognition algorithm is based on the moving direction and distance change of the human hand and the change of the frontal surface area of hand towards radar sensor. By combining these changes while doing gestures, the algorithm may recognize basically 6 kinds of hand gestures. The experimental results show that these gestures are of quite good performance. The performance analysis from experiments is also given.展开更多
A 3-5 GHz low power BPSK modulated impulse radio UWB transmitter is implemented in 0.13μm CMOS technology. In this design the amplitude and spectrum of the output impulse are both tunable to solve the special problem...A 3-5 GHz low power BPSK modulated impulse radio UWB transmitter is implemented in 0.13μm CMOS technology. In this design the amplitude and spectrum of the output impulse are both tunable to solve the special problem in IR-UWB, where it is difficult to control the spectrum. Measurement results indicate that, by changing the control bits in the gain control circuit and differential circuit, the 3-step peak-to-peak voltage amplitudes are 240, 170 and 115 mV and the center frequency of the impulse can be tuned from 3.2 to 4.1 GHz. A power controlled output buffer is designed to drive the antenna. The total power consumption is only 4.44 mW when transmitting a baseband signal of 100 MHz. The chip area is 1.2 × 1.4 mm^2.展开更多
基金Sponsored by the National Natural Science Foundation of China (Grant No.60432040)the Natural Science Foundation of Guangdong Privince(Grant No.9451805707003235)
文摘For impulse radio ultra-wideband (IR-UWB) ranging systems,effects of the settings of transmitter-related parameters, which include the pulse shape, the bandwidth and the pulse repetition interval (PRI), on ranging accuracy were studied through theoretical analysis and simulations. Both the match-filtering based coherent TOA estimation algorithm and the energy-detection based non-coherent algorithm were used during simulations. Results show that the pulse shape has the least effect on the ranging accuracy. Increasing the pulse bandwidth can improve the ranging performance, but the performance is hardly improved any more when the bandwidth is increased beyond a certain level. PRI should be set long enough to guarantee the accurate ranging, because when PRI is shorter than the maximum excess delay of the channel, the ranging accuracy will be deteriorated by inter-pulse interference.
文摘人体呼吸系统相关疾病常常伴随着呼吸深度和节律的异常,因此呼吸信号监测和呼吸模式识别在医疗健康领域中尤其是对于睡眠监测、疾病预断具有重要意义。其中,非接触式的脉冲式超宽带雷达(Impulse Radio Ultra-Wideband,IR-UWB)因具有良好的距离分辨率和穿透能力以及全天候全天时、安全无创的检测优势,正逐步成为睡眠健康监护领域中最关键的感知技术之一。然而受睡眠监测特定的室内场景影响,复杂的测量环境给呼吸模式特征的准确提取带来了限制和挑战,传统的雷达呼吸模式识别算法主要关注一维呼吸时、频域特征,而IR-UWB雷达目标回波信息分散在多个距离门内,使用一维特征识别准确率较低。为此,本文针对IR-UWB雷达中人体呼吸在时间上慢速起伏运动、在距离上是扩展目标的信号模型特点,提出了一种引入时距信息的IR-UWB雷达多域特征融合呼吸模式识别方法。算法在提取一维呼吸信号波形时、频域特征的基础上更进一步挖掘雷达二维时距图像中潜在的呼吸模式形态特征,通过多域特征融合实现呼吸模式的非接触式检测和识别。在图像处理上,针对图像受呼吸异常节律影响呈现局部粘连特性导致呼吸周期提取难的问题,提出一种通过相位矩阵图像处理来检测雷达图像中的呼吸时距条带从而获取图像特征的方法。实验结果表明,利用该算法提取的多域特征对六种呼吸模式进行机器学习的分类识别,可以实现96.3%的识别准确率。
文摘研究了一种基于时域射线追踪技术(Time Domain Ray Tracing)适用于大尺度室内环境传播建模的IR-UWB信号传播模型。该模型综合考虑室内传播存在的多径效应、阴影效应和穿墙效应等物理现象,引入墙体内部的时域传输系数和墙体至空气的时域透射系数,分析并解释了时域传播系数的物理意义。模型利用了IR-UWB信号时域极窄的特点,与传统的FDTD方法相比,能够显著提高大尺度环境下的计算效率。最后通过与实测结果的对比,验证了该模型的有效性,详细研究了模型的计算精度及误差成因。
基金This work was supported by the National Key Research and Development Program of China(2018YFC0810202)the National Defence Pre-research Foundation of China(61404130119).
文摘Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.
文摘目的:为解决穿透条件下多人体目标识别定位问题,提出一种基于多基地脉冲超宽谱(impluse radio ultra wideband,IR-UWB)生物雷达系统的多人体目标识别定位方法。方法:基于多基地IR-UWB生物雷达系统,采用回波二次拐点和相关系数相结合的方法,对穿墙条件下采集的多目标雷达回波信号进行处理和目标识别,再根据计算出的各目标在3个通道中的径向距离和获得的方位信息对目标进行定位。为验证方法的有效性,在实验室条件下进行多人体目标识别定位实验。结果:该方法可以对多人体目标进行正确识别和定位,3个目标的径向距离定位结果与实测距离误差均小于0.1 m。结论:基于多基地IR-UWB生物雷达系统的多人体目标识别定位方法可在穿墙条件下实现3个人体目标的探测定位,大大提高了非接触生命探测的效率。
文摘This paper introduces a human gesture recognition algorithm using an impulse radio ultra-wide- band (IR-UWB) radar sensor. Human gesture recognition has been one of the hottest research topics for quite a long time. Many gesture recognition algorithms or systems using other sensors have been proposed such as using cameras, RFID tags and so on. Among which gesture recognition systems using cameras have been extensively studied in past years and widely used in practical. While it might show some deficiencies in some cases. For example, the users might not like to be filmed by cameras considering their privacies. Besides, it might not work well in very dark environments. While RFID tags could be inconvenient to many people and are likely to be lost. Our gesture recognition algorithm uses IR-UWB radar sensor which has pretty high resolution in ranging and adjustable gesture recognition range, meanwhile, does not have problems in privacy issues or darkness. In this paper, the gesture recognition algorithm is based on the moving direction and distance change of the human hand and the change of the frontal surface area of hand towards radar sensor. By combining these changes while doing gestures, the algorithm may recognize basically 6 kinds of hand gestures. The experimental results show that these gestures are of quite good performance. The performance analysis from experiments is also given.
文摘A 3-5 GHz low power BPSK modulated impulse radio UWB transmitter is implemented in 0.13μm CMOS technology. In this design the amplitude and spectrum of the output impulse are both tunable to solve the special problem in IR-UWB, where it is difficult to control the spectrum. Measurement results indicate that, by changing the control bits in the gain control circuit and differential circuit, the 3-step peak-to-peak voltage amplitudes are 240, 170 and 115 mV and the center frequency of the impulse can be tuned from 3.2 to 4.1 GHz. A power controlled output buffer is designed to drive the antenna. The total power consumption is only 4.44 mW when transmitting a baseband signal of 100 MHz. The chip area is 1.2 × 1.4 mm^2.
