A Method of Fast Extract Signal Subspace Based on the Householder Transformation

The technologies of array signal processing based on subspace decomposition can break the Rayleigh limit, and have great performance and angular resolution. However, in order to obtain signal subspace, traditional methods need to apply singular value decomposition on the signal covariance matrix. Because of the large amount of calculation of singular value decomposition, it is difficult to satisfy the requirements in real-time. Given that the signal covariance matrix is conjugate-symmetric, this paper proposes a new method that can fast compute signal subspace depending on repeatedly applying householder transformation to reduce the covariance matrix order based on the power method, and it has fewer iterations and less amount of calculation.