Optimal configuration design of regional observation heterogeneous satellite constellation based on multi-objective genetic algorithm

The increasing demand for comprehensive, accurate, and rapid satellite remote sensing data has necessitated the development of heterogeneous satellite constellations. These constellations, equipped with diverse payloads, are designed for cooperative ground observation. Unlike traditional homogeneous constellations, heterogeneous constellations often incur higher risks due to varying altitudes and inclinations among their sub-constellations. This diversity increases the likelihood of potential disruptions and necessitates significant long-term maintenance costs. This paper introduces a novel approach to constellation design that concurrently optimizes observation capabilities and maintenance costs. The design challenge is reformulated as a multi-objective optimization (MO) problem, tackled using a combination of System Tool Kit (STK) and MATLAB integration. The approach utilizes the Non-dominated Sorting Genetic Algorithm II (NSGA-II) alongside a fuzzy set algorithm to achieve a balance across multiple criteria. The optimization model considers four main objectives: minimizing the average maximum revisit time, maximizing the total duration of inter-satellite link connectivity, and reducing the maintenance costs associated with constellation configuration, which includes minimizing the total drift in right ascension of the ascending node and satellite altitude adjustments. Two sets of simulations are conducted to evaluate the method: one using the multi-objective optimization framework (MO) and the other based on a single-objective optimization (SO). The results reveal that while the MO-based designs result in a longer average maximum revisit time compared to SO, they excel in terms of inter-satellite connectivity. Additionally, these designs demonstrate a reduction in the overall maintenance costs. This showcases the effectiveness of the proposed method in optimizing trade-offs between different operational objectives, thus enhancing the sustainability and efficiency of satellite constellations.