基于互补滤波的动中通天线姿态估计

为了满足低动态下天线稳定的要求,构建了一个基于微机械陀螺、加速度计和磁强计组合的动中通低成本姿态测量系统.该系统利用加速度计重力场分量估计的倾角和磁强计地磁场分量估计的航向角作为辅助信息,校正陀螺漂移误差.根据陀螺与辅助传感器的互补特性,设计一个多轴互补滤波器,利用陀螺的高频分量和辅助信息的低频分量估计姿态角.根据载体机动状态调整控制器参数,使滤波器能自适应选择交接频率,减小机动加速度对姿态估计的影响.实验结果表明,互补滤波能有效地估计出姿态,系统的动态估计精度在±2°内.     

两种多天线GNSS定姿方法的精度分析

基于高精度多天线GNSS基线分量及精度估计结果,实现了两种常用的多天线定姿方法:直接姿态法和最小二乘姿态法。利用一套车载三天线GNSS实测数据和高精度惯性导航系统(陀螺漂移0.005(°)/h,加速度计零偏优于10~(-3)g)输出的姿态结果,深入分析了两种定姿方法的内、外符合精度。实验结果表明:两种定姿所解算的航向角、俯仰角和横滚角的精度分别为:直接法的内符合精度约为0.3°~0.5°、0.3°~1.0°、0.5°~1.0°,最小二乘法约为0.1°、0.2°~0.5°、0.5°~2.0°,即最小二乘法对航向角估计有明显改善,对俯仰角和横滚角改善不明显;两种方法的姿态外符合精度(消除航向系统偏差)基本一致,约为0.08°、0.15°、0.42°,但是最小二乘法得到的航向角系统偏差更小。     

低成本车载GPS/INS组合导航姿态角更新算法

低成本INS系统的元件误差严重影响INS导航精度.针对车载系统,提出一种低成本车载GPS/INS组合导航姿态角更新算法.首先在GPS/INS组合导航Kalman滤波方程基础上,给出两种姿态角更新的观测方程.然后给出利用GPS测速确定航向角的原理,并且对低成本车载INS系统的俯仰角和翻滚角进行了分析,指出由INS随机误差造成的俯仰角和翻滚角误差比其本身量值要大,建议令俯仰角和翻滚角数值保持不变.利用实测算例确定了不同速度下的航向角精度,并且验证了该算法的有效性,以及相对于基于位置、速度组合的Kalman滤波,导航精度有明显提高.     

模糊推理在捷联航姿系统中的应用

为了减小捷联航姿系统航姿解算过程中陀螺漂移和积分过程等因素对航姿精度的影响,结合各传感器输出与载体运动状态相关的特性,提出了一种基于模糊推理的IMU(惯性测量组件)/磁传感器信息融合方法.通过模糊推理系统判断出载体当前的运动状态,在准静态下对IMU中陀螺解算的姿态信息和加表解算的姿态信息进行融合可提高载体的姿态精度,对陀螺解算的航向信息和准静态下磁罗经提供的航向信息进行融合可提高载体的航向精度.经过跑车试验且与跑车过程中作为基准的光纤/GPS航姿系统的航姿结果进行比较,验证了该推理过程和融合算法的正确性.     

基于联邦滤波的INS/GPS/CNS位置、姿态组合算法

为了充分利用姿态量测信息来提高组合导航系统的姿态精度,以联邦滤波为基础,研究了以姿态和位置信息作为观测量的多信息融合导航技术,提出了位置、姿态组合模型,并详细推导了基于联邦滤波的位置、姿态组合算法的观测矩阵的具体形式,最后对系统进行了仿真.仿真结果表明,基于联邦滤波的位置、姿态组合滤波算法能够给出正确的INS误差的估计值,且估计精度较高,平台水平误差角的估计误差控制在10″以内,平台方位误差角的估计误差控制在20″以内,有效地提高组合导航系统的姿态精度.     

航向信息辅助的MIMU/GPS高精度组合导航方法

为了在卫星颗数少于四颗时实现高精度低成本导航,提出了一种基于航向信息辅助的MIMU/GPS高精度组合导航方法。采用MIMU与GPS构成MIMU/GPS组合导航系统;针对GPS卫星颗数少于四颗而无法定位的问题,利用MIMU导航解算获得的位置信息与GPS星历数据信息构造等效伪距,将其与GPS输出的伪距对应相减作为组合导航量测之一;针对组合后航向精度较低甚至发散的问题,利用GPS输出的水平速度计算获得伪航向角,将MIMU导航解算获得的航向角与该伪航向角相减作为量测之二;采用卡尔曼滤波设计组合导航滤波算法。跑车实验结果表明,在多次出现卫星颗数少于四颗时,该组合导航方法的位置精度达到±10.3 m(3σ),水平姿态精度达到±20.1′(3σ),航向精度达到±19.5′(3σ)。因此,该方法有效解决了卫星颗数少于四颗时的高精度导航问题,而且显著提高了航向精度,特别是在失准角较大的情况下也能够实现滤波快速收敛。     

基于递推最小二乘的航姿系统罗差校正

为校正姿态与航向参考系统使用环境中软硬铁产生的罗差,提出了一种利用地磁场连续转动信息补偿三轴软硬铁的方法.由于陀螺短时精度高,初始对准后短时内可得到精度较高的捷联矩阵,如果已知当地磁倾角,由捷联矩阵可将已知的地磁场投影到载体系.当航姿系统改变姿态角连续转动时,采用递推最小二乘算法来估计12个罗差参数.实验说明,与常用罗差校正方法相比,此方法在全姿态范围内效果更好,水平时航向角精度为0.3°,35°倾角航向角精度为1.1°,59°倾角航向角精度为1.2°.     

基于光照区太阳敏感器和陀螺辅助修正的微小卫星磁测技术

微小卫星经常用磁强计作为姿态测量的主要部件,磁强计的测量精度是影响微小卫星定姿性能的重要指标。为提高磁场估计精度,采用太阳敏感器和陀螺对磁强计误差进行辅助测量与修正,推导了磁强计误差估计方法,在光照区以太阳敏感器与陀螺输出作为俯仰滤波器观测量,估计出卫星俯仰角度和角速度。再采用最小二乘方法,利用滤波输出量对磁强计误差进行估计,估计的结果进入滤波器对磁场输出进行测量修正。仿真表明该方法简单易行,姿态角精度提高了1°左右,角速度精度最高提高了0.003(°)/s左右,并增强了卫星稳定性,有利于成像等任务的完成,有效提高了微小卫星导航系统性能。     

光纤罗经和卫星测姿的组合导航算法

为了提高光纤罗经和卫星测姿的组合导航精度和系统稳定性,提出了一种光纤罗经/卫星测姿的组合导航算法。首先分别对光纤罗经、卫星测姿和组合系统的误差进行了数学建模,以姿态作为组合系统的观测量,建立了组合系统的状态方程和观测方程。然后,给出了一种改进的Kalman滤波器,这种滤波器不但能够保证滤波器稳定可靠,防止滤波发散,还提高了准确度,有助于提高组合导航精度。最后,通过静态试验和动态跑车试验得出,光纤罗经/卫星测姿组合导航系统的航向角误差在0.1°以内;通过极区航行实验得出,船舶在高纬度航行中组合导航系统航向角误差在0.5°以内。     

基于单轴旋转INS/GPS组合姿态误差观测的垂线偏差测量方法

单轴旋转INS/GPS组合导航系统的姿态误差直接受垂线偏差的影响,因此利用对单轴旋转INS/GPS组合的姿态误差观测也可实现垂线偏差的估计。首先,利用INS中的三个激光陀螺构建了激光陀螺组合体(LGU)并进行自主姿态测量,以LGU作为姿态基准以获取INS/GPS组合的姿态误差。然后,建立垂线偏差测量的观测方程和状态方程。最终采用Kalman滤波/平滑算法同时实现垂线偏差和其他系统误差的最优估计。通过对状态变量精确、合理地建模,并利用全球重力模型补偿垂线偏差信号的低频分量,从而实现垂线偏差与系统误差的解耦。通过仿真验证了该方法的可行性,仿真所用的航迹由实测数据生成。仿真结果表明该方法能够有效地测量垂线偏差的高频扰动量。由于该方法的测量精度依赖于所采用的陀螺性能,采用角随机游走较小的陀螺可以获得较好的垂线偏差测量结果。船载实验结果表明,该方法测量得到的垂线偏差数据重复性精度优于0.5″。     

Digital filtering of speckle-photography data

Optical methods for nondestructive analysis of strain fields are continuing to generate a great deal of interest among experimentalists; the potential of these methods is considered to be great. One persistent obstacle to the accuracy of such methods is the contamination of the data by ‘optical noise’. This paper describes a digital method which allows extensive reduction of noise components from data records obtained in point-by-point interrogation of double-exposure speckle photographs. The computations prove to be inexpensive and effective. Sample results are given and further applications are suggested.     

Interferogram processing by spatial filtering

This paper describes a technique of interferogram processing by the use of spatial-frequency filtering. Proper part of Fourier spectrum of the interferogram is blocked out by a matched mask located in the focal plane of the imaging system. Depending on the mask shape and dimensions one can obtain

1. interferogram images with delineating fringes or
2. interferogram images of one component of strain.

     

Stochastic filtering of multiphase transport phenomena

Whether or not a multiphase mixture is to be considered heterogeneous is a function of scale and hence also a function of the measurement process. Heterogeneities manifested through the measurement process and sampling frequency (extrinsic heterogeneity) are discussed in relationship to the intrinsic heterogeneity associated with the true physical environment. The question of whether or not a multiphase environment may be scaled is partially a function of the scale of the extrinsic heterogeneity of interest. Thus, it is also a function of the instrumental apparatus, which implies that the instrument must also be scaled. We review restrictive scaling constraints in frequency space that an instrument must satisfy for proper scaling of an experiment. Cushman (1984 Water Resour. Res. and 1985 Acta Appl. Math) developed a theory that incorporates the scale and measurement process directly into the multiphase transport equations and which in turn allows for correlation of field properties over scales of motion. We discuss a generalization of this theory which accounts for integral representations of distributional stochastic processes as a function of the scale of the instrument used in the measurement of the field variables. This allows us to solve the stochastic transport equations in an operational setting, i.e., in terms of measurable quantities. Throughout the article examples are presented to illustrate the concepts.     

H 2 optimal filtering for bilinear systems

The filtering problem is among the fundamental issues in control and signal processing. Several approaches such as H ₂ optimal filtering and H _?? optimal filtering have been developed to address this issue. While the optimal H ₂ filtering problem has been extensively studied in the past for linear systems, to the best of our knowledge, it has not been studied for bilinear systems. This is indeed surprising, since bilinear systems are important class of nonlinear systems with well-established theories and applications in various fields. The problem of H ₂ optimal filtering for both discrete-time and continuous bilinear systems is addressed in this paper. The filter design problem is formulated in the optimization framework. The problem for the discrete-time case is expressed in terms of linear matrix inequalities which can be efficiently solved. The results are used for the optimal filtering of a bilinear model of an electro-hydraulic drive.     

Multi-level convolution filtering technique for digital laser-speckle-velocimetry

A new evaluation method for velocity measurements using digitized, single exposed speckle images is presented. The method is based on a convolution filtering technique used on different levels. Beginning with the computation of a small number of velocity vectors on the coarsest level, the solution is determined step by step on the finer levels, and the number of points is squared from one level to the next. On the coarsest level the vectors are computed with high accuracy, and good approximation is obtained through interpolation of the solution on the next, finer level. Preprocessing of the images considerably improves the accuracy and evaluation speed of the measurement. The computation of the displacement vectors on the finest level without interpolation shows that the number of erroneous vectors computed during the binarization of the images can be reduced by up to 70%. Using the convolution filtering technique on three levels allows for a further reduction of erroneous vectors by up to 40%. Use of smaller kernels and reduction of the kernel and the image area after every interpolation step reduces the computation time for a velocity vector field to 50% compared to the one-level algorithm.List of symbols A image area of the convolution - K kernel of the convolution - O overlapping area - Pc number of multiplications and additions necessary for the computation of a velocity vector - R correlation coefficient - S _c size of the field of the correlation coefficients - S _A size of the image area for the convolution - S _K size of the kernel - c column index - d displacement of the speckles - i, j index of the kernel - n _i number of points of gridi - r row index - t time of capture of the first speckle-image - t time difference between the capture of the two speckle-images - T temperature difference in the thermocapillary convection experiment - z distance of the gridpoints The authors acknowledge the support of the Deutsche Agentur für Raumfahrtangelegenheiten (DARA) under grant number 5o-QV 88981.     

Non-linear filtering for a dust-perturbed two-body model

In standard textbooks on classical mechanics, the two-body central forcing problem is formulated as a system of the coupled non-linear second-order deterministic differential equations. Uncertainties, introduced by the astronomical ‘dust’, are not assumed in the orbit dynamics. The dust population produces an additional random force on the orbiting particle. This work is a continuation of the paper (Sharma and Parthasarathy, Proc. R. Soc. A: Math. Phys. Eng. Sci. 463:979–1003, [2007]) in which the authors developed and analyzed the dust-perturbed two-body model, which accounts for the dust perturbation felt by the orbiting particle. The theory of the dust-perturbed stochastic system was developed using the Fokker–Planck equation. This paper discusses the problem of realizing non-linear stochastic filters for estimating the states of the dust-perturbed planar two-body stochastic system, especially from noisy observations. This paper utilizes the Kushner’s theory of non-linear filtering, which involves stochastic observation term in the evolution of conditional probability density, for deriving the stochastic evolutions of the conditional mean and conditional covariance. The effectiveness of the non-linear filters of this paper is examined on the basis of their ability to preserve the perturbation effect, less random fluctuations in the mean trajectory and stability characteristics in the mean and variance trajectories. Most notably, this paper reveals the efficacy of the second-order approximate Kushner filter for the estimation procedure in contrast to the first-order approximate filter. Simulation results are introduced to demonstrate the usefulness of an analytic theory developed in this paper.     

Unscented Kalman filtering for nonlinear structural dynamics

Joint estimation of unknown model parameters and unobserved state components for stochastic, nonlinear dynamic systems is customarily pursued via the extended Kalman filter (EKF). However, in the presence of severe nonlinearities in the equations governing system evolution, the EKF can become unstable and accuracy of the estimates gets poor. To improve the results, in this paper we account for recent developments in the field of statistical linearization and propose an unscented Kalman filtering procedure. In the case of softening single degree-of-freedom structural systems, we show that the performance of the unscented Kalman filter (UKF), in terms of state tracking and model calibration, is significantly superior to that of the EKF.     

基于改进灵敏度过滤策略的SIMP方法

在传统变密度法SIMP(Solid Isotropic Microstructures with Penalization)中,Sigmund灵敏度过滤策略是解决拓扑优化结果数值不稳定问题的重要方法之一。但在SIMP方法中采用Sigmund灵敏度过滤策略时,有时优化结果会有较多的灰度单元。为了减少拓扑优化结果中灰度单元的数量,提出了一种基于改进灵敏度过滤策略的SIMP方法。在过滤后单元灵敏度的计算中,增加了一个与中心单元过滤前灵敏度有关的部分,该部分在过滤后灵敏度中所占的比重需要通过过滤权重来调节。通过对灵敏度过滤需要的分析,确定了过滤半径和中心单元密度值是影响过滤权重的因素。根据拓扑优化实例的优化结果给出了过滤半径影响过滤权重的情况,并基于过滤半径对过滤权重的影响情况构建了过滤权重的函数。在改进灵敏度过滤策略的基础上,结合双重SIMP算法给出了本文SIMP方法的流程。最后,以悬臂梁结构和简支梁结构为例,验证了本文方法的有效性。与Sigmund灵敏度过滤策略相比,改进的灵敏度过滤策略能有效地减少灰度单元。与双重SIMP方法相比,本文SIMP方法能有效地减少数值不稳定现象。     

Stepped and swept control-based continuation using adaptive filtering

Nonlinear Dynamics - This paper introduces a new online method for performing control-based continuation (CBC), speeding up the model-less identification of stable and unstable periodic orbits of...