基于遗传算法的交叉定标基准载荷轨道优化方法

史树峰; 武海雷

doi:10.11834/jrs.20231793

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基于遗传算法的交叉定标基准载荷轨道优化方法
Orbit optimization method of reference payload cross-calibration based on the genetic algorithm
2023年27卷第5期页码：1114-1120
收稿：2021-12-02，

纸质出版：2023-05-07
DOI： 10.11834/jrs.20231793
稿件说明：

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史树峰，武海雷.2023.基于遗传算法的交叉定标基准载荷轨道优化方法.遥感学报，27（5）： 1114-1120 DOI： 10.11834/jrs.20231793.

Shi S F and Wu H L. 2023. Orbit optimization method of reference payload cross-calibration based on the genetic algorithm. National Remote Sensing Bulletin， 27（5）：1114-1120 DOI： 10.11834/jrs.20231793.

摘要

针对星间交叉定标和地面固定场地交叉定标两种辐射定标方案，利用卫星的轨道参数建立了交叉定标轨道模型，提出了定标交叉频次的计算方法。研究了各轨道参数对交叉频次的影响程度，经过分析限定了轨道高度、升交点赤经、纬度幅角是影响交叉频次的主要因素。提出了基于遗传算法的服务于多目标载荷轨道的基准载荷轨道优化方法，通过选择合适的适应度函数，优化得到的基准载荷轨道相较于未优化前，单位仿真周期内总体交叉频次和对各目标载荷的交叉均匀度都有明显改善。仿真分析结果有助于开展服务多目标载荷的基准载荷轨道优化设计。

Abstract

The objective of this paper is to develop a well-performing reference payload orbit design method for in-orbit radiometric cross-calibration. The satellite sensor is used as the target payload

and the satellite sensor with high calibration accuracy is used as the reference payload. The cross-calibration method can be carried out when the two sensors observe the same target at the same time or almost the same time. Precise atmospheric measurements are not required

but the calibration accuracy of the reference sensor is very demanding. The SGP4 orbit prediction model can be used to predict the orbits of remote sensing satellites to maximize calibration crossings. To develop a method to find the orbit of the reference payload

various factors affecting the cross-calibration frequency of remote sensing satellites need to be analyzed. The main influencing factors can then be highlighted

and the reference payload orbit optimization can be implemented with pertinence. There are two cross-calibration modes: inter-satellite cross-calibration and fixed-site cross-calibration. Based on the orbit models obtained for these modes

the effect of each of the six orbital elements on the crossover frequency can be explored by the fixed-variable method. Results indicate that the orbital altitude has the greatest influence on the crossover frequency

followed by the right ascension of ascending node and the argument of latitude

and less by the eccentricity and orbital inclination. To optimize the reference payload orbit

a method based on genetic algorithm is proposed. The optimization algorithm only needs to select the three main elements out of all six orbital elements as optimization parameters. By selecting the appropriate fitness function for the inter-satellite cross-calibration and the fixed-site cross-calibration

the overall crossover frequency and crossover uniformity of each target payload in the unit simulation cycle are significantly improved compared with that before optimization. The simulation results are helpful in carrying out the reference payload orbit optimization design for serving multi-objective payload.

关键词

Keywords

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