Fast Active Error Calibration Algorithm for Array Chanel Uncertainty

Zhang Ke; Cheng Ju-ming; Fu Jin

doi:10.11999/JEIT141651

Volume 37 Issue 9

Sep. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(9): 2110-2116

Zhang Ke, Cheng Ju-ming, Fu Jin. Fast Active Error Calibration Algorithm for Array Chanel Uncertainty[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2110-2116. doi: 10.11999/JEIT141651

Citation:

Zhang Ke, Cheng Ju-ming, Fu Jin. Fast Active Error Calibration Algorithm for Array Chanel Uncertainty[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2110-2116. doi: 10.11999/JEIT141651

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Fast Active Error Calibration Algorithm for Array Chanel Uncertainty

doi: 10.11999/JEIT141651

1.
(School of Information?Engineering, Xuchang University, Xuchang 461000,China)
2.
(College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001,China)

Received Date: 2014-12-29
Rev Recd Date: 2015-03-31
Publish Date: 2015-09-19

Abstract

Abstract

Aiming the error calibration for the array channel uncertainty, a new fast algorithm named Simplified Multi-Stage Wiener Filter (SMSWF) based on the Multi-Stage Wiener Filter (MSWF) is proposed. The SMSWF takes the advantages of the DOA and the waveform of the cooperative source to estimate the gain and the phase factors, and it does not need to estimate the covariance matrix and the eigendecomposition operations. Compared with the eigendecomposition algorithm, the SMSWF has the same performance for estimating gain and phase factors while greatly reduce the complexity. The researches show that if a single source with a known waveform incidence on the array, the signal subspaces obtained by the SMSWF and one obtained by the eigendecomposition are equipollent, which demonstrate that the SMSWF is able to replace the eigendecomposition. The complexity of signal processing methods based on the eigendecomposition can greatly be reduced by replacing the eigendecomposition with the SMSWF. The extensive computer simulations and experiment in anechoice water tank show the superiori performance of the proposed algorithm.
- Signal processing,
- Array calibration,
- Active calibration,
- Gain and phase errors,
- Multi-Stage Wiener Filter (MSWF)

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References(27)

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