  We propose a new estimation method for the blind source separation model of
Bachoc et al. (2020). The new estimation is based on an eigenanalysis of a
positive definite matrix defined in terms of multiple normalized spatial local
covariance matrices, and, therefore, can handle moderately high-dimensional
random fields. The consistency of the estimated mixing matrix is established
with explicit error rates even when the eigen-gap decays to zero slowly. The
proposed method is illustrated via both simulation and a real data example.
