Surface-Tracing-Based LASAR 3-D Imaging Method via Multiresolution Approximation

• Published in: IEEE transactions on geoscience and remote sensing Vol. 46; no. 11; pp. 3719 - 3730
• Main Authors: Jun, Shi, Xiaoling, Zhang, Yang, Jianyu, Yinbo, Wang
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied geophysics; Back propagation; Computational complexity; Computational efficiency; Discrete element method; Earth sciences; Earth, ocean, space; Elevation; Exact sciences and technology; Fluctuations; Gaussian distribution; High-resolution imaging; Image analysis; Image resolution; Imaging; Imaging techniques; Internal geophysics; Linear-array synthetic-aperture radar (LASAR); multiresolution approximation (MRA); Prediction algorithms; Radar polarimetry; Searching; Studies; surface-tracing-based (STB) 3-D SAR imaging; US Department of Transportation; algorithms; cost; maps; digital elevation models; remote sensing; frequency; interpolation; multiresolution approximation (MRA); fluctuations; three-dimensional models; prediction; Linear-array synthetic-aperture radar (LASAR); errors; Synthetic aperture radar; surface-tracing-based (STB) 3-D SAR imaging
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2008.2001170

This paper concerns the surface-tracing-based (STB) linear-array synthetic-aperture-radar (LASAR) 3-D imaging technique. The basic idea of this technique is to consider the 3-D SAR imaging problem as tracing a surface in the low height-resolution level. The STB 3-D imaging technique first initiates a low-resolution digital elevation map (DEM) using 3-D backprojection (BP) algorithm, predicts a higher resolution DEM from the known elevation using multivariate-interpolation technique, searches from the predicted elevation and obtains a higher resolution DEM, then repeats the prediction and searching recursively and obtains the fine-resolution DEM finally. By converting the 3-D LASAR imaging problem to a 2-D surface-tracing problem, the STB 3-D imaging technique can reduce the computational complexity by one order. The computational cost of STB 3-D imaging technique is analyzed, and we find out that the computational cost of STB 3-D LASAR imaging technique is determined by the surface prediction error and the fluctuation of ground. In particular, for normal distribution, when one of the earlier two factors is small, the computational cost is proportional to the other factor approximately. Finally, a new STB 3-D BP algorithm that implements the surface-prediction operation via multiresolution-approximation (MRA) technique (named as MRA 3-D BP algorithm) is presented. By operating the interpolation in frequency domain, the computational cost of MRA algorithm for sparse LASAR is near to that of RD algorithm for full-element LASAR.