Research On Particle Filtering Technique And Its Application In Strapdown Inertial Navigation System With Fiber Optic Gyro

Particle filtering is a key technique in nonlinear filtering. It can be applied to state estimation for any nonlinear system and effectively solve the nonlinear filtering problem in fiber optic strap-down inertial navigation system. Based on the property of fiber optic strap-down inertial navigation system, this paper makes an in-depth research on the basic theory of particle filter and its application to inertial instrument error compensation, to fast initial alignment of inertial navigation system and to inertial / satellite integrated navigation system. The advantages of particle filter are brought into full play to address the non-linear filtering problem in fiber optic strap-down inertial navigation system, to improve the system precision and thus lay the foundation for the enhancement of accurate targeting and attacking of weapons and equipments.Firstly, based on the basic theory of particle filtering, a thorough study is made on the problem of particle degeneracy. The improved particle filtering algorithm is investigated from two aspects: the selection of better importance density and the increase of particle diversity. Started from the point of finding a better importance density, combined with MCMC transfer method, this research first designs the importance density grounded on 2-Order interpolation filters. And then brings forward an improved particle filtering algorithm based on 2-Order interpolation filtering. In terms of particle efficiency and particle diversity, the research first analyzes the characteristics of different approximation methods, studies particle filtering algorithm based on grid, then introduces stratified approximation to solve the problem of even grid approxiamtion, and finally proposes an improved particle filter algorithm using stratified approximation.In order to improve the applied precision of FOG, this paper has studied noise removal performance of particle filtering in fiber optic gyro ARIMA. Based on FOG ARIMA modeling method, the research combines ARIMA model identification with FOG state estimation, constructs a nonlinear filtering FOG ARIMA model and puts forward a FOG ARIMA model identification method based on particle filtering. Data collected from FOG in both static and dynamic states experiments indicates that the proposed method can estimate ARIMA model parameters in response to the outputs of FOG, improve the accuracy of FOG state estimation and reduce signal noise of FOG in different motion states.In view of initial alignment speed and accuracy for fiber optic SINS, this study initiates two fast initial alignment methods based on particle filter. On the basis of large misalignment angle alignment in nonlinear filtering model, this research introduces the measurement information from the equivalent of east gyro and comes up with a fast initial alignment algorithm based on marginalized particle filter. In addition, after a thorough analysis on conventional two-position initial alignment method is made, the nonlinear attitude angle calculation and filter modeling is carefully deduced. Finally, a two-position fast initial alignment algorithm for particle filter feasible to fiber optic strap-down inertial navigation system is proposed. The new approach can effectively improve the accuracy and speed of initial alignment in fiber optic strap-down inertial navigation system, and thus is of great engineering application value.At last, considering the nonlinear characteristics of fiber optic strap-down inertial / GPS integrated navigation system, this research effectively combines particle filtering with other nonlinear filtering method to make the best use of the traits and advantages of all the filtering methods. A fiber optic strap-down inertial / GPS loose integrated navigation scheme based on particle filter is brought forward. With the precision of integrated navigation assured, this scheme can effectively reduce the computational workload of particle filter, and thus improve the real time performance of particle filter used in fiber optic strap-down inertial / GPS integrated navigation system.Closely linked to engineering applications, this dissertation has carried out a thorough and systematic research on particle filtering technique and its applications to fiber optic strap-down inertial navigation system. Achievements of the study will be valuable reference to the engineering application and promotion of nonlinear particle filter technique.