Satellite imaging payload design optimization

This paper focuses upon the development of an efficient method for design optimization of an imaging payload of a remote sensing satellite. In this paper, the design of the imaging payload is defined as a multi-objective optimization problem. In the formulation of the problem, the aperture diameter and quality factor are used as a design variable and constraints, respectively, with maximization of signal to noise ratio (SNR) and minimization of the spherical aberration values. This paper presents a new method of involving the above two contradictorily objective functions. The approach adapted in this paper achieves the prescribed degree of quality of images and design constraints, whilst minimizing the weight of the payload in comparison with the conventional experimental approaches. The optimization algorithm used to solved the problem based on the genetic algorithms. Results obtained in this study, show that the method introduced in this paper provides an effective way of improving imaging payload in the design of a space system.