Optical Communications Crude Aiming System Sensor Adaptive Signal Processing Research

With the rapid development of information industry in China,microwavecommunication gradually cannot satisfy people’s growing communication needs. A newgeneration of space laser communication technology will become the master of futurecommunication market because of its large transmission capacity, transmission speedand strong confidentiality and other advantages which cannot be compared bymicrowave communication. However, space laser communication put forward higherrequest for precise aiming, tracking and measuring technology. Absolute photoelectricshaft encoder are widely used in the precise alignment technology for its advantages ofhigh precision and high stability. As a spaceborne device, the traditional structure ofphotoelectric encoder and the decoder system can not adapt to bad space environmentbecause of their own factors limit. In order to improve the optical thick aiming systemaccuracy and reliability, a kind of decoding system of bad space environment adaptivecharacteristics and intelligent filter method are designed and this is of great significanceto the development of space laser communication technology.In this paper, the basic structure and working principle of the optical thick sensorsof aiming system is introduced firstly. Then, the rough error of the aiming system sensorin space environment is analyzed respectively from three aspects of the structure,photoelectric encoder grating signal and decoding method. And the error caused byvarious factors are quantitatively calculated and simulation tested. Againstdisadvantages of traditional decoding system, the adaptive compensation function of thenew coding system is designed, and the hardware circuit and software algorithm ofadaptive decoding system is made through high and low temperature test experiments.Its compensation effect is verified good.Finally, in order to improve coarse aiming system sensor accuracy effectively,combined with the essence of second harmonic in code signal, the characteristics ofthree harmonic and noise current, the traditional butterworth filter and IIR filter and FIRfilter for filtering the simulation test is used, and the strength and weakness of eachprocess are diliberated. In order to solve the shortcomings in view of the traditionalfilter method, BP neural network algorithm is used to improve the structure of FIR filter,and the adaptive filter based on LMS algorithm is applied to variable frequency signalde-noising, after filtering simulation and testing, precise code signal quality has thedistinct improvement.