International Journal of Remote Sensing
Noise-Residue Filtering Based on Unsupervised Clustering for Phase Unwrapping
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
IEEE Transactions on Signal Processing
Modeling and processing L-band ground based radar data for landslides early warning
Journal of Electrical and Computer Engineering - Special issue on Advances in Radar Technologies
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This work addresses the derivation of the phase difference-based maximum likelihood (ML) phase unwrapping algorithm. To this end, we derive the joint statistics of the phase differences on a two-dimensional grid for the multichannel case, where several scaled wrapped phase values are available. Subsequently, we determine and study the structure of the phase difference-based ML estimator and compare it to known phase unwrapping techniques. This work allows us to frame single and multichannel algorithms in a common formulation. Moreover, among the known single-channel phase difference-based procedures, we identify those attaining an ML solution. We also show that multichannel phase difference-based and, recently proposed, phase-based ML algorithms achieve equivalent solutions.