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Ansheng Ni

Publications and source records attributed to Ansheng Ni.

2 recordsLinked to original sources

[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.

Adult↗

[Study on eliminating self-dithering interference of the system for non-contact detecting life parameters based on an adaptive algorithm].

The non-contact life parameters detecting systems can detect many important life parameters such as heartbeat and breathing at certain distance. In practice, the self-dithering interference of the system is produced by some factors; it makes the signal-to-noise ratio (SNR) of the recorded signal lower. This paper is discussed an adaptive technology based on a variable step-size LMS algorithm, which is used to eliminate the self-dithering interference of the system and hence to raise the SNR of the detecting signal. A method to obtain the reference signal by vibration sensor is brought forward and the optimum parameters settings are discussed. The results show that the reference signal is an integral part of output signal of the vibration sensor and has a relationship with the setting direction of the sensor. The conclusion is that the method is effective and feasible; also the algorithm is well convergent.

Algorithms↗