摘要
针对传感器观测相关的条件下最优分布式检测融合算法较为复杂这一问题,提出了一种基于似然比判决规则的系统性能优化方法.该方法的基本思想是,限定各部传感器采用似然比判决规则,并在此约束条件下,联合优化各部传感器的判决门限,以使系统检测性能达到最优.对于由N部传感器组成的分布式串行检测融合系统,在Bayes准则下推导了各部传感器判决门限联合最优化的必要条件,得到了最优传感器判决门限满足的系统方程,并在此基础上给出了求解最优传感器判决门限的数值迭代算法.由于将传感器判决规则的联合优化问题简化为了判决门限的联合优化问题,因此该算法计算量较小,收敛性较好,更加便于工程应用.
In order to reduce the computational complexity of optimal fusion algorithms with dependent sensor observations, a method for optimizing the system performance based on likelihood ratio decision rules is proposed. The basic idea of the method is to optimize the system performance by constraining the sensor decision rules to be likelihood ratio decision rules, and optimizing the sensor decision thresholds jointly. The necessary condition for the joint optimal sensor decision thresholds is derived for the distributed serial detection systems consisting of N sensors under Bayesian criterion, and the system equations that are satisfied by the optimal sensor decision thresholds are obtained. An iterative algorithm is also proposed to solve for the optimal sensor decision thresholds. Since the joint-optimization of sensor decision rules is simplified to the jointoptimization of decision thresholds, the amount of computational costs is reduced. The algorithm converges well and is more applicable in real applications.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2008年第10期1209-1212,1234,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(60472005)
关键词
分布式串行检测系统
检测融合
似然比判决规则
distributed serial detection systems
detection fusion
likelihood ratio decision rule
