Transfer Alignment Method Research Articles

A rapid and accurate transfer alignment method using inertial instrument measurement information

A rapid and accurate transfer alignment method using inertial instrument measurement information

Study on the method of transfer alignment based on the distributed inertial network of guided submunition

Aiming at the problem of poor transfer alignment accuracy between missiles with a high length-to-diameter ratio as a carrier missile and the internally carried guided submunition, this study proposes a transfer alignment method based on the distributed inertial network of the guided submunition. Initially, considering the influence of the deflection deformation of the carrier missile body and the dynamic nonlinear deformation of the lever arm on the transfer alignment accuracy, the corresponding error model is established and compensated for the sub-inertial guide velocity to improve the accuracy of the observed quantities. Additionally, in response to the high failure rate of low-cost inertial guidance systems equipped with guided submunition, we used an inertial network data fusion architecture based on the isolation of device failure monitoring, which effectively isolates the faulty data through the fusion of inertial measurements at the sensor level and optimal fusion of filtering to further improve the reliability of transmission alignment. The effectiveness of the method proposed in this paper is verified through a large number of simulation experiments. Compared with the traditional transfer alignment method between a single master inertial guide and a sub inertial guide, the method in the paper has obvious improvement in the transfer alignment accuracy. In addition, this method is not affected by the failure of inertial devices in the distributed inertial network, and can continuously maintain a high transfer alignment accuracy. For this kind of missile-borne distributed inertial network with a sub-node sets layer, it is found after comparison that: the transmission alignment error is basically the same for different slave nodes in the same sub-node sets; between different sub-node sets, the closer to the master inertial guide the transmission alignment error is smaller. This study provides a new solution idea and certain reference value for solving the problem of poor transfer alignment accuracy between missiles with a high length-to-diameter ratio as a carrier missile and the internally carried guided submunition.

Transfer alignment method based on installation deviation angle estimation for array POS

Transfer alignment of array Position and Orientation System (POS) is the key technology to provide motion information for airborne earth observation high-precision imaging. Because the large deviation angle between main Inertial Measurement Unit (IMU) and slave IMU is difficult to accurately measure by existing methods, the transfer alignment accuracy will be seriously affected. Aiming at this issue, a transfer alignment method based on installation deviation angle estimation for array POS is proposed. This method includes two steps: pre-estimation and improved transfer alignment. First, two deviation angles are calculated by angular velocity and acceleration using quaternion optimization method respectively. The higher-precision deviation angle is fused by two deviation angles using their respective weights, which are calculated by Signal to Noise Ratios (SNRs). Second, the result of pre-estimation is used in transfer alignment. Residual errors of deviation angle are considered as state variables and be compensated online. Compared with the existing methods, the velocity, position and attitude errors calculated by this method are reduced by 15.4%, 31.7% and 66.5% respectively. The proposed method significantly reduces the adverse effect of installation deviation angle on measurement accuracy of array POS.

Multi-Node Motion Estimation Method Based on B-Spline of Array Position and Orientation System

The array position and orientation system (array POS), composed of one main POS and multiple sub-inertial measurement units (sub-IMUs), is key equipment in the aerial remote-sensing system, especially the multi-load system, which can provide motion compensation for the multi-load remote-sensing system to improve imaging quality. Nevertheless, the measurement information of each sub-IMU can only realize the motion information of the corresponding remote-sensing load. Ideally, each remote-sensing load should be equipped with a sub-IMU for motion compensation, which is impossible in actual engineering considering the volume, weight and cost. To solve this problem, a multi-node motion estimation method based on the B-spline of the array POS is proposed to realize the motion compensation of remote-sensing loads without sub-IMUs. Firstly, the transfer alignment method based on fiber-grating multi-dimensional deformation measurement was adopted. Motion parameters of the remote-sensing payload equipped with sub-IMUs at different times can be obtained by observing and correcting the errors between the main POS and sub-IMUs. In this way, the space-time characteristics of each interpolation point are fully utilized. Additionally, the motion information of the main POS and all sub-IMUs is fitted through the estimation method based on the B-spline, during which wing deformation is considered to obtain the motion parameters of the remote-sensing payload equipped without a sub-IMU. In this way, the spatial correlation between the information of each node is fully utilized. Due to the full utilization of the spatiotemporal correlation of the motion information of each sub node, high-precision and highly reliable motion information of the remote-sensing loads not equipped with sub-IMUs is obtained. Furthermore, the proposed method can be modified locally without affecting other nodes, and has the advantages of a simple algorithm and easy engineering implementation. Finally, a semi-physical simulation based on ground-loading test was conducted. The results show that the baseline in the X-axis, Y-axis and Z-axis direction is improved by 0.484 mm, 0.137 mm and 1.225 mm, respectively, and that the measurement accuracy of roll angle is improved by 0.011°.

Rapid Transfer Alignment for Large and Time-Varying Attitude Misalignment Angles

Transfer alignment is an effective method to estimate the attitude difference between two inertial platforms. Traditional transfer alignment methods are either meant for small misalignments or use nonlinear filtering. Linear methods for large misalignments use quaternion attitude representation, but their performance degrades when the misalignment is not constant or slowly varying. This work proposes applying rapid transfer alignment to the inertial stabilization of a Satcom On-The-Move antenna. In this application case, the two inertial platforms are connected by a kinematic chain, meaning the attitude difference between the inertial platforms is both large and time-varying. This work proposes a method to estimate this attitude difference, with a Kalman filter used for the estimation of the unknown angles. To that effect, a new propagation model is developed to take into account the misalignment variations using master and slave rotation rates. Simulation results show the performance of the proposed solution in a Satcom antenna inertial stabilization case.

A New Polar Rapid Transfer Alignment Method Based on Grid Frame for Shipborne SINS

A polar grid rapid transfer alignment method for shipborne strapdown inertial navigation system (SINS) is studied. The basic framework and the specific process of grid rapid transfer alignment are built. The grid equations of attitude error, velocity error and position error of SINS are deduced. The math model of alignment with velocity plus attitude quaternion method is established. The velocity plus attitude quaternion method and velocity plus attitude angle method are derived and compared. On this basis, the Kalman filter algorithm is used to design grid alignment filter. The ship trajectory is designed and generated, and the researched alignment method is simulated and verified by MATLAB. Simulation results show that the proposed method can accurately estimate the attitude error angle, velocity error, deflection deformation angle and installation error angle, except at the poles, whether in mid latitude or high latitude, and regardless of the sea state level. The horizontal estimation accuracy of attitude error angle is 0.8’, the azimuth estimation accuracy is within 1.8’, the velocity error is within 0.03m/s, and the estimation accuracy of deflection angle and installation error angle is within 1.2’. Finally, the ship experiment is carried out, and the experimental results show that the actual application effect of the proposed method was as satisfactory as in the simulation experiment. During the estimation time of 20 s, the attitude misalignment angle error is 0.2 ’, the velocity error is 0.05 m/s, and the estimation accuracy of deflection deformation angle and installation error angle is less than 1’.

Design and Development of Array POS for Airborne Remote Sensing Motion Compensation

Multi-antenna airborne remote sensing systems have received more attention recently because they can realize high-resolution three-dimensional (3-D) imaging, such as array Synthetic Aperture Radar (SAR). Their high-precision imaging needs multi-antenna motion and relative motion between antennas. However, the existing facility and technology hardly meet the motion measurement precision demand of array SAR. To solve this problem, an array Position and Orientation System (POS) for airborne remote sensing motion compensation is designed and developed. It is composed of a high-precision POS, several small-size Inertial Measurement Units (IMU), and a 6-D deformation measurement system based on Fiber Bragg Grating (FBG) sensors. Firstly, the transfer alignment method based on 6-D deformation is used to measure the relative motion between array POS. Then, the motion conversion method from array POS to array SAR is presented to obtain the multi-antenna motion and relative motion between antennas. Finally, the ground experiment results identify that the accuracies of multi-antenna position, multi-antenna attitude, and flexible baseline length between antennas are superior to 3 cm, 0.01°, and 0.1 mm, respectively, which can meet the motion measurement precision demand of array SAR.

A transfer alignment algorithm based on combined double-time observation of velocity and attitude

PurposeThis paper aims to present a novel transfer alignment method based on combined double-time observations with velocity and attitude for ships’ poor maneuverability to address the system errors introduced by flexural deformation and installing which are difficult to calibrate.Design/methodology/approachBased on velocity and attitude matching, redesigning and deducing Kalman filter model by combining double-time observation. By introducing the sampling of the previous update cycle of the strapdown inertial navigation system (SINS), current observation subtracts previous observation are used as measurements for transfer alignment filter, system error in measurement introduced by deformation and installing can be effectively removed.FindingsThe results of simulations and turntable tests show that when there is a system error, the proposed method can improve alignment accuracy, shorten the alignment process and not require any active maneuvers or additional sensor equipment.Originality/valueCalibrating those deformations and installing errors during transfer alignment need special maneuvers along different axes, which is difficult to fulfill for ships’ poor maneuverability. Without additional sensor equipment and active maneuvers, the system errors in attitude measurement can be eliminated by the proposed algorithms, meanwhile improving the accuracy of the shipboard SINS transfer alignment.

A fast and accurate transfer alignment method without relying on the empirical model of angular deformation

AbstractThis paper, in allusion to the limitations of traditional transfer alignment methods based on the external measurement equipment or the empirical model of angular deformation, proposes a rapid and accurate transfer alignment method without relying on the empirical angular deformation model. Firstly, the relationship between the actual angular deformation and the angular velocities measured by the gyroscopes in the master and slave inertial navigation systems (INSs) is derived to roughly estimate the angular deformation. Secondly, according to the error characteristics of gyroscopes, the error model of angular deformation is established. Thirdly, expanding the angular deformation error instead of the installation error angle, flexure angle and flexure angle rate into the state vector, a low-order transfer alignment filtering model independent of the empirical angular deformation model is established. The proposed method not only gets rid of the dependence on an empirical angular deformation model, but also realises the rapid and accurate initial alignment of the slave INS without adding any external measurement equipment. The simulations and experiments evidence the validity of the proposed transfer alignment method.

Rapid Reduction Dimensionality Transfer Alignment Method Based on CKF for SINS of Ship-borne Aircraft with GNSS Assistance

Abstract Aiming at the problem of rapid transfer alignment of inertial navigation system in shipborne environment with large azimuth misalignment angle, a dimension reduction fast transfer alignment scheme of shipborne aircraft inertial navigation system based on CKF algorithm is designed. Firstly, the nonlinear attitude error equation, velocity error equation and position error equation of the Global Navigation Satellite System (GNSS) assisted strapdown inertial navigation system in the case of large azimuth misalignment are analyzed. Secondly, the nonlinear dimensionality reduction rapid transfer alignment state equation and measurement equation are derived. Finally, the CKF algorithm is simulated and verified, and compared with EKF algorithm and UKF algorithm. The simulation results show that the reduced dimension fast transfer alignment method of shipborne aircraft inertial navigation system based on CKF algorithm can complete the estimation of attitude error angle in 80s, with horizontal estimation error of 1’ and azimuth error of 4’, and the estimation accuracy is equivalent to EKF and UKF, with less calculation and better rapidity.

Adaptive transfer alignment method based on the observability analysis for airborne pod strapdown inertial navigation system

For the airborne pod strapdown inertial navigation system, it is necessary to use the host aircraft's inertial navigation system for the transfer alignment as quickly and accurately as possible in the flight process of the aircraft. The purpose of this paper is to propose an adaptive transfer alignment method based on the observability analysis for the strapdown inertial navigation system, which is able to meet the practical need of maintaining the navigation accuracy of the airborne pod. The observability of each state variable is obtained by observability analysis of system state variables. According to the weight of the observability, a transfer alignment filter algorithm based on adaptive adjustment factor is constructed to reduce the influence of weak observability state variables on the whole filter, which can improve the estimation accuracy of transfer alignment. Simulations and experiment tests of the airborne pod and the master strapdown inertial navigation systems show that the adaptive transfer alignment method based on the observability analysis can overcome the shortage of the weak observability state variables, so as to improve the alignment and the navigation performance in practical applications, thus improving the adaptability of the airborne pod.

A Novel Transfer Alignment Method of Array POS Based on Lever-Arm Estimation

A Novel Transfer Alignment Method of Array POS Based on Lever-Arm Estimation

A transfer alignment method for inertial attitude correction of spherical motor on moving base

Inertial attitude measurement of spherical motor on moving base (SMMB) confronts the problems of unobservable azimuth and acceleration interference. This paper presents a transfer alignment method for inertial attitude correction of SMMB with specific exterior excitation. Because of the low friction torque of the spherical joint in the SMMB, the rotation is not able to be wholly transferred from base to rotor, which is required in the common method of velocity-attitude matching. With an explicit model about the acceleration transfer, the accumulation of unobservable error based on nominal-state is derived. Then the transfer alignment algorithm with innovation-based adaptive filter is proposed. The method brings external acceleration measurement into regular attitude estimation and adopts both estimation of unobservable error and acceleration transfer error into adaptive filter for the balance of azimuth correction and tilt error suppression. The simulation and analysis show that the method can correct the unobservable azimuth angle in high amplitude and frequency excitation as well as better tilt error suppression for transfer error with 20% uncertainty. The method is verified in a prototype platform.

Vehicle-borne non-strapdown transfer alignment method and application with poor attitude observation information

For transfer alignment in elevation maneuver, the system accuracy will be decreased or divergent because of the poor attitude observation information. What is the impact on the transfer alignment with poor attitude observation information caused by non-strapdown installation is still a problem. This paper proposes a vehicle-borne non-strapdown transfer alignment method to analyze it and to reduce the impact of poor attitude observation information and establishes observation equation that match with the physical model with poor attitude observation information. The design and comparison of 37° and 80° elevation maneuver angles are carried out. Because of lacking one-degree-of-freedom attitude information, the accuracy will be lower than that of the three-degree-of-freedom attitude information. In addition, both simulation and experiments show that the proposed method can improve the alignment accuracy under the condition of poor attitude observation information. When the elevation maneuver angle is close to 90°, the proposed method has better observation performance, and the relative heading error is close to the alignment precision which is under good attitude observation information.

The transfer alignment method based on the inertial network

The purpose of this paper is to propose a new transfer alignment approach based on the inertial network. The inertial network is described, and the measurement models are built firstly. The inertial device fusion and fault detection algorithm are analyzed with the redundancy technology of devices in the inertial network to enhance the reliability and security of the system. Then the improved model of the system is built and the transfer alignment algorithm method for the inertial network is proposed. Several experiments have been performed to validate the performance of the proposed transfer alignment scheme. Different simulation experiments and real ground vehicle test results showed that the transfer alignment with the inertial network can obtain the better precision result and shorter convergence time, which can also improve the fault detection and recognition ability of the system. A transfer alignment method based on the inertial network is proposed to improve the fault tolerance ability and enhance the accuracy of the system. The primary advantage is that each node is able to communicate with other nodes, which allows for sharing information in the inertial network.

Applied singular value decomposition method in transfer alignment and bias calibration

The transfer alignment accuracy between the master inertial navigation system (MINS), the slave inertial navigation system (SINS) and the online calibration capability of SINS are the important factors that affect the system performance. The traditional Kalman filtering-based transfer alignment method greatly depends on the prior information. The alignment and calibration based on optimisation-based alignment are preliminarily achieved without the prior information, but many deductions are required to achieve an optimal solution. In this study, a novel method aimed at transfer alignment and bias calibration is proposed, which is based on singular value decomposition by the inertial measurement vector matching equation to construct the least-squares solution. The performance of the system is analysed from the transfer alignment accuracy and the inertial instrument error estimation, respectively. The simulation and flight experiment results demonstrate that the proposed method is concise and effective without complex deduction and calculation. The relative attitude angle between MINS and SINS can be estimated accurately as well as the bias of SINS.

Airborne Distributed Position and Orientation System Transfer Alignment Method Based on Fiber Bragg Grating.

With the demand for high resolution remote sensing, load array technology has gradually become an effective measure to improve imaging resolution. However, the external flow and internal engine vibration disturbance may lead to the flexible deformation of wings. The traditional rigid baseline error compensation method cannot solve the problem of serious coupling movement error caused by flexible deformation. To address the problem, a transfer alignment model based on fiber Bragg grating for distributed position and orientation system is proposed in this paper. Firstly, based on the multidimensional requirements of flexible deformation information, the layout scheme of fiber Bragg grating was designed, then the continuous strain in the wing surface was obtained after the quadratic fitting of strain measured by fiber Bragg gratings, and the deformation displacement and angle are calculated. Thirdly, flexible deformation compensation for distributed position and orientation system based on fiber Bragg grating was studied. The state equation including position error, velocity error, misalignment angle, and inertial device error was established. The position and attitude information compensated by the flexible lever arm was used as the quantitative measurement. The filtering estimation improved the measurement accuracy of the slave inertial navigation systems. At last, the experiment was carried out and showed that the accuracy of the transfer alignment has been improved significantly.

Variational Bayesian Cubature RTS Smoothing for Transfer Alignment of DPOS

Multi-task remote sensing sensors have become attractive development directions of aerial remote sensing system, which rely on distributed position and orientation system (DPOS) to provide multi-node motion parameters to achieve superior performance. DPOS depends on transfer alignment from its master system to slave inertial measurement units to obtain multi-node motion information. However, for DPOS, there are many factors like carrier maneuver mode and external disturbance which will result in time-varying measurement noise and further degrade transfer alignment performance of DPOS obviously. In this work, a transfer alignment method based on variational Bayesian cubature RTS smoothing is developed to improve the accuracy of DPOS, which is implemented by combining the cubature RTS smoothing algorithm and variational Bayesian estimation method to deal with the time-varying measurement noise. A semi-physical simulation based on real flight experiment has been conducted, the results show that the motion parameter accuracy has achieved noticeable enhancement than the existing cubature RTS smoothing algorithm.

Hull Deformation Measurement With Large Angles Based on Inertial Sensors

The partial reference is used in large ships to measure the hull deformation, which is normally realized through the transfer alignment between the master inertial navigation system and the slave inertial navigation system. In recent years, the matching methods based on several inertial measurement units has become the development trend to avoid the initial alignment of the slave system. However, these methods always require that the deformation angle is small and the system model can be regarded as a linear model. The purpose of this article is to solve the large deformation problem through coarse estimation based on the optimized attitude determination and propose an improved transfer alignment method based on the attitude matching in the inertial frame. The coarse estimation does not rely on the deformation model and can decrease the deformation error to a small angle in a short time. Then the system model and the measurement model are built to carry out the attitude matching in the inertial frame, which is stable and can avoid initial alignment. The swing table test show that the proposed method can estimate the large deformation between the two IMUs rapidly and precisely.

A Nonlinear Transfer Alignment of Distributed POS Based on Adaptive Second-Order Divided Difference Filter

Distributed position and orientation system (POS) uses transfer alignment to accurately measure multi-node time-spatial reference information, which is urgently demanded to compensate motion error of imaging sensors for aerial survey. The lever-arm deformation in transfer alignment will result in nonlinear error and time-varying measurement noise covariance, which decreases the accuracy of real-time estimation. In order to solve this problem, a nonlinear transfer alignment method of distributed POS based on an adaptive second-order divided difference filter (ADDF2) is proposed. First, a transfer alignment model for distributed POS is established. Furthermore, an ADDF2 based on adaptive innovation estimation is proposed to solve the nonlinear problem and adaptively adjust the measurement noise covariance matrix of transfer alignment in real time. The flight experiment results show that the proposed method is effective to improve the precision of distributed POS.