Mobile equipment position estimation method based on multi-base-station channel state information fusion

Abstract

The invention discloses a mobile equipment position estimation method based on multi-base-station channel state information fusion, and belongs to the technical field of radio mobile positioning. The method comprises the following steps: enabling a base station to collect a non-real-time channel state information sample from mobile equipment; extracting angular domain power spectrum channel characteristics; calculating the difference degree between the samples according to the angular domain power spectrum channel characteristics to obtain a single base station sample difference degree matrix; enabling a data fusion node to fuse the plurality of single base station sample difference degree matrixes to obtain a global sample difference degree matrix; enabling the data fusion node to create a channel map for the sample data set according to the global sample difference degree matrix, and calibrate the channel map; and enabling the base station to collect real-time channel state information from the mobile equipment, and performs matching positioning by combining the sample data set and the channel map to obtain real-time position information of the mobile equipment. Accurate time synchronization between the base stations is not needed, field survey is not needed, the manual participation degree is reduced, and automatic operation of the mobile positioning system is achieved.

Description

technical field [0001] The invention belongs to the technical field of radio mobile positioning, and in particular relates to a method for estimating the position of a mobile device based on fusion of channel state information of multiple base stations. Background technique [0002] Mobile location information acquisition technology is the key support for the construction of smart cities. By sensing and collecting the time and space location information of crowds, logistics, vehicles and other IoT devices, it can be used for automatic management of wireless network spectrum resources, automatic driving, smart city lighting, Provide basic data for application scenarios such as smart logistics, smart security, mobile Internet social networking, and social situational awareness. [0003] With the application of massive multiple-input multiple-output (massive MIMO), ultra-dense networking, ultra-broadband and other technologies in 5G mobile networks, 5G base stations have strong...

AI Technical Summary

Problems solved by technology

[0004] Technical problem: In view of the existing mobile device positioning methods, which require high time synchronization accuracy between base stations and manual site surveys to achieve effective positioning, the present invention provides a mobile device position estimation based on multi-base station channel state information fusion method, which can realize mobile positioning and tracking under the conditions of low base station time synchronization accuracy and unsupervised conditions

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