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.
| Original language | English |
|---|---|
| Pages (from-to) | 2110-2116 |
| Number of pages | 7 |
| Journal | Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology |
| Volume | 37 |
| Issue number | 9 |
| DOIs | |
| State | Published - 1 Sep 2015 |
| Externally published | Yes |
Keywords
- Active calibration
- Array calibration
- Gain and phase errors
- Multi-Stage Wiener Filter (MSWF)
- Signal processing
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