Performance metric in closed-loop sensor management for stochastic populations
Performance metric in closed-loop sensor management for stochastic populations
复制标题
随机群体闭环传感器管理的性能指标
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Daniel E. Clark
中科院分区：
文献类型：
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作者：
E. Delande;J. Houssineau;Daniel E. Clark
传感器控制方法对于现代监控和传感系统至关重要，以实现资源的有效分配和优先级排序。部分观测马尔可夫决策过程的框架，使决策的基础上接收到的数据的传感器在信息理论的背景下。这项工作解决的问题，闭环传感器管理中的多目标监视的情况下，每个目标被假定为独立于其他目标移动。针对一类精确多目标跟踪滤波器，基于雷诺发散度，得到了信息增益的解析表达式。所提出的方法是足够的一般性，以解决广泛的传感器管理问题，通过由运营商定义的应用程序特定的奖励功能。
Methods for sensor control are crucial for modern surveillance and sensing systems to enable efficient allocation and prioritisation of resources. The framework of partially observed Markov decision processes enables decisions to be made based on data received by the sensors within an information-theoretic context. This work addresses the problem of closed-loop sensor management in a multi-target surveillance context where each target is assumed to move independently of other targets. Analytic expressions of the information gain are obtained, for a class of exact multi-target tracking filters are obtained and based on the Rényi divergence. The proposed method is sufficiently general to address a broad range of sensor management problems through the application-specific reward function defined by the operator.