WSN (wireless sensor network) rapid self-positioning method based on triangle form estimation

Abstract

The invention discloses a WSN (wireless sensor network) rapid self-positioning method based on triangle form estimation. From the aspect of triangle form estimation, a triangle centroid positioning algorithm having the minimal error is studied, and a concept of effective triangle is proposed. The triangle centroid algorithm is used on effective triangles and the error in positioning is minimal. The positioning algorithm is used on all triangles which satisfy basic conditions of effective triangle. All solved possible points are formed into a polygon. The centroid is obtained again, and an estimated position of an unknown node is obtained. Accidental calculation error is prevented by using anchor node information in a network and through a method of obtaining a mean value from multiple possible results. A method of two points positioning is introduced. In the case of only two anchor nodes, the positioning of the unknown node is realized by using an auxiliary anchor node. The positioning coverage rate of nodes is effectively improved without increasing hardware equipment and complexity.

Description

technical field [0001] The invention relates to a fast self-location method of WSN based on triangle shape estimation. Background technique [0002] Acronyms and key term definitions [0003] [0004] 1.1 Background technology: for the convenience of readers to understand the technical background of the present invention [0005] Wireless Sensor Networks (WSN) node positioning technology is one of the important applications of wireless sensor networks. Building a positioning algorithm with low cost, low energy consumption and low computational complexity is also an entry point for the research of key positioning technologies. [0006] The triangle centroid algorithm is a combination of trilateration and centroid algorithm. In a wireless sensor network, a two-dimensional spatial coordinate system is usually used, so as long as the distance between an unknown node and the three surrounding anchor nodes is known, the coordinates of the unknown node can be calculated by tri...

AI Technical Summary

Problems solved by technology

However, this solution does not consider how to deal with overlapping areas that are not triangles, for example, when a circle contains two other circles, such as Figure 4 as shown; or the situation where the three circles cannot form an overlapping area, such as Figure 5 shown; also does not consider the unknown node outside the triangle of the anchor node, such as Image 6 shown

[0037] (2) When the angle condition is not satisfied, there is no backup positioning scheme, which may cause a large number of nodes to be unable to be positioned, making the feed coverage of the nodes low

[0038] (3) This scheme only selects 3 effective anchor nodes for positioning, and does not make full use of the anchor node information in the network, and it is easy to cause accidental calculation errors

[0053] 1.3.2 Shortcomings of the second prior art

[0054] (1) Technical solution 2 only considers the intersection of three circles when using the trilateration method. Although the number of intersections is divided into 2, 1, and 0, the shape of the anchor triangle is not considered. , and the impact of the relative position of the unknown node on the positioning accuracy, these shortcomings are similar to technical solution 1, without considering Figure 4 , Figure 5 and Image 6 special circumstances

[0055] (2) This scheme does not consider how to locate unknown nodes in areas where anchor nodes are sparsely deployed. It may reduce the location coverage of nodes because some unknown nodes cannot be located.

[0056] (3) This scheme only selects 3 effective anchor nodes for positioning, and does not make full use of the anchor node information in the network, and it is easy to cause accidental calculation errors

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