Application Of Semi-tensor Compressed Sensing In Wireless Sensor Networks

During the distributed wireless transient pressure test,the signal has a short time span and a wide frequency spectrum.In order to collect this signal with high-precision,the continuous high sampling rate,which the collection system maintain,produces massive data,consumes much time and energy.Therefore it will shorten the life cycle of sensor nodes.At the same time,the shockwave data,transmitted by open wireless links,is exposed insecure environment and vulnerable to malicious attacks,such as monitoring and tampering.Based on the distributed wireless transient signal testing system,this paper studies the conflict between continuous high sampling rate and limited node resources,especially transmission bandwidth.The main research contents are summarized as follows:(1)Aiming at the problem of massive data caused by continuous high sampling rate,which brings data processing and storage pressure to sensor nodes,a semi-tensor compressed sensing shockwave signal acquisition method based on Hilbert space is proposed in this paper.Firstly,the semi-tensor theory is used to break through the dimension limitation of matrix multiplication and reduce the dimension of the observation matrix at the coding end.Secondly,by using the orthogonal space of Hilbert and Fourier transform to approximate the energy of shockwave signal,a sparser expression is obtained.Finally,an optimal atom selection strategy without prior information is adopted,and energy regularization and variable step updating are used to simplify the estimation of the support set to ensure high-precision reconstruction at the decoding end.The method proposed in this paper can lower the sampling rate,reduce the total amount of data,and ensure the real-time communication.Compared with the traditional compressed sensing,the dimension of observation matrix is reduced by 2 times,and the reconstruction time of the improved reconstruction algorithm is shortened by about 87%,and the reconstruction error is less than 10-6.(2)Aiming at the problem that sensor node data is transmitted through open wireless link,which makes the data easy to be intercepted,tampered with and intercepted,and the data security is difficult to be guaranteed,this paper proposes a data compression encryption method combining two-dimensional coupling cascade chaos and semi-tensor compressed sensing.Firstly,a sinusoidal chaotic coupling cascade map is constructed,which improves the dynamic degradation and randomness of one-dimensional chaotic system.Then,the initial chaotic values and chaotic parameters are used as keys to replace the observation matrix.Secondly,data sampling,compression and encryption are carried out synchronously.Finally,the data transmission efficiency is improved while the storage space of the key is reduced.In this paper,the simulation experiment of measured shockwave signal proves that the scheme can not only ensure the efficient and safe transmission of data under the attack of additional noise,but also further reduce the complexity of key transmission and improve the utilization rate of storage space of sensor nodes.In this paper,shockwave collection technology based on semi-tensor compressed sensing is studied.And shockwave signal sampling,compression and data encryption are realized,which not only reduces system transmission and storage pressure by compressing massive data,but also ensures data security.