平衡WSN目标失跟率的自适应采样频率方法

针对WSN固定采样频率下机动性目标失跟率较高的问题，分析了机动性目标失跟的机理，建立了表征失跟率、采样频率、目标速率关系的数学模型，提出了平衡目标失跟率的自适应采样频率方法，并对速度大小、方向变化的机动性目标跟踪问题进行仿真实验。结果表明，自适应采样频率方法（采样间隔距离参量 取不同值时）相比固定采样频率方法的失跟率平均可降低3.3%-6%；当 等于50米时，失跟率平均降低6%，网络能耗降低13.1%。

Adaptive Sampling Frequency Method Balancing Target Loss Rates in WSN

Aiming at the problem of high loss rate of maneuvering target with fixed sampling frequency, the principle of maneuvering target’s loss is analyzed and the mathematical model of relation between loss rate, sampling frequency and target’s velocity is also established in this paper. Based on this, a novel adaptive sampling frequency method to balance loss rates of target is proposed and the simulation experiments are performed for the maneuvering target tracking with variable velocity and moving direction. The experimental results show the loss rates of adaptive sampling frequency method decrease by 3.3 percent to 6 percent in comparison with fixed sampling frequency method when the distance values in sampling interval is different. Particularly, the loss rate is decreased by 6 percent on average with the energy consumption decreased by 13.1 percent when distance in sampling interval is equal to 50 meters