Topographic mapping with multiple antenna SAR interferometry: a Bayesian model-based approach

Multiple-antenna SAR interferometry involves the use of three or more antennas to reduce the overall phase ambiguities and phase noise in interferometric data. This paper presents a Bayesian approach to topographic mapping with multiple-antenna SAR interferometry. Topographic reconstruction is formulated as a parameter estimation problem in the model-based Bayesian inference framework. An InSAR simulator based on a forward model is developed for simulating SAR data from multiple-antenna InSAR for evaluating the Bayesian topographic reconstruction algorithms. A Bayesian point position algorithm is developed to estimate the height of a point in the image. A measure of the uncertainty in estimated position and height is also defined in terms of the spread of the dominant mode of the posterior distribution. An example demonstrating the performance of the algorithm for a three-antenna InSAR system is reported, and conclusions are drawn regarding the performance and improvements are proposed.