Guohua Lu

Human-Target Detection and Surrounding Structure Estimation Under a Simulated Rubble via UWB Radar

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.

Contact-free Measurement of Heart Rate Variability via a Microwave Sensor.

Measures of heart rate variability (HRV) are widely used to assess autonomic nervous system (ANS) function. HRV can be recorded via electrocardiography (ECG), which is both non-invasive and widely available. However, ECG needs three electrodes touching the body of the subjects, which makes them feel nervous and uncomfortable, thus potentially affecting the recording. Contact-free detection of the heartbeat via a microwave sensor constitutes another means of determining the timing of cardiac cycles by continuous monitoring of mechanical contraction of the heart. This technique can measure the heartbeat without any electrodes touching human body and penetrate the clothes at some distances, which in some instances may prove a practical basis for HRV analysis. Comparison of 5-minute recordings demonstrated that there were no significant differences in the temporal, frequency domains and in non-linear dynamic analysis of HRV measures derived from heartbeat and ECG, which suggested this technique may prove a practical alternative to ECG for HRV analysis.

A NEW METHOD FOR NON-LINE-OF-SIGHT VITAL SIGN MONITORING BASED ON DEVELOPED ADAPTIVE LINE ENHANCER USING LOW CENTRE FREQUENCY UWB RADAR

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.

A Novel Radar Sensor for the Non-Contact Detection of Speech Signals

Different speech detection sensors have been developed over the years but they are limited by the loss of high frequency speech energy, and have restricted non-contact detection due to the lack of penetrability. This paper proposes a novel millimeter microwave radar sensor to detect speech signals. The utilization of a high operating frequency and a superheterodyne receiver contributes to the high sensitivity of the radar sensor for small sound vibrations. In addition, the penetrability of microwaves allows the novel sensor to detect speech signals through nonmetal barriers. Results show that the novel sensor can detect high frequency speech energies and that the speech quality is comparable to traditional microphone speech. Moreover, the novel sensor can detect speech signals through a nonmetal material of a certain thickness between the sensor and the subject. Thus, the novel speech sensor expands traditional speech detection techniques and provides an exciting alternative for broader application prospects.

Contact-free measurement of heartbeat signal via a doppler radar using adaptive filtering

It has been proven that the cardiopulmonary signs, including respiration and heartbeat signal, can be contact-free measured via a Doppler radar. However, the heartbeat signal cannot be identified when the human subject does not hold his or her breath. To resolve the problem, the adaptive noise canceller (ANC) based on recursive-least square (RLS) algorithm is presented to simultaneously measure the heartbeat and the respiration signal. Experimental results showed that not only can the heartbeat signal be well identified, but the heart rate also strongly correlated with that derived from the electrocardiogram (ECG).

A Method for Remotely Sensing Vital Signs of Human Subjects Outdoors

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.

An Interference Suppression Technique for Life Detection Using 5.75- and 35-GHz Dual-Frequency Continuous-Wave Radar

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.

A NEW KIND OF NON-ACOUSTIC SPEECH ACQUISITION METHOD BASED ON MILLIMETER WAVERADAR

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.

A 94-GHz Millimeter-Wave Sensor for Speech Signal Acquisition

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.

Contact-Free Detection of Obstructive Sleep Apnea Based on Wavelet Information Entropy Spectrum Using Bio-Radar

Judgment and early danger warning of obstructive sleep apnea (OSA) is meaningful to the diagnosis of sleep illness. This paper proposed a novel method based on wavelet information entropy spectrum to make an apnea judgment of the OSA respiratory signal detected by bio-radar in wavelet domain. It makes full use of the features of strong irregularity and disorder of respiratory signal resulting from the brain stimulation by real, low airflow during apnea. The experimental results demonstrated that the proposed method is effective for detecting the occurrence of sleep apnea and is also able to detect some apnea cases that the energy spectrum method cannot. Ultimately, the comprehensive judgment accuracy resulting from 10 groups of OSA data is 93.1%, which is promising for the non-contact aided-diagnosis of the OSA.