基于改进惯性权重PSO算法的目标位置测量技术

A target location measurement method based on an improved inertia weight particle swarm optimizer algorithm

针对现有目标位置求解算法推导复杂和标准粒子群算法易陷入局部最优点的问题,提出了一种基于改进惯性权重粒子群算法的目标位置测量方法。该方法通过引进指数因子改进标准粒子群算法的惯性权重,平衡了其全局和局部搜索能力,实现了目标位置的高精度测量。仿真结果表明利用该方法能有效地对目标进行位置测量,测量精度达到0.5%。该方法对无线传感器网络定位、移动通信定位等工程问题也具有一定的研究意义和应用价值。

A target location measurement method based on an improved inertia weight particle swarm optimizer algorithm is proposed in view of the shortcoming of the existing target position measurement algorithm and standard particle swarm optimizer algorithm, which has a complex calculation and is easy to be trapped in the local optimum point. Measuring a target location with high precision has been realized by introducing the exponential factor to improve the inertia weight of the standard particle swarm optimizer algorithm and balance its global and local search ability. The measurement accuracy can reach 0. 5%, in the use of the improved inertia weight PSO algorithm to measure the target location more effectively, showed in the simulation. The novel approach has potential significance in the positioning in Wireless Sensor Network, Mobile Communication System as well as some other engineering.