RBF neural network indoor positioning method based on sample clustering

A neural network and indoor positioning technology, applied in the design field of indoor positioning, RBF neural network indoor positioning method, can solve the problem of low accuracy of indoor positioning method, and achieve the effect of fast convergence speed and rich information

Inactive Publication Date: 2014-02-05
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to propose a RBF neural network indoor positioning method based on sample clustering for the problem of low accuracy of the indoor positioning method in the above-mentioned prior art

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  • RBF neural network indoor positioning method based on sample clustering
  • RBF neural network indoor positioning method based on sample clustering
  • RBF neural network indoor positioning method based on sample clustering

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Embodiment Construction

[0027] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0028] Such as figure 1 Shown is the flowchart of the RBF neural network indoor positioning method based on sample clustering according to the embodiment of the present invention, which specifically includes,

[0029] S1. Set the location of the indoor beacon nodes, record the corresponding location coordinates, and install signal receiving equipment at each beacon node;

[0030] S2. Select a reference point, record the position coordinates of the reference point, place a signal transmitter at each reference point, and the signal transmitter sends a fixed number of positioning data packets to the beacon node respectively with different signal transmission powers, and record the beacon node The packet loss rate of different power packets at the position constitutes the sample set Q; as figure 2 Shown is the network topology diagram of the po...

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Abstract

The invention relates to an RBF neural network indoor positioning method based on sample clustering. According to the method, signal packet loss rates under different transmitting power are taken as basic data, a clustering algorithm is adopted for screening out a training sample set with similar feature points, then the sample set is trained through an RBF neural network, and finally the position coordinate of an unknown mobile node is predicted. Due to the relation of communication distances and the packet loss rates, the sample set of the RBF neural network indoor positioning method is rich in information, and relation of signals and the distances can be depicted better; meanwhile, the clustering algorithm is adopted for screening out the position similar feature points and RBF neural network training data, so that data under large-scale and large-range conditions are convenient and easy to collect, the purpose of practicability is achieved really, and meanwhile the algorithm has the advantages of being high in convergence rate, accurate in positioning and the like.

Description

technical field [0001] The invention belongs to the technical field of radio frequency communication, and relates to an indoor positioning method, in particular to the design of a sample clustering-based RBF neural network indoor positioning method. Background technique [0002] Positioning technology is one of the most important information technologies today, ranging from the national defense and military related to national security to the daily life of ordinary people, all need a lot of location information assistance. Traditional positioning technologies are some large-scale positioning systems, which are generally used in outdoor environments, such as the GPS in the United States and the Beidou satellite navigation system in China. However, for many indoor environments with complex structures, these positioning system signals are blocked by obstacles such as walls, and cannot provide indoor positioning. Therefore, indoor positioning technology is a good complement to t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00
Inventor 徐展张国伟刘丹邓翀蒋平川
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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