OACRR-PSO Algorithm for Anti-ship Missile Path Planning
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摘要: 为了提高反舰导弹航路规划算法的搜素效率,从几何学角度对航路规划空间进行了研究,在将功能区域概念融入 逆向航路规划的过程中发现了功能区域的几何学渐变规律,据此提出功能区域簇作为其物理载体.将功能区域簇引入粒子群优化(Particle swarm optimization, PSO)算法,提出了功能区域簇实时约束(Operational area cluster real-time restriction, OACRR)的PSO算法(OACRR-PSO).为了便于表示功能区域簇,采用航路极坐标编码方式.与传统的PSO算法不同的是,考虑到 粒子中分量之间的关联性,该算法在优化过程中并不是对粒子的整个速度分量同时进行更新,而是引入一种分步递归进化 策略对粒子的分量逐步进行更新.在粒子的更新过程中,使用功能区域簇来实时限定粒子位置分量的准确更新范围,使得 算法搜索空间逐步减小,从而加速算法收敛.仿真实验结果表明,分步递归进化策略能够非常显著地提高算法的全局搜索 性能,并且算法收敛速度快、稳定性好.Abstract: In order to improve the search efficiency of path planning algorithm for anti-ship missile, the planning space is researched based on geometric principle. The geometric gradual transformation rule of operational area is revealed when fusing the concept of operational area into the process of converse path planning, hereby, the operational area cluster is proposed to be its physical carrier. By introducing the operational area cluster into particle swarm optimization (PSO) algorithm, a PSO algorithm real-time restricted by operational area cluster (OACRR-PSO) is proposed. To express the operational area cluster expediently, the polar coordinates code mode is adopted in path coding. Considering the relationship between the adjoining vectors of particle, OACRR-PSO does not update all the velocity vectors of particle simultaneously in the course of optimization, which is different from conventional PSO, but updates sequentially by adopting the strategy of sequential recursion evolution. In the course of updating particle, the operational area cluster is used to restrict the position vectors of particle in exact updating area in real-time, which reduces the search space step by step to increase the convergence velocity. Simulation results indicate that the strategy of sequential recursion evolution could improve the algorithm's global search capabilities and the algorithm possesses a better convergence rate and robustness.
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