Accelerated Left/right Ambiguity Resolving and Angular Super-resolution For Dual-Channel Forward-Looking SAR Imaging

By combining the echoes of two channels in azimuth, and utilizing the super-resolution algorithm for ill-posed problems, the left/right ambiguity in forward-looking synthetic aperture radar (SAR) can be resolved. However, due to the large size of the echo matrix and the need for multiplication and inversion operations, a heavy computational burden is usually encountered. In this paper, based on the time-frequency-space steering matrix, an accelerated left/right ambiguity resolving and angular super-resolution scheme for dual-channel forward-looking SAR imaging is proposed. In the scheme, the Hermitian Toeplitz Block Toeplitz (HTBT) property is exploited to accelerate the construction of the sample covariance matrix. Then, based on the Gohberg Semencul (GS) decomposition theorem and the 2D Levinson Durbin recursive algorithm, the inversion process of the high dimensional covariance matrix is transformed into a large number of low dimensional matrix inversion operations. Finally, based on the Toeplitz multiplication and the trigonometric polynomial expansion theories, the multiplication operations involved between the inverse sample covariance matrix and matrices or vectors are realized by FFT. Simulation and measured data demonstrate that this scheme is more efficient than existing algorithms while maintaining imaging performance.