Low complexity time delay estimation using propagator based on matrix partitioning

In this paper, low complexity time delay estimation (TDE) method based on data matrix partitioning is proposed. The dimension of signal subspace was increased by stacking data matrices for performance improvement of TDE. Increment of the size of data matrix causes high computational complexity of TDE. The proposed algorithm, which only requires propagator with smaller data matrix than original data matrix, can avoid high computational cost. Each of the partitioned matrices is used for the derivation of the averaged propagator matrix. The estimation error of the proposed method is approximately identical to that of the conventional propagator with less computational complexity by using the averaged propagator matrix.