Distributed compressed sensing for shockwave field signal acquisition

Mingchi Ju; Tailin Han; Man Zhao; Bo Xu; Xuan Liu

doi:10.1117/12.2639695

19 October 2022 Distributed compressed sensing for shockwave field signal acquisition

Mingchi Ju, Tailin Han, Man Zhao, Bo Xu, Xuan Liu

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122940K (2022) https://doi.org/10.1117/12.2639695
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

In testing gun muzzle blast fields, deploying distributed wireless sensor networks is a flexible and efficient data acquisition method. However, the data transmission characteristics with the high sampling rate of single nodes and the high concurrency of multiple nodes lead to an excessively large overall data volume, which exceeds the existing wireless bandwidth carrying capacity. Therefore, this paper introduces distributed compressed sensing into the shock wave field test to reduce the overall transmission data volume by downsampling the sensor sources to meet the bandwidth requirements. Firstly, the paper analyses the signal-to-signal correlation of multiple shockwave signals within the network to meet the DCS down sampling constraints. Secondly, the performance of typical reconstruction algorithms in single and joint reconstruction is compared. Finally, the feasibility of applying DCS to shockwave field testing is verified, which provides a new idea for the data acquisition method of distributed wireless sensing networks.

Citation Download Citation

Mingchi Ju, Tailin Han, Man Zhao, Bo Xu, and Xuan Liu "Distributed compressed sensing for shockwave field signal acquisition", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122940K (19 October 2022); https://doi.org/10.1117/12.2639695

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KEYWORDS

Reconstruction algorithms

Sensor networks

Compressed sensing

Sensors

Data transmission

Data acquisition

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