Probability distribution evolution algorithm to inertial parameters identification for space target

A new probability distribution evolution algorithm (PDE) is proposed for inertial parameters identification of space target. Based on the conservation of angular momentum, the number of space target's inertial unknown parameters is reduced from 10 to 4 by using pseudo inverse operation. The pseudo-inverse solution consistency in multiple groups status is proposed as the optimization evaluation index, and identification simulations are carried out using PDE. A evaluation strategy is given to significantly improve identification accuracy while a small increase of calculation consumption. The statistical results of identification simulation examples show that by only using angular momentum measurement data, the proposed PDE and strategy can achieve the high precision identification for the target inertial parameters with large range change. And PDE is equivalent to the optimization ability of typical evolutionary algorithms, such as genetic algorithm (GE) and differential evolution algorithm (DE).