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
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
Roll-isolation is an effective way for spinning vehicle to greatly reduce the roll gyro range of strapdown Inertial Navigation System(SINS)and increase the accuracy of inertial navigation.However,during a recent fligh...Roll-isolation is an effective way for spinning vehicle to greatly reduce the roll gyro range of strapdown Inertial Navigation System(SINS)and increase the accuracy of inertial navigation.However,during a recent flight test,the roll-isolated control system failure was observed under a large pitch angle(706 h 685),which introduces a sharply increase in the roll angular velocity,the saturation of roll gyro and the inertial navigation failure.To address this issue,the governing equation of the roll-isolated system is derived with the consideration of various disturbance factors.The control failure is reproduced by numerical simulation.And the results show that the pitch and yaw angular velocity can cause a dramatic increase in roll rate under the large pitch angle,resulting in the roll-isolated control failure.Meanwhile,an improved roll-isolated control system is developed using PI controller,which is verified by mathematical simulation.展开更多
A new adaptive federal Kalman filter for a strapdown integrated navigation system/global positioning system (SINS/GPS) is given. The developed federal Kalman filter is based on the trace operation of parameters estima...A new adaptive federal Kalman filter for a strapdown integrated navigation system/global positioning system (SINS/GPS) is given. The developed federal Kalman filter is based on the trace operation of parameters estimation's error covariance matrix and the spectral radius of update measurement noise variance-covariance matrix for the proper choice of the filter weight and hence the filter gain factors. Theoretical analysis and results from simulation in which the SINS/GPS was compared to conventional Kalman filter are presented. Results show that the algorithm of this adaptive federal Kalman filter is simpler than that of the conventional one. Furthermore, it outperforms the conventional Kalman filter when the system is undertaken measurement malfunctions because of its possession of adaptive ability. This filter can be used in the vehicle integrated navigation system.展开更多
With the development of rail transit,subway is playing an increasingly important role in peoples daily life.The positioning technology of subway is the key of communication based on train control system(CBTC).Consider...With the development of rail transit,subway is playing an increasingly important role in peoples daily life.The positioning technology of subway is the key of communication based on train control system(CBTC).Considering that the global positioning system(GPS)cant be utilized in the subway and the ground equipment is complex and expensive,a self-positioning method based on inertial measurement unit(IMU)and speed sensor is put forward,and the track electronic map is used to reduce the error.This method can suppress the error divergence of Strapdown inertial navigation system(SINS)and reduce the cumulative error of dead reckoning(DR)due to attitude error.In accordance with the particularity of railway lines,using the least squares method to match the line and revise the error caused by the navigation,can greatly improve the positioning accuracy and reduce the dependency on the ground equipment,and the costs of construction and maintenance can be lowered.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
Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small...Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small areas.This paper considers the problem of vision-aided inertial navigation(VIN)for aircrafts equipped with a strapdown inertial navigation system(SINS)and a downward-viewing camera.This is different from the traditional VIO problems in a larger working area with more precise inertial sensors.The goal is to utilize visual information to aid SINS to improve the navigation performance.In the multistate constraint Kalman filter(MSCKF)framework,we introduce an anchor frame to construct necessary models and derive corresponding Jacobians to implement a VIN filter to directly update the position in the Earth-centered Earth-fixed(ECEF)frame and the velocity and attitude in the local level frame by feature measurements.Due to its filtering-based property,the proposed method is naturally low computational demanding and is suitable for applications with high real-time requirements.Simulation and real-world data experiments demonstrate that the proposed method can considerably improve the navigation performance relative to the SINS.展开更多
The traditional train positioning methods suffer from inadequate accuracy and high maintenance costs,rendering them unsuitable for the development requirements of lightweight and intelligent train positioning technolo...The traditional train positioning methods suffer from inadequate accuracy and high maintenance costs,rendering them unsuitable for the development requirements of lightweight and intelligent train positioning technology.To address these restraints,the BeiDou navigation satellite system/strapdown inertial navigation system(BDS/SINS)integrated train positioning system based on an adaptive unscented Kalman filter(AUKF)is proposed.Firstly,the combined denoising algorithm(CDA)and Lagrange interpolation algorithm are introduced to preprocess the original data,effectively eliminating the influence of noise signals and abnormal measurements on the train positioning system.Secondly,the innovation theory is incorporated into the unscented Kalman filter(UKF)to derive the AUKF,which accomplishes an adaptive update of the measurement noise covariance.Finally,the positioning performance of the proposed AUKF is contrasted with that of conventional algorithms in various operation scenes.Simulation results demonstrate that the average value of error calculated by AUKF is less than 1.5 m,and the success rate of positioning touches 95.0%.Compared to Kalman filter(KF)and UKF,AUKF exhibits superior accuracy and stability in train positioning.Consequently,the proposed AUKF is well-suited for providing precise positioning services in variable operating environments for trains.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
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
A tightly coupled GPS （ global positioning system ）/SINS （ strap down inertial navigation system） based on a GMDH （ group method of data handling） neural network was presented to solve the problem of degraded ac...A tightly coupled GPS （ global positioning system ）/SINS （ strap down inertial navigation system） based on a GMDH （ group method of data handling） neural network was presented to solve the problem of degraded accuracy for less than four visible GPS satellites with poor signal quality. Positions and velocities of the satellites were predicted by a GMDH neural network, and the pseudo ranges and pseudo range rates received by the GPS receiver were simulated to ensure the regular op eration of the GPS/SINS Kalman filter during outages. In the mathematical simulation a tightly cou pled navigation system with a proposed approach has better navigation accuracy during GPS outages, and the anti jamming ability is strengthened for the tightly coupled navigation system.展开更多
The error of the conventional velocity numerical integration algorithm was evaluated through the Taylor series expansion. It is revealed that neglecting the second- and higher-order terms of attitude increments will l...The error of the conventional velocity numerical integration algorithm was evaluated through the Taylor series expansion. It is revealed that neglecting the second- and higher-order terms of attitude increments will lead to the velocity numerical integration error, which is proportional to the triple cross product of the angular rate and specific force. A selection criterion for the velocity numerical integration algorithm was established for strapdown inertial navigation system (SINS) in spinning missiles. The spin angular rate with large amplitude will cause the accuracy of the conventional velocity numerical integration algorithm in SINS to decrease dramatically when the ballistic missile is spinning fast. Therefore, with the second- and higher-order terms of attitude increments considered, based on the rotation vector and the velocity translation vector, the velocity numerical integration algorithm was optimized for SINS in spinning ballistic missiles. The superiority of the optimized algorithm over the conventional one was analytically derived and validated by the simulation. The optimized algorithm turns out to be a better choice for SINS in spinning ballistic missiles and other high-precision navigation systems and high-maneuver applications.展开更多
Allan variance(AV)stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme.However,the latter usually employs a traditional hard threshold or soft ...Allan variance(AV)stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme.However,the latter usually employs a traditional hard threshold or soft threshold that presents some mathematical problems.An adaptive dual threshold for discrete wavelet transform(DWT)denoising function overcomes the disadvantages of traditional approaches.Assume that two thresholds for noise and signal and special fuzzy evaluation function for the signal with range between the two thresholds assure continuity and overcome previous difficulties.On the basis of AV,an application for strap-down inertial navigation system(SINS)stochastic model extraction assures more efficient tuning of the augmented 21-state improved exact modeling Kalman filter(IEMKF)states.The experimental results show that the proposed algorithm is superior in denoising performance.Furthermore,the improved filter estimation of navigation solution is better than that of conventional Kalman filter(CKF).展开更多
The outlier detection and accommodation of integration navigation of strapdown inertial navigation systems and global position system（SINS/GPS） were studied.Based on analyzing the innovation orthogonal property in K...The outlier detection and accommodation of integration navigation of strapdown inertial navigation systems and global position system（SINS/GPS） were studied.Based on analyzing the innovation orthogonal property in Kalman filter,an outlier adaptive detection approach was first presented,which included the determination of evaluation function and threshold and the logic decision of outlier occurrence.To effectively attenuate the influence on estimation accuracy,a modified Kalman filter algorithm was proposed by accommodation of the dynamic data with outlier.Results of data processing from vehicle-test SINS/GPS integration navigation show the effectiveness of the proposed method.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
The integrated strap-down inertial nav igation system/olelestial navigation system(SINS/CNS)i an important autonomous navigation method with efective concealment and high predision.Both accelerometer biss and star ens...The integrated strap-down inertial nav igation system/olelestial navigation system(SINS/CNS)i an important autonomous navigation method with efective concealment and high predision.Both accelerometer biss and star ensor installation error ame important factors that aflect the performanoe of this mavigation system,which needl to be calibratexd and compensatedl.A new acelerometer bias and star sensor installation error joint calibration method for the SINS/CNS integrated navigation system i propoeed.In this newly propoeed method,the installation error of star sensor is augmented to the state vector,and the star vector,nadir angle,horkzontal poeition error and velbcity error ame ueed a8 measurementa to calbrate the two errors mentioned above.Simulations show that both accelerometer bias and star sensor installation enror an be calibratedl efectively.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
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.
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co-supported by the National Science Foundation of China(No.11532002)Science Challenge Project of China(No.TZ2018001)。
文摘Roll-isolation is an effective way for spinning vehicle to greatly reduce the roll gyro range of strapdown Inertial Navigation System(SINS)and increase the accuracy of inertial navigation.However,during a recent flight test,the roll-isolated control system failure was observed under a large pitch angle(706 h 685),which introduces a sharply increase in the roll angular velocity,the saturation of roll gyro and the inertial navigation failure.To address this issue,the governing equation of the roll-isolated system is derived with the consideration of various disturbance factors.The control failure is reproduced by numerical simulation.And the results show that the pitch and yaw angular velocity can cause a dramatic increase in roll rate under the large pitch angle,resulting in the roll-isolated control failure.Meanwhile,an improved roll-isolated control system is developed using PI controller,which is verified by mathematical simulation.
文摘A new adaptive federal Kalman filter for a strapdown integrated navigation system/global positioning system (SINS/GPS) is given. The developed federal Kalman filter is based on the trace operation of parameters estimation's error covariance matrix and the spectral radius of update measurement noise variance-covariance matrix for the proper choice of the filter weight and hence the filter gain factors. Theoretical analysis and results from simulation in which the SINS/GPS was compared to conventional Kalman filter are presented. Results show that the algorithm of this adaptive federal Kalman filter is simpler than that of the conventional one. Furthermore, it outperforms the conventional Kalman filter when the system is undertaken measurement malfunctions because of its possession of adaptive ability. This filter can be used in the vehicle integrated navigation system.
基金Gansu Province Natural Youth Fund(No.1606RJYA225)Gansu Province Science and Technology Support Program(No.1604GKCA009)+1 种基金Natural Science Foundation of Gansu Province(No.1606RJYA225)Gansu Province Science and Technology Support Program(No.1604GKCA009)
文摘With the development of rail transit,subway is playing an increasingly important role in peoples daily life.The positioning technology of subway is the key of communication based on train control system(CBTC).Considering that the global positioning system(GPS)cant be utilized in the subway and the ground equipment is complex and expensive,a self-positioning method based on inertial measurement unit(IMU)and speed sensor is put forward,and the track electronic map is used to reduce the error.This method can suppress the error divergence of Strapdown inertial navigation system(SINS)and reduce the cumulative error of dead reckoning(DR)due to attitude error.In accordance with the particularity of railway lines,using the least squares method to match the line and revise the error caused by the navigation,can greatly improve the positioning accuracy and reduce the dependency on the ground equipment,and the costs of construction and maintenance can be lowered.
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supported by the National Natural Science Foundation of China(61773306).
文摘Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small areas.This paper considers the problem of vision-aided inertial navigation(VIN)for aircrafts equipped with a strapdown inertial navigation system(SINS)and a downward-viewing camera.This is different from the traditional VIO problems in a larger working area with more precise inertial sensors.The goal is to utilize visual information to aid SINS to improve the navigation performance.In the multistate constraint Kalman filter(MSCKF)framework,we introduce an anchor frame to construct necessary models and derive corresponding Jacobians to implement a VIN filter to directly update the position in the Earth-centered Earth-fixed(ECEF)frame and the velocity and attitude in the local level frame by feature measurements.Due to its filtering-based property,the proposed method is naturally low computational demanding and is suitable for applications with high real-time requirements.Simulation and real-world data experiments demonstrate that the proposed method can considerably improve the navigation performance relative to the SINS.
基金supported by Project Fund of China National Railway Group Co.,Ltd.(No.N2022G012)Natonal Natural Science Foundation of China(No.61661027)。
文摘The traditional train positioning methods suffer from inadequate accuracy and high maintenance costs,rendering them unsuitable for the development requirements of lightweight and intelligent train positioning technology.To address these restraints,the BeiDou navigation satellite system/strapdown inertial navigation system(BDS/SINS)integrated train positioning system based on an adaptive unscented Kalman filter(AUKF)is proposed.Firstly,the combined denoising algorithm(CDA)and Lagrange interpolation algorithm are introduced to preprocess the original data,effectively eliminating the influence of noise signals and abnormal measurements on the train positioning system.Secondly,the innovation theory is incorporated into the unscented Kalman filter(UKF)to derive the AUKF,which accomplishes an adaptive update of the measurement noise covariance.Finally,the positioning performance of the proposed AUKF is contrasted with that of conventional algorithms in various operation scenes.Simulation results demonstrate that the average value of error calculated by AUKF is less than 1.5 m,and the success rate of positioning touches 95.0%.Compared to Kalman filter(KF)and UKF,AUKF exhibits superior accuracy and stability in train positioning.Consequently,the proposed AUKF is well-suited for providing precise positioning services in variable operating environments for trains.
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 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.
文摘A tightly coupled GPS （ global positioning system ）/SINS （ strap down inertial navigation system） based on a GMDH （ group method of data handling） neural network was presented to solve the problem of degraded accuracy for less than four visible GPS satellites with poor signal quality. Positions and velocities of the satellites were predicted by a GMDH neural network, and the pseudo ranges and pseudo range rates received by the GPS receiver were simulated to ensure the regular op eration of the GPS/SINS Kalman filter during outages. In the mathematical simulation a tightly cou pled navigation system with a proposed approach has better navigation accuracy during GPS outages, and the anti jamming ability is strengthened for the tightly coupled navigation system.
基金Project supported in part by Program for New Century Excellent Talents in University (NCET) of China
文摘The error of the conventional velocity numerical integration algorithm was evaluated through the Taylor series expansion. It is revealed that neglecting the second- and higher-order terms of attitude increments will lead to the velocity numerical integration error, which is proportional to the triple cross product of the angular rate and specific force. A selection criterion for the velocity numerical integration algorithm was established for strapdown inertial navigation system (SINS) in spinning missiles. The spin angular rate with large amplitude will cause the accuracy of the conventional velocity numerical integration algorithm in SINS to decrease dramatically when the ballistic missile is spinning fast. Therefore, with the second- and higher-order terms of attitude increments considered, based on the rotation vector and the velocity translation vector, the velocity numerical integration algorithm was optimized for SINS in spinning ballistic missiles. The superiority of the optimized algorithm over the conventional one was analytically derived and validated by the simulation. The optimized algorithm turns out to be a better choice for SINS in spinning ballistic missiles and other high-precision navigation systems and high-maneuver applications.
文摘Allan variance(AV)stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme.However,the latter usually employs a traditional hard threshold or soft threshold that presents some mathematical problems.An adaptive dual threshold for discrete wavelet transform(DWT)denoising function overcomes the disadvantages of traditional approaches.Assume that two thresholds for noise and signal and special fuzzy evaluation function for the signal with range between the two thresholds assure continuity and overcome previous difficulties.On the basis of AV,an application for strap-down inertial navigation system(SINS)stochastic model extraction assures more efficient tuning of the augmented 21-state improved exact modeling Kalman filter(IEMKF)states.The experimental results show that the proposed algorithm is superior in denoising performance.Furthermore,the improved filter estimation of navigation solution is better than that of conventional Kalman filter(CKF).
基金Sponsored by the National Natural Science Foundation of China(60774071)the National High Technology Research and Development Program of China("863"Program)(2008AA121302)the National Basic Research Program of China("973"Program)(2009CB724000)
文摘The outlier detection and accommodation of integration navigation of strapdown inertial navigation systems and global position system（SINS/GPS） were studied.Based on analyzing the innovation orthogonal property in Kalman filter,an outlier adaptive detection approach was first presented,which included the determination of evaluation function and threshold and the logic decision of outlier occurrence.To effectively attenuate the influence on estimation accuracy,a modified Kalman filter algorithm was proposed by accommodation of the dynamic data with outlier.Results of data processing from vehicle-test SINS/GPS integration navigation show the effectiveness of the proposed method.
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.
文摘The integrated strap-down inertial nav igation system/olelestial navigation system(SINS/CNS)i an important autonomous navigation method with efective concealment and high predision.Both accelerometer biss and star ensor installation error ame important factors that aflect the performanoe of this mavigation system,which needl to be calibratexd and compensatedl.A new acelerometer bias and star sensor installation error joint calibration method for the SINS/CNS integrated navigation system i propoeed.In this newly propoeed method,the installation error of star sensor is augmented to the state vector,and the star vector,nadir angle,horkzontal poeition error and velbcity error ame ueed a8 measurementa to calbrate the two errors mentioned above.Simulations show that both accelerometer bias and star sensor installation enror an be calibratedl efectively.
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.
