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.