1. 河南大学计算机科学学院,河南,开封,475001
2. Department of Electronic Engineering,Beijing Institute of Technology,Beijing,China,100081
3. Department of Automatic Control,Northwestern Ploytechnical University,Shaanxi,Xi'an,China,710072
4. 河南大学计算机科学学院,河南,开封,475001
5. Department of Electronic EngineeringBeijing Institute of TechnologyBeijing 100081China
6. Department of Automatic ControlNorthwestern Ploytechnical UniversityXi'anShaanxi 710072China
纸质出版:2002
移动端阅览
申石磊, 刘先省, 潘 泉, 等. 基于运动模型的一类传感器管理方法[J]. 电子学报, 2002,30(2):201-204.
SHEN Shi-lei, LIU Xian-xing, PAN Quan. A Method of Sensor Management Based on Dynamical Model[J]. Acta Electronica Sinica, 2002, 30(2): 201-204.
利用目标检测前后信息熵的变化以及卡尔曼滤波方程中协方差的预测与更新阵
可以计算出传感器对目标进行检测或跟踪所产生的信息增量
并给出了一类基于信息增量最大化传感器管理方法.仿真结果表明:与顺序跟踪方法相比
该方法能够更合理分配有限的传感器资源
提高跟踪系统的整体性能;与随机检测与跟踪方法相比
该方法在保证一定跟踪精度的前提下
能最大限度地发现并跟踪新目标.
By using evolution of information entropy in target detection and prediction and updating matrices of covariance in Kalman filter equations
we can solve information gain in a measurement for target detection or tracking
and present a method of sensor management based on maximization of information gain.Simulation results show that this method can rationally assign the limited sensor resources and improve the whole performance of tracking system compared with sequence tracking method
and can maximally detect and track new targets under a certain tracking precision compared with random detection and tracking.
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