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
Discuss and develop some contents which are relevant to the IEEE Std 647TM-2006 in this paper. The IEEE Std only involves Allan variance, and decomposes it into five primary noise terms, in which, however, the noise n...Discuss and develop some contents which are relevant to the IEEE Std 647TM-2006 in this paper. The IEEE Std only involves Allan variance, and decomposes it into five primary noise terms, in which, however, the noise nature of the so called "rate random walk noise" and the "rate ramp" is doubted by the IEEE Std editors. Here we use a mathematical identity to entirely affirm the first query and partially the second query as mentioned above. Besides, we argue that only the classical variance can be used in navigation, not the Allan variance. In order to seek the true nature of all drift terms in the variance, we adopt our original work that represents the noises as damped oscillations, to obtain the power spectral density (PSD) of the noises which is then transformed back into time domain. When the damped time constant is much longer than the sampling interval, the re-sulting slow variation term may be expanded into three terms: ordinary bias instability, rate random walk, and rate ramp. Therefore, these "noise terms" are not independent, and they are more of deterministic errors than random noises, and can be explained quantitatively. The resulting fast variation drift may be expanded into two terms. The first term is the same as angle random noise, while the second term adds to the true quantization noise term to form a new combined term called "quantiza-tion noise term". As the result of our research, not only the IEEE Std editors’ suspicions above are answered completely, but a new theory to analyze the laser gyro drifts is also presented, with several supporting examples to explain and verify the theory.展开更多
A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG tempe...A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.展开更多
Gyro＇s drift is not only the main drift error which influences gyro＇s precision but also the primary factor that affects gyro＇s reliability. Reducing zero drift and random drift is a key problem to the output of a ...Gyro＇s drift is not only the main drift error which influences gyro＇s precision but also the primary factor that affects gyro＇s reliability. Reducing zero drift and random drift is a key problem to the output of a gyro signal. A three-layer de-nosing threshold algorithm is proposed based on the wavelet decomposition to dispose the signal which is collected from a running fiber optic gyro （FOG）. The coefficients are obtained from the three-layer wavelet packet decomposition. By setting the high frequency part which is greater than wavelet packet threshold as zero, then reconstructing the nodes which have been filtered out noise and interruption, the soft threshold function is constructed by the coefficients of the third nodes. Compared wavelet packet de-noise with forced de-noising method, the proposed method is more effective. Simulation results show that the random drift compensation is enhanced by 13.1%, and reduces zero drift by 0.052 6°/h.展开更多
Some construct characteristics and composing material of the new Gyro's rotor are introduced. Some factors resulting in deformation of the rotor surface are analyzed. Under different loads such as the force of def...Some construct characteristics and composing material of the new Gyro's rotor are introduced. Some factors resulting in deformation of the rotor surface are analyzed. Under different loads such as the force of deflecting center, the change of temperature, the force of pressure and couple factors, the deformation of rotor is analyzed with the wavelet finite element simulation software. The vector distributing map of rotor reformation is given. The deformation resulting from the pressure force of photon is studied. Finally, the influence on Gyro's performance because of anomalous surface of rotor due to deformation of rotor is researched and the result is useful to forecast the performance of the drift of gyroscope. The disturbing moment resulting from the deformation of rotor can be compensated using the mathematic method, and provides an important reference for both design and optimization of the rotor.展开更多
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.
基金supported by the "Tenth five" Obligatory Budget of PLA (Grant No.9140A09010807KG0191)
文摘Discuss and develop some contents which are relevant to the IEEE Std 647TM-2006 in this paper. The IEEE Std only involves Allan variance, and decomposes it into five primary noise terms, in which, however, the noise nature of the so called "rate random walk noise" and the "rate ramp" is doubted by the IEEE Std editors. Here we use a mathematical identity to entirely affirm the first query and partially the second query as mentioned above. Besides, we argue that only the classical variance can be used in navigation, not the Allan variance. In order to seek the true nature of all drift terms in the variance, we adopt our original work that represents the noises as damped oscillations, to obtain the power spectral density (PSD) of the noises which is then transformed back into time domain. When the damped time constant is much longer than the sampling interval, the re-sulting slow variation term may be expanded into three terms: ordinary bias instability, rate random walk, and rate ramp. Therefore, these "noise terms" are not independent, and they are more of deterministic errors than random noises, and can be explained quantitatively. The resulting fast variation drift may be expanded into two terms. The first term is the same as angle random noise, while the second term adds to the true quantization noise term to form a new combined term called "quantiza-tion noise term". As the result of our research, not only the IEEE Std editors’ suspicions above are answered completely, but a new theory to analyze the laser gyro drifts is also presented, with several supporting examples to explain and verify the theory.
基金supported by the National Natural Science Foundation of China(6110418440904018)+3 种基金the National Key Scientific Instrument and Equipment Development Project(2011YQ12004502)the Research Foundation of General Armament Department(201300000008)the Doctor Innovation Fund of Naval University of Engineering(HGBSCXJJ2011008)the Youth Natural Science Foundation of Naval University of Engineering(HGDQNJJ12028)
文摘A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.
文摘Gyro＇s drift is not only the main drift error which influences gyro＇s precision but also the primary factor that affects gyro＇s reliability. Reducing zero drift and random drift is a key problem to the output of a gyro signal. A three-layer de-nosing threshold algorithm is proposed based on the wavelet decomposition to dispose the signal which is collected from a running fiber optic gyro （FOG）. The coefficients are obtained from the three-layer wavelet packet decomposition. By setting the high frequency part which is greater than wavelet packet threshold as zero, then reconstructing the nodes which have been filtered out noise and interruption, the soft threshold function is constructed by the coefficients of the third nodes. Compared wavelet packet de-noise with forced de-noising method, the proposed method is more effective. Simulation results show that the random drift compensation is enhanced by 13.1%, and reduces zero drift by 0.052 6°/h.
文摘Some construct characteristics and composing material of the new Gyro's rotor are introduced. Some factors resulting in deformation of the rotor surface are analyzed. Under different loads such as the force of deflecting center, the change of temperature, the force of pressure and couple factors, the deformation of rotor is analyzed with the wavelet finite element simulation software. The vector distributing map of rotor reformation is given. The deformation resulting from the pressure force of photon is studied. Finally, the influence on Gyro's performance because of anomalous surface of rotor due to deformation of rotor is researched and the result is useful to forecast the performance of the drift of gyroscope. The disturbing moment resulting from the deformation of rotor can be compensated using the mathematic method, and provides an important reference for both design and optimization of the rotor.
