基于UKF信息融合的多旋翼飞行器姿态估计

姿态估计是多旋翼飞行控制的基础,为实现多旋翼三轴姿态估计,构建了基于MEMS陀螺、加速度计和磁力计的低成本姿态测量系统.该系统采用STM32F103作为控制器,集成加速度计和陀螺仪MPU6050,磁强计HMC5883作为测量传感器.针对多旋翼飞行器单一传感器无法准确测量姿态信息的问题,提出了基于无迹卡尔曼滤波信息融合的姿态估计算法.以陀螺仪为状态矢量,加速度计和磁强计解算的姿态角为观测矢量,无迹卡尔曼滤波器将陀螺的良好动态性能与加速度计、磁强计的良好静态性能结合起来,提高姿态测量精度,具有良好的动态跟踪性能.通过飞行测试,与高性能成品飞行器的姿态信息做对比,验证和分析该低成本姿态测量系统的有效性.实验结果表明,基于无迹卡尔曼滤波的姿态测量系统实现了动态环境下低成本多旋翼的精密姿态测量,为无人机自主飞行控制奠定了基础.     

用于微小型飞行器姿态估计的四元数扩展卡尔曼滤波算法

针对MEMS陀螺、加速度计、磁强计组合的姿态确定系统,笔者设计了用于微小型飞行器姿态估计的四元数扩展卡尔曼滤波算法．取姿态误差四元数和陀螺随机漂移构建滤波状态向量,通过误差四元数微分方程和陀螺随机误差模型建立了卡尔曼滤波状态方程;采用改进的高斯-牛顿算法将传感器观测量转化为四元数,通过与利用陀螺信息估计的四元数相乘,得到姿态误差四元数作为卡尔曼滤波量测值,显著减小了机动加速度对姿态估计的影响．仿真实验显示：四元数静态估计误差小于0．22％,在动态情况下,四元教估计值能够较好地跟踪真实值的变化,表明该滤波算法能够有效提高姿态估计的精度．     

基于MEMS陀螺仪和加速度计的自适应姿态测量算法

针对MEMS陀螺仪以及加速度计传感器单独测姿时,传感器数据中存在复杂噪声和测量误差导致测量得不到最优姿态角的问题,设计了一种基于MEMS陀螺仪和加速度计的自适应姿态测量算法.算法采用扩展卡尔曼滤波方法实现数据融合,并且在利用Allan方差估计MEMS陀螺动态噪声的同时,加入了遗忘因子和限定记忆的算法思想,从而实时地跟踪数据的量测噪声,实时修正角度估计误差,有效地提高了姿态测量系统的精度.实验结果表明,二者组合定姿可实现高精度的姿态测量,验证了算法良好的动态噪声抑制能力,提高了系统对环境变化的适应性.     

地磁姿态检测系统弹体摆动误差 分析与补偿方法

针对地磁/GPS组合姿态检测系统测量精度受弹体摆动影响较大的问题,在分析地磁/GPS组合姿态检测系统的弹体摆动误差的基础上,提出了基于地磁陀螺组合的姿态检测方法,建立了地磁陀螺组合姿态检测模型,利用两轴MEMS陀螺测量的角速率实时积分求解弹体偏航角,结合地磁模块输出的三维地磁分量,组合求解弹体姿态信息.结果表明,与地磁/GPS组合方案相比,增加陀螺模块可消除滚转角和俯仰角随弹体摆动而产生的误差波动,测姿能够适应各种运动环境变化,并保持良好的稳定性.     

基于三子样更新的EKF低成本MEMS姿态估计算法

针对低成本MEMS惯性器件精度较低、噪声较大、存在误差随时间积累而无法满足长时间载体姿态测量的问题,提出一种基于三子样姿态更新的扩展卡尔曼姿态估计算法。该算法结合三子样构造姿态更新四元数作为扩展卡尔曼滤波的状态量,利用当地导航系下重力场、磁场中相关数据通过比例积分控制器完成对角速率误差的一次补偿,同时作为扩展卡尔曼观测信息,完成对姿态四元数的实时校正,以此降低误差随时间积累的影响。为验证算法精度,设计转台静态及车载动态试验,试验结果表明在测试约为400 s的时间内,航向角误差约为5°,俯仰角及滚转角误差低于2°,且无发散问题,满足长时姿态测量要求。     

基于MEMS陀螺的压气机静子叶片安装角度测量系统研究

介绍了一种基于MEMS陀螺的高精度压气机静子叶片安装角度测量系统的设计方案。从测量需求入手,利用双轴MEMS陀螺角度传感器和基准工装对小空间、高精度的静子叶片安装角进行测量,推导了倾角测量算法,进行了误差分析,并设计了基于MEMS陀螺的角度测量系统。     

基于MEMS的分散式低阶AHPRS系统设计

设计一种基于MEMS陀螺、加速度计、磁强计以及GPS模块姿态航向位置参考系统(AHPRS).首先,姿态航向参考系统主要由姿态估计卡尔曼滤波器与补偿卡尔曼滤波器构成,通过补偿滤波器周期修正姿态估计滤波器,从而弥补了由于机体的刚体运动而导致姿态角的估计误差;其次,采用分散式卡尔曼滤波器的设计思路,以估计的误差姿态角作为导航系统卡尔曼滤波器的输入量,有效降低了导航滤波方程的阶次,减小了对姿态解算计算机的性能要求;最后,通过仿真与飞行试验验证该AHPRS有效地克服了动态环境下对系统姿态估计偏差大的缺点,提高了系统的姿态航向与速度位置估计精度.     

基于MEMS传感器的高精度姿态角测量研究

针对传统姿态参考系统姿态解算容易受到载体运动加速度的干扰,导致系统精度变低、稳定性变差等问题,提出一种改进的卡尔曼滤波算法。该算法建立基于四元数的惯性系统姿态解算数学模型,并根据载体运动加速度的大小,适时调整卡尔曼滤波器的量测噪声方差的大小,以此减弱卡尔曼滤波过程中运动加速度对姿态角解算精度的影响。采用MEMS三轴陀螺仪、加速度计和磁阻传感器完成载体在电梯升降过程中的测量,对实验测量数据进行姿态解算,结果表明改进后的卡尔曼滤波算法能够有效减小运动加速度对姿态解算的影响,姿态角的均方根误差相对于传统的姿态参考系统降低约40%。     

旋转弹用MEMS陀螺性能测试

常规弹药在发射过程中具有高过载及高速旋转的特点,导致惯性测量单元由于过载和传感器量程不足无法实现正确测量,针对该问题设计了一种基于弹体自身旋转作为驱动的三轴MEMS陀螺.本文首先对该陀螺的工作原理及输出特性进行了分析,设计了相应的测试平台;然后借鉴常规陀螺的测试方法对其进行测试标定;最后对该陀螺输出与加速度关系、标度因数、非线性度、分辨率等性能进行了测试.从而验证该陀螺能够实现对外部角速率的测量,且能够正确敏感外部角速率的变化,最终验证了所设计陀螺的正确性.     

旋转矢量多迭代捷联姿态解算误差补偿算法

为克服高动态条件下的捷联姿态解算存在不可交换性误差的问题,达到进一步增强捷联姿态误差抑制效果的目的,基于角速率的输出提出了等效旋转矢量三子样二次迭代优化算法,推导对应的圆锥补偿算法方程及其表达式。分别在不同圆锥运动频率情况下和不同姿态更新频率情况下,展开仿真验证算法的漂移误差和俯仰角误差,以传统的四元数法、三子样算法为对照,分析仿真数据曲线,得出本改进算法在精度和稳定性方面均有较大提高。在单轴速率转台上进行光纤陀螺的实测验证中,通过调整圆锥运动半偏角和频率,测量获取光纤陀螺惯组输出情况,结果表明:该算法在高动态条件下受圆锥半角、圆锥运动频率的影响较小,性能更加优越。     

等效旋转矢量法在旋转弹姿态解算中的应用

作为捷联惯导的核心问题,姿态更新算法的选择至关重要.针对旋转弹的姿态测试问题,在四元数增量算法的基础上利用等效旋转矢量法对姿态进行优化,给出了姿态解算的数学模型.仿真结果显示,该算法对不可交换误差的抑制效果明显,同时,在一定程度上减小了累积误差,提高了导航精度.     

A Small Low-Cost Hybrid Orientation System and Its Error Analysis

Inertial orientation systems have many potential uses beyond air- and spacecraft applications. Compared to the conventional large-scale system, the novel aspects of an orientation system based on micro electromechanical systems (MEMS) are small size, lightweight, low-power consumption, and low cost by the inclusion of microsensors with on-chip functionality, such as micromachined rate gyroscopes, accelerometers, and etc. However, the performance associated with these low-cost MEMS sensors is generally not satisfied. A conventional strapdown method based on integral of angular rate to figure out attitudes will inevitably induce long-term drift. For eliminating this accumulative error and thus using the low-cost navigation system for a long-duration mission, a hybrid configuration by combining a MEMS-based azimuth-level detector with the conventional strapdown system is proposed in this paper. The azimuth-level detector is composed of three-axis MEMS accelerometers and three-axis MEMS magnetometers. With an absolute solution based on the gravity and the earth magnetic field rather than the integral algorithm, attitude and heading estimation without drift errors can be obtained so as to facilitate adjusting the attitude and heading for the conventional strapdown system. The hierarchical computation process for estimating the attitude and heading using the hybrid system is depicted first. Then, comprehensive system errors including transformation errors of the computation, such as skew, scale, and drift errors, are analyzed. Finally, it is verified by both of formula analysis and experimental test that the accumulative errors can be effectively eliminated via this hybrid scheme.      

Calibration of a Novel MEMS Inertial Reference Unit

This paper describes a novel low-cost inertial reference unit (IRU) developed for spin-stabilized sounding rockets, as well as a method to calibrate the IRU using a one-axis rate table. The IRU contains three orthogonally mounted microelectromechanical system (MEMS) gyros and is intended for use in a low-cost system for attitude determination of sounding rockets. The high spin velocity of the rockets (4–6 r/s) causes sensor misalignments and scale factor errors to have a large effect on the gyro outputs. The performance of the IRU is considerably improved by detailed calibration, including temperature compensation. For sounding rocket applications, the total rate error is typically reduced by more than one order of magnitude. The calibration procedure uses a ramp profile calibration maneuver input at all three sensor axes and a Kalman filter to estimate the 12 error parameters.      

Huber-based unscented filtering and its application to vision-based relative navigation

A new algorithm called Huber-based unscented filtering (UF) is derived and applied to estimate the precise relative position, velocity and attitude of two unmanned aerial vehicles in the formation flight. The relative states are estimated using line-of-sight measurements between the vehicles along with acceleration and angular rate measurements of the follower. By making use of the Huber technique to modify the measurement update equations of standard UF, the new filtering could exhibit robustness with respect to deviations from the commonly assumed Gaussian error probability, for which the standard unscented filtering would exhibit severe degradation in estimation accuracy. Furthermore, contrast to standard extended Kalman filtering, more accurate estimation and faster convergence could be achieved from inaccurate initial conditions. During filter design, the global attitude parameterisation is given by a quaternion, whereas a generalised three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is used to guarantee that quaternion normalisation is maintained in the filter. Simulation results are shown to compare the performance of the new filter with standard UF and standard extended Kalman filtering for non-Gaussian case.     

Quaternions Complementary Filter for Attitude Algorithm Research

Quaternions complementary filter attitude algorithm was conducted on the unmanned aerial vehicle( UAV) platform. This introduces traditional attitude algorithm and attitude quaternion complementary filter algorithm difference,and the attitude quaternion complementary filter algorithm realization are introduced in details.     

基于MEMS陀螺的低成本捷联惯导系统设计

介绍了一种基于MEMS陀螺和石英挠性加速度计的低成本捷联惯性导航系统的设计与实现方法。给出了惯性测量单元(IMU)的模型方程,并在全温下对IMU的输出进行补偿;采用"四元数"法进行姿态计算,通过坐标变换、积分运算确定载体的速度、位置;对惯测样机进行了60 s的静态测试,结果表明该系统短期准确度满足SINS/GPS组合导航系统需求。     

基于GPS与惯性组件的复合测姿系统设计

针对微小型载体空间有限而无法安装大型测姿系统,提出了一种低成本的微型复合测姿方案.复合测姿系统由单天线GPS和MEMS惯性组件构成.利用扩展卡尔曼滤波将单天线GPS和MEMS惯性组件信息融合,提高了姿态估计精度.室外车载实验结果表明,利用该复合测姿系统解算的滚角和俯仰角误差可控制在1°以内,航向角误差可控制在2°以内.     

Precision pointing of imaging spacecraft using gyro-based attitude reference with horizon sensor updates

Remote sensing satellites are required to meet stringent pointing and drift rate requirements for imaging operations. For achieving these pointing and stability requirements, continuous and accurate three-axis attitude information is required. Inertial sensors like gyros provide continuous attitude information with better short-term stability and less random errors. However, gyro measurements are affected by drifts. Hence over time, attitudes based on the gyro reference slowly diverge from the true attitudes. On the other hand, line-of-sight (LOS) sensors like horizon sensors provide attitude information with long-term stability. Their measurements however are affected by the presence of random instrumental errors and other systematic errors. The limitations of inertial and line-of-sight sensors are mutually exclusive. Hence, by optimal fusion of attitude information from both these sensors, it is possible to retain the advantages and overcome the limitations of both, thereby providing the precise attitude information required for control. This paper describes an improved earth-pointing scheme by fusion of the three-axis attitude information from gyros and horizon sensor roll and pitch measurements along with yaw updates from the digital sun sensor. A Kalman Filter is used to estimate the three-axis attitude by online estimation and corrections of various errors from the sensor measurements. Variations in orbit rate components are also accounted for using spacecraft position and velocity measurements from the satellite positioning system. Thus precise earth-pointing is achieved     

Estimation of Attitude and External Acceleration Using Inertial Sensor Measurement During Various Dynamic Conditions

This paper proposes a Kalman filter-based attitude (i.e., roll and pitch) estimation algorithm using an inertial sensor composed of a triaxial accelerometer and a triaxial gyroscope. In particular, the proposed algorithm has been developed for accurate attitude estimation during dynamic conditions, in which external acceleration is present. Although external acceleration is the main source of the attitude estimation error and despite the need for its accurate estimation in many applications, this problem that can be critical for the attitude estimation has not been addressed explicitly in the literature. Accordingly, this paper addresses the combined estimation problem of the attitude and external acceleration. Experimental tests were conducted to verify the performance of the proposed algorithm in various dynamic condition settings and to provide further insight into the variations in the estimation accuracy. Furthermore, two different approaches for dealing with the estimation problem during dynamic conditions were compared, i.e., threshold-based switching approach versus acceleration model-based approach. Based on an external acceleration model, the proposed algorithm was capable of estimating accurate attitudes and external accelerations for short accelerated periods, showing its high effectiveness during short-term fast dynamic conditions. Contrariwise, when the testing condition involved prolonged high external accelerations, the proposed algorithm exhibited gradually increasing errors. However, as soon as the condition returned to static or quasi-static conditions, the algorithm was able to stabilize the estimation error, regaining its high estimation accuracy.