An Optimization Method for Satellite Data Structure Design Based on Improved Ant Colony Algorithm

The telemetry data structure is the embodiment of satellite telemetry format, the rationality and correctness of which determine the satellite telemetry capacity as well as transmission capability. Conventional satellite telemetry data structure designs excessively depend on manual experience, easily leading to problems such as waste of satellite resources, low telemetry transmission efficiency and unintuitive ground decoding. In this paper, a novel method was proposed to optimize the design of satellite telemetry data structure, based on rasterized modeling to visualize the design constraints, and an improved ant colony algorithm with grey relational analysis to optimize the telemetry data structure. The method is not only effective in preventing the deficiencies of conventional approaches, but also beneficial to the rational allocation of telemetry resources. The feasibility was verified by the telemetry data of a satellite with DFH-4 platform, and the results showed favorable convergence, along with valid improvement of the design process efficiency and application effect.