Deterministic Compressed Sensing Sampling Strategy for Diagnosis of Defective Array Elements Using Far-field Measurements

Wei LI; Weibo DENG; Qiang YANG; Marco Donald MIGLIORE

doi:10.11999/JEIT180175

Volume 40 Issue 11

Oct. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(11): 2541-2546

Wei LI, Weibo DENG, Qiang YANG, Marco Donald MIGLIORE. Deterministic Compressed Sensing Sampling Strategy for Diagnosis of Defective Array Elements Using Far-field Measurements[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2541-2546. doi: 10.11999/JEIT180175

Citation:

Wei LI, Weibo DENG, Qiang YANG, Marco Donald MIGLIORE. Deterministic Compressed Sensing Sampling Strategy for Diagnosis of Defective Array Elements Using Far-field Measurements[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2541-2546. doi: 10.11999/JEIT180175

Citation:

Wei LI, Weibo DENG, Qiang YANG, Marco Donald MIGLIORE. Deterministic Compressed Sensing Sampling Strategy for Diagnosis of Defective Array Elements Using Far-field Measurements[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2541-2546. doi: 10.11999/JEIT180175

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Deterministic Compressed Sensing Sampling Strategy for Diagnosis of Defective Array Elements Using Far-field Measurements

doi: 10.11999/JEIT180175

Wei LI^{1, 2},
Weibo DENG^{1, 2
,
,},
Qiang YANG^{1, 2},
Marco Donald MIGLIORE³

1.
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
2.
Key Laboratory of Marine Environmental Monitoring and Information Processing, Ministry of Industry and Information Technology, Harbin 150001, China
3.
School of Telecommunications and Information Engineering, University of Cassino, Cassino 03043, Italy

Funds: The Short-term Visiting Abroad Program for Doctoral Candidates of Harbin Institute of Technology (AUDQ9802200116), The Fundamental Research Funds for the Central Universities (HIT.MKSTISP.2016 13, HIT.MKSTISP.2016 26)

Received Date: 2018-02-09
Rev Recd Date: 2018-08-22

Available Online: 2018-08-28

Publish Date: 2018-11-01

Abstract

Abstract

The structured random sampling strategy adopted in array diagnosis has negative influence on the performance of measurement matrix. Therefore, a compressed sensing based deterministic sampling strategy to diagnose defective array elements using far-field measurements is investigated in this paper. In the case of the number of failed elements satisfies sparsity, the sparse vector is constructed by subtracting incentives of reference array without failures and the array under test. Deterministic Partial Fourier Matrix (DPFM) is then formulated by the proposed strategy as the measurement matrix. Finally, accurate diagnosis with high probability is achieved by l₁ norm minimization. Theoretical analysis and simulation results demonstrate that the proposed method can avoid the adverse impact on the performance of measurement matrix effectively arising from the random distribution of sampling positions, simplify the sampling procedure and improve the probability of success rate of diagnosis.
- Array diagnosis,
- Compressed Sensing (CS),
- Deterministic Partial Fourier Matrix (DPFM),
- Sparse recovery,
- Antenna measurement

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References(16)

References

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