Jianqi Wang
Fourth Military Medical University
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Publication
Featured researches published by Jianqi Wang.
IEEE Transactions on Microwave Theory and Techniques | 2013
Zhao Li; Wenzhe Li; Hao Lv; Yang Zhang; Xijing Jing; Jianqi Wang
Detection of trapped survivors under collapsed buildings using impulse-radio ultra-wideband (IR-UWB) radar has become an important research topic. However, due to the jitter or drift of the radar, clutter reflected from walls or rubble is similar to the human respiratory response in some scenarios. Thus, it becomes difficult to determine the presence or absence of the survivor under ruins. In this paper, a novel dual-frequency IR-UWB radar with low center frequencies is developed and a method based on adaptive clutter cancellation is proposed to eliminate the respiration-like clutter. Experiments are carried out in both through-wall and simulated rubble cases, and the results shows that the proposed method outperforms the common method, which is based on linear-trend subtraction with single-frequency IR-UWB radar in removing the respiration-like clutter and improves the radar performance in life detection.
IEEE Geoscience and Remote Sensing Letters | 2013
Zhu Zhang; Xiao Zhang; Hao Lv; Guohua Lu; Xijing Jing; Jianqi Wang
The presence of a human target and the surrounding rubble structure are both important information in postdisaster rescue. In this letter, we study the signal-processing algorithm for detecting a human target in radar echo data. Furthermore, a solution is proposed to estimate the surrounding structure-the distance between the human target and the top wall of the cavity where the human target is trapped. In the latter procedure, the human position estimated before is used as a prior knowledge. In order to verify the feasibility of the proposed method, experiments are carried out with a human subject lying under the simulated rubble structure. The results show prospects of the proposed method.
Progress in Electromagnetics Research-pier | 2013
Wen Zhe Li; Zhao Li; Hao Lv; Guohua Lu; Yang Zhang; Xijing Jing; Sheng Li; Jianqi Wang
The physiological parameters monitoring of human target are considered to be a meaningful and challenging task in non-lineof-sight (NLOS) scenes such as rescue of trapped survivors in postdisaster. In this paper, a new method based on developed adaptive line enhancer (DALE) is proposed to monitor vital signs via ultra-wideband (UWB) radar with centre frequency of 400MHz. The validity of this new method is proved by means of two experiments with different positions of human target. The good results demonstrate that this new method can be used for vital sign monitoring including respiration and heartbeat through the obstacle. Furthermore, the motion responses due to respiration and heartbeat in different body positions are also discussed.
Sensors | 2015
Chuantao Li; Fuming Chen; Jingxi Jin; Hao Lv; Sheng Li; Guohua Lu; Jianqi Wang
After chemical or nuclear leakage or explosions, finding survivors is a huge challenge. Although human bodies can be found by smart vehicles and drones equipped with cameras, it is difficult to verify if the person is alive or dead this way. This paper describes a continuous wave radar sensor for remotely sensing the vital signs of human subjects. Firstly, a compact and portable 24 GHz Doppler radar system is designed to conduct non-contact detection of respiration signal. Secondly, in order to improve the quality of the respiration signals, the self-correlation and adaptive line enhancer (ALE) methods are proposed to minimize the interferences of any moving objects around the human subject. Finally, the detection capabilities of the radar system and the signal processing method are verified through experiments which show that human respiration signals can be extracted when the subject is 7 m away outdoors. The method provided in this paper will be a promising way to search for human subjects outdoors.
IEEE Geoscience and Remote Sensing Letters | 2015
Yang Zhang; Teng Jiao; Hao Lv; Sheng Li; Changzhi Li; Guohua Lu; Xiao Yu; Zhao Li; Jianqi Wang
Life detection radar can detect human physiological signals (respiration, heartbeat, body movement, etc.) from a long distance away by penetrating nonmetal mediums (brick walls, ruins, etc.). However, interference is often caused by respiratory movements of the radars operator when detecting vital signs of another human target. The detection accuracy can be significantly influenced by this kind of interference. In this letter, an experimental setup with a dual-frequency continuous-wave life detection radar is investigated. The system operates with different frequencies of 5.75 and 35 GHz. An adaptive filtering method is applied to suppress the interference caused by the operators respiratory movements. Experimental results show that this method can effectively suppress respiratory interference and improve detection accuracy.
Progress in Electromagnetics Research-pier | 2012
Sheng Li; Ying Tian; Guohua Lu; Yang Zhang; Hui Jun Xue; Jianqi Wang; Xijing Jing
Air is not the only medium that can spread and can be used to detect speech. In our previous paper, another valuable medium | millimeter wave (MMW) was introduced to develop a new kind of speech acquisition technique (6). Because of the special features of the MMW radar, this speech acquisition method may provide some exciting possibilities for a wide range of applications. In the proposed study, we have designed a new kind of speech acquisition radar system. The super-heterodyne receiver was used in the new system so that to mitigate the severe DC ofiset problem and the associated 1=f noise at baseband. Furthermore, in order to decrease the harmonic noise, electro-circuit noise, and ambient noise which were combined in the MMW detected speech, an adaptive wavelet packet entropy algorithm is also proposed in this study, which incorporates the wavelet packet entropy based voice/unvoiced radar speech adaptive detection method and the human ear perception properties in a wavelet packet time- scale adaptation speech enhancement process. The performance of the proposed method is evaluated objectively by signal-to-noise ratio and subjectively by mean-opinion-score. The results conflrm that the proposed method ofiers improved efiects over other traditional speech enhancement methods for MMW radar speech.
ieee region 10 conference | 2013
Hao Lv; Miao Liu; Teng Jiao; Yang Zhang; Xiao Yu; Sheng Li; Xijing Jing; Jianqi Wang
Being capable of sensing human through obstacles, bio-radar is promising in many applications like healthcare, public securities, emergency rescue and so on. In these applications, the presence of human and the human count are among the most important issues that are concerned by people. At present plenty of studies deal with the former issue but theres no study dealing with the latter one. To this end, a framework of determining the count of human targets using ultra-wideband (UWB) bio-radar was presented in this paper. It was developed based on multiple antennas and correlation processing of sensed respiration among the data channels. In the experiment, the UWB bio-radar could distinguish among the cases of no target, single target, two targets and three targets present behind a brick wall and determine the target count with no priori information. On this basis, multi-target estimation and localization can be further realized.
IEEE Transactions on Geoscience and Remote Sensing | 2014
Hao Lv; Wenzhe Li; Zhao Li; Yang Zhang; Teng Jiao; Huijun Xue; Miao Liu; Xijing Jing; Jianqi Wang
Impulse-radio ultrawideband (IR-UWB) radar is a popular research topic in the field of post-earthquake search and rescue. By lowering center frequency, it can penetrate through earthquake rubble to detect trapped victims mainly by identifying their respiratory-motion response. Thus, low-center-frequency IR-UWB respiratory-motion response is characterized for the first time in this paper. On this basis, a novel constant false alarm rate (CFAR) algorithm that automatically identifies the response is developed. The IR-UWB respiratory-motion response has range extension and interrelation characteristics. With these characteristics, the algorithm can effectively improve the estimation accuracy of clutter energy in CFAR detection. The characteristics and the algorithm performance are verified by experiment results, which show not only great promise in practice but also significance for future research of IR-UWB radar for detection of trapped victims.
Sensors | 2013
Sheng Li; Ying Tian; Guohua Lu; Yang Zhang; Hao Lv; Xiao Yu; Huijun Xue; Hua Zhang; Jianqi Wang; Xijing Jing
High frequency millimeter-wave (MMW) radar-like sensors enable the detection of speech signals. This novel non-acoustic speech detection method has some special advantages not offered by traditional microphones, such as preventing strong-acoustic interference, high directional sensitivity with penetration, and long detection distance. A 94-GHz MMW radar sensor was employed in this study to test its speech acquisition ability. A 34-GHz zero intermediate frequency radar, a 34-GHz superheterodyne radar, and a microphone were also used for comparison purposes. A short-time phase-spectrum-compensation algorithm was used to enhance the detected speech. The results reveal that the 94-GHz radar sensor showed the highest sensitivity and obtained the highest speech quality subjective measurement score. This result suggests that the MMW radar sensor has better performance than a traditional microphone in terms of speech detection for detection distances longer than 1 m. As a substitute for the traditional speech acquisition method, this novel speech acquisition method demonstrates a large potential for many speech related applications.
computer science and information engineering | 2009
Sheng Li; Jianqi Wang; Jing XiJing; Tian Liu
A new kind of nonacoustic sensor speech detecting system is developed in our laboratory. Since the special attribute of the millimeter wave, this method may provide some exciting opportunity for wide applications. However, due to the special feature of the nonacoustic sensor speech detecting principle, the additive combined noises corrupted the nonacoustic sensor speech greatly. Therefore, an improved spectrum subtract algorithm, which is based on the wavelet packet entropy analysis is proposed in order to enhance the nonacoustic sensor speech. The results are also compared to the traditional spectral subtraction algorithm, suggest that this method achieves a better reduction of the whole-frequency noise, and yields good speech quality.