基于禁忌搜索算法的AUV动态路径规划策略

发布时间：2018-06-11 20:44

本文选题：水下传感器网络 + AUV节点　；参考：《南京大学学报(自然科学)》2017年01期

【摘要】：为有效提高水下传感器网络中未知节点的定位效率并降低网络能耗,提出一种改进禁忌搜索算法的Autonomous Underwater Vehicle(AUV)动态路径规划策略.所提出的算法和策略,采用六边形部署算法,寻找合适的虚拟锚节点位置,以达到最佳覆盖效果;然后通过在AUV节点上配置定向天线,获取未知节点方位信息;再次,利用改进的禁忌搜索算法,选定AUV节点下一步目标虚拟锚节点,引导AUV节点移动.该文通过改进的禁忌搜索算法设置两个禁忌集,防止AUV节点重复搜索,并辅助AUV节点移动方向判定,保证未知节点的定位覆盖率.为验证所提策略有效性,对所提该策略和静态路径规划算法中的典型算法Scan算法进行对比分析计算.仿真表明,基于禁忌搜索算法的AUV动态路径规划策略较Scan算法移动路径长度明显减少,虚拟锚节点数目有所降低,能有效降低能耗,延长网络寿命.同时,由于Received Signal Strength Indicator(RSSI)测距法存在误差,误差值设置为虚拟锚节点到未知节点的真实距离的10%,仿真得出基于禁忌搜索算法的AUV动态路径规划策略较Scan算法,定位精度有所提高.
[Abstract]:In order to improve the localization efficiency of unknown nodes in underwater sensor networks and reduce network energy consumption, an improved Tabu search algorithm for dynamic path planning of Autonomous underwater vehicle (AUV) is proposed. The proposed algorithm and strategy, using hexagonal deployment algorithm, to find the appropriate location of virtual anchor node to achieve the best coverage effect; then through the configuration of directional antenna on the AUV node to obtain the unknown node azimuth information; again, By using the improved Tabu search algorithm, the next target virtual anchor node of AUV node is selected to guide the AUV node to move. In this paper, two Tabu sets are set up by the improved Tabu search algorithm to prevent the AUV nodes from searching repeatedly, and to assist in the determination of the moving direction of the AUV nodes, so as to ensure the location coverage of the unknown nodes. In order to verify the effectiveness of the proposed strategy, the proposed strategy and the static path planning algorithm of the typical algorithm scan algorithm are compared and calculated. Simulation results show that the dynamic path planning strategy of AUV based on Tabu search algorithm reduces the length of moving path and reduces the number of virtual anchor nodes. It can effectively reduce energy consumption and prolong network life. At the same time, due to the error of received signal standing indicator (RSSI) ranging method, the error value is set to 10% of the real distance between virtual anchor node and unknown node. The simulation results show that the dynamic path planning strategy based on Tabu search algorithm is more accurate than scan algorithm.
【作者单位】：海军指挥学院信息系;
【基金】：全军军事类研究生资助课题(2013JY411;2015JY373)
【分类号】：TP212.9

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