晃动基座下激光陀螺捷联导航系统初始对准的预滤波

针对激光陀螺捷联惯性导航系统在晃动基座下进行初始对准时激光陀螺和加速度计噪声过大,而采用低通滤波或小波方法不能有效实时地实现噪声抑制的问题,提出一种采用IIR低通滤波器和基于隐式马尔可夫模型的稳态卡尔曼滤波相结合的新的预滤波方法。首先,将传感器输出通过低通滤波,然后,再通过一个基于隐式马尔可夫模型的稳态卡尔曼滤波,从而有效地降低基座晃动带来的噪声,而不降低对准精度。实验结果表明,本文提出的预滤波方法计算复杂度低,滤波效果明显,在发动机开动的情况下,可以把导航系统激光陀螺的噪声标准差由300°/h降至1°/h,加速度计的噪声标准差由11 mg降至40μg。结果表明,提出的预滤波器能够很好地辅助激光陀螺捷联导航系统在晃动基座下完成精对准。

惯性捷联导航系统的标定和数据对准技术

惯性捷联导航系统是基于牛顿力学原理进行导航数据采集的系统,在舰船等领域有非常广泛的应用。由于惯性捷联导航系统工作过程中与载体的运动是耦合关系,因此,惯性捷联导航系统的误差分析和测量参数标定非常重要,是提高惯性捷联导航系统导航精度的关键。本文研究船舶惯性捷联导航系统的基本原理、惯性捷联导航系统的关键部件测量误差建模、测量数据的标定和数据对准等,有助于提高船舶惯性捷联导航系统的数据精度。

导航系统实验教学的研究

实验教学是培养学生动手实践、工程意识和创新能力的主要手段。紧密结合航空航天特色专业必修课程导航系统的授课情况,开设了完整的适用于本科阶段培养的导航系统系列实验,从而提升了学生对课程核心内容的掌握程度,提高了学生设计实验方案、解决实验问题、分析实验结果的能力,达到了激发学生学习热情与创造性思维能力培养的目的。

新型双CPU架构的捷联惯性导航微机系统

介绍了一种以TI公司高性能DSP芯片TMS320C6713作为捷联解算核心处理器和凌阳SPCE061A单片机作为数据采集和接口控制器的双CPU结构的新型捷联导航系统.该系统充分利用了TMS320C6713的处理速度快、浮点数据处理能力强和SPCE061A控制能力强的各自特性.双机通过DSP的HPI接口完成快速的数据通讯.该系统具有处理速度快、体积小、重量轻、功耗小、性能稳定等优点.

激光捷联惯性/卫星组合导航系统基本原理及应用情况

激光捷联惯性/卫星组合导航系统是国外飞机上普遍采用的一种导航设备,但在国内飞机上的应用则刚刚起步。本文简要介绍了激光捷联惯性/卫星组合导航系统的基本原理及应用情况。

基于FPGA+DSP的微小型捷联惯导系统的设计

为满足导航系统设计的小型化、实时性要求,本文提出了一种基于FPGA+DSP的实现方案。该方案的设计思路是:将FPGA映射到DSPEMIF的一段地址空间,并用FPGA来完成多通道信号的采集;DSP根据接收到的数据完成导航解算并以总线(如CAN)形式输出给控制设备和外部测试设备。本文重点介绍了惯性测量单元、数据采集与接口电路和导航计算机等方面的硬件和软件设计;最后对已完成的试验样机进行全面性能测试,结果表明此设计可以达到预期的设计要求。

单目视觉里程计/惯性组合导航算法(英文)

提出一种单目视觉里程计/捷联惯性组合导航定位算法。与视觉里程计估计相机姿态不同,惯导系统连续提供相机拍摄时刻对应的三维姿态,克服了单纯由视觉估计相机姿态精度低造成的长距离导航误差大的问题。通过配准和时间同步,用惯导系统解算的速度和视觉里程计计算的速度之差作为组合导航的观测量,采用Kalman滤波修正组合导航系统的误差,同时估计视觉里程计标度因数误差。分别在室内外不同环境下进行了22 m的推车实验和1412 m的跑车实验,定位误差分别为3.2%和4.0%。与Clark采用姿态传感器定期更新相机姿态估计结果的方法相比,单目视觉里程计/惯性组合导航定位精度更高,定位误差随距离增长率低,适合步行机器人或轮式移动机器人在复杂地形环境下车轮严重打滑时的自主定位导航。

基于UKF的新型北斗/SINS组合系统直接法卡尔曼滤波

针对传统的间接法卡尔曼滤波在北斗/捷联惯导(serial inertial navigation system,SINS)组合导航系统中无法实现较高的定位精度且计算的冗余度大的缺点,提出一种基于无迹卡尔曼滤波(unscented Kalman filter,UKF)的新型组合系统滤波算法。本算法以SINS输出的导航参数及平台误差角等作为系统状态,无源北斗输出的位置速度参数作为量测,采用改进的UKF方法进行数据融合,并直接计算组合系统导航参数的最优估计。实验结果表明,新算法可以降低对伪距误差模型的精确度要求,同时避免非线性系统状态方程的线性化,简化滤波参数的调整过程,从而有效地缩短组合导航系统的解算时间,提高定位精度。

动调陀螺标度因数非线性误差补偿研究

捷联惯性测量组件的非线性误差主要体现在陀螺和加速度计的标度因数上,为了减小捷联惯性测量组件中的动调陀螺的非线性误差,提出了一种对陀螺测量曲线进行自适应分段最佳逼近拟合方法.该方法在分析陀螺非线性误差产生的原因基础上,推导出陀螺的标度因数非线性误差补偿模型,设计了试验标定方案,在惯性测量组件的整个测量范围内进行自适应分段,每段用一个高次曲线最佳逼近,可得到陀螺测量模型在每个分段区间的精确函数描述,从而可以对陀螺非线性测量误差进行实时补偿.系统的速率试验和摇摆试验结果表明,自适应分段高次曲线最佳逼近的方法有效地提高了陀螺的角速度测量精度,最大能提高约10倍.

Initial Alignment Technique for SINS of Vehicles in the Moving State

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.

AN IMPROVED ROTATION VECTOR ATTITUDE ALGORITHM FOR LASER STRAP-DOWN INERTIAL NAVIGATION SYSTEM

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.

DESIGN AND REALIZATION OF SINS/TWO-ANTENNA GPS INTEGRATED NAVIGATION SYSTEM

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.

Application of unscented Kalman filter to novel terrain passive integrated navigation system

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.

An improved computation scheme of strapdown inertial navigation system using rotation technique

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.

Federated unscented particle filtering algorithm for SINS/CNS/GPS system

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.

Adaptive filter for a miniature MEMS based attitude and heading reference system

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,

Evaluation and optimization of strapdown velocity numerical integration algorithms for SINS in spinning ballistic missiles

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.

Subway location method based on SINS/DR integrated navigation and map-matching technology

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.

Magnetometer calibration algorithm based on ellipsoid constraint

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.