Positioning method of weighted wireless sensor network nodes based on RSSI and LQI

Abstract

The invention relates to a positioning method of weighted wireless sensor network nodes based on an RSSI and an LQI, which is characterized in that (1) the parameters of the RSSI and the LQI, which can be acquired easily from a hardware register, are used for positioning, thus the method can be realized easily and has few required hardware resources; (2) an LQI ranging model obtained by fitting experimental data is combined with an RSSI ranging model to select anchor nodes; and (3) an RSSI value and an LQI value which pass through an average filter are weighted and combined, an improved weighted centroid algorithm is used for estimating the positions of nodes to be detected, the data is broadcasted to cluster nodes, and then, the data is uploaded to a monitoring centre through a wired network. The positioning method of invention has the advantages of high positioning accuracy without being influenced by the environment easily, easy implementation of hardware, lower cost and smaller computation complexity.

Description

Technical field: [0001] The present invention relates to a wireless sensor network, in particular to a wireless sensor network node positioning method based on received signal strength indicator RSSI (Received Signal Strength Indicator) and link quality indicator LQI (link quality indicator) weighting with low computational complexity and easy implementation . Background technique: [0002] The positioning technology in Wireless Sensor Networks (WSN) is very important. If the data measured by the sensor has no corresponding position information, then this data has almost no practical value. [0003] Depending on whether the positioning process relies on measuring distance, the positioning technology can be divided into range-based and range-free. The ranging-based positioning technology provides high-precision node position information by measuring the point-to-point distance or angle information between nodes, and using trilateration, triangulation or maximum likelihood es...

AI Technical Summary

Problems solved by technology

[0008] 3. The RSSI value is affected by the power of the transmitter. For a battery-powered system such as a wireless sensor network, the voltage drop of the battery after a period of use will also affect the RSSI value;

[0009] 4. The accuracy of RSSI is far from enough for more accurate ranging, and the error is large

[0010] In addition, since the RSSI value has no obvious change trend after the distance exceeds a certain threshold, it cannot be detected by a specific RF chip, so its positioning distance is very limited

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