Multiobjective Optimization Design of TomoSAR Satellite Orbit Based on Multireference Transfer Orbit

Abstract

This paper investigates an optimal orbit design method for single-satellite synthetic aperture radar tomography (TomoSAR) missions. Satellites require multibaseline observations for three-dimensional imaging. Thus, we need to weigh performance indicators such as global coverage, sampling rate, fuel consumption, and revisit accuracy. Considering these performance indicators, this paper proposes a multiobjective optimization algorithm based on multireference transfer orbit (M-RTO), which demonstrates superiority in fuel consumption. Fuel consumption is the primary optimization objective as it determines the lifetime of the satellite. First, we use Pareto optimization for the objectives of revisit time and fuel consumption. Then, we adopt an adaptive hybrid genetic algorithm (AHGA) for the objectives of revisit accuracy and fuel consumption. Numerical simulation verifies that compared with the single-reference transfer orbit method, the multireference transfer orbit method decreases fuel consumption by ∼37%, and the rest of the performance indicators meet the mission requirements.