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Received signal strength and multi-path information combined neural network indoor positioning method

A technology for receiving signal strength and indoor positioning, which is applied in positioning, wireless communication, nan and other directions, and can solve problems such as the influence of RSS accuracy

Inactive Publication Date: 2014-07-23
TSINGHUA UNIV
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Problems solved by technology

Some studies have pointed out that many factors can affect the accuracy of RSS

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  • Received signal strength and multi-path information combined neural network indoor positioning method

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[0034] The present invention provides a neural network indoor positioning method combined with received signal strength and multipath information. The positioning method includes positioning in the offline stage and the online stage: the embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, and the examples of the embodiments are in the appended In the drawings, the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0035] In describing the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", " The orientations or positional relationships indicated by "vertical",...

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Abstract

The invention belongs to the technical field of positioning, and discloses a received signal strength and multi-path information combined neural network indoor positioning method. The method includes the offline stage and the online stage. In the offline stage, reference points distributed in the indoor environment are determined according to the characteristics of the indoor environment; each selected reference point is measured to obtain signals, from different access points, of each reference point; the RSS and multi-path characteristic parameters are extracted from the received signals; the extracted RSS and the extracted multi-path characteristic parameters are normalized. In the online stage, signals from all the access points are received in real time; the RSS and the multi-path parameters are extracted from the signals which are received in real time; the RSS and the multi-path parameters are normalized through the offline normalization value; the normalized parameters serve as input of an offline trained neural network, and output is obtained to serve as estimation of the current position. According to the method, the problem that positioning accuracy is low can be solved, and positioning accuracy can be effectively improved.

Description

technical field [0001] The invention relates to the technical field of positioning, in particular to an indoor positioning method of a neural network combined with received signal strength and multipath information. Background technique [0002] There is an obvious shortcoming in GPS positioning technology, that is, positioning cannot be realized in an indoor environment, and the main reason is that the indoor environment lacks line-of-sight transmission. [0003] At present, there are various ways of indoor positioning, and most of them use existing infrastructure, such as ultra-wideband (UWB), wireless local area network (WLAN), and so on. One of the positioning methods is an indoor positioning method based on received signal strength (RSS) fingerprints. This method can locate people or objects in an indoor environment, but this method also has some problems. Some studies have pointed out that many factors can affect the accuracy of RSS. To improve the precision and acc...

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Application Information

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IPC IPC(8): H04W4/04G01S5/02
Inventor 肖立民陈国峰许希斌张焱周世东
Owner TSINGHUA UNIV
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