It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present...It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.展开更多
Cameras can reliably detect human motions in a normal environment, but they are usually affected by sudden illumination changes and complex conditions, which are the major obstacles to the reliability and robustness o...Cameras can reliably detect human motions in a normal environment, but they are usually affected by sudden illumination changes and complex conditions, which are the major obstacles to the reliability and robustness of the system. To solve this problem, a novel integration method was proposed to combine hi-static ultra-wideband radar and cameras. In this recognition system, two cameras are used to localize the object＇s region, regions while a radar is used to obtain its 3D motion models on a mobile robot. The recognition results can be matched in the 3D motion library in order to recognize its motions. To confirm the effectiveness of the proposed method, the experimental results of recognition using vision sensors and those of recognition using the integration method were compared in different environments. Higher correct-recognition rate is achieved in the experiment.展开更多
For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform d...For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform design which is aimed to improve the ability of discriminating target and clutter from the radar scene. Firstly, a sequence of Morlet wavelet pulses with frequency hopping and pulse position modulation by Welch-Costas array is designed. Then a waveform optimization solution is proposed which is achieved by applying the minimization mutual-information（MI） strategy. After that, with subsequent iterations of the algorithm, simulation results demonstrate that the optimal waveform design method brings an improvement in the target detection ability in the presence of noise and clutter.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
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
Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target...Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target echo and RFI have different Region Of Support (ROS) in 2-D fast- time wavenumber and aperture wavenumber domain. Consequently, a novel adaptive filter is pro- posed according to the Wiener optimum criterion on the distinct ROS characteristics of target echo and RFI. Compared with the notch filter and the Least Mean Square (LMS) adaptive filter in previ- ous literatures, the proposed method is more computationally efficient with satisfactory suppression results. In terms of Signal-to-Interference Ratio Improvement (SIRI) and processing time, the per- formance of the proposed adaptive filter is verified with the field data collected with a UWB SAR system.展开更多
Noncoherent communication receivers (differential-detectors) have simple design, however, they always incur bit error rate (BER) performance loss up to 3dB compared to coherent receivers. In this paper, a differential...Noncoherent communication receivers (differential-detectors) have simple design, however, they always incur bit error rate (BER) performance loss up to 3dB compared to coherent receivers. In this paper, a differential-detector is proposed for impulse radio ultra wideband (IR-UWB) communication systems. The system employs bit-level differential phase shift keying (DPSK) combined with code division (CD) for IR-UWB signals to support multiple-access (MA). It is analyzed under additive white Gaussian noise (AWGN) corrupted by multiple-access interference (MAI) channel. Its BER performance is compared against a reference coherent receiver using Monte-Carlo simulation method. A closed form expression for its average probability of error is derived analytically. Simulation results and theoretical analysis confirm the applicability of the proposed differential-detector for IR-UWB communication systems.展开更多
文摘It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.
基金Supported by National Natural Science Foundation of China(No.50875193)
文摘Cameras can reliably detect human motions in a normal environment, but they are usually affected by sudden illumination changes and complex conditions, which are the major obstacles to the reliability and robustness of the system. To solve this problem, a novel integration method was proposed to combine hi-static ultra-wideband radar and cameras. In this recognition system, two cameras are used to localize the object＇s region, regions while a radar is used to obtain its 3D motion models on a mobile robot. The recognition results can be matched in the 3D motion library in order to recognize its motions. To confirm the effectiveness of the proposed method, the experimental results of recognition using vision sensors and those of recognition using the integration method were compared in different environments. Higher correct-recognition rate is achieved in the experiment.
基金supported by the National Natural Science Foundation of China(6107114561271331)
文摘For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform design which is aimed to improve the ability of discriminating target and clutter from the radar scene. Firstly, a sequence of Morlet wavelet pulses with frequency hopping and pulse position modulation by Welch-Costas array is designed. Then a waveform optimization solution is proposed which is achieved by applying the minimization mutual-information（MI） strategy. After that, with subsequent iterations of the algorithm, simulation results demonstrate that the optimal waveform design method brings an improvement in the target detection ability in the presence of noise and clutter.
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Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target echo and RFI have different Region Of Support (ROS) in 2-D fast- time wavenumber and aperture wavenumber domain. Consequently, a novel adaptive filter is pro- posed according to the Wiener optimum criterion on the distinct ROS characteristics of target echo and RFI. Compared with the notch filter and the Least Mean Square (LMS) adaptive filter in previ- ous literatures, the proposed method is more computationally efficient with satisfactory suppression results. In terms of Signal-to-Interference Ratio Improvement (SIRI) and processing time, the per- formance of the proposed adaptive filter is verified with the field data collected with a UWB SAR system.
文摘Noncoherent communication receivers (differential-detectors) have simple design, however, they always incur bit error rate (BER) performance loss up to 3dB compared to coherent receivers. In this paper, a differential-detector is proposed for impulse radio ultra wideband (IR-UWB) communication systems. The system employs bit-level differential phase shift keying (DPSK) combined with code division (CD) for IR-UWB signals to support multiple-access (MA). It is analyzed under additive white Gaussian noise (AWGN) corrupted by multiple-access interference (MAI) channel. Its BER performance is compared against a reference coherent receiver using Monte-Carlo simulation method. A closed form expression for its average probability of error is derived analytically. Simulation results and theoretical analysis confirm the applicability of the proposed differential-detector for IR-UWB communication systems.
