Binary Tree Based Classification Method for the Material Layer and Multilink Conversion Model of Signal Propagation Process of Information Acquisition

This research proposed a binary tree based classification method, which classifies sensory mechanisms according to material movements. This classification is a beneficial attempt that tries to explain the working mechanisms of sensors from a global view for the material layer of the discipline of information acquisition science and technology. Almost all types of mechanisms have been expressed with the Boolean symbol. The binary expression method presented in the paper also describes the deference of sensors' performances, including accuracy and dynamic performance. One actual application was analyzed to verify the reliability of the relation concluded from the binary classification presented in this paper. The results showed that this method could be used to forecast the performances of new sensor to a certain extent, especially in the inertial sensor field. A multilink conversion conception of sensing mechanisms is put forward to characterize the error propagation phenomenon. Corresponding mathematical expressions have been set up, which indicates a way to decrease total error by reducing signal conversion links. This deduction is supported by the binary tree based classification method.