Abstract

This paper presents an algorithm for simulating tomographic synthetic aperture radar (SAR) data based on another stack actually gathered by a real acquisition system. Through the procedure here proposed, the simulated system can be evaluated according to its capability to image complex natural media rather than reference point targets. This feature is particularly important whenever the biophysical properties of the target of interest must be preserved and cannot be easily modeled. The system to be simulated may be different from the original one concerning resolution, off-nadir angles, bandwidth and central frequency. The algorithm here proposed handles these differences by properly taking into account the wavenumbers of the target illuminated by the real survey and requested by the simulated one. The complex images constituting the synthetic stack are associated with the effective vertical interferometric wavenumber peculiar of the geometry to be simulated, regardless of the original data. Furthermore, the three-dimensional resolution cell of the simulated tomographic system is consistent with the simulated geometry concerning size and spatial orientation. These two latter features cannot be guaranteed by simply filtering the original stack. The simulator here proposed has been used to simulate the tomographic stack expected from the forthcoming European Space Agency (ESA) BIOMASS mission. The relationship between baseline distribution and 3D focusing capability was explored; special attention has been paid to the robustness of tomographic power at being a good proxy for the above ground biomass in tropical regions.

Highlights

  • The design of any spaceborne synthetic aperture radar (SAR) mission poses several challenges, among others the definition of the orbital path or the amount of propellent on board

  • This paper presents an algorithm for simulating tomographic synthetic aperture radar (SAR) data based on another stack gathered by a real acquisition system

  • This paper is organized as follows: in Section 2 a short description of tomographic SAR imaging in the wavenumber domain is presented, highlighting the differences between airborne and spaceborne systems; in Section 3 the procedure for simulating tomographic stacks starting from real acquisitions is detailed (The simulation strategy described in this paper was used to simulate BIOMASS data on boreal and tropical forests that were delivered to European Space Agency (ESA) as a part of the SARSIM database [18]); Section 4 illustrates some features of the synthetic tomographic stack; Section 5 presents the analysis of the impact of orbital inaccuracies on Above Ground Biomass (AGB) estimates; in Section 6 conclusions are drawn

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Summary

Introduction

The design of any spaceborne synthetic aperture radar (SAR) mission poses several challenges, among others the definition of the orbital path or the amount of propellent on board. Particular attention has been paid to the power fluctuations due to inaccurate orbital control, that is to irregular baseline sampling This fluctuations impact on the capability of the BIOMASS system of producing measurements to be used as proxy for AGB estimates. This paper is organized as follows: in Section 2 a short description of tomographic SAR imaging in the wavenumber domain is presented, highlighting the differences between airborne and spaceborne systems; in Section 3 the procedure for simulating tomographic stacks starting from real acquisitions is detailed (The simulation strategy described in this paper was used to simulate BIOMASS data on boreal and tropical forests that were delivered to European Space Agency (ESA) as a part of the SARSIM database [18]); Section 4 illustrates some features of the synthetic tomographic stack; Section 5 presents the analysis of the impact of orbital inaccuracies on AGB estimates; in Section 6 conclusions are drawn

Wavenumbers in SAR Acquisitions
Wavenumbers in Airborne and Spaceborne SAR Surveys
Cross Sensor Simulation
Features of the Simulated Stack
Application to BIOMASS
Findings
Conclusions
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