Research On Inertial Measurement Signals Separation Method Based On Blind Source Separation Technology

The photoelectric tracking system installed on the moving carrier is widely used in monitoring and searching,range measurement and laser communication.Its basic principle is to ensure that the target is in the center of sight as far as possible by means of miss distance information measured by CCD sensor.However,due to the influence of external interference and vibration of the carrier,the stability of the carrier is insufficient,and additional inertial sensor is needed to assist the stability.The measurement signal of the sensor is a mixture of target tracking signal,carrier disturbance signal and noise signal.The disturbance is isolated by the closed-loop suppression ability of the tracking system to disturbance.However,when the disturbance of the carrier is severe,the high accuracy and stability of the LOS in the system cannot be achieved.In order to eliminate the influence of disturbance at the source,this paper separates each component signal from the mixed measurement signal by means of signal processing,and then separately controls the carrier disturbance signal and noise by means of control method,so as to eliminate the influence of disturbance on the system and improve the disturbance rejection accuracy of the photoelectric tracking system.At present,the processing of mixed inertial measurement signal mainly focuses on the noise elimination of signals.The main method is to extract useful signals through signal filtering.However,the method cannot separate the components of the mixed inertial measurement signal at the same time,and the method needs to rely on the prior knowledge of the signal to build models and set parameters,which has poor adaptability.The Blind Source Separation(BSS)algorithm can recover all the components of the signal at the same time only through the mixed inertial measurement signal when the model of the component signal is unknown and the transmission channel parameters of the component signal are unknown.It is more suitable for processing complex inertial measurement signal with unknown prior knowledge.In this paper,Blind Source Separation method is used to separate target tracking signal,carrier disturbance signal and noise signal from mixed signal simultaneously and separately.In order to solve the problem that the number of inertial measurement signals in photoelectric tracking system is insufficient and the assumption of blind source separation cannot be satisfied,two methods of blind source separation based on over-sampling and local mean decomposition are proposed in this paper.By means of multi-channel reconstruction,single inertial measurement signal is converted into multi-channel signal,and then processed by BSS method.The simulation results show that the two methods can separate the target tracking signal and the carrier disturbance signal in the mixed signal.Build an experimental platform to verify the effectiveness of the method.Target tracking signal and carrier disturbance are added to the platform.Build separation of inertial measurement signals based on over-sampling is used to separate the mixed FOG signals from the platform.The correlation coefficients between the two separated signals and the two added signals are 0.9327 and 0.9976,and the spectral aliasing between separated signals is low,which shows that the separation result is accurate.The experimental results are compared with the results of the wavelet filtering method.The results show that the BSS method of channel reconstruction is effective.Compared with the wavelet filtering method,it has better separation effect.When the precision of inertial sensors used in the system is not highly,the inertial measurement signal of the system consists of three signals: target tracking signal,carrier disturbance signal and noise signal.In order to solve the problem that there is no mature algorithm for simultaneous separation of multi-channel component signals in the mixed inertial measurement signal,this paper presents a method for separation of multi-channel components of inertial measurement signal,which separates the three components of inertial measurement signals separately.In this paper,the effectiveness of this method is verified by synthetic signal simulation and real data simulation.The simulation results of this method are compared with those of EEMD_ICA method and wavelet filtering method.The correlation coefficients obtained by this method are 0.8712?0.9716?0.9994,EEMD_ICA method are 0.7987?0.9379?0.9474,and wavelet filtering method are 0.8133?0.5829?0.7697.The correlation coefficients obtained by this method are higher and the separation results are better.In addition,the feasibility of this method is verified by the simulation of measured data and platform experiments.