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Spatial Baseline Optimization for Spaceborne Multistatic SAR Tomography Systems
Jiuchao Zhao1, Anxi Yu2, Yongsheng Zhang3
1College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China. zhaojiuchao17@nudt.edu.cn.
Sensors (Basel, Switzerland)
|May 10, 2019
Summary
Optimizing baseline distribution in spaceborne multistatic synthetic aperture radar (SAR) tomography (SMS-TomoSAR) is crucial for high-precision 3D imaging. This study proposes a method for uniform baseline distribution, enhancing height-dimensional imaging performance.
Area of Science:
- Geosciences
- Remote Sensing
- Radar Technology
Background:
- Spaceborne multistatic synthetic aperture radar (SAR) tomography (SMS-TomoSAR) offers advanced 3D imaging and deformation measurement capabilities.
- Key challenges in SMS-TomoSAR include baseline optimization, error estimation, and algorithm selection, impacting imaging and measurement performance.
Purpose of the Study:
- To investigate the influence of baseline distribution on SMS-TomoSAR height-dimensional imaging.
- To propose and validate a feasible baseline optimization method for improved SMS-TomoSAR performance.
Main Methods:
- Equating multistatic SAR baselines to equivalent monostatic SAR baselines.
- Modeling equivalent baselines using a symmetric-geometric approach to analyze non-uniform distributions.
- Conducting experimental simulations and model analysis to evaluate imaging performance.
Main Results:
- An approximately uniform baseline distribution demonstrates superior SMS-TomoSAR imaging performance in the height dimension.
- A baseline design method is proposed for uniform-perturbation sampling with Gaussian error.
- The study quantifies imaging performance across different perturbation levels and defines maximum allowable baseline perturbation.
Conclusions:
- Baseline distribution significantly impacts SMS-TomoSAR height-dimensional imaging.
- A uniform baseline distribution is recommended for optimal SMS-TomoSAR performance.
- The proposed baseline optimization method provides a practical approach for system design.
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