自适应SA-ACO地磁匹配导航算法

Adaptive SA-ACO geomagnetic matching navigation algorithm

基本蚁群算法的地磁匹配算法易陷入局部最优且算法鲁棒性、稳定性较低,针对这些不足提出一种改进的地磁匹配导航算法。新算法改进了蚁群算法的信息素更新策略并引入参数自适应调整来避免算法陷入局部最优;同时采用带有记忆功能和自适应选择初始温度的模拟退火(SA)算法,无论算法是否陷入局部最优时通过在本次迭代最优路径上强行随机扰动以实现继续寻优。实验结果表明,新算法比传统蚁群优化(ACO)算法有更强的鲁棒性和稳定性。

In view that the geomagnetic matching algorithm based on the basic ant colony algorithm tends to fall in local optimum and the robust and stability of the basic algorithm are low, an improved geomagnetic matching navigation algorithm is proposed. To avoid the algorithm fall in the local optimum, the strategy of pheromone updating is improved and the adaptive adjustment of parameters are introduced. Meanwhile, the simulated annealing algorithm with memory function and adaptive determination of initial temperature is also introduced. So whether the algorithm fall in local optimum or not, it could continue to search better route by applying random disturbances on the best route of this iteration to achieve continued optimization. The experiment results show that the new algorithm is more robust and stability than traditional ant colony optimization.