To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environme...To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environment and AUV navigation requirements of low cost and high accuracy, a novel TPINS is designed with a configuration of the strapdown inertial navigation system （SINS）, the terrain reference navigation system （TRNS）, the Doppler velocity sonar （DVS）, the magnetic compass and the navigation computer utilizing the unscented Kalman filter （UKF） to fuse the navigation information from various navigation sensors. Linear filter equations for the extended Kalman filter （EKF）, nonlinear filter equations for the UKF and measurement equations of navigation sensors are addressed. It is indicated from the comparable simulation experiments of the EKF and the UKF that AUV navigation precision is improved substantially with the proposed sensors and the UKF when compared to the EKF. The TPINS designed with the proposed sensors and the UKF is effective in reducing AUV navigation position errors and improving the stability and precision of the AUV underwater integrated navigation.展开更多
The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improv...The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improved algorithmal expressions for strap down attitude ut ilizing the angular increment output by the laser gyro from the last two and cur rent updating periods according to the number of gyro samples, and analyses the algorithm error in the classical coning motion. Compared with the conventional algorithms, simulational results show that this improved algorithm has higher precision. A new way to improve the rotation vector algorithms is provided.展开更多
An initial alignment technique for the strapdown inertial navigation system (SINS) of vehicles in the moving state is researched. By selecting an odometer as the system’s external sensor, the mathematical model for t...An initial alignment technique for the strapdown inertial navigation system (SINS) of vehicles in the moving state is researched. By selecting an odometer as the system’s external sensor, the mathematical model for the alignment in the moving state is established and the observability of the system is analyzed. The results show that the SINS can successfully achieve the precision alignment in 10 min when the vehicle is moving toward the prearranged place after its staying for several seconds to perform the coarse alignment. The precision of alignment can also be improved in the moving state compared with that in the static state.展开更多
The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phas...The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.展开更多
To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,a...To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.展开更多
An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. ...An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good eslimates of the states. When the system is in the high dynamic mode and the bias has converged to an aceurate estimate, the attitude caleulation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance,展开更多
To solve the problem of information fusion in the strapdown inertial navigation system(SINS)/celestial navigation system(CNS)/global positioning system(GPS) integrated navigation system described by the nonlinear/non-...To solve the problem of information fusion in the strapdown inertial navigation system(SINS)/celestial navigation system(CNS)/global positioning system(GPS) integrated navigation system described by the nonlinear/non-Gaussian error models,a new algorithm called the federated unscented particle filtering(FUPF) algorithm was introduced.In this algorithm,the unscented particle filter(UPF) served as the local filter,the federated filter was used to fuse outputs of all local filters,and the global filter result was obtained.Because the algorithm was not confined to the assumption of Gaussian noise,it was of great significance to integrated navigation systems described by the non-Gaussian noise.The proposed algorithm was tested in a vehicle's maneuvering trajectory,which included six flight phases:climbing,level flight,left turning,level flight,right turning and level flight.Simulation results are presented to demonstrate the improved performance of the FUPF over conventional federated unscented Kalman filter(FUKF).For instance,the mean of position-error decreases from(0.640×10-6 rad,0.667×10-6 rad,4.25 m) of FUKF to(0.403×10-6 rad,0.251×10-6 rad,1.36 m) of FUPF.In comparison of the FUKF,the FUPF performs more accurate in the SINS/CNS/GPS system described by the nonlinear/non-Gaussian error models.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
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
Calibration of magnetometer is an essential part to obtain high measurement precision.However,the existing calibration methods are basically the calibration of all attitudes,which means tough work when the magnetomete...Calibration of magnetometer is an essential part to obtain high measurement precision.However,the existing calibration methods are basically the calibration of all attitudes,which means tough work when the magnetometer is applied in strapdown inertial navigation system(SINS).So a quick,easy and effective calibration algorithm is developed based on the ellipsoid constraint to calibrate magnetometers.In this paper,the measuring principle and error characteristic of the magnetometer are analysed to study its magnetic interference.During the process,a magnetometer calibration model is set up to convert the calibration to ellipsoid fitting based on the characteristic of hard magnetic interference and soft magnetic interference.Then the algorithm is tested by mimic experiment.The result shows that measurement precision is improved after the calibration,and then the magnetometer is installed in a control cabin of an underwater robot which is designed and developed by us,and actual magnetometer calibration experiments are conducted to further verify the validity of the algorithm.展开更多
China has developed an airborne gravimetry system based on SINS/DGPS named SGA-WZ, the first system in which a strap- down inertial navigation system （SINS） has been used for airborne gravimetry in China. This gravi...China has developed an airborne gravimetry system based on SINS/DGPS named SGA-WZ, the first system in which a strap- down inertial navigation system （SINS） has been used for airborne gravimetry in China. This gravity measurement system consists of a strap-down inertial navigation system and a differential global positioning system （DGPS）. In April 2010, a flight test was carried out in Shandong Province of China to test the accuracy of this system. The test was designed to assess the re- peatability and accuracy of the system. Two repeated flights and six grid flights were made. The flying altitude was about 400 m. The average flying speed was about 60 m/s, which corresponds to a spatial resolution of 4.8 km when using 160-s cutoff low-pass filter. This paper describes the data processing of the system. The evaluation of the internal precision is based on repeated flights and differences in crossover points. Gravity results in this test from the repeated flight lines show that the re- peatability of the repeat lines is 1.6 mGal with a spatial resolution of 4.8 kin, and the internal precision of grid flight data is 3.2 mGal with a spatial resolution of 4.8 km. There are some systematic errors in the gravity results, which can be modeled using trigonometric function. After the systematic errors are compensated, the precision of grid flight data can be better than 1 mGal.展开更多
An effective and flexible rotation and compensation scheme is designed to improve the accuracy of rotating inertial navigation system （RINS）. The accuracy of single-axial R1NS is limited by the errors on the rotatin...An effective and flexible rotation and compensation scheme is designed to improve the accuracy of rotating inertial navigation system （RINS）. The accuracy of single-axial R1NS is limited by the errors on the rotating axis. A novel inertial measurement unit （IMU） scheme with error compensation for the rotating axis of fiber optic gyros （FOG） RINS is presented. In the scheme, two couples of inertial sensors with similar error characteristics are mounted oppositely on the rotating axes to compensate the sensors error. Without any change for the rotation cycle, this scheme improves the system＇s precision and reliability, and also offers the redundancy for the system. The results of 36 h navigation simulation prove that the accuracy of the system is improved notably compared with normal strapdown INS, besides the heading accuracy is increased by 3 times compared with single-axial RINS, and the position accuracy is improved by 1 order of magnitude.展开更多
基金Pre-Research Program of General Armament Department during the11th Five-Year Plan Period (No51309020503)the National Defense Basic Research Program of China (973Program)(No973-61334)+1 种基金the National Natural Science Foundation of China(No50575042)Specialized Research Fund for the Doctoral Program of Higher Education (No20050286026)
文摘To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environment and AUV navigation requirements of low cost and high accuracy, a novel TPINS is designed with a configuration of the strapdown inertial navigation system （SINS）, the terrain reference navigation system （TRNS）, the Doppler velocity sonar （DVS）, the magnetic compass and the navigation computer utilizing the unscented Kalman filter （UKF） to fuse the navigation information from various navigation sensors. Linear filter equations for the extended Kalman filter （EKF）, nonlinear filter equations for the UKF and measurement equations of navigation sensors are addressed. It is indicated from the comparable simulation experiments of the EKF and the UKF that AUV navigation precision is improved substantially with the proposed sensors and the UKF when compared to the EKF. The TPINS designed with the proposed sensors and the UKF is effective in reducing AUV navigation position errors and improving the stability and precision of the AUV underwater integrated navigation.
文摘The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improved algorithmal expressions for strap down attitude ut ilizing the angular increment output by the laser gyro from the last two and cur rent updating periods according to the number of gyro samples, and analyses the algorithm error in the classical coning motion. Compared with the conventional algorithms, simulational results show that this improved algorithm has higher precision. A new way to improve the rotation vector algorithms is provided.
文摘An initial alignment technique for the strapdown inertial navigation system (SINS) of vehicles in the moving state is researched. By selecting an odometer as the system’s external sensor, the mathematical model for the alignment in the moving state is established and the observability of the system is analyzed. The results show that the SINS can successfully achieve the precision alignment in 10 min when the vehicle is moving toward the prearranged place after its staying for several seconds to perform the coarse alignment. The precision of alignment can also be improved in the moving state compared with that in the static state.
文摘The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.
基金Project(60604011) supported by the National Natural Science Foundation of China
文摘To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.
文摘An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good eslimates of the states. When the system is in the high dynamic mode and the bias has converged to an aceurate estimate, the attitude caleulation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance,
基金Project(60535010) supported by the National Nature Science Foundation of China
文摘To solve the problem of information fusion in the strapdown inertial navigation system(SINS)/celestial navigation system(CNS)/global positioning system(GPS) integrated navigation system described by the nonlinear/non-Gaussian error models,a new algorithm called the federated unscented particle filtering(FUPF) algorithm was introduced.In this algorithm,the unscented particle filter(UPF) served as the local filter,the federated filter was used to fuse outputs of all local filters,and the global filter result was obtained.Because the algorithm was not confined to the assumption of Gaussian noise,it was of great significance to integrated navigation systems described by the non-Gaussian noise.The proposed algorithm was tested in a vehicle's maneuvering trajectory,which included six flight phases:climbing,level flight,left turning,level flight,right turning and level flight.Simulation results are presented to demonstrate the improved performance of the FUPF over conventional federated unscented Kalman filter(FUKF).For instance,the mean of position-error decreases from(0.640×10-6 rad,0.667×10-6 rad,4.25 m) of FUKF to(0.403×10-6 rad,0.251×10-6 rad,1.36 m) of FUPF.In comparison of the FUKF,the FUPF performs more accurate in the SINS/CNS/GPS system described by the nonlinear/non-Gaussian error models.
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.
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Supported by the National High Technology Research and Development Programme of China(No.2011AA04201)
文摘Calibration of magnetometer is an essential part to obtain high measurement precision.However,the existing calibration methods are basically the calibration of all attitudes,which means tough work when the magnetometer is applied in strapdown inertial navigation system(SINS).So a quick,easy and effective calibration algorithm is developed based on the ellipsoid constraint to calibrate magnetometers.In this paper,the measuring principle and error characteristic of the magnetometer are analysed to study its magnetic interference.During the process,a magnetometer calibration model is set up to convert the calibration to ellipsoid fitting based on the characteristic of hard magnetic interference and soft magnetic interference.Then the algorithm is tested by mimic experiment.The result shows that measurement precision is improved after the calibration,and then the magnetometer is installed in a control cabin of an underwater robot which is designed and developed by us,and actual magnetometer calibration experiments are conducted to further verify the validity of the algorithm.
基金supported by the National High-Tech Research&Development Program of China(Grant No.2006AA06A202)the Youth Innovation Foundation of China Aero Geophysical Survey&Remote Sensing Center for Land and Resources(Grant No.2010YFL05)
文摘China has developed an airborne gravimetry system based on SINS/DGPS named SGA-WZ, the first system in which a strap- down inertial navigation system （SINS） has been used for airborne gravimetry in China. This gravity measurement system consists of a strap-down inertial navigation system and a differential global positioning system （DGPS）. In April 2010, a flight test was carried out in Shandong Province of China to test the accuracy of this system. The test was designed to assess the re- peatability and accuracy of the system. Two repeated flights and six grid flights were made. The flying altitude was about 400 m. The average flying speed was about 60 m/s, which corresponds to a spatial resolution of 4.8 km when using 160-s cutoff low-pass filter. This paper describes the data processing of the system. The evaluation of the internal precision is based on repeated flights and differences in crossover points. Gravity results in this test from the repeated flight lines show that the re- peatability of the repeat lines is 1.6 mGal with a spatial resolution of 4.8 kin, and the internal precision of grid flight data is 3.2 mGal with a spatial resolution of 4.8 km. There are some systematic errors in the gravity results, which can be modeled using trigonometric function. After the systematic errors are compensated, the precision of grid flight data can be better than 1 mGal.
基金supported by the National Natural Science Foundation of China (No.40904018)the Key Laboratory Foundation of the Ministry of Education of China (No.201001)the Doctoral Innovation Foundation of Naval University of Engineering (No.BSJJ2011008)
文摘An effective and flexible rotation and compensation scheme is designed to improve the accuracy of rotating inertial navigation system （RINS）. The accuracy of single-axial R1NS is limited by the errors on the rotating axis. A novel inertial measurement unit （IMU） scheme with error compensation for the rotating axis of fiber optic gyros （FOG） RINS is presented. In the scheme, two couples of inertial sensors with similar error characteristics are mounted oppositely on the rotating axes to compensate the sensors error. Without any change for the rotation cycle, this scheme improves the system＇s precision and reliability, and also offers the redundancy for the system. The results of 36 h navigation simulation prove that the accuracy of the system is improved notably compared with normal strapdown INS, besides the heading accuracy is increased by 3 times compared with single-axial RINS, and the position accuracy is improved by 1 order of magnitude.
