FSM model correlation identification method based on invert-repeated m-sequence

Abstract

Fast steering mirror (FSM) is one of the most important components in electro-optical tracking system and access to FSM model is the basis for controlling and fault diagnosis. This paper presented a correlation identification method based on Invert-Repeated m-sequence which can be used in the electro-optical tracking system to achieve the model of FSM under low sampling rate. Firstly, this article discussed the properties of the Invert-Repeated m-sequence and program implemented in matlab language, then analyzed the principle of correlation identification method based on Invert-Repeated m-sequence by utilizing Wiener-Hopf equation which is simple to achieve with strong anti-jamming capability and small perturbations on the system. Finally, a FSM model with the experiment data got by Dynamic Signal Analyzer was built in Matlab/Simulink and identified by the method mentioned in the paper. The experiment showed that correlation identification method which has certain actual application value, based on Invert-Repeated m-sequence can obtain more accurate recognition results even if the FSM system’s output signal contained large variance noise.