Research On Redundancy Technology Of Missile-borne Strapdown Inertial Navigation System

Precision guided munitions can greatly improve the accuracy and efficiency of fire strike,and become one of the important means of strike in the battlefield,and also become the development direction of military weapons and equipment in various countries.The key of precision strike of guided ammunition lies in how to accurately obtain the real-time motion information of missile body.Strapdown inertial navigation system(SINS)is widely used in the field of guidance transformation of conventional artillery ammunition because of its independence,high short-term accuracy and no external interference.At present,for inertial devices,there are two main problems in inertial measurement under missile borne environment: one is that the reliability of inertial devices / components / systems declines sharply under high overload environment;the other is that the reliability of inertial devices /components / systems decreases sharply under high overload environment;Secondly,the range and accuracy of missile borne gyroscope are contradictory under the condition of high-speed rotation.In order to solve the above two problems,this paper designs a Redundant Strapdown Inertial Navigation System with high precision and high reliability based on missile borne environment.Firstly,the paper analyzes the configuration of redundant sensors.In the redundant inertial navigation system,the navigation performance and reliability of the navigation system increase with the number of redundant sensors.However,when there are too many devices,the difficulty of system integration will be greatly increased,and the cost will also be significantly increased.Therefore,this paper defines a performance index related to system reliability to quantitatively describe the relationship between the number of redundant sensors and the reliability of inertial navigation system.Through the analysis and calculation of reliability performance index,the number of sensors which can make the system reliability and economy optimal is obtained.On the basis of determining the number of sensors,through the research on the configuration scheme of redundant sensors,the optimal configuration scheme of redundant sensors is obtained,which can make the navigation performance and fault detection and isolation performance(FPI)of the navigation system reach the optimal at the same time.Theoretical derivation and simulation results show that the dodecahedron configuration of six inertial sensors is the optimal configurationSecondly,the paper studies the data fusion method of redundant sensors.The data obtained by redundant sensors are fused optimally by data fusion algorithm to improve the accuracy of redundant inertial navigation system.The principle is as follows: the output vector of redundant sensor is projected to the left zero space of the configuration matrix to obtain the redundant observation of fusion algorithm.The optimal estimation of redundant observation can maximize the performance of each sensor.In addition,in order to solve the problem of unknown noise characteristic parameters and the measurement noise not satisfying the Gaussian distribution,the filter performance of the standard Kalman filter algorithm is not known,an enhanced adaptive optimal fusion algorithm is proposed.The algorithm introduces the elimination factor into the prediction process of covariance matrix,improves the ability to deal with state mutation,suppresses the divergence of filter over time to a certain extent,and improves the accuracy of the filtering algorithm;By combining adaptive filtering algorithm with Huber generalized maximum likelihood estimation method,the problem of distortion of filter model caused by Non-Gaussian measurement noise is solved.Finally,by simulating the motion state of the projectile in flight,the enhanced adaptive optimal fusion algorithm is simulated and analyzed with the optimal fusion algorithm based on standard Kalman filter and adaptive optimal fusion algorithm.The results show that the enhanced adaptive optimal fusion algorithm can effectively improve the fusion accuracy of redundant sensor output data when the measurement noise of inertial sensor satisfies the non Gaussian distribution.