A positioning method for location-resistant fingerprints

Abstract

The invention discloses a robust position fingerprint positioning method which comprises the following steps of 1, acquiring an RSSI reference value and an MAC address of a nearby access point at a reference point in a square grid form; 2, acquiring an RSSI measurement value and an MAC address of a nearby access point at the user terminal; 3, calculating the dispersion between the RSSI measurementvector of the user terminal and the RSSI reference vector of the reference point, and selecting k reference points with the minimum dispersion; 4, checking whether the first four reference points inthe k reference points form four vertexes of a square grid or not; 5, if the first four reference points cannot form the four vertexes of the square grid, removing the access point with the minimum RSSI measurement value in the RSSI measurement vector of the user terminal, and repeating the step 3 to the step 5; and 6, estimating the position of the user terminal by adopting a weighted K-nearest neighbor algorithm. According to the invention, the influence caused by fluctuation or abnormality of the RSSI measurement values of one or more access points can be effectively eliminated, and the precision, stability and robust capability of a user position fingerprint positioning result are improved.

Description

technical field [0001] The invention relates to the fields of Internet of Things, indoor positioning, and location-based services. In particular, it relates to a method for locating a difference-resistant position fingerprint. Background technique [0002] Location fingerprinting (Fingerprint) is a commonly used method in various existing indoor positioning technologies. Its basic principle is to abstract and formally describe the characteristics of the positioning environment. , AP) received signal strength indication (Received Signal Strength Indication, RSSI) describes the location information in the positioning environment, and establishes a reference location fingerprint database (Database) by collecting these RSSI measurement values. When the user is actually locating, the RSSI measurement value obtained by the real-time measurement of the user's own equipment is matched with the RSSI reference value in the location fingerprint database, and several reference points w...

AI Technical Summary

Problems solved by technology

However, the main reason for limiting the accuracy and stability of location fingerprinting lies in the complexity and uncertainty of the spatial transmission of radio signals in indoor environments.

On the one hand, the radio signals of sensors such as Wi-Fi and Bluetooth will produce various diffraction, refraction, and scattering effects due to the occlusion of walls, doors, windows, furniture, and human bodies, which will bring unknown errors to the RSSI measurement results of user equipment ; On the other hand, affected by the flow of people and other objects, the RSSI measurement background environment during the offline training phase and the user's online positioning phase will not be exactly the same

Therefore, when the RSSI measurement value of one or more access points in the positioning area is abnormal or has errors, it will bring a large error to the positioning process, and ultimately affect the user positioning performance and user experience

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