In view of the weak resolution ability of traditional spectral matching operators in the phenomenon of “foreign objects in the same spectrum”, a spectral matching operator based on position vector measurement (PVS) is proposed, and a method of improving target recognition by fusion of matching operators is proposed. PVS operator is an extension of the absorption depth in the spectral absorption feature. The operator first uses the position vector to amplify the spectral curve, and then uses the method of voting statistics to divide the ground features. The experimental results show that when the detection probability is 70%, the false alarm rate of PVS operator is reduced by 1.73 percentage points and 4.77 percentage points on average in the two datasets. At the same time, in the case of the detection probability of 75.43%, the false alarm rate of the fused PVS operator can be reduced by 2.35 percentage points and 8.26 percentage points on average on the two datasets, respectively.