A parameter estimation algorithm of 2D harmonic signal based  on SVD of data matrix without pairing

In this paper， we put forward a parameter estimation algorithm of two-dimensional harmonic signal. It’s based on the singular value decomposition (SVD) of data matrix， and the pairing step is performed at the same time. In the algorithm， the parameter estimation problem of two-dimensional harmonic signal is decomposed to the problem of two one-dimensional harmonic signal estimation in multi-sample condition. We can perform SVD of data matrix once to obtain the signal subspace in two directions at the same time， and use the corresponding relationship between these two signal subspaces to diagonalize Fx and Fy in the two directions at the same time. Thus we can complete the pairing step of poles in the two directions， when estimating the parameters of the two one-dimensional harmonic signal. This algorithm does not need to rearrange the data matrix in the form of Hankel block for SVD， and does not need extra pairing step. Those characteristics reduce the computational complexity greatly. And obvious superiority is exhibited when the dimension of data matrix is high enough. The results using simulation and measured data prove the correctness and effectiveness of the algorithm.