基于异构传感器网络的随机系统节点协同方法研究

针对传感器网络的通信延迟和切换拓扑,提出运动目标的随机状态协同估计算法。采用具有各种状态组合的不同测量矢量的异构传感器和卡尔曼滤波器对动态目标系统的状态进行估计。通过数值模拟方法验证协同式算法的可行性,对比SAA算法、CLACF算法和协同式算法的定位覆盖率和定位精度。结果表明,该算法性能最优,且不受通信限制。

NODE COOPERATIVE METHOD OF STOCHASTIC SYSTEM BASED ON HETEROGENEOUS SENSOR NETWORKS

Aiming at the communication delay and switching topology of sensor networks,this paper proposes a stochastic state cooperative estimation algorithm for moving targets.We used the heterogeneous sensor and Kalman filter with different measurement vectors of various state combinations to estimate the state of the dynamic target system,and verified the feasibility of the cooperative algorithm by numerical simulation method.We compared the positioning coverage rate and positioning accuracy of SAA algorithm,CLACF algorithm and the collaborative algorithm.The results show that our algorithm has the best performance,and it is not restricted by communication.