Raw Signal Simulation of Synthetic Aperture Radar Altimeter Over Complex Terrain Surfaces

Abstract

In comparison with the conventional radar altimeter, synthetic aperture radar altimeter (SRAL) is developed with better along‐track spatial resolution and height precision. When SRAL improves the performance of height measurement, it also complicates the radar system designing, signal processing, data analyzing, and system testing. The SRAL raw signal is the result of the interaction between the transmitted signal and the complex terrain surfaces. Generally, the SRAL is used in ocean applications since the PDF can be derived from different ocean surfaces. However, the actual acquired SRAL waveforms can be from complex and variable surface, which may include mountains, cities, forests, lakes, and other types of terrain surfaces. These waveforms contain information about the surfaces of the Earth although difficult to analyze. This paper focuses on the study of the raw signal simulation of SRAL for complex terrain surfaces including land surfaces. The principle of radar altimeter, the electromagnetic characteristics of land targets, and the SRAL signal processing are analyzed. The geometric models are extracted from digital elevation model, and the scattering characteristics of the terrain surface are established with three scattering models. Finally, three cases of terrain surfaces, namely, ice surface, mountain area, and urban area, are simulated and validated against actual SRAL signals measured by the Sentinel‐3 SRAL sensor.

Above Ground Level Estimation of Airborne Synthetic Aperture Radar Altimeter by a Fully Supervised Altimetry Enhancement Network

“…Therefore, although SARAL observes the ground target located at the nadir point, the power is still largely based on scattering. The Ulaby model [37] is an empirical model that can describe the backscattering coefficient of common landform-covering media and is widely used in radar altimeter research [38,39]. Consequently, the backscatter property of each scatter is described as (8) using the Ulaby.…”

A Novel SAR Fractal Roughness Modeling of Complex Random Polar Media and Textural Synthesis Based on a Numerical Scattering Distribution Function Processing

“…In general, this work extends numerous studies [2, 10, 13, 23, 36, 41-43, 45, 49, 52-53, 56-59, 61, 63, 70-71, 73-79] that were only concerned with 1D or 2D formulations and never addressed seaice roughness modeling and the relevant textural evaluation. This evaluation includes the spectral property extraction of texture based on PSD modeling [53,57] and an electromagnetic interaction investigation in terms of received backscattered data generation [59,70,72,76,80], as well as surface tension synthesis based on a tensor structure descriptor (TSD) field map [73]. The reference CRPM function is a modified two-scale JONSWAP directional spectrum function [79], which has been extended as a function of sea state for roughness modeling [61].…”

Sea Surface Imaging Simulation for 3D Interferometric Imaging Radar Altimeter

“…Jung et al [18] simulated the raw data and interferograms of the SuperSAR multi-azimuth synthetic aperture radar imaging system, which is used to investigate the feasibility of detecting precise 3D surfaces. Zhu et al [19] focuses on the study of the raw signal simulation of synthetic aperture radar altimeter (SRAL) for complex terrain surfaces including ice and land surfaces. They analyzed the principle of SRAL, the electromagnetic characteristics of land targets, and the signal processing of SRAL.…”