Smart phone WiFi indoor positioning method
A smart phone, indoor positioning technology, used in location-based services, specific environment-based services, short-distance communication services, etc., can solve the problem of low indoor positioning accuracy, achieve the best generalization performance, fast learning speed , the effect of good tolerance
Active Publication Date: 2019-07-30
SHANDONG UNIV OF SCI & TECH
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Problems solved by technology
[0007] Aiming at the problem that the existing indoor positioning accuracy is not high, the present invention provides a smart phone WiFi indoor positioning method based on standardized waveform trend and kernel extreme learning machine
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Embodiment 1
[0059] combine Figure 1 to Figure 4 , a smartphone WiFi indoor positioning method based on standardized waveform trend and kernel extreme learning machine, comprising the following steps:
[0060] Step 1: Experimental environment deployment: Select the environment in the laboratory, and divide the indoor plane using two-dimensional coordinates. For convenience, the unit spacing of the XY axis used in this method is that the side length of the indoor square floor tile is 1.2m.
[0061] Deploy WiFi routers in the laboratory. In this embodiment, eight routers of the same model are deployed in even corners of the room, and are numbered in a unified naming manner;
[0062] Select reference training points and test points. In this embodiment, a total of 100 training points and 20 test points are set.
[0063] Step 2: Offline collection: Use a smartphone installed with a positioning app to record the coordinates of the reference training point, and collect the signal strength and n...
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The invention discloses a smart phone WiFi indoor positioning method based on a standardized waveform trend and a nuclear extreme learning machine. In the prior art, most of the received signal intensities are adopted as fingerprint characteristics, but the received signal intensities are easily influenced by a dynamic indoor environment, so that various noises exist, and the positioning precisionis seriously reduced. Further, the high computational costs have become the bottleneck of large-scale applications. Standardized waveform trend of received signal strength is used as fingerprint characteristics of indoor positioning, and the method has good tolerance to equipment heterogeneity and indoor dynamic environment. The standard waveform trend and the nuclear extreme learning machine areintegrated, an efficient and steady indoor positioning method is designed, the learning speed is very high, and the optimal generalization performance is provided. According to the method, the high-precision positioning of the smart phone can be realized in an indoor environment, and the robustness to the dynamic change of the environment is good.
Description
technical field [0001] The invention relates to the field of indoor positioning, in particular to a WiFi indoor positioning method for smartphones based on standardized waveform trends and kernel extreme learning machines. Background technique [0002] Over the past two decades, with the growing popularity of smart devices (e.g. smartphones, tablets, etc.), the demand for location-based services is increasing, such as driving to destinations, tracking and recording our movements. These services are implemented outdoors through the Global Positioning System (GPS) and its derivative applications. However, GPS technology cannot be used inside buildings due to weak satellite signal reception in indoor environments. [0003] In cities there are more and more shopping malls with various shops on each floor, as well as large parking lots. GPS cannot achieve positioning services indoors with satisfactory accuracy. Therefore, many indoor positioning technologies have emerged, such...
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Login to View More IPC IPC(8): H04W4/029H04W4/33H04W4/80H04W64/00
CPCH04W4/029H04W4/33H04W4/80H04W64/006
Inventor 李玉霞崔玮李俊良王海霞卢晓张治国盛春阳
Owner SHANDONG UNIV OF SCI & TECH