Multireceiver SAS Imagery With Generalized PCA
Xuebo Zhang, Peixuan Yang, Mingzhang Zhou
Abstract
Before directly using imaging algorithms based on monostatic synthetic aperture sonar (SAS), the phase center approximation (PCA) is used to transform multireceiver SAS data to monostatic SAS equivalent signal. This operation often contains phase compensation and interpolation. However, the space variance of phase error makes the equivalent conversion a challenge. This letter develops a generalized PCA model considering the space variance of approximation error. Traditional PCA models are just the simplification of the presented model. With our preprocessing step, the space-variant phase error is compensated by using a sub-block processing approach instead of interpolation. Then any imaging algorithms designed for conventional SAS are directly used. Based on simulations, the focused images of the traditional PCA method would suffer from image distortion, which is successfully avoided by the presented algorithm.