Area partitioning and positioning method and system based on space partitioning

A technology of area division and positioning method, which is applied in the direction of service, instrument, character and pattern recognition based on location information.

Inactive Publication Date: 2018-07-20
武汉创驰蓝天信息科技有限公司
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Problems solved by technology

But strictly speaking, these clustering methods only play the role of database filtering by dividing the location fingerprints. During the user positioning process, the corresponding sub-location fingerprint databases can be selected for calculation, which saves the time required for the algorithm to traverse the database. It optimizes the system performance, but it cannot really realize the indoor area positioning function
This is precisely because when the location fingerprint map is divided by signal strength features, it does not take into account whether the actual reference point locations are also gathered together in physical space, so it is inevitable that there will be some reference points due to similar RSS similarity metrics (such a

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  • Area partitioning and positioning method and system based on space partitioning
  • Area partitioning and positioning method and system based on space partitioning
  • Area partitioning and positioning method and system based on space partitioning

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Embodiment Construction

[0062] Such as figure 1 Shown, a kind of area division and location method based on space division, it comprises the following steps:

[0063] S1. After the user specifies the number of sub-regions, determine the optimal initial cluster center position through distance calculation, integrate K-means method, Fisher criterion and self-organizing iterative analysis algorithm, and introduce intra-class distance, inter-class distance, and reference point distance Constraining conditions, through multiple clustering, merging and splitting processes, the goal of regional division is finally completed;

[0064] S2. Implementing sub-region positioning by applying machine learning technology in a semi-supervised manner.

[0065] The step S2 includes realizing the sub-region localization combined with the support vector machine method or the sub-region localized realization combined with the random forest method.

[0066] Before step S1, also include:

[0067] In the initialization ph...

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Abstract

The invention provides an area partitioning and positioning method based on space partitioning. The method comprises the following steps that 1, after a user designates the subarea number, various optimal initial cluster center positions are determined through distance calculation, the within-class distance, the between-class distance and the reference point spacing limiting condition are introduced by integrating a K-means algorithm, a Fisher criterion and a self-organizing iterative analysis algorithm, and by means of multiple times of the cluster merging and splitting process, the area partitioning target is completed finally; and 2, subarea positioning is achieved by applying a machine learning technology in a semi-supervised mode. The invention further provides an area partitioning and positioning system based on space partitioning.

Description

technical field [0001] The present invention relates to the technical field of indoor positioning, in particular to a region division and positioning method and system based on space partitioning. Background technique [0002] The general clustering algorithm can reasonably divide the location fingerprint database according to the received signal strength characteristics. But strictly speaking, these clustering methods only play the role of database filtering by dividing the location fingerprints. During the user positioning process, the corresponding sub-location fingerprint databases can be selected for calculation, which saves the time required for the algorithm to traverse the database. It optimizes the system performance, but it cannot really realize the indoor area positioning function. This is precisely because when the location fingerprint map is divided by signal strength features, it does not take into account whether the actual reference point locations are also ...

Claims

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Application Information

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IPC IPC(8): H04W4/021H04W4/029G06K9/62
CPCH04W4/021H04W4/023G06F18/23213
Inventor 刘芬
Owner 武汉创驰蓝天信息科技有限公司
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