Abstract
Synthetic aperture radar (SAR) tomography (TomoSAR) estimates scene reflectivity along elevation coordinates, based on multi-baseline measurements. Common TomoSAR approaches are based on every single range-azimuth cell or the cell’s neighborhood. By using an additional synthetic aperture for elevation, these techniques have higher resolution power for elevation, to discriminate scatterers with differences in location in the same range-azimuth cell. However, they cannot provide sufficient range resolution power to discriminate these scatterers by joining different spectra to a wider range spectrum, which limits the resolution power of TomoSAR. Therefore, in this paper, we proposed using a compressive sensing (CS) technique to reconstruct range and elevation signals from multi-baseline SAR images. This TomoSAR method not only retrieves the vertical signals but also improves the resolution in the range, which helps improve the resolution power of the TomoSAR technique. We present the theory of the CS-based two-dimensional TomoSAR technique and compare it to the CS-based one-dimensional TomoSAR technique. The excellent resolution power and scatterer localization accuracy of this novel technique are demonstrated using simulations and real data obtained by RADARSAT-2 in Lanzhou, China.
Highlights
The study of urban environments and dynamics is a key research field in the geoscience community
We can see that the closest range distance of two scatterers such that they can be discriminated with a detection rate more than 90% is nearly 1.8 m
In addition facilitating of the compressive sensing (CS) 2D TomoSAR method, Tomographic we used the CS 1. One-dimensional (1D) TomoSAR method to compare with the new method
Summary
The study of urban environments and dynamics is a key research field in the geoscience community. By the elevation coordinates but atand different ranges, such as the adjacent scatterers on the wall limited of building elevation resolution, these approached cannot discriminate scatterers that are located at very close (Figure 3) To distinguish such scatterers, a better method is to enhance the range resolution if a larger elevation coordinatesisbut at different ranges, such as thethe adjacent on the wall ofband building signal bandwidth available. A problem that occurs is that the range resolution improvement influences the phase information, which results in incorrect inversion results for elevation Another way to enhance range resolution is the use of 2D spectrum analysis techniques [20,21,22,23,24], but in practice, a uniform distribution baseline is required, or else these techniques cannot be used.
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