Journal of Remote Sensing (Jan 2024)

Conceptual Study and Performance Analysis of Tandem Multi-Antenna Spaceborne SAR Interferometry

  • Fengming Hu,
  • Feng Xu,
  • Robert Wang,
  • Xiaolan Qiu,
  • Chibiao Ding,
  • Yaqiu Jin

DOI
https://doi.org/10.34133/remotesensing.0137
Journal volume & issue
Vol. 4

Abstract

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Multi-baseline synthetic aperture radar interferometry (InSAR), capable of mapping 3D surface model with high precision, is able to overcome the ill-posed problem in the single-baseline InSAR. Current tandem SAR mission utilizes a two-stage global coverage to get the dual-baseline interferograms, which achieves the trade-off between the unwrapping errors and height precision. However, the baseline adjustment will decrease the timeliness of the data acquisition, which is not suitable for monitoring temporal changes of the ground targets. Designing a SAR mission with the single-pass multi-baseline acquisition will improve the practical capability in fast 3D reconstruction. Following the asymptotic 3D phase unwrapping proposed for the airborne array InSAR system, it is possible to get a reliable 3D reconstruction using very sparse acquisitions but the interferograms should follow the optimal baseline configuration. In this article, a new concept of tandem multi-antenna SAR interferometry system for acquiring optimal single-pass multi-baseline interferograms is proposed. Two indicators, i.e., expected relative height precision and successful phase unwrapping rate, are selected to optimize the system parameters. Additionally, taking the satellites with two antennas as an example, the performances of various baseline configurations in typical scenarios and the impact of different error sources are investigated correspondingly. The simulation-based experiments demonstrate that the proposed system acquires the optimal MB interferograms for asymptotic 3D phase unwrapping, and thus enables good performance in both urban and forest area in a single flight. This system has the potential applications in accurate digital surface model acquisition, 3D target recognition, and biomass estimation.