A Novel Multi-Channel Phase Error Estimation Method Based On Stochastic Optimization For Tomographic Sar Autofocusing

Tomographic SAR (TomoSAR) technology has gained significant attention in recent years due to its three-dimensional imaging capability. However, in practical applications, phase errors between different channels can degrade the quality of three-dimensional imaging. Current state-of-the-art methods for phase error compensation based on autofocus techniques suffer from high computational complexity, making them unsuitable for large-scale three-dimensional imaging. In this paper, we propose a multi-channel phase error estimation method based on error back-propagation training optimization. By utilizing the TomoSAR model that incorporates phase errors from multiple channels, we construct a matrix containing the parameters to be estimated for inter-channel phase errors. Through stochastic gradient descent algorithm, we iteratively optimize the parameters of the phase error matrix, ultimately obtaining an estimation of the inter-channel phase errors. Experimental results validate the accuracy of the proposed method.