A simple multi-sensor data fusion algorithm based on principal component analysis

In view of the uncertainty of data in multi-sensor sample system, a simple algorithm of determining the integrated support degree of each sensor based on principal component analysis is proposed. The algorithm defines the fuzzy-index function as support degree matrix of sensors. By principal component analysis, each sensor´s integrated support degree score is obtained. According to their scores, valid observation values of sensors are determined and fused by allocating corresponding weight coefficients, so that the final expression of data fusion and estimation is obtained. The algorithm needs less calculation and can objectively reflect the mutual support degree of sensors without knowing any prior knowledge. Simulation shows that the proposed method not only has higher fusion precision compared with other methods, but also has excellent ability against disturbance.