WLAN (Wireless Local Area Network) indoor positioning method based on subregion information entropy gain

An indoor positioning and information entropy technology, applied in the field of WLAN indoor positioning, can solve the problems of removal, poor positioning ability in other areas, and unfavorable partial area positioning.

Active Publication Date: 2012-12-12
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, an AP has different positioning contributions to different positions in the positioning environment. For example, an AP may have a good positioning ability for a certain area, but a poor positioning ability for other areas. If AP selection is performed in a large positioning environment as a whole, such APs are likely to be removed due to the small average positioning contribution, which is not conducive to positioning in some areas

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  • WLAN (Wireless Local Area Network) indoor positioning method based on subregion information entropy gain
  • WLAN (Wireless Local Area Network) indoor positioning method based on subregion information entropy gain
  • WLAN (Wireless Local Area Network) indoor positioning method based on subregion information entropy gain

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specific Embodiment approach 1

[0049] The specific embodiment one, based on the WLAN indoor positioning method of partition information entropy gain, it is realized by the following steps:

[0050] Step 1. Arrange m access points (APs) (APs) for the indoor environment j ,1≤j≤m), ensuring that any point in the environment is covered by signals from two or more APs;

[0051] Step 2. Set reference points evenly in the indoor environment, choose a reference point as the origin to establish a rectangular coordinate system, obtain the coordinate positions of each reference point in the rectangular coordinate system, and use the signal receiver to collect and collect the coordinates of each reference point on each reference point. Record the received signal strength RSS value k times from each AP and perform corresponding data processing;

[0052] Step 3, according to the K-means clustering algorithm, the indoor positioning environment is divided into K sub-areas, and the received signal strength RSS values ​​of ...

specific Embodiment approach 2

[0056] Specific embodiment 2. This specific embodiment is a further limitation of the WLAN indoor positioning method based on partition information entropy gain described in specific embodiment 1. In step 2 of specific embodiment 1, using signal reception at each reference point The computer collects and records the received signal strength RSS value k times from each AP and performs corresponding data processing. The specific steps are as follows:

[0057] Step A1: Obtain a k×m order matrix for each reference point, and the i'th row and j'th column of the matrix represent the RSS value received from the jth AP in the i'th collection;

[0058] Step A2. Add all the elements in the k×m order matrix column vector obtained by each reference point to obtain a value, and then divide this value by k, so that each reference point obtains a 1×m vector, For each reference point, this vector is called the feature vector of the reference point, and the jth element in the vector (that is, ...

specific Embodiment approach 3

[0060] Specific embodiment three. This specific embodiment is a further limitation of the WLAN indoor positioning method based on partition information entropy gain described in specific embodiment two, and the indoor positioning according to the K-means clustering algorithm described in step three in specific embodiment one The specific steps for dividing the environment into K sub-regions are:

[0061] Step B1, each location fingerprint in the Radio Map, that is, the feature vector should be represented by the RSS mean value vector on the corresponding reference point. Input the eigenvectors of all reference points measured in step A2 and the number of subregions K; in order to avoid the negative impact of the randomness of the initial cluster center selection on the clustering algorithm, the data obtained from step A2 are uniformly selected according to the physical space position The RSS values ​​of K reference points (that is, the eigenvectors of each reference point) are...

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Abstract

The invention proposes a WLAN (Wireless Local Area Network) indoor positioning method based on subregion information entropy gain, relating to a WLAN indoor positioning method; and the WLAN indoor positioning method based on the subregion information entropy gain can be used for reducing the amount of computation required for positioning and improving the accuracy of the WLAN indoor positioning simultaneously. According to the method, at an offline stage, firstly RSS (Received Signal Strength) values are measured and received from all APs (Access Points) at all reference points and used as position fingerprint information, then a positioning space is partitioned by using a K-mean clustering algorithm, and t APs with the strongest positioning capabilities are selected in a manner that an information entropy gain model is introduced into each subregion; and at an online stage, firstly the subregion where a test point is located is determined according to the size of distances between the test point and eigenvectors of all clustering centers, and then the accurate positioning of the test point is realized by applying a K-nearest neighbor positioning algorithm in a manner that the selected t APs are respectively utilized in the subregions. The WLAN indoor positioning method based on the subregion information entropy gain is applicable to the WLAN indoor positioning.

Description

technical field [0001] The invention relates to a WLAN indoor positioning method. Background technique [0002] At present, with the development of wireless networks, many technologies and applications related to indoor positioning have emerged. Among them, with the introduction of the IEEE 802.11 standard, WLAN (Wireless Local Area Networks) has been further adopted by various organizations and organizations worldwide. Individuals are widely deployed in different environments. The indoor positioning system based on WLAN technology has been widely valued because of its convenient deployment, low cost, and no need to add special hardware for positioning measurement. [0003] In the WLAN environment, by measuring the received signal strength RSS (Received Signal Strength) value from the access point AP (Access Point) to obtain the corresponding location information, combined with the signal strength database solution to determine the location of the mobile user. Among them, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00
Inventor 马琳马欣茹刘曦周才发徐玉滨强蔚
Owner HARBIN INST OF TECH
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