In B-ISAR imaging

the range resolution and cross-range resolution are dependent on the signal band and the coherent processing interval

respectively. Generally

the B-ISAR image is seriously affected by noise. In this paper

a matrix form of complex approximate message passing algorithm based on two dimensional coupled dictionaries (MCAMP-TCD) is presented

by considering the 2D coupling sparse feature of the echo. Firstly

the range-azimuth 2D joint B-ISAR imaging model is established. Then the 2D joint super-resolution imaging problem is converted into a complex basis pursuit denoising (C-BPDN) problem through vectorization operation. Secondly

two strategies are implemented to solve C-BPDN problem quickly

the first strategy is utilizing the relation between vectorization operation and Kronecker product to derivate the matrix form of complex approximate message passing algorithm

which can avoid the high computational complexity and memory requirements due to vectorization operation. In second strategy

the two dimensional fast Fourier transform (2D FFT) is introduced to equivalent matrix multiplication

which further reduces the computational complexity of the single iteration. At last

the imaging capability under low signal to noise ratio (SNR) is improved by the ability to accurately approximate the noise threshold of the MCAMP-TCD. Simulation results verify the effectiveness of the proposed method.