Human and non-human object identification method based on PIR (Pyroelectric Infrared) detector

Abstract

The invention discloses a human and non-human object identification method based on a PIR (Pyroelectric Infrared) detector, belongs to the technical fields of digital signal processing and mode identification, and particularly relates to infrared intrusion application in a security system. The core thought is based on a general PIR detector, a human and non-human object detection model is established in combination with the characteristic of a bodily form difference between a human and a non-human object, a theoretical basis is laid for the analysis of a signal difference between the human and the non-human object, and a PIR signal characteristic extraction method applicable to human and non-human object identification is provided technically. The PIR signal characteristic extraction method comprises the following steps: 1, performing de-noising and normalization preprocessing on a PIR signal; 2, computing the zero-cross rate of the preprocessed PIR signal; 3, performing first-order difference processing on the preprocessed PIR signal, performing AR (Automatic Regression) model analysis, and solving the regression coefficient of a model by using a Marple algorithm; and 4, applying the zero-cross rate obtained in the step 2 and the regression coefficient obtained in the step 3 to human and non-human object identification as characteristic descriptions of the PIR signal. Lastly, as proved by experiments, the method has high reliability in human and non-human object identification.

Description

technical field [0001] The invention belongs to the technical field of digital signal processing and pattern recognition, and particularly relates to the application of infrared intrusion alarm in security systems. Background technique [0002] With the development of the economy and the advancement of science and technology, people have put forward higher requirements for social public safety and home environment safety; the safe city construction carried out by the government also poses higher technical challenges to various security products. PIR (Pyroeletric Infrared) detectors, also known as passive infrared detectors, can effectively detect mobile infrared radiation sources in sensitive areas at room temperature, realize infrared intrusion alarms, and have good concealment, stable performance, no lighting requirements, and cost-effective High, so it has great potential for development in the field of security. [0003] The sensing object of the PIR detector is a movin...

AI Technical Summary

Problems solved by technology

Among them, the time-domain analysis method, such as the peak-finding algorithm, is greatly affected by the randomness of the PIR signal, and its reliability is very low; the frequency-domain analysis method, such as performing FFT transformation on the PIR signal to obtain the The lack of time-domain features of the signal leads to a low recognition rate of people and non-humans; wavelet analysis is a typical time-frequency domain analysis method, which first transforms the PIR signal from the time domain to the wavelet domain, and then extracts the time domain and frequency The signal features in the two scale directions of the domain, this method can better realize the recognition of people and non-humans, but the algorithm complexity is relatively large

In general, in view of the high false alarm rate of general-purpose PIR detectors caused by non-human beings, there is currently a lack of theoretical analysis of the difference between human and non-human PIR signals, and there are few methods for extracting PIR signal features related to human and non-human recognition. Research is still in its infancy

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