The identification of the coefficients in the drift error model of a floated gyro inertial navigation platform was investigated by following the principle of the inertial navigation platform and using gyro and acceler...The identification of the coefficients in the drift error model of a floated gyro inertial navigation platform was investigated by following the principle of the inertial navigation platform and using gyro and accelerometer output models, and a complete platform drift error model was established, with parameters as state variables, thereby establishing the system state equation and observation equation. Since these two equations are both nonlinear, the Extended Kalman Filter (EKF) was adopted. Then the problem of parameter identification was converted into a problem of state estimation. During the simulation, multi position testing schemes were designed to motivated the parameters by gravity acceleration. Using these schemes, twenty four error coefficients of three gyros and six error coefficients of three accelerometers were identified, which showed the feasibility of this method.展开更多
Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The ...Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The grid optimization method is always used to find proper initial matrix for off-line estimation.However,the grid method has the draw back being time consuming hence,coarse grid followed by a fine grid method is adopted.To further improve efficiency without the loss of estimation accuracy,we propose a genetic algorithm for the coarse grid optimization in this paper.It is recognized that the crossover rate and mutation rate are the main influencing factors for the performance of the genetic algorithm,so sensitivity experiments for these two factors are carried out and a set of genetic algorithm parameters with good adaptability were selected by testing with several gyros’experimental data.Experimental results show that the proposed algorithm has higher efficiency and better estimation accuracy than the traversing grid algorithm.展开更多
文摘The identification of the coefficients in the drift error model of a floated gyro inertial navigation platform was investigated by following the principle of the inertial navigation platform and using gyro and accelerometer output models, and a complete platform drift error model was established, with parameters as state variables, thereby establishing the system state equation and observation equation. Since these two equations are both nonlinear, the Extended Kalman Filter (EKF) was adopted. Then the problem of parameter identification was converted into a problem of state estimation. During the simulation, multi position testing schemes were designed to motivated the parameters by gravity acceleration. Using these schemes, twenty four error coefficients of three gyros and six error coefficients of three accelerometers were identified, which showed the feasibility of this method.
文摘Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The grid optimization method is always used to find proper initial matrix for off-line estimation.However,the grid method has the draw back being time consuming hence,coarse grid followed by a fine grid method is adopted.To further improve efficiency without the loss of estimation accuracy,we propose a genetic algorithm for the coarse grid optimization in this paper.It is recognized that the crossover rate and mutation rate are the main influencing factors for the performance of the genetic algorithm,so sensitivity experiments for these two factors are carried out and a set of genetic algorithm parameters with good adaptability were selected by testing with several gyros’experimental data.Experimental results show that the proposed algorithm has higher efficiency and better estimation accuracy than the traversing grid algorithm.
