Reference Network Construction for Persistent Scatterer Detection in SAR Tomography: Ant Colony Search Algorithm (ACSA)

Synthetic aperture radar (SAR) tomography is a powerful multibaseline technique allowing to reconstruct volume structures by using datasets of the same area with slightly different viewing angles. Nowadays, the reference network technique (RNT) is widely applied in SAR tomography to detect single and double scatterers with no need for preliminary removal of atmospheric phase screen (APS). Therein, reference network (RN) construction as the basis of RNT is vitally important for effective APS calibration to successfully detect persistent scatterers (PSs) over the entire scene. Aiming at whole-scene PS detection, RN should be constructed with global distribution throughout the whole built environment. For the moment, standard RNT cannot achieve this goal because of the damage to network connectivity in the RN construction process. In this article, an ant colony search algorithm (ACSA) is designed for whole-scene RN construction via step-by-step exploring and retaining reliable single scatterers around each ant. The effectiveness of the proposed ACSA for RN construction is demonstrated through the three-dimensional SAR tomography experiments on high-resolution TerraSAR-X SAR data stack in Shenzhen, China.