Locating and finding car method in indoor parking lot based on nearest neighbor

Abstract

The invention provides an indoor parking area vehicle locating and searching method based on a nearest neighbor. The method comprises the following steps: building a locating system of an LANDMARC framework; performing one-time scan round by using all readers; when a certain to-be-located label is detected by three readers, recording a binary string matrix corresponding to each reader and reading the condition of a reference label so as to select the nearest neighbor; calculating the position coordinates of the to-be-located label by using the coordinates of the nearest neighbor. According to the method disclosed by the invention, the hardware cost for building the locating system is greatly lowered; the method is adaptive to dynamic uncertainty caused by changes of wall bodies, object shielding, ineffectiveness of the readers and the like in an indoor environment; when the quantity of the readers is high, the calculation amount can be effectively reduced, and the location accuracy can be improved.

Description

technical field [0001] The invention belongs to the electronic technical field of intelligent traffic systems, and relates to an RFID-based real-time intelligent area positioning method. Background technique [0002] At present, more than 20 of the 33 customer services of the Intelligent Transport System (ITS, Intelligent Transport System) architecture involve real-time positioning of vehicles. Therefore, the study of accurate and efficient vehicle real-time positioning technology has become a hot spot in the field of intelligent transportation recently. In the intelligent parking management system, it is a specific application of this research to solve the problem that the car owner is difficult to find the car when he leaves. [0003] The core of realizing fast car finding in indoor parking lot is efficient and accurate positioning algorithm. At present, common indoor positioning is mainly realized by using technologies such as infrared, wireless local area network, ultr...

AI Technical Summary

Problems solved by technology

However, there are two shortcomings in the LANDMARC positioning algorithm when solving the "nearest neighbor": (1) All reference labels participate in the calculation as the candidate labels of the "nearest neighbor", which brings a significant increase in the amount of calculation; (2) the existing path loss formula Caused by "the farther the tag is from the reader, the faster the signal loss and the greater the error"

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