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WLAN indoor positioning method based on matrix correlation

An indoor positioning and matrix technology, applied in the field of pattern recognition, can solve problems such as missing RSS information, and achieve the effect of avoiding information loss and accurate positioning results

Active Publication Date: 2012-11-28
HARBIN INST OF TECH
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  • Summary
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the existing location fingerprint matching algorithm based on neighbor selection and the location fingerprint matching algorithm based on machine learning are used for indoor positioning. During the positioning process, a lot of useful RSS information is lost, and the collected RSS samples are not fully utilized. positioning problem, a WLAN indoor positioning method based on matrix correlation is proposed

Method used

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  • WLAN indoor positioning method based on matrix correlation
  • WLAN indoor positioning method based on matrix correlation
  • WLAN indoor positioning method based on matrix correlation

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specific Embodiment approach 1

[0021] Specific implementation mode one: the following combination Figure 4 Describe this embodiment, the WLAN indoor positioning method based on matrix correlation described in this embodiment, the method includes the following steps:

[0022] Step 1. In the offline stage, arrange M access points AP in the indoor target positioning environment i , i=1, 2,...M, create a two-dimensional Cartesian coordinate system in this positioning environment, and select L reference points RP j , j=1, 2,...L, record the coordinates of each reference point and W RSS samples collected at each reference point, and establish the position according to the coordinates of L reference points and the RSS samples of each reference point fingerprint database;

[0023] Step 2. In the online phase, the user receives RSS samples of M access points at each test point. When the user receives N RSS samples at a test point, the N samples are arranged into an M×N measurement matrix Each row represents N ...

specific Embodiment approach 2

[0030] Specific implementation mode 2: This implementation mode further explains the implementation mode 1. In step 3, the calculation matrix rss and the RSS matrix RSS of each reference point l The Pearson correlation coefficient r between l Obtain according to the following formula:

[0031] r l = Σ m = 1 M Σ n = 1 N ( rss ...

specific Embodiment approach 3

[0033] Specific implementation mode three: the following combination Figure 1 to Figure 3 Specific examples are given.

[0034] exist figure 1 The effectiveness of the method is tested in the experimental environment, in which 9 Linksys WAP54G APs are arranged in an indoor environment of 24.9m×66.4m. The experimental path is from point A in the room to point B in the corridor with a width of 3 meters. The experiment uses an ASUS laptop to collect data. It is equipped with Intel PRO / Wireless 3945ABG wireless network card and RSS sample collection software NetStumbler, and the sampling rate is 2 RSS samples per second. In the offline stage, 24 RPs are selected in the room and 67 RPs are selected in the 3-meter-wide corridor, and a total of 300 RSS samples are collected for 150 seconds on each RP. In the online stage, a total of 65 test points were selected along the experimental path with a spacing of 0.6m. Considering the number and arrangement of RP, when K=9 is selected...

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Abstract

The invention discloses a WLAN (wireless local area network) indoor positioning method based on matrix correlation, which belongs to the field of pattern recognition, and aims to solve the problem that in the conventional indoor positioning process adopting both a position fingerprint matching algorithm based on nearest neighbor selection and a position fingerprint matching algorithm based on machine learning, a lot of useful RSS (received signal strength) information is lost. The WLAN indoor positioning method based on the matrix correlation comprises the following steps: 1, under an indoor WLAN environment, selecting a certain number of reference points off line, recording coordinates and RSS samples of the reference points, and establishing a position fingerprint database; 2, measuring positioned points, and recording real-time RSS samples received by a user terminal; and arranging the received original RSS samples into a matrix, and converting RSS data of all reference points in the position fingerprint database into matrixes with the same dimension; 3, computing a Pearson correlation coefficient; and 4, selecting at most K reference points corresponding to the Pearson correlation coefficient, and taking the average of the coordinates of the reference points as a positioning result.

Description

technical field [0001] The invention relates to a WLAN indoor positioning method based on Matrix Correlation (MC), and belongs to the field of pattern recognition. Background technique [0002] With the continuous popularity of global positioning system (Global Positioning System, GPS) terminal equipment, people's demand for location-based services (Location Based Services, LBS) is also increasing. Although satellite navigation systems such as GPS can provide satisfactory location service requirements in outdoor environments, they are not suitable for indoor environments due to the shielding of signals by buildings. The positioning system based on the cellular network is also not suitable for indoor environments due to its large positioning error. Therefore, in order to meet people's demand for location-based services in indoor environments such as airports, shopping centers, underground parking lots, etc., many indoor positioning systems have been developed, such as ultra-...

Claims

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Application Information

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IPC IPC(8): H04W64/00G01S5/02
Inventor 徐玉滨孙永亮马琳刘宁庆邓志安
Owner HARBIN INST OF TECH
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