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.

remote sensing satellite;orbit prediction;reference payload;cross calibration;orbit optimization