Optimization Deployment of Multi-Sensor Platforms in Near-Space Based on Adaptive Genetic Algorithm

Four optimization deployment performance indexes have been proposed for the problem of multi-sensor platforms optimization deployment in near-space. An adaptive GA algorithm is used to optimize the latitude and longitude points´ positions of multi-sensor platforms in near-space. Then a linear fitness function is constructed based on the four indexes. The crossing probability and mutation probability have been made to adapt to the change of the fitness values. For the appointed ground area, optimization deployment simulations of multisensor platforms are carried out and the latitude and longitude values of every platform for different number of platforms have been calculated. The optimization results demonstrate that the indexes proposed in this paper are reasonable and the latitude and longitude values calculated by the adaptive GA algorithm completely meet the need of multi-sensor platforms deployment, and the optimization speed also meets the synchronization´s need for acquiring informations.