Abstract:

For the low-angle estimation problem of meter-wave radars, based on the signal spatial sparseness and the complex steering vector in multipath, a new high-resolution angle estimation method is proposed. First, this method utilizes priori information of the multipath model to produce complex steering vector, and then the compressed sensing matrix is constructed, which contains priori information such as multipath attenuation coefficient and angle relationship. Meanwhile, by singular value decomposition (SVD) of the multi-snap data matrix, a data matrix with higher signal-noise-ratio (SNR) can be obtained. Afterwards, the compressed sensing matrix and the new data matrix are used to construct the optimal L1-norm constraint model. Finally, convex optimality tools are used to calculate the sparse spectral function. This method can improve the sparseness of information vector and it has a high-resolution performance at low SNR in multipath. Simulation results demonstrate the advantage of the proposed method over the L1-SVD method.