Wireless sensor network positioning method based on RSSI vector similarity degree and generalized inverse

Abstract

The invention discloses a wireless sensor network positioning method based on the RSSI vector similarity degree and generalized inverse. Gauss curve fitting is carried out on the probability of a specific RSSI value occurring at different distances, piecewise linear interpolation is carried out on an RSSI-d (relation between intensity and distances) curve, and a positioning algorithm that a quadrangle serves as a positioning unit, internal positioning of the positioning unit and external positioning of the positioning unit are carried out, and areas where nodes are likely to exist are rapidly locked is designed; meanwhile, by compassion of the similarity degree between RSSI vectors of unknown nodes and RSSI vectors of reference nodes, the reference anchor node nearest to the unknown nodes is continuously updated and determined, and the area where the unknown nodes are located is narrowed; for the situation that the distance measurement error is random and can not be controlled due to randomness of RSSI measurement errors, the generalized inverse method is introduced as the supplement of the positioning algorithm, the whole positioning algorithm is perfected, and the actual feasibility of the algorithm is improved.

Description

technical field [0001] The invention relates to a wireless sensor network positioning technology, in particular to a wireless sensor network positioning method based on RSSI vector similarity and generalized inverse. Background technique [0002] In various applications of Wireless Sensor Networks (WSN, Wireless Sensor Network), only by combining the information captured and collected by sensor nodes with the node's own position can it accurately explain the "where the event happened" and truly reflect the target. Monitor area. Obviously, the location information of the nodes is the prerequisite for sensor nodes to perceive and collect data. There is only the sensory data of the nodes without the location information of the source of the sensory data, which lacks practical significance. Therefore, node positioning in wireless sensor networks is particularly important, and positioning technology must become an essential function and a key supporting technology of wireless se...

AI Technical Summary

Problems solved by technology

[0005] Liu Shaofei and others proposed an improved DV-Hop algorithm based on average hop distance estimation and position correction to solve the problem that the average network hop distance estimated by a single anchor node cannot reflect the real network average hop distance. good positioning accuracy

However, the range of positioning accuracy of the algorithm is based on the cyclic correction algorithm of the position. If the position correction iteration is wrong, the positioning result will still be affected.

Images