Searching High-dimension Ambiguity Based on Self-adaptive Differential Evolution Algorithm

In this paper, a new algorithm is proposed to solve the problem of high dimensional ambiguity resolution. The self-adaptive differential evolution algorithm is used to fix the high dimensional ambiguity with its global, fast and parallel search. According to the characteristics of the problem to be solved, some parameters are reset on the basis of the original adaptive differential evolution algorithm so as to realize the quick search of the ambiguity. Based on the solution and operation rate of LAMBDA algorithm, the correctness of the algorithm and the rapidity of solution are verified. It is proved that the algorithm has certain application reference value for high dimensional ambiguity resolution, and it has good reliability and robustness by simulating and measuring the data with different dimensions.