An improved covariance matrix encoding scheme wherein a covariance matrix is described in terms of Euler angles and eigenvalues. A covariance matrix, P, is decomposed into its eigenvalues and eigenvectors. The eigenvalues and their corresponding eigenvectors are arranged starting with the smallest value, and the next two ordered such that, the eigenvector set comprises a right-handed coordinate system. Each eigenvalue is then encoded with a logarithmic or other compression scheme. Euler angles are calculated and angle is compressed and an offset is added to each angle. The covariance matrix is then reconstructed from the encoded values to test if the encoded matrix completely covers the original matrix. If necessary, a scale factor is applied to all reconstructed eigenvalues and the scaled versions are then re-encoded as described above. The scaling and re-encoding process ensures that the encoded matrix covers the original matrix.