Research On Automatic Recognition Technology Of Artificial Morse Optical Signal

With the rapid development of wireless technology,Morse code is relatively less used in the field of radio,but it is still widely used in visible light communication between ships.In the process of visible light communication,the sender manipulates the light equipment to deliver the message,and the receiver receives the message by the visual system.The traditional manual way has higher requirements on the receiver.Training a qualified receiver requires lots of time,human and material resources.Moreover,the traditional manual way is susceptible to influences of external factors,resulting in decoding results with reduced accuracy.The purpose of this paper is to study,design and implement an automatic recognition technology.This technology can decode the Morse optical signal automatically,and replace the person to finish the receiving work by embedded device,which can effectively reduce the workload of the receiver.The main work of this paper is as follows:(1)Discuss the research results related to this topic,study the general rules and characteristics of Morse code,study the transmission loss of optical signals in free space and the background-light noise,which lay a foundation for the design and implementation of the new recognition algorithm.(2)Several key technologies in the automatic recognition system are studied in detail,including digital filtering,clustering algorithm,and string similarity algorithm.In view of the actual application scenario,this paper improves the process of cluster analysis based on the k-Means algorithm.(3)Design the implementation scheme of the whole system,improve the processing flow of each functional module,the scheme and diagrammatic sketch are given too.Finally,use C language to develop the automatic recognition technology in the STM32 embedded system.(4)Complete the functional simulation of the system,and then design a complete experimental scheme according to the relevant characteristics of the embedded system*.Moreover,verify the function of automatic recognition in the optical path.Finally,simulating different channel conditions to test the overall performance of the system.The experimental results show that the accuracy of automatic decoding is greater than 95%when the signal to noise ratio of the input signal is not less than 4 dB.