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Interferometric Synthetic Aperture Radar (InSAR) is a microwave imaging system with all-weather earth observation. Because of its wide observation area, high precision, day and night operational capabilities, it has a significant advantage in monitoring large-scale surface deformation. Phase unwrapping is a key step in InSAR data processing. The core of Goldstein traditional branch unwrapping method is the establishment of branch-cutting lines. The shorter the overall length of the branch line, the solution is more accurate. Based on the idea of solving the shortest path of Travelling Salesman Problem (TSP), a new algorithm combining ant colony algorithm and genetic algorithm is proposed. Based on the advantages of these two algorithms, we avoid the disadvantages of excessive parameters, slow calculation speed and low efficiency in ant colony algorithm, reduce the time consumed by ant colony algorithm in solving local optimal solution, improve the local search ability of ant colony algorithm, establish shorter branch line than traditional branch method, prevent "islanding effect" and improve the precision of phase unwrapping. The tests performed on real and simulated interferometric SAR data confirm the validity of the proposed method.
Inspec keywords: radar imaging; genetic algorithms; travelling salesman problems; optimisation; synthetic aperture radar; radar interferometry; remote sensing by radar
Subjects: Geophysical techniques and equipment; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Optical, image and video signal processing; Radar equipment, systems and applications; Combinatorial mathematics; Optimisation techniques; Optimisation techniques