Indoor positioning method based on antenna expansion

Abstract

An indoor positioning method based on antenna expansion comprises the steps: dividing a positioning area into a plurality of small grid areas, and collecting the CSI data of the positioning area in the center of each small grid as fingerprint features; constructing a position fingerprint database, and extracting amplitude information and phase information corresponding to each antenna after CSI phase matching; performing feature extraction on the amplitude and phase information by adopting DNN of angle domain assisted positioning to obtain a training model; in the online testing stage, collecting the real-time CSI and carrying out phase processing to obtain position information of a to-be-positioned point, and obtaining position coordinates through the trained deep neural network for angle domain assisted positioning according to fingerprint data. According to the invention, on the basis of not increasing wireless links, better direction estimation and higher-precision positioning are carried out by utilizing spatial diversity and multiplexing gain provided by more antennas, namely more CSI fingerprint characteristics.

Description

technical field [0001] The present invention relates to a technology in the field of wireless indoor positioning, specifically an indoor positioning method based on antenna extension and with an average positioning error of less than 1m, which can be used in other wireless communication systems such as multi-antenna array combination and LTE / NR. Background technique [0002] With the large-scale deployment of Wi-Fi systems in indoor environments, it has been applied to high-precision positioning. Common Wi-Fi-based indoor positioning technologies generally include triangulation and location fingerprinting. The trilateral positioning method does not need to spend a lot of manpower and material resources to build an offline fingerprint database, but the positioning accuracy of the positional fingerprinting method is higher, so this embodiment adopts the positional fingerprinting method, and selects channel state information (CSI) as the fingerprint feature. The main reason is ...

AI Technical Summary

Problems solved by technology

However, improving localization accuracy through spatial domain extension is not straightforward due to the following reasons

First, existing spatial domain schemes rely on computing geometric positions by measuring time-of-flight (ToF) and angle-of-arrival (AoA), and the corresponding resolution does not scale linearly with the number of available wireless links

Second, deploying more wireless links using expensive components, including low-noise amplifiers, analog-to-digital converters, or digital-to-analog converters, is costly

Third, the processing complexity increases exponentially with the number of wireless links

These reasons make indoor positioning rely on large-scale antenna arrays to improve accuracy, and there are some problems.

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