A Novel Distance Estimation Method for Near-Field Synthetic Aperture Interferometric Radiometer

Abstract

The visibility samples generated by the synthetic aperture interferometric radiometer (SAIR) under near-field observation conditions contain information about the distance from the target to the instrument. This requires a precise understanding of the target–instrument distance to guarantee imaging quality in near-field SAIR applications. In this paper, we introduce a novel distance estimate approach for near-field SAIR systems, which achieves satisfactory imaging performance in the absence of prior information on target–instrument distance. First, we reformulate the signal model of near-field SAIR from the fractional Fourier transform (FRFT) perspective. This formulation ties the distance that is variable to the visibility function in a straightforward manner, offering an efficient solution for image reconstruction in near-field SAIR. Subsequently, we present an iterative strategy for target–instrument distance estimation based on simulated annealing (SA). In each iteration, the modified average gradient (MAG) of images reconstructed within the FRFT framework is evaluated, and based on the Metropolis criterion, the estimated target–instrument distance is optimally updated iteratively. Finally, the validity and effectiveness of the proposed distance estimation method for near-field SAIR imaging systems are demonstrated through numerical simulation and real experiments.