A low complexity OMP sparse channel estimation algorithm in OFDM system

Channel estimation is the key to underwater acoustic OFDM systems. Considering the sparsity of the underwater acoustic channel, compressed sensing is used for channel estimation. However, many existing algorithms are either too complicated or cannot guarantee the accuracy of reconstruction. Therefore, a fast twice orthogonal matching pursuit (TOMP) channel estimation algorithm is proposed. The orthogonality of some measurement atoms is exploited to eliminate the iteration steps in the first OMP, and the number of measurement atoms is reduced according to the relationship between the different over-sampling factors of the measurement matrix in the second OMP. Compared with the conventional OMP algorithm, TOMP can reduce by about 2/3 computational complexity, and maintain accuracy in the sparse underwater acoustic channel estimation. Both the simulation and the sea experiment in the south China sea results show the feasibility of proposed algorithm.