Multipath Interferences in Ground-Based Radar Data: A Case Study
AbstractMultipath interference can occur in ground-based radar data acquired with systems with a large antenna beam width in elevation in an upward looking geometry, where the observation area and the radar are separated by a reflective surface. Radiation reflected at this surface forms a coherent overlay with the direct image of the observation area and appears as a fringe-like pattern in the data. This deteriorates the phase and intensity data and therefore can pose a considerable disadvantage to many ground-based radar measurement campaigns. This poses a problem for physical parameter retrieval from backscatter intensity and polarimetric data, absolute and relative calibration on corner reflectors, the generation of digital elevation models from interferograms and in the case of a variable reflective surface, differential interferometry. The main parameters controlling the interference pattern are the vertical distance between the radar antennas and the reflective surface, and the reflectivity of this surface. We used datasets acquired in two different locations under changing conditions as well as a model to constrain and fully understand the phenomenon. To avoid data deterioration in test sites prone to multipath interference, we tested a shielding of the antennas preventing the radar waves from illuminating the reflective surface. In our experiment, this strongly reduced but did not completely prevent the interference. We therefore recommend avoiding measurement geometries prone to multipath interferences. View Full-Text
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Lucas, C.; Leinss, S.; Bühler, Y.; Marino, A.; Hajnsek, I. Multipath Interferences in Ground-Based Radar Data: A Case Study. Remote Sens. 2017, 9, 1260.
Lucas C, Leinss S, Bühler Y, Marino A, Hajnsek I. Multipath Interferences in Ground-Based Radar Data: A Case Study. Remote Sensing. 2017; 9(12):1260.Chicago/Turabian Style
Lucas, Célia; Leinss, Silvan; Bühler, Yves; Marino, Armando; Hajnsek, Irena. 2017. "Multipath Interferences in Ground-Based Radar Data: A Case Study." Remote Sens. 9, no. 12: 1260.
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