Research On Filtering And Estimating Systematic Errors For SINS/CNS/SAR Integrated Vehicle Navigation System

As science and technology is developed rapidly,especially the performance of the navigation positioning and development cycle are demanded higher and higher for modern wars.Integrated navigation system can combine the advantages of various navigation systems and improve the precision of navigation information to meet the requirements of the users on the navigation system performance.So the navigation technology combined and integrated is an inevitable trend.SINS/CNS/SAR integrated navigation system has the advantages of SINS,CNS and SAR,not only has better reliability,but also has better independence and higher positioning accuracy.It satisfies the requirements of navigation of the air vehicle.It's a kind of independently integrated navigation system that is widely used and promising.In this thesis,we make a research about the SINS/CNS/SAR integrated navigation technology and the estimation method of this system error.The following are the main work and innovative contributions of this thesis:(1)The principle of SINS/CNS/SAR integrated navigation system is studied and the mathematical model of this system is set up.A kind of filtering method that is suitable for this integrated navigation system is designed.The information fusion algorithm of SINS/CNS/SAR integrated navigation system is presented and this system has been studied on computer simulation.The results show that this integrated navigation system has higher positional accuracy,it can satisfy the requirements of most air vehicle.(2)To solve the problems of SAR data output delay in the SINS/SAR integrated navigation system,the kalman algorithm based on multi-model prediction and the interpolation prediction algorithm are studied.Those algorithms are applied on the SINS/SAR integrated navigation in computer simulation.This proves the algorithms are useful.Then,the CNS navigation positioning algorithm in SINS/CNS integrated navigation system is studied.The error of CNS is analyzed.Attitude error compensation method for inertial navigation system and celestial navigation position algorithm are studied.The results of the test of SINS/CNS system indicate that the accuracy of attitude determination of SINS/CNS integrated navigation system is much higher,and this system can improve the heading precision.(3)An algorithm with random weighting is proposed for SINS/CNS/SAR integrated navigation error estimation and filtering calculation.This algorithm is used for estimating state prediction vector and covariance matrix of system.This can control the influence of state parameter estimation of dynamical system model error and improve filtering calculation accuracy of navigation system.The simulation results show that the proposed algorithm can improve the filtering accuracy and calculation speed of dynamic navigation.(4)A random weighting estimation method of dynamic navigation system state noise is provided.This method can weight for state noise vector and covariance matrix according to actual requirement.It can adjust factors at any moment and control the influence of state estimation caused by noise abnormity.The simulation results indicate that this method can improve filtering accuracy of dynamic calculation.(5)Estimation algorithm with emerging random weighting to estimate integrated navigation system error in the observation model is proposed.This proves that the random weighting observation system error estimate is unbiased.The random weighting for the covariance matrix of observation error vector is used to reduce the influence of observation model noise on state parameter value and to enhance the filtering calculating precision of the dynamic navigation.Then we make a simulation for this algorithm on computer.In this thesis,the research results can make contributions to the design of vehicle integrated navigation system in the aerospace field,error estimation of dynamic system model,filtering calculating of integrated navigation and information fusion of dynamics system.If the results are extended,they can also be used on the design of vehicle integrated navigation system,error estimation of dynamic system model and filtering calculating of other fields.