Abstract:The key problem of eigen-subspace methods is the estimation of signal or noise subspace. In practical situations, there exist signals whose statistic characteristics always change over time. To obtain the real-time estimates of signal parameters, it is necessary to update the signal/noise subspace according to newly received array sampled output. In this paper, 3D Unitary ESPRIT algorithm is proposed to achieve the combined estimation of 2D DOA and carrier frequency of impinging signals, then a subspace tracking algorithm based on spherically averaged ULV decomposition is presented. With combination of the above subspace tracking algorithm with 3D Unitary ESPRIT algorithm, adaptive 3D Unitary ESPRIT algorithm is presented to track the time-varying multidimensional parameter estimates. Computer simulation results are provided to demonstrate the effectiveness of the proposed algorithm.