Identifiability Analysis for Array Shape Self-Calibration Based on Hybrid Cramér-Rao Bound

@article{Wan2014IdentifiabilityAF,
  title={Identifiability Analysis for Array Shape Self-Calibration Based on Hybrid Cram{\'e}r-Rao Bound},
  author={Shuang Wan and Jun Tang and Wei Zhu and Ning Zhang},
  journal={IEEE Signal Processing Letters},
  year={2014},
  volume={21},
  pages={473-477}
}
In array shape self-calibration where the sensor position errors and source locations are both unknown, the identifiability of the unknowns is a fundamental problem. Previously, using an approximate hybrid Cramér-Rao bound (HCRB), it was found that under the assumption of small random errors, a nominally linear array is impossible to self-calibrate, but a nominally non-linear array is possible to self-calibrate with three noncollinear far-field sources. In this letter, both small and large… CONTINUE READING

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