基于混沌粒子群与Taylor算法的协同定位算法研究
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摘要
针对无线传感器网络中运用TDOA方法定位时,Taylor算法容易受到初始估计值影响,导致节点定位精度低、不容易收敛,因此提出了一种基于混沌粒子群与Taylor算法协同定位的方法。该算法首先运用混沌粒子群算法求解TDOA方程组,得到一个具有较高精度的未知节点的估计坐标值,将这个估计值作为Taylor算法的初始值进行迭代运算,最终完成对未知节点的坐标估计。仿真结果表明,该算法提高了节点的定位精度和定位速度。
Aiming at using the method of TDOA localization in wireless sensor network,initial estimation error affected the Taylor algorithm,resulting in low positioning accuracy and difficult to converge. A co-location method based on chaos particle swarm and Taylor algorithm was proposed. The algorithm first solved the TDOA equations with chaos particle swarm,obtaining the estimated coordinate value of the unknown node with high precision,using the estimated value as the initial value of the Taylor algorithm for iterative operation,and finally completing the coordinate estimation of the unknown node. The simulation results show that the algorithm improves the location accuracy and positioning speed of the nodes.
Aiming at using the method of TDOA localization in wireless sensor network,initial estimation error affected the Taylor algorithm,resulting in low positioning accuracy and difficult to converge. A co-location method based on chaos particle swarm and Taylor algorithm was proposed. The algorithm first solved the TDOA equations with chaos particle swarm,obtaining the estimated coordinate value of the unknown node with high precision,using the estimated value as the initial value of the Taylor algorithm for iterative operation,and finally completing the coordinate estimation of the unknown node. The simulation results show that the algorithm improves the location accuracy and positioning speed of the nodes.
引文
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[6]冯慧昭,张正平,秦水介.一种基于最小二乘和Taylor级数展开法的协同定位算法[J].通信技术,2009,42(2):210-211.
[7] FANG B T. Simple solutions for hyperbolic and related fixes[J]. IEEE Trans On Aerospace and Electronic Systems,1990,26(5):748-753.
[8]罗平,向凤红,毛剑琳,等.基于自然选择的线性递减权重PSO与Taylor算法的TDOA协同定位算法研究[J].计算机应用研究,2014,31(4):1144-1146.
[9] CLERC M,KENNEDY J. The particle swarmexplosion,stability,and convergence in a multidimensional complex space[J]. IEEE Trans on Evolutionary Computation,2002,6(1):58-73.
[10]刘影,钱志鸿,王雪,等.基于到达时间差的无线传感器网络质心定位算法[J].吉林大学学报(工),2010,40(1):245-249.
[11]王亚子,杨建辉.改进粒子群算法的无线传感器网络节点定位[J].计算机工程与应用,2014,50(18):99-102.
[12]刘道华,原思聪,兰洋,等.混沌映射的粒子群优化方法[J].西安电子科技大学学报(自然科学版),2010,37(4):764-769.
[13]史洪宇,燕莎,曹建忠.无线传感器网络节点定位的混沌粒子群优化算法[J].探测与控制学报,2010,32(5):46-49.
[14] BERGH F,ENGELBRECHT A P. A Cooperative Approach to Particle Swarm Optimization[J]. IEEE Trans on Evolutionary Computation,2004,8(3):225-239.
[15]曾晶.基于量子遗传算法和混沌粒子群的无线传感器网络节点定位算法研究[D].赣州:江西理工大学,2013.
[2] WU Y I,WANG H,ZHENG X. WSN Localization Using RSS in Three-Dimensional Space-A Geometric Method With Closed-From Solution[J]. IEEE Sensors Journal,2016(11):4397-4404.
[3] HARA S,ANZAI D,YABU T,et al. A Perturbation Analysis on the Performance of TOA and TDOA Localization in Mixed LOS/NLOS Environments[J]. IEEE Transactions on Connunications,2013,61(2):679-689.
[4]诸燕平,黄大庆,李勃.基于AOA的无线传感器网络节点定位算法[J].传感器微系统,2010,29(1):98-101.
[5]吕淑芳.无线传感器网络节点定位研究综述[J].传感器与微系统. 2016,35(5):1-3.
[6]冯慧昭,张正平,秦水介.一种基于最小二乘和Taylor级数展开法的协同定位算法[J].通信技术,2009,42(2):210-211.
[7] FANG B T. Simple solutions for hyperbolic and related fixes[J]. IEEE Trans On Aerospace and Electronic Systems,1990,26(5):748-753.
[8]罗平,向凤红,毛剑琳,等.基于自然选择的线性递减权重PSO与Taylor算法的TDOA协同定位算法研究[J].计算机应用研究,2014,31(4):1144-1146.
[9] CLERC M,KENNEDY J. The particle swarmexplosion,stability,and convergence in a multidimensional complex space[J]. IEEE Trans on Evolutionary Computation,2002,6(1):58-73.
[10]刘影,钱志鸿,王雪,等.基于到达时间差的无线传感器网络质心定位算法[J].吉林大学学报(工),2010,40(1):245-249.
[11]王亚子,杨建辉.改进粒子群算法的无线传感器网络节点定位[J].计算机工程与应用,2014,50(18):99-102.
[12]刘道华,原思聪,兰洋,等.混沌映射的粒子群优化方法[J].西安电子科技大学学报(自然科学版),2010,37(4):764-769.
[13]史洪宇,燕莎,曹建忠.无线传感器网络节点定位的混沌粒子群优化算法[J].探测与控制学报,2010,32(5):46-49.
[14] BERGH F,ENGELBRECHT A P. A Cooperative Approach to Particle Swarm Optimization[J]. IEEE Trans on Evolutionary Computation,2004,8(3):225-239.
[15]曾晶.基于量子遗传算法和混沌粒子群的无线传感器网络节点定位算法研究[D].赣州:江西理工大学,2013.