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Wireless sensor network forest positioning method

A wireless sensor and network positioning technology, applied in the field of forest management, can solve the problems of large positioning errors, errors, and inability to meet the positioning of sensor nodes.

Active Publication Date: 2017-11-24
ZHEJIANG FORESTRY UNIVERSITY
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Problems solved by technology

At present, the main problem in the research of WSN network forest positioning is that the positioning environment is complex, and the signal has multipath effect, which leads to large positioning errors.
In ranging and positioning, the signal strength is severely interfered by obstacles, making the ranging inaccurate, so the traditional path loss model is not suitable for forest positioning
Due to the complexity of the forest environment, the received signal strength (ReceivedSignalStrengthIndication, RSSI) error is large, and the current RSSI path loss model cannot meet the needs of sensor node positioning in the forest

Method used

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  • Wireless sensor network forest positioning method

Examples

Experimental program
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Embodiment

[0120] Using Telosb sensor nodes for experiments, 15 anchor nodes are evenly deployed in a 30m×30m bamboo forest, and 5 unknown nodes are randomly deployed. The Telosb sensor node sends information to the computer for positioning experiments. The experimental scene is a bamboo forest with uneven density. In the experiment, the sensor nodes are placed on a shelf with a height of 1.2m to ensure that the sensor nodes are deployed at the same height level.

[0121] Positioning area division:

[0122] Since the density of trees in different areas in the forest environment is very different, if the positioning experiment is not treated differently, it will have a great impact on the positioning accuracy. In this paper, the discrete situation of RSSI in different areas is used to divide the location area, and the density of trees in the same area is very close. The experiment tests the RSSI dispersion within 25m from the transmitting node. Since the main factor affecting RSSI is t...

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Abstract

The invention discloses a forest wireless sensor network positioning method, comprising (1), dividing a whole positioning region into m positioning subregions according to dispersion coefficients of RSSI (Received Signal Strength Indication) in different areas and fitting established RSSI path loss model R<j><N> of each positioning subregion to form an RSSI path loss model R<N> of the whole positioning region; (2), fusing the RSSI path loss model R<N> of the whole positioning region and a logarithm path loss model R<D> of the whole positioning region, thereby obtaining a forest path loss model R; (3), determining a plurality of wireless sensor positioning nodes through adoption of a subregion trilateration positioning method according to the forest path loss model R; and (4), clustering the plurality of wireless sensor positioning nodes through adoption of a k-means clustering method and determining final wireless sensor positioning nodes. According to the method, influences of a complex forest environment on the strength of wireless sensor signals are taken into full consideration, and the positioning for wireless sensors can be obtained accurately.

Description

technical field [0001] The invention belongs to the field of forest management, in particular to a wireless sensor network (Wireless SensorNetwork, WSN) forest positioning method. Background technique [0002] The localization of wireless sensor networks in the forest has become one of the key issues in wireless sensor network research. At present, the main problem of WSN network forest positioning research is that the positioning environment is complex, and the signal has multipath effect, which leads to large positioning errors. In ranging and positioning, the signal strength is seriously interfered by obstacles, making the ranging inaccurate, so the traditional path loss model is not suitable for forest positioning. Due to the complexity of the forest environment, the Received Signal Strength Indication (RSSI) error is relatively large, and the current RSSI path loss model cannot meet the needs of sensor node positioning in the forest. Contents of the invention [000...

Claims

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Application Information

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IPC IPC(8): H04W4/02H04W64/00G01S5/14
Inventor 余乐易晓梅莫路锋
Owner ZHEJIANG FORESTRY UNIVERSITY
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