考虑自支持度和互支持度的多传感器一致性测度算子

Measuring Operator Considering Self-Support and Mutual-Support for Estimating Consistency of Multi-Sensor Observations

针对传感器观测结果可能存在虚假甚至错误信息从而影响数据融合估计的问题,研究了一种度量多传感器观测结果一致性的测度算子.在进行数据融合估计之前,首先对多传感器的观测结果进行一致性检验,从而识别并剔除失效传感器的观测结果,最终获得一致性估计.该一致性测度算子基于Hampel粗差鉴别思想,同时考虑传感器的自支持度和传感器之间的互支持度,经过综合后给出传感器观测结果的一致性测度信息.仿真实验结果表明,该方法简单有效,能够准确识别传感器的虚假和错误观测结果,剔除失效传感器,同时能够给出传感器观测结果的质量评价,为数据融合估计提供可靠的一致性传感器组.

Focusing on the possibility for observed results with false or erroneous information of a sensor to affect data fusion estimation,an operator measuring consistency of the observed results of a multi-sensor is introduced.Before data fusion estimation,the consistency checking on the observed results is taken to identify and remove the observations of failed sensors,and obtain the consistent estimating.Based on the Hampel gross error identifier,the consistency measuring operator is able to take both self-support and mutual support between the sensors into account,to obtain the consistency information of observations.The simulation shows the simplicity and effectiveness for identifying false and erroneous observed results,eliminating the failed sensors,evaluating the quality of each sensor observations,and providing data fusion estimation with reliable consistent sensor group.