摘要
针对传感器网络(sensor network,SN)目标融合检测应用中融合中心无法精确地获得局部传感器节点检测性能参数的问题,建立了基于SN的目标融合检测系统,提出了一种非理想信道条件下在线决策融合的目标检测方法。该方法依据解调后数据构建了节点未知虚警概率、检测概率以及节点与融合中心信道平均传输错误概率等未知参数求解模型,并采用非线性最小二乘方法在线地估计出这些未知参数。进而通过选择性能优的节点参与融合,最大化融合检测系统检测概率。仿真结果表明:这种在线决策融合方法能够准确地估计出传感器节点的概率参数以及信道的平均传输错误率;相比于已知先验的最优似然比融合规则,在线决策融合规则检测性能相当。
To solve the problem that the fusion center in a sensor network （SN） cannot completely obtain the local detection performance indices, a target detection model based on the SN is established. An online deci- sion fusion method for target detection with the non-ideal channel between local sensors and the fusion center is proposed. This method constructs the model of solving unknown parameters including local false alarm proba- bilities, local detection probablities and the average bit error probability of the non-ideal transmission channels. The nonlinear least square method is employed to estimate the unknown parameters. In order to maximiae the system detection performance, the sensors with high detection performance are chosen to participate in the fu- sion. The simulation results show that the estimations tend to be with the true local probability values and the average bit error probability. Compared with the online decision fusion method exhibits only slight optimal likelihood ratio （LR） based fusion rule, the proposed performance degradation.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第8期1741-1747,共7页
Systems Engineering and Electronics
基金
国家自然科学基金(61401364)
教育部博士点基金(20136102120013)资助课题
