A Method of Establishing Mine Target Fingerprint Database Based on Distributed Compressed Sensing

Zijian TIAN; Fangyuan HE

doi:10.11999/JEIT180857

Volume 41 Issue 10

Oct. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(10): 2450-2456

Zijian TIAN, Fangyuan HE. A Method of Establishing Mine Target Fingerprint Database Based on Distributed Compressed Sensing[J]. Journal of Electronics & Information Technology, 2019, 41(10): 2450-2456. doi: 10.11999/JEIT180857

Citation:

Zijian TIAN, Fangyuan HE. A Method of Establishing Mine Target Fingerprint Database Based on Distributed Compressed Sensing[J]. Journal of Electronics & Information Technology, 2019, 41(10): 2450-2456. doi: 10.11999/JEIT180857

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A Method of Establishing Mine Target Fingerprint Database Based on Distributed Compressed Sensing

doi: 10.11999/JEIT180857

Zijian TIAN^,,
Fangyuan HE

School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Funds: The Special Program of the National Key Research and Development Plan of China (2016YFC0801804), The National Natural Science Foundation of China(51674269)

Received Date: 2018-09-03
Rev Recd Date: 2019-05-14

Available Online: 2019-05-24

Publish Date: 2019-10-01

Abstract

Abstract

A method of establishing a fingerprint database, which is based on distributed compressed sensing, is proposed to improve the low positioning accuracy and poor real-time positioning that exist in the current mine target positioning in China. Using the method, the fingerprint information of mine target fingerprint database can be reconstructed with high probability by collecting only a few fingerprint information (reference node IDs, Time Of Arrival (TOA) measurements based on electromagnetic wave and actual distance values) in the roadway in the off-line stage. Therefore, the data collection workload can be reduced and the work efficiency can be improved as well. In the subsequent on-line stage, according to the pattern matching method, the estimated distance between the target node and the reference nodes at the certain time can be obtained only by getting the reference node IDs and the real-time TOA measurements measured by the reference nodes at a certain moment, which guarantees the positioning accuracy and positioning real-time performance. Based on this method, an improved Compressive Sampling Modifying Matching Pursuit (CoSaMMP) algorithm is proposed to reconstruct the fingerprint information. The algorithm can effectively shorten the reconstruction time by using the folding method to increase the cutting force. The simulation results show that the proposed algorithm is feasible and effective.

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References(18)

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