Data processing method for wireless sensor real-time monitoring system based on compressive sensing

Abstract

The invention discloses a data processing method for a wireless sensor real-time monitoring system based on compressive sensing. A measurement matrix constructing mode in the compressive sensing is changed, a Gaussian random matrix is replaced by a two-dimensional random matrix, the original measurement matrix is subjected to block operation, and the position with the element value of 1 in a sparse two-dimensional matrix is determined by using a coordinate position matrix, so that the dimension of a reduction matrix is greatly reduced; and meanwhile, the original matrix multiplication is converted into matrix addition operation, the operation speed is increased, and the obvious effects are that due to the algorithm improvement, the compressive sensing algorithm can be realized in actual application, the requirement that a general wireless sensor node has low memory is met, the calculation amount is reduced, the problems that the storage of the sensor overflows and the calculation time is long are solved, and the data monitoring real-time property of the system is improved.

Description

technical field [0001] The invention belongs to information processing and data transmission technology in a wireless sensor network, in particular, a data processing method of a wireless sensor real-time monitoring system based on compressed sensing. Background technique [0002] In recent years, wireless sensor networks have been widely used in the field of real-time monitoring. In these applications, sensor nodes with low energy consumption and low computing power are usually used to collect data. In a large-scale wireless sensor network, the energy of each node (generally powered by batteries) is limited, and the appealing application faces the problem of limited energy consumption and transmission bandwidth. [0003] References: Donoho D.L, Compressed sensing, Technical Report, Stanford University, 2004. A compressed sensing theory (Compressive Sensing, CS) was proposed based on signal processing, wavelet analysis and calculation, statistics and other related theories....

AI Technical Summary

Problems solved by technology

However, in practical applications, we face the following problems: According to the compressive sensing theory, when compressing and processing data at the wireless sensor end, the measurement matrix that needs to be formed is too large, exceeding the memory capacity of the wireless sensor end; the second step is to perform measurement matrix and The multiplication operation of the original signal has a high time complexity of the algorithm

Images