Joint for time of arrival and direction of arrival estimation algorithm based on the subspace of extended hadamard product

In the joint estimation for time of arrival (TOA) and direction of arrival (DOA) in the narrow-band orthogonal frequency division multiplexing (OFDM) system with antenna arrays, the estimation accuracy is not high in the situation of few numbers of arrays. Especially, DOA cannot be estimated if the number of multiple paths is more than that of the arrays. For these problems, a joint estimation algorithm for TOA and DOA based on the subspace of the extended hadamard product is proposed. First of all, the algorithm constructs an extended channel response in frequency domain via channel estimation for each array in the frequency domain. Then, auto-correlation matrix of extended channel response in the frequency domain is estimated by sampling many times. This estimation method of channel response in the frequency domain can use the fast Fourier transform algorithm. And the hadamard product in the extended noise subspace is obtained by eigenvalue decomposition. Finally, the pseudo-spectral function is constructed and used to search for spectrum peaks, so as to realize the joint estimation of TOA and DOA. The proposed algorithm requires no parameter paring but needs a two-dimensional searching. Monte Carlo algorithm can be used to reduce computational complexity. Simulation results show that the root mean square error of the joint TOA and DOA estimation which can be matched automatically is closer to the Cramer-Rao bound than that using present algorithms. And the proposed algorithm can be still applied when the number of multiple paths is more than number of arrays.