In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system (SINS) is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing t...In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system (SINS) is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS' s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.展开更多
Initial alignment is the precondition for strapdown inertial navigation system(SINS)to navigate.Its two important indexes are accuracy and rapidity,the accuracy of the initial alignment is directly related to the work...Initial alignment is the precondition for strapdown inertial navigation system(SINS)to navigate.Its two important indexes are accuracy and rapidity,the accuracy of the initial alignment is directly related to the working accuracy of SINS,but in self-alignment,the two indexes are often contradictory.In view of the limitations of conventional data processing algorithms,a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed.By means of data storage,the same data is used in different stages of the initial alignment,which is beneficial to shorten the initial alignment time and improve the alignment accuracy.In order to verify the correctness of the compass algorithm based on stored data and repeated navigation calculation,the simulation experiment was done.In summary,when the computer performance is sufficiently high,the compass alignment method based on the stored data and the forward and reverse navigation calculation can effectively improve the alignment speed and improve the alignment accuracy.展开更多
This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system (SIAHRS) , which, by means of a Kalman filter, integrates...This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system (SIAHRS) , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit (IMU) , called damping attitudes, with those from the conventional IMU. As vehicle' s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle' s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.展开更多
Traditional strapdown inertial navigation system (SINS) algorithm studies are based on ideal measurements from gy- ros and accelerometers, while in the actual strapdown inertial measurement unit (SIMU), time-async...Traditional strapdown inertial navigation system (SINS) algorithm studies are based on ideal measurements from gy- ros and accelerometers, while in the actual strapdown inertial measurement unit (SIMU), time-asynchrony between each iner- tial sensor is inevitable. Testing principles and methods for time- asynchrony parameter identification are studied. Under the single- axis swaying environment, the relationships between the SINS platform drift rate and the gyro time-asynchrony are derived using the SINS attitude error equation. It is found that the gyro time- asynchrony error can be considered as a kind of pseudo-coning motion error caused by data processing. After gyro testing and synchronization, the single-axis tumble test method is introduced for the testing of each accelerometer time-asynchrony with respect to the ideal gyro triad. Accelerometer time-asynchrony parame- ter identification models are established using SINS specific force equation. Finally, all of the relative time-asynchrony parameters between inertial sensors are well identified by using fiber optic gyro SIMU as experimental verification.展开更多
The performance of a strapdown inertial navigation system(SINS)largely depends on the accuracy and rapidness of the initial alignment.A novel anti-interference self-alignment algorithm by attitude optimization estimat...The performance of a strapdown inertial navigation system(SINS)largely depends on the accuracy and rapidness of the initial alignment.A novel anti-interference self-alignment algorithm by attitude optimization estimation for SINS on a rocking base is presented in this paper.The algorithm transforms the initial alignment into the initial attitude determination problem by using infinite vector observations to remove the angular motions,the SINS alignment is heuristically established as an optimiza-tion problem of finding the minimum eigenvector.In order to further improve the alignment precision,an adaptive recursive weighted least squares(ARWLS)curve fitting algorithm is used to fit the translational motion interference-contaminated reference vectors according to their time domain characteristics.Simulation studies and experimental results favorably demonstrate its rapidness,accuracy and robustness.展开更多
A new nonlinear algorithm is proposed for strapdown inertial navigation system (SINS)/celestial navigation system (CNS)/global positioning system (GPS) integrated navigation systems. The algorithm employs a nonl...A new nonlinear algorithm is proposed for strapdown inertial navigation system (SINS)/celestial navigation system (CNS)/global positioning system (GPS) integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter (UKF) to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle's attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.展开更多
A method of improving the navigation accuracy of strapdown inertial navigation system (SINS) is studied. The particular technique discussed involves the continuous rotation of gyros and accelerometers cluster about th...A method of improving the navigation accuracy of strapdown inertial navigation system (SINS) is studied. The particular technique discussed involves the continuous rotation of gyros and accelerometers cluster about the vertical axis of the vehicle. Then the errors of these sensors will have periodic variation corresponding to components along the body frame. Under this condition, the modulated sensor errors produce reduced system errors. Theoretical analysis based on a new coordinate system defined as sensing frame and test results are presented, and they indicate the method attenuates the navigation errors brought by the gyros' random constant drift and the accelerometer's bias and their white noise compared to the conventional method.展开更多
Transfer alignment is an effective alignment method for the strapdown inertial navigation system (SINS) of airborne weapon systems. The traditional transfer alignment methods for large misalignment angles alignment ...Transfer alignment is an effective alignment method for the strapdown inertial navigation system (SINS) of airborne weapon systems. The traditional transfer alignment methods for large misalignment angles alignment use nonlinear transfer align- ment models and incorporate nonlinear filtering. A rapid transfer alignment method with linear models and linear filtering for ar- bitrary misalignment angles is presented. Through the attitude quaternion decomposition, the purpose of transfer alignment is converted to estimate a constant quaternion. Employing special manipulations on measurement equation, velocity and attitude linear measurement equations are derived. Then the linear trans- fer alignment model for arbitrary misalignment angles is built. An adaptive Kalman filter is developed to handle modeling errors of the measurement noise statistics. Simulation results show feasibili- ty and effectiveness of the proposed method, which provides an alternative rapid transfer alignment method for airborne weapons.展开更多
An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method ac...An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method achieves the alignment by virtue of a cascade of low-pass FIR filters, which attenuate the disturbing acceleration and maintain the gravity vector. The aligning time rests with the orders of the FIR filter group, and the method is suitable for large initial misalignment case. An alignment scheme comprising a coarse phase by the IFBA method and a fine phase by a Kalman filter is presented. Both vehicle-based and ship-based alignment experiments were carried out. The results show that the proposed scheme converges much faster than the traditional method at no cost of precision and also works well under any large initial misalignment.展开更多
In order to improve the survival ability and rapid response ability of the carrier craft,a new rapid transfer alignment method of the strapdown inertial navigation system(SINS) on a rocking base is put forward.In th...In order to improve the survival ability and rapid response ability of the carrier craft,a new rapid transfer alignment method of the strapdown inertial navigation system(SINS) on a rocking base is put forward.In the method,the aircraft carrier does not need any form of movement.Meantime,interfering motions such as rolling,pitching,and yawing motions caused by sea waves are effectively used.Firstly,the deck flexure deformation model is made.Secondly,the state space model of transfer alignment is presented.Finally,the feasibility of this method is validated by the simulation.Simulation results show that the misalignment angle error can be estimated and reach an anticipated precision-0.2 mrad in 5 s,while the deck deformation angle error can be estimated and reach a better precision- 0.1 mrad in 20 s.展开更多
A new two-iteration sculling compensation mathematical framework is provided for modern-day strapdown inertial navigation system(SINS) algorithm design that utilizes a new concept in velocity updating. The principal...A new two-iteration sculling compensation mathematical framework is provided for modern-day strapdown inertial navigation system(SINS) algorithm design that utilizes a new concept in velocity updating. The principal structure of this framework includes twice sculling compensation procedure using incremental outputs from the inertial system sensors during the velocity updating interval. Then, the moderate algorithm is designed to update the velocity parameter. The analysis is conducted in the condition of sculling motion which indicates that the new mathematical framework error which is smaller than the conventional ones by at least two orders is far superior. Therefore, a summary is given for SINS software which can be designed with the new mathematical framework in velocity updating.展开更多
Traditional orthogonal strapdown inertial navigation sys-tem (SINS) cannot achieve satisfactory self-alignment accuracy in the stationary base: taking more than 5 minutes and al the iner-tial sensors biases cannot ...Traditional orthogonal strapdown inertial navigation sys-tem (SINS) cannot achieve satisfactory self-alignment accuracy in the stationary base: taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS (RSINS) can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method: any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS (sub-SINS);the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated: the horizontal attitudes (pitch, rol ) errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.展开更多
Strapdown inertial navigation system(SINS) requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally us...Strapdown inertial navigation system(SINS) requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally used to estimate the initial attitude angles.This is possible because an accurate determination of the inertial measurement unit(IMU) motion is available based on the measurement obtained from global position system(GPS).But the update frequency of GPS is much lower than SINS.Due to the non-synchronous data streams from GPS and SINS,the initial attitude angles may not be computed accurately enough.In addition,the estimated initial attitude angles may have relatively large uncertainties that can affect the accuracy of other navigation parameters.This paper presents an effective approach of matching the velocities which are provided by GPS and SINS.In this approach,a digital high-pass filter,which implements a pre-filtering scheme of the measured signal,is used to filter the Schuler cycle of discrete velocity difference between the SINS and GPS.Simulation results show that this approach improves the accuracy greatly and makes the convergence time satisfy the required accuracy.展开更多
Fiber strapdown inertial navigation system (FSINS) is presently used in several applications related to marine navigation. However, the absolute position from FSINS contains the error that increases with time, which...Fiber strapdown inertial navigation system (FSINS) is presently used in several applications related to marine navigation. However, the absolute position from FSINS contains the error that increases with time, which prevents its long-term use for the ship cruise. In order to improve the performance of FSINS based on our present inertial sensors, the spin technology was proposed in the system to mitigate the navigation errors and a prototype of the proposed system was developed in Navigation Lab. The prototype contains the IMU, temperature controller, rotating configuration, navigation and I/O electronics group, control and display, power supply subsystem and other modules. In the proposed spin technology, the IMU is rotated back and forth in azimuth through four orthogonal positions relative to the ship’s longitudinal axis. Experimental testing was conducted for the prototype in the laboratory and the results showed that the RFSINS’s navigation performance is improved 10 times.展开更多
This paper proposes a technique that global positioning system(GPS)combines inertial navigation system(INS)by using unscented particle filter(UPF)to estimate the exact outdoor position.This system can make up for the ...This paper proposes a technique that global positioning system(GPS)combines inertial navigation system(INS)by using unscented particle filter(UPF)to estimate the exact outdoor position.This system can make up for the weak point on position estimation by the merits of GPS and INS.In general,extended Kalman filter(EKF)has been widely used in order to combine GPS with INS.However,UPF can get the position more accurately and correctly than EKF when it is applied to real-system included non-linear,irregular distribution errors.In this paper,the accuracy of UPF is proved through the simulation experiment,using the virtual-data needed for the test.展开更多
The state estimation strategy using the smooth variable structure filter (SVSF) is based on the variable structure and sliding mode concepts. As presented in its standard form with a fixed boundary layer limit, the ...The state estimation strategy using the smooth variable structure filter (SVSF) is based on the variable structure and sliding mode concepts. As presented in its standard form with a fixed boundary layer limit, the value of the boundary layer width is not precisely known at each step and may be selected based on a priori knowledge. The boundary layer width reflects the level of uncertainty in the model parameters and disturbance characteristics, where large values of the boundary layer width lead to robustness without optimality and small values of the boundary layer width provide optimality with poor robustness. As a solution and to overcome these limitations, an adaptive smoothing boundary layer is required to achieve greater robustness and suitable accuracy. This adapted value of the boundary layer width is obtained by minimizing the trace of the a posteriori covariance matrix. In this paper, the proposed new approach will be considered as another alternative to the extended Kalman filters (EKF), nonlinear H∞ and standard SVSF-based data fusion techniques for the autonomous airborne navigation and self-localization problem. This alternative is based on strapdown inertial navigation system (SINS) and GPS data using the nonlinear SVSF with a covariance derivation and adaptive boundary layer width. Furthermore, the full mathematical model of the SINS/GPS navigation system considering the unmanned aerial vehicle (UAV) position, velocity and Euler angle as well as gyro and accelerometer biases will be used in this paper to estimate the airborne position and velocity with better accuracy.展开更多
文摘In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system (SINS) is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS' s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.
基金This work was supported by the National Nature Science Foundation of China(Grant No.5200110367)Natural Science Foundation of Jiangsu Province(Grant No.SBK2020043219)+1 种基金Scientific Research Foundation of the Higher Education Institutions of Jiangsu Province(Grant No.19KJB510052)NUPTSF(Grant No.NY219023).
文摘Initial alignment is the precondition for strapdown inertial navigation system(SINS)to navigate.Its two important indexes are accuracy and rapidity,the accuracy of the initial alignment is directly related to the working accuracy of SINS,but in self-alignment,the two indexes are often contradictory.In view of the limitations of conventional data processing algorithms,a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed.By means of data storage,the same data is used in different stages of the initial alignment,which is beneficial to shorten the initial alignment time and improve the alignment accuracy.In order to verify the correctness of the compass algorithm based on stored data and repeated navigation calculation,the simulation experiment was done.In summary,when the computer performance is sufficiently high,the compass alignment method based on the stored data and the forward and reverse navigation calculation can effectively improve the alignment speed and improve the alignment accuracy.
基金Aeronautical Science Foundation of China(20080852011,20070852009)
文摘This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system (SIAHRS) , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit (IMU) , called damping attitudes, with those from the conventional IMU. As vehicle' s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle' s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.
基金supported by the National Natural Science Foundation of China(61273333)
文摘Traditional strapdown inertial navigation system (SINS) algorithm studies are based on ideal measurements from gy- ros and accelerometers, while in the actual strapdown inertial measurement unit (SIMU), time-asynchrony between each iner- tial sensor is inevitable. Testing principles and methods for time- asynchrony parameter identification are studied. Under the single- axis swaying environment, the relationships between the SINS platform drift rate and the gyro time-asynchrony are derived using the SINS attitude error equation. It is found that the gyro time- asynchrony error can be considered as a kind of pseudo-coning motion error caused by data processing. After gyro testing and synchronization, the single-axis tumble test method is introduced for the testing of each accelerometer time-asynchrony with respect to the ideal gyro triad. Accelerometer time-asynchrony parame- ter identification models are established using SINS specific force equation. Finally, all of the relative time-asynchrony parameters between inertial sensors are well identified by using fiber optic gyro SIMU as experimental verification.
基金supported by the National Natural Science Foundation of China(41174162).
文摘The performance of a strapdown inertial navigation system(SINS)largely depends on the accuracy and rapidness of the initial alignment.A novel anti-interference self-alignment algorithm by attitude optimization estimation for SINS on a rocking base is presented in this paper.The algorithm transforms the initial alignment into the initial attitude determination problem by using infinite vector observations to remove the angular motions,the SINS alignment is heuristically established as an optimiza-tion problem of finding the minimum eigenvector.In order to further improve the alignment precision,an adaptive recursive weighted least squares(ARWLS)curve fitting algorithm is used to fit the translational motion interference-contaminated reference vectors according to their time domain characteristics.Simulation studies and experimental results favorably demonstrate its rapidness,accuracy and robustness.
基金supported by the National Natural Science Foundation of China (60535010)
文摘A new nonlinear algorithm is proposed for strapdown inertial navigation system (SINS)/celestial navigation system (CNS)/global positioning system (GPS) integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter (UKF) to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle's attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.
文摘A method of improving the navigation accuracy of strapdown inertial navigation system (SINS) is studied. The particular technique discussed involves the continuous rotation of gyros and accelerometers cluster about the vertical axis of the vehicle. Then the errors of these sensors will have periodic variation corresponding to components along the body frame. Under this condition, the modulated sensor errors produce reduced system errors. Theoretical analysis based on a new coordinate system defined as sensing frame and test results are presented, and they indicate the method attenuates the navigation errors brought by the gyros' random constant drift and the accelerometer's bias and their white noise compared to the conventional method.
基金supported by the National Natural Science Foundation of China(61233005)
文摘Transfer alignment is an effective alignment method for the strapdown inertial navigation system (SINS) of airborne weapon systems. The traditional transfer alignment methods for large misalignment angles alignment use nonlinear transfer align- ment models and incorporate nonlinear filtering. A rapid transfer alignment method with linear models and linear filtering for ar- bitrary misalignment angles is presented. Through the attitude quaternion decomposition, the purpose of transfer alignment is converted to estimate a constant quaternion. Employing special manipulations on measurement equation, velocity and attitude linear measurement equations are derived. Then the linear trans- fer alignment model for arbitrary misalignment angles is built. An adaptive Kalman filter is developed to handle modeling errors of the measurement noise statistics. Simulation results show feasibili- ty and effectiveness of the proposed method, which provides an alternative rapid transfer alignment method for airborne weapons.
基金the National Natural Science Foundation of China (60604011)
文摘An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method achieves the alignment by virtue of a cascade of low-pass FIR filters, which attenuate the disturbing acceleration and maintain the gravity vector. The aligning time rests with the orders of the FIR filter group, and the method is suitable for large initial misalignment case. An alignment scheme comprising a coarse phase by the IFBA method and a fine phase by a Kalman filter is presented. Both vehicle-based and ship-based alignment experiments were carried out. The results show that the proposed scheme converges much faster than the traditional method at no cost of precision and also works well under any large initial misalignment.
基金supported by the Photoelectric Control Technology Project of National Defense Science and Technology Key Laboratory of China(20120224006)
文摘In order to improve the survival ability and rapid response ability of the carrier craft,a new rapid transfer alignment method of the strapdown inertial navigation system(SINS) on a rocking base is put forward.In the method,the aircraft carrier does not need any form of movement.Meantime,interfering motions such as rolling,pitching,and yawing motions caused by sea waves are effectively used.Firstly,the deck flexure deformation model is made.Secondly,the state space model of transfer alignment is presented.Finally,the feasibility of this method is validated by the simulation.Simulation results show that the misalignment angle error can be estimated and reach an anticipated precision-0.2 mrad in 5 s,while the deck deformation angle error can be estimated and reach a better precision- 0.1 mrad in 20 s.
基金supported by the National Natural Science Foundation of China(90816027)the Aviation Science Funds(20135853037)+1 种基金the Foundation of China Aerospace Science & Industry Corporation(2013HTXGD2014HTXGD)
文摘A new two-iteration sculling compensation mathematical framework is provided for modern-day strapdown inertial navigation system(SINS) algorithm design that utilizes a new concept in velocity updating. The principal structure of this framework includes twice sculling compensation procedure using incremental outputs from the inertial system sensors during the velocity updating interval. Then, the moderate algorithm is designed to update the velocity parameter. The analysis is conducted in the condition of sculling motion which indicates that the new mathematical framework error which is smaller than the conventional ones by at least two orders is far superior. Therefore, a summary is given for SINS software which can be designed with the new mathematical framework in velocity updating.
基金supported by the National Defense PreResearch Foundation of China(51309030102)
文摘Traditional orthogonal strapdown inertial navigation sys-tem (SINS) cannot achieve satisfactory self-alignment accuracy in the stationary base: taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS (RSINS) can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method: any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS (sub-SINS);the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated: the horizontal attitudes (pitch, rol ) errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.
基金supported by the National Natural Science Foundation of China (6083400560775001)
文摘Strapdown inertial navigation system(SINS) requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally used to estimate the initial attitude angles.This is possible because an accurate determination of the inertial measurement unit(IMU) motion is available based on the measurement obtained from global position system(GPS).But the update frequency of GPS is much lower than SINS.Due to the non-synchronous data streams from GPS and SINS,the initial attitude angles may not be computed accurately enough.In addition,the estimated initial attitude angles may have relatively large uncertainties that can affect the accuracy of other navigation parameters.This paper presents an effective approach of matching the velocities which are provided by GPS and SINS.In this approach,a digital high-pass filter,which implements a pre-filtering scheme of the measured signal,is used to filter the Schuler cycle of discrete velocity difference between the SINS and GPS.Simulation results show that this approach improves the accuracy greatly and makes the convergence time satisfy the required accuracy.
基金supported by the National Natural Science Foundation of China(Grant Nos.60834005,60775001 and 41304032)China Postdoctoral Science Special Foundation(Grant No.2013T60298)+3 种基金the China Postdoctoral Science Foundation(Grant No.2012M510830)the Research Project from Liaoning Education Department(Grant No.L2011047)the Startup Foundation for Doctors from Liaoning Science and Technology Department(Grant No.20121084)the Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing(Grant No.12P01)
文摘Fiber strapdown inertial navigation system (FSINS) is presently used in several applications related to marine navigation. However, the absolute position from FSINS contains the error that increases with time, which prevents its long-term use for the ship cruise. In order to improve the performance of FSINS based on our present inertial sensors, the spin technology was proposed in the system to mitigate the navigation errors and a prototype of the proposed system was developed in Navigation Lab. The prototype contains the IMU, temperature controller, rotating configuration, navigation and I/O electronics group, control and display, power supply subsystem and other modules. In the proposed spin technology, the IMU is rotated back and forth in azimuth through four orthogonal positions relative to the ship’s longitudinal axis. Experimental testing was conducted for the prototype in the laboratory and the results showed that the RFSINS’s navigation performance is improved 10 times.
基金The MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2012-H0301-12-2006)
文摘This paper proposes a technique that global positioning system(GPS)combines inertial navigation system(INS)by using unscented particle filter(UPF)to estimate the exact outdoor position.This system can make up for the weak point on position estimation by the merits of GPS and INS.In general,extended Kalman filter(EKF)has been widely used in order to combine GPS with INS.However,UPF can get the position more accurately and correctly than EKF when it is applied to real-system included non-linear,irregular distribution errors.In this paper,the accuracy of UPF is proved through the simulation experiment,using the virtual-data needed for the test.
基金supported by the National Natural Science Foundation of China(No.61375082)
文摘The state estimation strategy using the smooth variable structure filter (SVSF) is based on the variable structure and sliding mode concepts. As presented in its standard form with a fixed boundary layer limit, the value of the boundary layer width is not precisely known at each step and may be selected based on a priori knowledge. The boundary layer width reflects the level of uncertainty in the model parameters and disturbance characteristics, where large values of the boundary layer width lead to robustness without optimality and small values of the boundary layer width provide optimality with poor robustness. As a solution and to overcome these limitations, an adaptive smoothing boundary layer is required to achieve greater robustness and suitable accuracy. This adapted value of the boundary layer width is obtained by minimizing the trace of the a posteriori covariance matrix. In this paper, the proposed new approach will be considered as another alternative to the extended Kalman filters (EKF), nonlinear H∞ and standard SVSF-based data fusion techniques for the autonomous airborne navigation and self-localization problem. This alternative is based on strapdown inertial navigation system (SINS) and GPS data using the nonlinear SVSF with a covariance derivation and adaptive boundary layer width. Furthermore, the full mathematical model of the SINS/GPS navigation system considering the unmanned aerial vehicle (UAV) position, velocity and Euler angle as well as gyro and accelerometer biases will be used in this paper to estimate the airborne position and velocity with better accuracy.