Energy-saving transmission self-adaption recursive least squares (RLS) distributed-type detection method of wireless sensor network

Abstract

The invention discloses an energy-saving transmission self-adaption recursive least squares (RLS) distributed-type detection method of a wireless sensor network. Through the updating process of an increment of a distributed-type RLS weight number, the situation that measurement data of all-network nodes are utilized to train the distributed-type RLS weight number of a medium bridge of a bridge node set is achieved, convergence performance of an RLS algorithm is ensured, and the convergence performance is equivalent with that of an existing all-network distributed-type RLS algorithm. Distributed-type RLS weight number estimation is conducted on bridge nodes, adjacent transmission of the weight number is conducted on a sub-network of the bridge nodes, transmission updating of the weight number is achieved, and distributed-type detection is achieved. The energy-saving transmission self-adaption RLS distributed-type detection method of the wireless sensor network has the advantages that all-network parameter calculation and transmission in the prior art are avoided, communication traffic and node operation quantity are reduced, energy consumption is saved, and stability is high. In addition, the RLS weight number is calculated on the bridge nodes, all-network node data information is utilized, and performance of the algorithm is ensured. Under conditions of less energy consumption and lower network communication traffic, all-network detection performance can be achieved, and performance of the wireless sensor network is improved.

Description

Technical field [0001] The invention belongs to the field of communication technology, relates to distributed parameter estimation and distributed detection methods, and mainly relates to an adaptive RLS distributed detection method based on the propagation strategy of a sub-network composed of distributed wireless sensor network bridge nodes, specifically the energy saving of wireless sensor networks Propagating adaptive RLS distributed detection methods, which can use wireless sensor networks to achieve distributed detection. Without reducing the distributed detection performance of the wireless sensor network, it can save network energy consumption, reduce network traffic, and extend the service life of nodes. Background technique [0002] Wireless sensor network (WSN) integrates sensor technology, embedded computing technology, modern network and wireless communication technology, distributed information processing technology, etc. It can monitor, perceive and collect various...

AI Technical Summary

Problems solved by technology

However, when the network is huge and the number of nodes is large, due to the communication burden caused by the network-wide information interaction, the information cannot be transmitted in time, resulting in the algorithm not being able to converge quickly, and the real-time performance cannot be fully reflected.

[0006] To sum up, when the network is huge and the number of nodes is large in the information collection link and weight diffusion link of the original algorithm, there will be disadvantages such as network communication blockage, large amount of node calculation, and high energy consumption of nodes, which will further cause problems in the detection and judgment link. Because the information communication is not smooth, the information cannot be transmitted in time, resulting in the shortcomings of the distributed RLS detection algorithm that cannot converge quickly.

[0007] The above defects limit the performance of wireless sensor networks, resulting in increased energy consumption, shortened life cycle and increased network delay, thus affecting the application performance of distributed RLS detection methods based on propagation strategies in wireless sensor networks

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