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在多准则下考察传感器的融合权重,提出一种新的多传感器数据融合方法.通过多个性能指标折中估计传感器权重,以降低决策的主观性和偶然性;提出从不同融合级别来定义多个准则,定性地提高了多准则的信息量;在没有决策者对各准则偏好信息的情况下,以最小化准则冗余度和最大化评价差异度为原则建立多目标优化模型对准则权重向量优化求解.仿真实验结果表明,相比于单准则和单层次的融合方法,所提出方法具有更低的决策风险和更高的稳定性.
In this paper, a new multi-sensor data fusion method is proposed based on multi-criteria, and a new multi-sensor data fusion method is proposed. The weight of the sensor is compromised by multiple performance indices to reduce the subjectivity and contingency of decision making. Criterion to qualitatively improve the information quantity of multi-criteria; to establish the multi-objective optimization model based on the principle of minimizing the criterion redundancy and maximizing the evaluation difference, without the policy-maker’s preference information, weight vector optimization The simulation results show that the proposed method has lower decision risk and higher stability than single criterion and single-level fusion.