remove eigh

The original assumption that we can use eigh because the autocorrelation
matrix is Hermitian is not true. Although the true autocorrelation
matrix is Hermitian, this is not necessarily the case for the estimate we
use.

where_fi/processing/aoa.py

@@ -113,12 +113,11 @@ class AoA:
 
     def evaluate(self, theta: torch.Tensor, tof: torch.Tensor) -> torch.Tensor:
         R = torch.mean(self.historical_autocorr, dim=0)
-        assert (R == torch.conj(R).T).all()
 
         # The smallest eigenvectors span the noise subspace,
         # and the largest span the signal subspace.
         logger.debug(f"Calculating eigenvectors of R: {R.shape}")
-        eigvals, eigvecs = torch.linalg.eigh(R)
+        eigvals, eigvecs = torch.linalg.eig(R)
         assert isinstance(eigvals, torch.Tensor)
         assert isinstance(eigvecs, torch.Tensor)
         logger.info(f"Eigenvalues: {eigvals}")