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针对多个传感器对某一特性指标多次测量的数据融合问题,提出一种基于灰色关联度的多传感器数据融合新方法。该方法将各传感器测得的数据视为一个行为序列,利用灰色关联度对不同传感器测得数据之间的接近程度进行度量,并通过灰色关联矩阵全面衡量数据间的综合接近程度,然后根据非负对称矩阵的性质求得各传感器测得数据在数据融合表达式中的权重,从而实现多传感器数据的融合。仿真结果表明应用所提出方法对雷达数据进行处理,可有效降低跟踪误差,提高测量精度。
Aiming at the data fusion problem of multiple sensors measuring multiple times of a certain characteristic index, a new method of multi-sensor data fusion based on gray relational degree is proposed. The method takes the data measured by each sensor as a sequence of actions, measures the closeness between the data measured by different sensors by using the gray relational degree, and comprehensively measures the comprehensive proximity between the data by the gray relational matrix. Then, The property of negative symmetry matrix obtains the weight of each sensor measured data in the data fusion expression, in order to achieve the fusion of multi-sensor data. Simulation results show that applying the proposed method to radar data processing can effectively reduce the tracking error and improve the measurement accuracy.