Mesh network node positioning method

Abstract

The invention discloses a mesh network node positioning method which comprises (1) predicting a trajectory according to a historical trajectory; (2) controlling a transmitting power of a reference node to enable that a power value of a mobile node is the largest; and (3) performing dormancy processing on an unrelated reference node to achieve node energy control. According to the disadvantages of the existing Zigbee node positioning effect of CC2431 that the energy consumption is high, the precision is low; when arranging wireless sensor network reference nodes on a large scale, the overall energy consumption of the system is increased, the energy intensity of signals is enhanced, and the positioning effect of the system is essentially improved, but the positioning accuracy is not effectively improved; the mesh network node positioning method is aimed at providing a Zigbee positioning algorithm which is high in precision, saves the energy and reduces the consumption.

Description

technical field

[0001] The invention relates to a mesh network node positioning method, which is suitable for personnel positioning in medical treatment, mining, prison and other environments, and can well meet the requirements of material monitoring in farmland, logistics, storage, and other environments. Background technique

[0002] In recent years, the location-aware computing of indoor objects and people, and location-based services (LBS) have become research hotspots. How to determine the location of people or objects in an indoor environment is the core issue of location-based services. Therefore, indoor positioning systems are the key to realizing location-based services. Foundation. Zigbee is a low-cost, low-power, low-speed wireless connection technology. At present, the implementation of Zigbee positioning system mainly uses Chipcon's CC2430 chip and CC2431 chip with a positioning engine to realize wireless communication within a short distance. position. [000...

Examples

Embodiment Construction

[0022] 1) Predict the trajectory of the mobile node.

[0023] The moving window exponential weighted average method is used to predict the position of the mobile node. The moving window exponential weighted average method is calculated in an iterative manner, and the predicted value P at time n n (x n ,y n ) only with the predicted value P at the previous moment n-1 (x n-1 ,y n-1 ) is related to the current position P(x, y), the calculation formula is as follows:

[0024] P n (x)=α×P n-1 (x)+(1-α)P(x);

[0025] P n (y)=α×P n-1 (y)+(1-α)P(y)

[0026] Where: P n (x) represents the predicted value of the x coordinate at time n; α is the weight; P n-1 (x) represents the predicted value of the x-coordinate at time n-1; P(x) represents the x-coordinate at the current moment;

[0027] P n (y) represents the predicted value of the y coordinate at time n; P n-1 (y) indicates the predicted value of the y coordinate at time n-1; P(y) indicates the y coordinate at the curr...

technical field

[0001] The invention relates to a mesh network node positioning method, which is suitable for personnel positioning in medical treatment, mining, prison and other environments, and can well meet the requirements of material monitoring in farmland, logistics, storage, and other environments. Background technique

[0002] In recent years, the location-aware computing of indoor objects and people, and location-based services (LBS) have become research hotspots. How to determine the location of people or objects in an indoor environment is the core issue of location-based services. Therefore, indoor positioning systems are the key to realizing location-based services. Foundation. Zigbee is a low-cost, low-power, low-speed wireless connection technology. At present, the implementation of Zigbee positioning system mainly uses Chipcon's CC2430 chip and CC2431 chip with a positioning engine to realize wireless communication within a short distance. position. [000...

Examples

Embodiment Construction

[0022] 1) Predict the trajectory of the mobile node.

[0023] The moving window exponential weighted average method is used to predict the position of the mobile node. The moving window exponential weighted average method is calculated in an iterative manner, and the predicted value P at time n n (x n ,y n ) only with the predicted value P at the previous moment n-1 (x n-1 ,y n-1 ) is related to the current position P(x, y), the calculation formula is as follows:

[0024] P n (x)=α×P n-1 (x)+(1-α)P(x);

[0025] P n (y)=α×P n-1 (y)+(1-α)P(y)

[0026] Where: P n (x) represents the predicted value of the x coordinate at time n; α is the weight; P n-1 (x) represents the predicted value of the x-coordinate at time n-1; P(x) represents the x-coordinate at the current moment;

[0027] P n (y) represents the predicted value of the y coordinate at time n; P n-1 (y) indicates the predicted value of the y coordinate at time n-1; P(y) indicates the y coordinate at the curr...

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