Indoor positioning method for reducing fingerprint data acquisition workload

An indoor positioning and fingerprint data technology, applied in wireless communication services, electrical components, wireless communication and other directions, can solve the problems of large reference point collection interval, limitations of indoor positioning popularization and application, inability to guarantee the precision of RSS signals, etc., to reduce collection The effect of reducing the number of collection points and reducing the positioning error

Inactive Publication Date: 2014-09-10
CENT SOUTH UNIV
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Problems solved by technology

In the online positioning stage, the user is roughly positioned to the positioning sub-area through clustering and segmentation, and then the precise positioning is carried out. A total of 110 reference sample points are collected, and the distance between the sample points is about 1.52 meters. The positioning accuracy is 0.8 meters, but there are also articles pointing out that such a high positioning accuracy cannot be achieved when copying this method in other work
[0007] The above methods all nee

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  • Indoor positioning method for reducing fingerprint data acquisition workload
  • Indoor positioning method for reducing fingerprint data acquisition workload
  • Indoor positioning method for reducing fingerprint data acquisition workload

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[0025] The theoretical basis of the present invention is as follows:

[0026] Through the analysis of the physical distance between two points and the RSSI Euclidean distance under the logarithmic distance path loss model, we performed simulation experiments on 100 random points in the area with a path loss index of 3, 20*20, and obtained The physical distance between the two nodes and their RSSI difference (Euclidean distance) have a relatively high consistency and correlation. That is to say, the greater the RSSI difference between the two points, the farther their physical distance is. . For AP rules and irregularities, the simulation results are shown in Figure 1. The consistency increases as the number of APs increases, and becomes smaller as the standard deviation of the shadow effect increases.

[0027] Definition 1: Consistency refers to the relationship between the physical distance between a pair of nodes and their RSSI difference. Specifically, if the physical distance ...

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Abstract

The invention discloses an indoor positioning method for reducing fingerprint data acquisition workload. For a large number of point pairs with larger AP (Access Point) RSSI (Received Signal Strength Indicator) difference values, the physical distances are larger. The method comprises the following steps: calculating the RSSI 'distance value' between points by taking the RSSI values of multiple APs obtained at a certain position as high-dimension characteristic data of the position according to the characteristic for serving as the intimate relationship between two points; acquiring the relative position relationship of one low-dimension space between each object by using a multi-dimensional scaling analysis algorithm; evaluating the absolute positions of other points by taking a small number of sample points as anchor nodes. By adopting the method, the aim of reducing the acquisition number of sample points is fulfilled. A hierarchical region reducing method is put forward on the basis in order to further fulfill the aim of reducing the positioning error. Compared with a KNN (K Nearest Neighbor) algorithm, the method has the advantages that the sampling points can be reduced, and meanwhile the positioning error is reduced.

Description

technical field [0001] The invention relates to an indoor positioning method for reducing the workload of fingerprint data collection. Background technique [0002] Currently, common indoor positioning technologies include acoustic signals, FM signals, RFID, Bluetooth signals, cellular networks, ZigBee, UWB and WiFi. Generally speaking, the mode of wireless indoor positioning is to first obtain the physical measurement value of the wireless signal, and then either adopt the method of propagation model or the method based on fingerprint. [0003] Divided according to the physical measurement value utilized, it can be divided into time, angle and power. The time-based physical measurement values ​​include Time of Arrival (TOA) and Time Difference of Arrival (TDOA), and the power-based positioning methods include RSSI and CSI. In complex multi-path indoor environments, both TOA and AOA measurements require special hardware measurement equipment, and there is a large deviation...

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Application Information

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IPC IPC(8): H04W4/04H04W64/00
Inventor 张士庚王建新肖亚龙王伟平
Owner CENT SOUTH UNIV
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