Aiming at solving the problem that the non-uniformity of spatial frequency affects the accuracy in the process of two-dimensional cross-section imaging, an interpolation optimization algorithm based on truncated sine cardinal(sinc) function is proposed. The algorithm takes the sinc function as the convolution kernel to interpolate the data. Compared with the cell element interpolation method, the obtained scattering interpolation amplitude is closer to the actual value, and the imaging accuracy is higher. On this basis, sinc interpolation requires infinite summation and the amount of data to be calculated is huge, therefore, the interpolation summation should be truncated. The cross-sectional images formed by different truncation points are compared and processed by windowing to further optimize image quality. The simulation results verify the feasibility and accuracy of the optimization algorithm.