Attitude Angle Error Research Articles

Multi-Unmanned Aerial Vehicles Cooperative Trajectory Optimization in the Approaching Stage Based on the Attitude Correction Algorithm

This study investigated the problem of multi-UAVs cooperative trajectory optimization for remote maritime targets in the approach phase. First, based on the precise location information of the cooperative target, a real-time algorithm for correcting UAV attitude angles is proposed to reduce the impact of UAV attitude angle errors and observation system errors on target positioning accuracy. Then, the attitude correction algorithm is integrated into the interacting multiple model-cubature information filter (IMM-CIF) algorithm to achieve the fusion of multi-UAVs observation information. Furthermore, an improved receding horizon optimization (RHO) method is employed to plan the cooperative observation trajectories for UAVs in real time at the target approaching stage. Finally, numerical simulations are conducted to examine the proposed attitude correction and trajectory optimization algorithm, verifying the effectiveness of the proposed method and enhancing the tracking accuracy of the remote target.

Posture detection of athletes in sports based on posture solving algorithms

With the rapid development of science and technology, the field of sports is constantly exploring and applying new technical means to improve the training effect and competitive level of athletes. Among them, the athletes' posture detection technology based on the attitude solving algorithm has been widely concerned in recent years. However, the current attitude solving algorithm has the limitation of low precision and low efficiency. Aiming at this, a new attitude solving algorithm is proposed. Firstly, the coordinate system is determined according to the theory of inertial navigation, and the attitude Angle is obtained by calculating the acceleration and magnetic induction intensity. Then the current attitude matrix is calculated according to the obtained attitude Angle. The initializing quaternion based on the attitude matrix is studied. Then, according to the advantages and defects of the three sensors, a complementary filtering algorithm is proposed for data fusion, so as to reduce the error of the final attitude solution. In order to further improve the accuracy of attitude detection, the complementary filter algorithm and double-layer Kalman filter algorithm are combined to process the data, and finally the quaternion is updated. It can be seen that the detection error of the research constructed model is only 9.94%, and its three attitude angle errors are mainly concentrated between -0.5° and 0.5° The model constructed by the research can realize high-precision posture detection, which can provide more scientific and reliable training aids for gymnastics, which has very strict requirements for movements in sports. It has positive significance for the development of sports.

Design and verification of controller for a small coaxial dual-rotor aircraft

In recent years, coaxial dual-rotor aircraft has attracted much attention due to its unique aerodynamic layout. However, it is difficult to miniaturize the coaxial dual-rotor aircraft that relies on the principle of periodic pitch variation due to complex structure and control difficulties. This study proposes a small cylindrical coaxial dual-rotor aircraft based on a vector motor seat. For the control problems of such coaxial dual-rotor aircraft, a position and attitude controller based on neural networks and adaptive cascaded PID control is designed. A control system model was established and tested using MATLAB/Simulink. The proposed control scheme’s soundness and efficiency were confirmed by creating a prototype and performing flight trials. The results show that compared with the classic PID controller, the control effect of the controller has improved by 36.3% to 54.6%. In the centripetal rotation flight simulation experiment, the displacement error does not exceed 0.2 m, the speed error does not exceed 0.05 m/s, and the attitude angle error does not exceed 0.01 rad. This validates the effectiveness of the designed controller, indicating that the controller can enhance the stability of the system and achieve stable hovering and flight.

The Effect of Vehicles Attitude Angle Error on Magnetic Compass Heading Estimation

The three-component magnetic sensor is used to measure the heading of the vehicle. Under working, the magnetic sensor be rotated to the horizontal plane according to the attitude angle of the vehicle, and then the heading estimation is performed. However, the vehicle’s attitude angle measurement errors affect the accuracy of the magnetic sensor measurement’s east and north components and then lead to a false heading result. Based on the relation of magnetic field measurement error and magnetic heading error, the effect model of geomagnetic measurement error on magnetic heading error is derived in this paper. Finally, the characteristics of attitude angle errors on magnetic heading are verified by experiments, and the results show that particular angles can avoid the magnetic compass’s effect by the vehicle’s attitude angle error.

Straightness Measurement Based on FOG-IMU and Shearer Motion Constraints for Longwall Coal Mining

Straightness measurements of fully mechanized coal faces are a core requirement for intelligent, comprehensive coal mining. In coal mining, using an inertial measurement unit (IMU) assisted by an odometer for straightness measurement is vital for automating longwall mining. IMUs are less vulnerable to dim and harsh underground mining conditions. However, IMU divergence cannot be controlled solely by the forward velocity obtained from the odometer. To address this problem without external sensors, this paper proposes a straightness measurement method based on a fiber optic gyroscope-IMU/odometer and shearer motion constraints. The motion of the shearer is constrained to correct the pitch and roll attitude angle errors in strapdown inertial navigation solution (SINS) attitude solutions. An extended Kalman filter was established to combine the SINS and dead reckoning using the output from the odometer. Finally, the position estimation obtained by Kalman filter fusion was converted into straightness. An experiment based on a custom-built test rail demonstrated that the proposed algorithm effectively improved the accuracy of straightness measurements in multiple cutting cycles. The error of the results in the horizontal plane was reduced by 45% compared to the traditional IMU/odometer method. This study is important in promoting the unmanned and intelligent development of China’s coal industry.

Research on the application of inertially stabilized platform in the dynamic measurement of cold atomic gravimeter

Dynamic gravity field measurement based on the cold atom absolute gravity measurement system has important applications in geological exploration, gravity field mapping and other fields. The inertial stabilized platform is the key component of the dynamic cold atom absolute gravity measurement system, which can isolate the interference of carrier angle motion and keep the atomic gravimeter probe in the horizontal attitude during the measurement process. In this paper, according to the dynamic measurement requirements of atomic gravimeter, a high-precision two-axis inertial stabilized platform system is designed. The relationship between attitude angle and gravity measurement error is analyzed, and the stability of the system is enhanced by lead-lag method. Then the static vertical vibration power spectrum of the platform is measured to consider its influence on dynamic gravity measurement. Finally, a dynamic gravity test experiment was conducted in the Yellow Sea to verify the attitude control accuracy of the platform, and the attitude data of the platform under different heading were evaluated. The attitude standard deviation of the platform was better than 4 × 10−5 rad, and the absolute gravity standard deviation of the linear round-trip measurement reached 1.49 mGal. The experimental data show that the inertial stabilized platform can meet the dynamic measurement requirements of the cold atom gravimeter.

Error Analysis for Shipborne-based-based Single Band LiDAR Point Cloud Data

A new measuring technique called a ship-based single band LiDAR system is utilized to swiftly capture underwater terrain to employ dense and precise point cloud data on a vast region for bathymetry. The accuracy of point clouds is strongly impacted by the ease with which numerous error sources might affect shipborne single-band lidar measurement systems. Shipborne-based single-band LiDAR point cloud errors are mostly caused by GPS, attitude angle, range, and integration errors. This research explores and examines the impact of the scanning angle and attitude angle on bathymetry because they can fluctuate significantly throughout the actual measurement process. The point cloud errors resulting from numerous sets of scanning angle and attitude-angle data sets are calculated. The linear relationship and positioning accuracy between the three are intuitively depicted by comparable curves, presuming that other error causes are quantifiable. Analysis reveals that the error will also rise as the scanning angle increases.Additionally, the roll angle inaccuracy in the attitude angle has a minimal impact on the accuracy of the plane but a substantial impact on the accuracy of the elevation. Elevation error significantly impacts plane positioning accuracy but less on elevation accuracy. Positioning is only minimally affected by yaw angle inaccuracy.

Robot Bionic Eye Motion Posture Control System

This paper mainly studies the structure and system of robot bionic eye. Given that most robots usually run on battery power, the STM32L053C8T6 with high efficiency and super low power consumption was selected as the main control. By carrying IMU, the bionic eye attitude data can be acquired quickly and accurately, and the measurement data of accelerometer and gyroscope can be fused by the algorithm to obtain stable and accurate bionic eye attitude data. Thus, the precise control of the motor can be realized through the drive control system equipped with PCA9685, which can enhance the motion control precision of robot bionic eye. In the present study, three kinds of IMU sensors, MPU6050, MPU9250, and WT9011G4K, were selected to carry out experiments. Finally, MPU9250 with better power consumption and adaptability is selected. This is the attitude acquisition device of bionic eye. In addition, three different filters, CF, GD, and EKF, were used for data fusion and comparison. The experimental result showed that the dynamic mean errors of CF, GD, and EKF are 0.62°, 0.61°, and 0.43°, respectively, and the static mean errors are 0.1017°, 0.1001°, and 0.0462°, respectively. The result showed that, after the use of EKF, the robot bionic eye system designed in this paper can significantly reduce the attitude angle error and effectively improve the image quality. It ensures accuracy and reduces power consumption and cost, which has lower requirements on hardware and is easier to popularize.

Piecewise Trajectory and Angle Constraint Based Fractional-order Sliding Mode Control

This paper proposes an approach for piecewise trajectory planning and fractional-order sliding-mode guidance of a two-stage launched miniature munition with the laser beam riding steered guidance technology. In the proposed approach, firstly, the polynomial description is used as an expected trajec- tory. Then consider the random external disturbances/parametric uncertainties and other factors deteriorate the tracking control performances of the miniature munition. To reduce the chatter- ing caused by modeling errors and external disturbances and achieve fast speed and high accuracy tracking performances for miniature munition, based on adaptive multi-power reaching strategy, an integrated guidance and control (IGC) method with the fractional-order sliding-mode guidance law (FOSMGL) is introduced. The designed fractional-order sliding surfaces ultimately and successively allow both the trajectory and the attitude angle converge to expected value in a finite time. In addition, considering the case of a moving target, a feedfor- ward compensation mechanism, which decreases the lag of the guidance system, is imposed using an additional compensated term obtained from the attitude angle error. The convergence and reachability of the proposed algorithm in finite-time are analyzed using the Lyapunov function method. The validity and practicability of the proposed method are verified by a numerical example.

Adaptive attitude determination of bionic polarization integrated navigation system based on reinforcement learning strategy

<p style='text-indent:20px;'>The bionic polarization integrated navigation system includes three-axis gyroscopes, three-axis accelerometers, three-axis magnetometers, and polarization sensors, which provide pitch, roll, and yaw. When the magnetometers are interfered or the polarization sensors are obscured, the accuracy of attitude will be decreased due to abnormal measurement. To improve the accuracy of attitude of the integrated navigation system under these complex environments, an adaptive complementary filter based on DQN (Deep Q-learning Network) is proposed. The complementary filter is first designed to fuse the measurements from the gyroscopes, accelerometers, magnetometers, and polarization sensors. Then, a reward function of the bionic polarization integrated navigation system is defined as the function of the absolute value of the attitude angle error. The action-value function is introduced by a fully-connected network obtained by historical sensor data training. The strategy can be calculated by the deep Q-learning network and the action that optimal action-value function is obtained. Based on the optimized action, three types of integration are switched automatically to adapt to the different environments. Three cases of simulations are conducted to validate the effectiveness of the proposed algorithm. The results show that the adaptive attitude determination of bionic polarization integrated navigation system based on DQN can improve the accuracy of the attitude estimation.</p>

In-Flight Alignment of Integrated SINS/GPS/Polarization/Geomagnetic Navigation System Based on Federal UKF.

As a common integrated navigation system, the strapdown inertial navigation system (SINS)/global positioning system (GPS) can estimate velocity and position errors well. Many auxiliary attitude measurement systems can be used to improve the accuracy of attitude angle errors. In this paper, the in-flight alignment problem of the integrated SINS/GPS/Polarization/Geomagnetic navigation system is discussed. Firstly, the SINS/Geomagnetic subsystem is constructed to improve the estimation accuracy of horizontal attitude angles. Secondly, the polarization sensor is used to improve the estimation accuracy of heading angle. Then, a federal unscented Kalman filter (FUKF) with non-reset structure is applied to fuse the navigation data. Finally, simulation results for the integrated navigation system are provided based on experimental data. It can be shown that the proposed approach can improve not only the speed and position, but also the attitude error effectively.

A high-accuracy initial alignment method based on backtracking process for strapdown inertial navigation system

When the alignment time is short, the traditional initial alignment method of strapdown inertial navigation system has very low accuracy, and even the attitude angle error is difficult to converge. We propose a high-accuracy initial alignment method for strapdown inertial navigation system based on the backtracking process, which reuses short-time measurement data to improve the accuracy and speed of initial alignment. We introduce the backtracking process into coarse alignment and fine alignment of strapdown inertial navigation system. In the coarse alignment, the instantaneous acceleration error caused by the backtracking process is estimated and compensated. In the fine alignment, the optimal initialization method of the parameters in the Kalman filter is given. The initial alignment experimental results of strapdown inertial navigation system prove the effectiveness of the proposed method. Compared with the previous initial alignment method, the accuracy and speed of the proposed method are improved.

A Decoupling Three-Position Calibration Method Based on Observability Analysis for SINS/CNS Integrated Navigation

The integrated strap-down inertial/celestial navigation system (SINS/CNS) has been widely applied in autonomous navigation. For long-term high precision performance, initialization is a vital process including the calibration of misalignment angles and system-level parameters. This paper proposes a decoupling three-position calibration method based on a Kalman filter. By measuring the velocity error and attitude error, it is capable to estimate the attitude angle, gyro bias, accelerometer bias and installation error of star sensor. Firstly, the observability degree analysis provides a theoretical account of the coupling of states and the effect of different rotation maneuvers. Secondly, the limitation of gyro noise on the accuracy of accelerometer bias is clarified by comparative experiments. Simultaneously, results indicate that the proposed method can achieve arc-second accuracy in attitude angle and installation error angle, and limit the accelerometer bias error to less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${3}\%$ </tex-math></inline-formula> regardless of the IMU performance. It is an optimal calibration method with advantages of fast convergence, high accuracy, good stability and repeatability.

Error research of attitude measurements on low-cost UAV-borne missile

The framed gyroscope can significantly reduce the cost of missile. However, the gyroscope error problem restricts the acquisition probability and guidance precision of air-to-ground missile. A gyroscope error compensation method based on Taylor series formula is proposed in this paper. Gyro output error sources are analysed in detail, and the gyro output error model of unmanned aerial vehicle load space missile is established, and the mathematical relationship between missile attitude angle and the gyroscope output is deduced. Through the gyroscope on three-axis turntable hardware-in-the-loop simulation test, the correctness and effectiveness of the gyro error model established is verified. The test results show that the proposed error compensation method can control yaw attitude angle error and oblique attitude angle error of UAV-borne missile within 1° respectively in 20 s, and easy to project implementation.

Research on attitude measurement compensation technology under the influence of solar infrared radiation interference

Aiming at the problem that the dual-band infrared radiation attitude measurement cannot be used all day long, the dual-band solar infrared radiation interference analysis and compensation technology are studied. The proportion of solar direct and scattered infrared radiation in the total atmospheric radiation is counted by MODTRAN, and the influence of solar infrared radiation interference on dual-band attitude measurement is simulated. It shows that the medium wave infrared sensor cannot work normally under the influence of solar infrared radiation. When the long wave infrared sensor is facing the solar infrared radiation, it will produce an attitude angle error within 18 degrees, but when it is not facing the solar infrared radiation, the impact is small, and the attitude angle error is within 1 degree. Based on the solar infrared radiation interference law on long wave infrared radiation sensor, a four-axis attitude compensation algorithm with long wave infrared radiation sensor is designed. The semi-physical experimental results show that the attitude solution accuracy of the four-axis attitude compensation algorithm is within ±1 degree, which effectively improves the infrared radiation attitude test accuracy under the interference of solar infrared radiation. The algorithm is proved to be a solution with strong anti-interference ability for the dual-band infrared radiation attitude measurement of rotating projectile under all-day situation.

Study on Airborne Near-Nadir TOPS SAR Imaging With Attitude Angle Error

Combined with terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), near-nadir SAR (N-SAR) system has great potential for the surface water and ocean topography (SWOT) observation. However, one practical problem of the airborne N-SAR is the non-ideal attitude angle caused by the environment. Normally, the influence of attitude angle error can be considered as a constant squint angle of the system. However, in fact, for the near-nadir SAR system with TOPS SAR mode, the attitude angle error will cause a non-ideal 2-dimensional space-variant Doppler centroid for the receiving data and cause the traditional imaging algorithm failure. To deal with such problems, an imaging algorithm with attitude angle estimation for the near-nadir TOPS SAR system is proposed in this paper. Firstly, the influence of attitude angle error and the signal properties are analyzed. Secondly, based on the analysis, an attitude angle estimate algorithm (AAE), utilizing the nonlinear least square method (NLSM) and minimum entropy criterion, is proposed. Then, based on the estimated altitude angle, without data blocking, a full data imaging algorithm (FDA) is proposed. Its main idea is to obtain an un-ambiguous azimuth spectrum and design an appropriate range-variant azimuth filter through frequency chirp scaling (FCS). The numerical simulations and real data processing demonstrate that the proposed algorithm has good performance on attitude angle error estimation and well-focused image obtaining.

Derivative ratio attitude solution algorithm of tri-orthogonal magnetic sensor for spinning projectile

The tri-orthogonal geomagnetic attitude measurement model of a spinning projectile cannot be directly solved by a numerical method; therefore, it is usually in an auxiliary status in the attitude measurement system. In addition, a coning motion appears during the actual flight process of the spinning projectile. This is often ignored in conventional geomagnetic attitude measurements. To improve practicability, a tri-orthogonal geomagnetic attitude measurement model under the condition of coning motion was established, and a derivative ratio algorithm was proposed. The attitude angle errors from the coning motion were analyzed and corrected. The simulation and experimental results show that relatively accurate attitude angles can be obtained by the algorithm using only the outputs of the tri-orthogonal magnetic sensor. The algorithm is simple and efficient and is suitable for the actual measurement of the attitude angle for a high-dynamic-spinning projectile.

Adaptive control of missile attitude based on BP–ADRC

Purpose To improve the robustness of missile control system and reduce the error, a missile attitude adaptive control method based on active disturbance rejection control technology (ADRC) and BP neural network is innovatively proposed. Design/methodology/approach ADRC improves the performance of the missile control system by estimating and eliminating the total disturbance of the system. BP neural network adjusts the parameters of ADRC controller according to the state of the system to realize adaptive control. Based on the control system and missile dynamics model, the convergence analysis of the extended state observer and the stability analysis of the closed-loop system after embedding BP neural network are given. Findings The simulation results show that the adaptive control method can adjust the coefficient of error feedback rate according to the system input, output and error change rate, which accelerates the response speed of missile attitude angle and reduces the attitude angle error. Practical implications BP–ADRC further improves the robustness and environmental adaptability of the missile control system. The BP–ADRC control method proposed in this paper is proved feasible. Originality/value Different from the traditional ADRC, the BP–ADRC feedback signal proposed in this paper uses the output signal and its rate of the closed-loop system instead of the system state quantity estimated by extended state observer (ESO). This innovative method combined with BP neural network can make the system output meet the requirements when ESO has errors in the estimation of missile dynamics model.

Automatic recognition and location system for electric vehicle charging port in complex environment

This study proposes an automatic recognition and location system of electric vehicle charging port with application to automatic charging. The system obtains the charging port posture through image processing, and performs the insertion motion in combination with the robot arm to complete the charging gun insertion of the automatic charging link. The framework of the system is mainly divided into three parts, recognition, location and insertion. In the charging port recognition, the convolutional neural network-based method is used, and the recognition success rate is up to 98.9% under the light intensity of 4000 lux; in the location of the charging port, the method of solving the pose based on the circle feature is adopted. The average value of the position error is within 1.4 mm, and the average value of the attitude angle error is within 1.6°, which meets the accuracy requirement of the insertion experiment; in the charging gun insertion, the motion of the robot is planned by interpolation algorithm. The lower limit of the successful insertion is about 135 lux and the upper limit is about 9350 lux.

Алгоритмы и конфигурация системы ориентации подвижных объектов на микромеханических чувствительных элементах

Inertial systems for attitude control, stabilisation and navigation of moving objects boast a range of unique qualities, the most important of which are autonomy and interference immunity. At present, strap-down inertial navigation systems using inexpensive and compact microelectromechanical sensors are popular. The biggest disadvantage of the attitude control systems utilising microelectromechanical sensors is rapid error accumulation over time. The main error sources in strap-down inertial navigation systems are the errors of angular velocity sensors and accelerometers. Currently the accuracy required is ensured by the attitude control system processing the following two signals simultaneously: the magnetometer signal and the signal received from global navigation satellite systems such as GPS (NAVSTAR) and/or GLONASS. We developed an unconventional approach to integrating the two systems, that is, a strap-down inertial navigation system and a global navigation satellite system. It involves using the difference between the accelerations computed according to the global navigation satellite systems and those computed by the acelerometers and transformed to the geographic coordinate system for evaluating and compensating for the error of attitude angle assessment via the kinematic channel. Since this approach does not use integration of accelerometer readings, the attitude angle errors at the initial stage do not accumulate over time. Numerical simulation results of the algorithms developed show that the attainable attitude angle estimation accuracy significantly exceeds the accuracy of conventional methods