Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array.

It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor's respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person's head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors.

A Novel Method for Speech Acquisition and Enhancement by 94 GHz Millimeter-Wave Sensor.

In order to improve the speech acquisition ability of a non-contact method, a 94 GHz millimeter wave (MMW) radar sensor was employed to detect speech signals. This novel non-contact speech acquisition method was shown to have high directional sensitivity, and to be immune to strong acoustical disturbance. However, MMW radar speech is often degraded by combined sources of noise, which mainly include harmonic, electrical circuit and channel noise. In this paper, an algorithm combining empirical mode decomposition (EMD) and mutual information entropy (MIE) was proposed for enhancing the perceptibility and intelligibility of radar speech. Firstly, the radar speech signal was adaptively decomposed into oscillatory components called intrinsic mode functions (IMFs) by EMD. Secondly, MIE was used to determine the number of reconstructive components, and then an adaptive threshold was employed to remove the noise from the radar speech. The experimental results show that human speech can be effectively acquired by a 94 GHz MMW radar sensor when the detection distance is 20 m. Moreover, the noise of the radar speech is greatly suppressed and the speech sounds become more pleasant to human listeners after being enhanced by the proposed algorithm, suggesting that this novel speech acquisition and enhancement method will provide a promising alternative for various applications associated with speech detection.

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.

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 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.

[Study on second filtering algorithm based on tracing the interfering spectral peaks of radar non-contact life-parameter detection system].

To develop a filtering algorithm which could trace the spectral peaks of the interference and which was used to extract the breath signal with the same band interference in radar non-contact life-detecting system, second filtering algorithm was studied. Through first filtering,the probable interfering spectral peaks (ISP) could be detected by Yule-Walker spectrum estimating and could be located by calculating the coefficients of normalized cross-correlation function according to standard breath signal. Thus the breath signal could be extracted through a second filtering. By using the second filtering algorithm (SFA), the same band interfering spectral peaks with breath signal could be recognized and inhibited. So we conclude that the same band mono-ISP could be inhibited by using SFA and breath signals could be effectively extracted.

[A study on technology to identify human beings or animals in life-detector based on radar].

To determine whether a living object is human being or animal by detecting the respiration signal using the life-detector based on radar to penetrate the building or debris. To fully utilize the nonstationary character of the respiration signal, short time Fourier transform (STFT) is employed to get the signal's time-frequency representation. Singular value decomposition (SVD) is then used in the spectrogram to extract feature vector for pattern identification. Human beings and animals can be identified from the respiration sensed by the life-detector based on radar. Experimental results show that the method based on STFT and SVD is stable and efficient to differ from the human being and animal.