Personnel action recognition and position estimation method based on channel state information

Abstract

The invention relates to a personnel action recognition and position estimation method based on channel state information (CSI) contained in a received signal. The method comprises the steps of in theoffline stage, at different reference position points, performing different action postures by a personnel target, and measuringCSI information of a router transmitting signal on a receiving networkcard; constructing a database and a database corresponding to each action label; preprocessing the constructed training database by using a data normalization and principal component analysis method;and performing action label-based classification learning on the database by utilizing a support vector machine to obtain an action-based classification model; in the online stage, according to the received CSI information, after data normalization and data preprocessing of principal component analysis are carried out, obtaining a personnel target action estimation result through an action classification model; and on the basis, obtaining a position estimation result of the personnel through a position regression model corresponding to the personnel action target estimation result.

Description

technical field [0001] The invention mainly utilizes the channel state information of the router signal received by the wireless network card, and uses the learning method of the support vector machine to perform action recognition and position estimation on the personnel target, belonging to the field of positioning and navigation. Background technique [0002] Action recognition and location estimation of human objects have various applications in daily life, such as elderly monitoring, fitness tracking, and smart home, and have attracted extensive attention from both academia and industry. Traditional human target action recognition and location estimation adopt methods based on devices, such as vision devices, wearable sensors or internal sensors of mobile phones. However, this method has certain application limitations. Vision-based systems cannot penetrate walls, require good lighting conditions, and violate human privacy. Sensor-based approaches employ devices that ...

AI Technical Summary

Problems solved by technology

However, this method has certain application limitations

Vision-based systems cannot penetrate walls, require good lighting conditions, and violate human privacy

Sensor-based approaches use devices that are inconvenient to wear in some situations, so are limited in scope and expensive to equip

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