The performance of a distributed Neyman-Pearson detection system is considered with the decision rules of the sensors given and the decisions from different sensors being mutually independent conditioned on both hypot...The performance of a distributed Neyman-Pearson detection system is considered with the decision rules of the sensors given and the decisions from different sensors being mutually independent conditioned on both hypothese. To achieve the better performance at the fusion center for a general detection system of n 〉 3 sensor configuration, the necessary and sufficient conditions are derived by comparing the probability of detec- tion at the fusion center with that of each of the sensors, with the constraint that the probability of false alarm at the fusion center is equal to that of the sensor. The conditions are related with the performances of the sensors and using the results we can predict the performance at the fusion center of a distributed detection system and can choose appropriate sensors to construct efficient distributed detection systems.展开更多
为在预警监视系统中对多目标的检测、跟踪、识别过程进行统一处理,提出一种基于跳转马尔可夫系统模型高斯混合概率假设密度滤波(jump Markov system model Gaussian mixture probability hypothesis density filtering,JMS-GMPHDF)算法...为在预警监视系统中对多目标的检测、跟踪、识别过程进行统一处理,提出一种基于跳转马尔可夫系统模型高斯混合概率假设密度滤波(jump Markov system model Gaussian mixture probability hypothesis density filtering,JMS-GMPHDF)算法的雷达、电子支援措施(electronic support measures,ESM)综合多目标检测、跟踪与识别方法。该方法首先根据不同类别目标设计各自的多目标多模型高斯混合概率假设密度滤波器,并在各滤波器处理过程中同时对高斯项进行编号;然后,根据目标速度与加速度模型信息进行高斯项综合与类别判决,同时根据ESM测量信息进行型号判决;最后,通过航迹综合管理,形成具有运动状态信息以及类别、型号、航迹编号信息的确定航迹。仿真实验验证了该方法能够有效综合雷达、ESM测量数据,在进行多目标检测、跟踪的同时进行正确的类别、型号判决,并形成确定航迹。展开更多
基金Sponsored by the National Natural Science Foundation of China(60232010)
文摘The performance of a distributed Neyman-Pearson detection system is considered with the decision rules of the sensors given and the decisions from different sensors being mutually independent conditioned on both hypothese. To achieve the better performance at the fusion center for a general detection system of n 〉 3 sensor configuration, the necessary and sufficient conditions are derived by comparing the probability of detec- tion at the fusion center with that of each of the sensors, with the constraint that the probability of false alarm at the fusion center is equal to that of the sensor. The conditions are related with the performances of the sensors and using the results we can predict the performance at the fusion center of a distributed detection system and can choose appropriate sensors to construct efficient distributed detection systems.
文摘为在预警监视系统中对多目标的检测、跟踪、识别过程进行统一处理,提出一种基于跳转马尔可夫系统模型高斯混合概率假设密度滤波(jump Markov system model Gaussian mixture probability hypothesis density filtering,JMS-GMPHDF)算法的雷达、电子支援措施(electronic support measures,ESM)综合多目标检测、跟踪与识别方法。该方法首先根据不同类别目标设计各自的多目标多模型高斯混合概率假设密度滤波器,并在各滤波器处理过程中同时对高斯项进行编号;然后,根据目标速度与加速度模型信息进行高斯项综合与类别判决,同时根据ESM测量信息进行型号判决;最后,通过航迹综合管理,形成具有运动状态信息以及类别、型号、航迹编号信息的确定航迹。仿真实验验证了该方法能够有效综合雷达、ESM测量数据,在进行多目标检测、跟踪的同时进行正确的类别、型号判决,并形成确定航迹。
