The identification of weak vital signs has always been one of the difficulties in the field of life detection. In this paper, a novel vital sign detection and extraction method with high efficiency, high precision, high sensitivity and high signal-to-noise ratio is proposed. Based on the NVA6100 pulse radar system, the radar matrix which contains several radar pulse detection signals is received. According to the characteristics of vital signs and radar matrices, the Singular Value Decomposition (SVD) is adopted to perform signal denoising and decomposition after preprocessing, and the temporal and spatial eigenvectors of each principal component are obtained. Through the energy proportion screening, the Wavelet Transform decomposition and linear trend suppression, relatively pure vital signs in each principal component, are obtained. The human location is detected by the Energy Entropy of spatial eigenvectors, and the respiratory signal and heartbeat signal are restored through a Butterworth Filter and an MTI harmonic canceller. Finally, through an analysis of the performance of the algorithm, it is proved to have the properties of efficiency and accuracy.

/pdf/a-vital-signs-fast-detection-and-extraction-method-of-uwb-1qpjysrp.pdf

X-Ray Pulsar Signal De-noising Using Lifting Scheme Wavelet

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

In the X-ray pulsar navigation process, since the pulsar signal obtained by the epoch folding contains a large amount of noise, the signal must be denoised in order to obtain higher positioning accuracy. In order to further optimize the denoising effect and improve the algorithm in real time, this paper proposes a pulsar wavelet base and implements its lifting scheme. In this paper, wavelet multi-level decomposition is performed on the pulsar outline, then a wavelet base based on the pulsar's own signal is constructed according to the low-frequency coefficients, and its lifting method is realized. Matlab simulation shows that compared with db4 and db5 methods, the proposed method performs better in terms of signal-to-noise ratio, mean square error, peak relative error, peak position error and real-time performance. Although the peak error of the db1 wavelet is relatively small, its signal-to-noise ratio is too large, and the overall performance is obviously not as good as the proposed method. The proposed signal-to-noise ratio is up to 4.2dB higher than the db4 and db5 methods, and the mean square error is only 24.3% of the db4 and db5 methods. The peak position error is only 50% of the db4 and db5 methods.

X-Ray Pulsar Signal De-noising Using Lifting Scheme Wavelet

Citations

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

Lifting wavelet denoising based on pulsar wavelet basis

References

Lifting wavelet denoising based on pulsar wavelet basis

Related Papers (5)

Denoising of Pulsar Signal Using Wavelet Transform

Lifting wavelet denoising based on pulsar wavelet basis

De-Noising of Gaussian Noise using Discrete Wavelet Transform

De-noising of spectral signal based on stationary wavelet transform

De-noising of ECG Signal Based on Stationary Wavelet Transform