Interferometric SAR Phase Unwrapping Method Based on Improved Markov Energy Model

Phase unwrapping has always been a major issue in the field of interferometric SAR measurement, and it is also a particularly critical stage in InSAR data processing. The interferometric phase corresponds to elevation, and its unwrapping accuracy directly affects the accuracy of elevation measurement. The traditional classical unwrapping algorithms are mostly affected by coherence and noise, and the unwrapping results are poor and even some regions cannot be unwrapped. In this paper, the phase unwrapping algorithm based on the Markov energy model is divided into two steps. First, according to the relationship corresponding to the winding phase, using statistical theory, a Markov field is established to derive the Markov energy function, so that the original complex solution can be deduced. The entanglement problem is transformed into an optimal problem, and the second step is to solve the optimal problem according to the principle of minimum cost, and obtain the fuzzy number. This paper mainly introduces a phase unwrapping method based on the Markov energy model, and solves the problems of absolute phase offset of unwrapping and poor unwrapping effect in some regions that may occur in traditional unwrapping algorithms. The optimization is improved on the basis of the original algorithm, and a satisfactory unwrapping result is obtained, which makes it universal.