Distance correction weighted centroid localization method based on reception signal intensity optimization

Abstract

The invention relates to a distance correction weighted centroid localization method based on reception signal intensity optimization and aims to realize precise localization through moving an unknown node in a complex indoor environment. The method comprises steps that RSSI signal processing optimization strategies are comprised, that is, a Gauss mean value mixing filtering model is utilized to optimize an RSSI value, a problem of severe jittering existing in the RSSI value is solved, and a more reliable and reasonable RSSI value is acquired; timely beacon node combination is carried out, that is, the smallest four nodes are selected by utilizing a bubble sorting method from small to large to carry out combination localization; whether two circles in the combination intersect is determined, if not, a distance correction scheme is utilized to carry out optimization, and fault tolerance capability, adaptability and localization precision of the localization algorithm are improved; a four-side weighted centroid localization algorithm is utilized to carry out timely localization, and the position information of the unknown node is acquired. Through the method, localization precision is improved through the optimized localization method, stronger adaptability and higher fault tolerance capability are realized, and the method is suitable for realizing application and popularization in the complex indoor environment.

Description

technical field [0001] The invention relates to a distance correction weighted centroid positioning method. In particular, it relates to a distance-corrected weighted centroid positioning method based on received signal strength optimization that optimizes RSSI measurement values ​​and improves weighted centroid positioning in complex indoor environments. Background technique [0002] With the rapid growth of information, how to deal with big data and how to provide reliable information has become the key. Attaching positioning tags to information has become one of the most commonly used processing methods. With the popularity of mobile and personal devices, location is all the rage. The positioning system can determine the location information of the device, and at the same time use the location information for location-based services, such as navigation, tracking, monitoring, etc. The GPS system can conveniently provide outdoor personal positioning information, but GPS ...

AI Technical Summary

Problems solved by technology

Although it has low implementation complexity, it is limited by the multipath propagation of signals, non-line-of-sight (NLOS) and low accuracy of coordinate calculation, so there are often situations where positioning fails, which brings great harm to the equipment. Positioning error, so that it cannot meet the needs of indoor positioning in real life

[0005] For example, due to the interference of noise such as multipath attenuation and obstacles, the signal strength value often fluctuates greatly, which makes the distance value converted from the RSSI value have a large error, resulting in the distance from the unknown node to the beacon node obtained based on the RSSI ranging method. The distance is far from the actual distance, so that the three circles cannot satisfy the intersection of two pairs, and the weighted centroid positioning algorithm fails

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