顾及有色噪声的光纤陀螺随机噪声自适应滤波方法

作为光纤陀螺误差的重要组成部分,随机噪声严重影响着光纤陀螺的精度,对光纤陀螺随机噪声进行准确建模和补偿是提升陀螺精度的有效方式。本文针对光纤陀螺随机噪声的复杂性,难以对其进行精确分析,ARIMA （auto-regressive moving average）模型Kalman滤波中有色噪声不能使用状态扩充法建模的问题,扩展了Harvey方程,实现有色噪声白化。同时,考虑先验噪声的不确定性以及模型参数在线更新导致的参数与状态噪声相互耦合,分析了动态Allan方差估计量测噪声的不足,使用VBAKF （variational Bayesian adaptive Kalman filter）实时修正滤波状态噪声与量测噪声。试验表明,Harvey法较传统滤波建模方式,随机噪声序列方差降低40%,Harvey法结合VBAKF使序列方差降低了54%;VBAKF较动态Allan方差,可以更好地估计量测噪声。结果表明,此方法可有效抑制随机噪声Kalman滤波中有色噪声和随机模型不准确的影响,提高随机误差补偿精度。     

动力学模型自适应滤波算法研究

在全球导航卫星系统（global navigation satellite system,GNSS）动态测量中,常采用Kalman滤波进行导航解算。但是,载体运动的不规则性经常会导致动力学模型偏差增大,从而出现定位精度下降的问题。针对此,在实时估计协同转弯模型（coordinated turn,CT）转弯率的基础上提出了两种减弱动力学模型偏差影响的自适应滤波算法。一种是实时估计转弯率的CT模型与改进的椭球约束方程相结合的滤波算法;另一种是通过对载体运动规律的分析,推导了实时估计转弯率的三维转弯模型,提出了一种三维转弯模型与新息向量构造的自适应因子相结合的自适应滤波算法。实验结果表明,这两种算法在不同的机动情况下都能较好地控制动力学模型误差的影响,其精度明显优于标准Kalman滤波和CT模型与常速度模型相结合的滤波算法。尤其是第二种算法,不仅通过自适应估计提高了动力学模型的精确性,还通过自适应因子进一步控制了动力学模型扰动的影响,显著提高了动态导航解的精度和可靠性。     

低精度光纤陀螺随机误差的辨识与仿真

陀螺随机漂移是影响惯性导航和组合导航精度的重要因素。为了有效辨识出光纤陀螺随机漂移噪声的参数,采用了自相关函数、功率谱密度和Allan方差对实测陀螺数据进行分析。实验结果表明:自相关函数、功率谱密度和Allan方差都能有效辨识出陀螺输出信号中的角度随机游走噪声,只有Allan方差能辨识出其中的角速率随机游走噪声。Allan方差可以为光纤陀螺随机漂移建模提供参考。     

GPS/陀螺组合测姿中整周模糊度的快速解算

采用方向余弦矩阵描述姿态,建立GPS/陀螺组合姿态确定系统模型,由矩阵Kalman滤波方法解算整周模糊度的浮点解,然后再利用MCLambda方法得到整周模糊度固定解。仿真实验结果表明,附加方向余弦矩阵约束的Kalman滤波方法可以有效地提高整周模糊度浮点解的精度,使得整周模糊度的固定成功率和效率均得到提高,尤其是在GPS观测条件较差的情况下。     

星敏感器/GNSS定姿系统的联合非线性预测滤波算法

提出一种联合式非线性预测滤波算法,解决该系统在姿态动力学模型误差非高斯分布条件下的多敏感器信息融合问题。从算法结构和估计准则两个方面证明非线性预测滤波(NPF)与Kalman滤波的等效性,分析联合式NPF的算法流程,讨论模型误差方差矩阵的计算方法,给出加权系数矩阵的设计准则;介绍星敏感器和全球卫星导航系统(GNSS)的定姿原理,推导星敏感器/GNSS组合姿态确定系统的联合式NPF滤波模型,分析系统的算法实现流程;进行数值仿真试验,结果表明联合式NPF算法融合NPF与联邦滤波的优良品质,可有效解决姿态动力学模型误差非高斯分布条件下无陀螺姿态确定系统的多敏感器信息融合问题。     

静基座捷联惯导解析法对准研究

初始对准是捷联惯导系统的关键技术之一,对准精度直接影响到导航系统的导航解算精度,静基座捷联惯导卡尔曼滤波法对准的精度和收敛时间受模型参数以及初始条件的影响,对于低精度的捷联惯导,这种影响更大,滤波结果往往不能收敛,甚至发散。采用解析法对准是解决上述问题的有效途径,针对静基座解析法对准做了系统研究,推导了惯性器件误差的解析表达式,分析了对准时间与仪器误差估计精度的关系。实测试验结果表明,给予适当的对准时间,解析法对准亦可接近极限精度;同时,在解析法初始对准中,等效天向加速度计零偏可得到有效估计;等效天向、北向陀螺漂移虽可估计,但随机游走对估计结果的影响不可忽视。     

基于渐消因子的改进Kalman滤波时间尺度估计算法

Kalman滤波时间尺度算法是一种实时的原子钟状态估计方法，在守时实验室具有重要实用价值。由于原子钟状态模型误差估计存在偏差，Kalman滤波时间尺度算法中状态估计可能出现相应异常扰动，应当对状态模型误差进行实时控制。对此，引入基于渐消因子的改进Kalman滤波时间尺度算法。对状态预测协方差矩阵引入渐消因子，利用统计量实时计算渐消因子的量值，控制状态预测协方差阵的增长，降低了原子钟状态估计的扰动。实验结果表明，相比于标准Kalman滤波时间尺度算法和基于预测残差构造自适应因子的Kalman滤波算法，基于渐消因子的改进Kalman滤波时间尺度算法能够提高原子钟状态估计的准确度，改进时间尺度的稳定度。     

GPS/BDS组合姿态测量及精度分析

给出了GPS/BDS组合双差观测模型和姿态测量解算算法,采用Kalman滤波进行动态基线解算的参数估计,利用LAMBDA方法固定双系统模糊度,获得动态基线固定解,最后通过基线的坐标系转换获得姿态角。比较了单系统和GPS/BDS双系统静态姿态角与动态短基线解算结果。试验结果表明,GPS/BDS组合姿态测量的精度和可靠性较GPS单系统都有显著提高。     

基于Partial-EIV模型的TLS姿态估计方法

推导了基于乘性姿态角误差的观测方程,顾及其系数矩阵也含有误差的特点提出一种利用整体最小二乘原理估计姿态参数的新思路。该问题的系数矩阵中同时存在随机元素和固定元素且存在结构性特征,故引入Partial-EIV模型,设计了一种符合其系数矩阵结构特点的新模型。最后通过两组仿真实验将其与已有姿态估计方法进行对比,得出结论:基于Partial-EIV模型的整体最小二乘解法解算精度高于常规最小二乘法;其解算效果与基于乘性姿态角误差的最小二乘法基本一致。表明本文提出的方法正确有效。     

三频BDS/INS紧组合的抗差自适应Kalman滤波

构建了适合北斗三频信号的北斗/惯性紧组合模型。针对三频模糊度解算算法的错误整数解可能对滤波结果造成"污染"这一问题,应用了抗差自适应Kalman滤波算法,优化了所建的模型。车载组合导航实验结果表明:三频模糊度解算算法得到的模糊度正确率平均值为99.84%,直接用于紧组合模型将造成最高达0.7 m的天向位置误差;抗差自适应Kalman滤波算法能消除错误模糊度整数解的影响,东、北、天三个方向的位置最大偏差值在厘米级。此外,载体姿态和速度频繁变化造成的状态预测误差也被自适应处理校正,组合导航的位置均方根误差为东向0.007 m,北向0.014 m,天向0.023 m。研究表明,在三频信号条件下,所采用的抗差自适应Kalman滤波能够增强所构建的紧组合模型的可靠性。     

Airborne vector gravimetry using precise,position-aided inertial measurement units

Vector gravimetry using a precise inertial navigation system continually updated with external position data, for example using GPS, is studied with respect to two problems. The first concerns the attitude accuracy requirement for horizontal gravity component estimation. With covariance analyses in the space and frequency domains it is argued that with relatively stable uncompensated gyro drift, the short-wavelength gravity vector can be estimated without the aid of external attitude updates. The second problem concerns the state-space estimation of the gravity signal where considerable approximations must be assumed in the gravity model in order to take advantage of the ensemble error estimation afforded by the Kalman filter technique. Gauss-Markov models for the gravity field are specially designed to reflect the attenuation of the signal at a specific altitude and the omission of the long-wavelength components from the estimation. With medium accuracy INS/GPS systems, the horizontal components of gravity with wavelengths shorter than 250 km should be estimable to an accuracy of 4–6 mgal (µg); while high accuracy systems should yield an improvement to 1–2 mgal.     

一种基于多普勒频移的GPS自适应滤波算法研究

针对接收机的动态模型对GPS定位精度的影响,提出了一种基于多普勒频移观测的高动态GPS自适应滤波算法。该算法利用GPS伪距测量值以及利用信号载波的多普勒频移所获得的伪距率测量值,在GPS动态滤波中同时观测伪距和伪距率。借助于移动目标的运动矢量模型以及GPS定位误差模型建立了滤波方程。重点讨论了运用该模型进行Kalman滤波的实现过程。仿真实验表明,该模型与传统的方差自适应模型相比,位置精度提高了32%、速度精度提高了25%,应用本文算法能够提高定位精度和改善接收机的动态性能,拓宽高精度、高动态导航的应用范围。     

自适应抗差Kalman滤波在多天线原始观测值瞬时姿态确定中的应用

由载波相位观测值直接解算姿态能实现观测及姿态约束信息的最优利用。本文推导了基于失准角及乘性误差四元数的载波相位观测模型,分别建立了有外部角速度传感器和无外部传感器辅助下姿态参数估计的状态模型;利用自适应抗差滤波估计姿态误差,借鉴分类自适应因子的思想,分别确定模糊度和姿态误差参数的自适应因子,其中姿态自适应因子由Ratio值构造的三段函数确定。自适应抗差滤波能够充分利用约束信息和历史信息,将其融合在浮点解计算过程中,极大提高模糊度浮点解精度及其协方差的结构,在此基础上使用整数最小二乘模糊度降相关平差法(least-squares ambiguity decorrelation adjustment,LAMBDA)方法即能快速搜索出固定解,满足实时性需求。采用实测舰载GNSS 3天线测姿算例对方法进行了验证,结果表明,基于自适应抗差滤波的观测值直接定姿方法效率高、可靠性好。     

海空重力测量关键技术指标体系论证与评估

技术规程是开展海空重力测量作业的重要依据。针对我国现行海空重力测量规范或标准缺乏现势性的问题,开展了海空重力测量测线布设密度、测量精度、空间分辨率、海空重力仪零点漂移与动态重复性等关键性指标分析和论证,提出了由测点重力中误差、系统差和平均误差3个指标组成的测量精度评估体系,以及由格值标定相对精度、零点月漂移量、月漂移非线性变化中误差和月漂移非线性变化限差4个指标组成的海空重力仪稳定性评估体系,给出了相关技术指标的验证和评估方法,同时对涉及船载重力测量测点归算、航空重力测量厄特沃什改正、测量平台倾斜改正及海空重力测量精度评估等关键性数学模型进行了分析和改进,旨在为下一步启动军民融合海空重力测量作业规程编制工作提供技术支撑。     

Robust adaptive filter for shipborne kinematic positioning and velocity determination during the Baltic Sea experiment

Information on trajectory and attitude is essential for analyzing gravimetric data collected on kinematic platforms. Usually, a Kalman filter is used to obtain high-accuracy positional and velocity information. However, this can be affected by measurement outliers and by state disturbances that occur frequently under a fast-changing environment. To overcome these problems, a robust adaptive Kalman filtering algorithm is applied for state estimates, which introduces an equivalent weight to resist measurement outliers and an optimal adaptive factor to balance the contributions of the kinematic model information and the measurements. In addition to the conventional robust estimator, an improved Current Statistical (CS) model is proposed. The improved CS model adopts a variance adaptive learning algorithm, and it can perform self-adaptation of acceleration variance with the innovation information; thus, it can overcome the shortcoming of lower tracking accuracy and avoid setting the maximum acceleration. Following a gravimetry campaign on the Baltic Sea, it is shown in theory and in practice that the robust adaptive Kalman filter is not only simple in its calculation but also more reliable in controlling the colored observation noise and kinematic state disturbance compared with the classical Kalman filter. The improved CS model performs best, especially when analyzing the positioning errors at the turns due to the target maneuvering. Compared to the CS model, the RMS values of the positional estimates derived from the improved CS model decrease by almost 30% in the horizontal direction, and no significant improvement in the vertical direction is found.     

航空重力测量在近海区域的精度评估与分析

利用泊松积分法和点质量法对澳大利亚West Arnhem Land区域的航空重力测量数据进行了精度评估,两种方法得到精度结果基本一致,评估结果表明GT-1A测量系统2′分辨率数据的测量精度优于3×10-5 m/s2,5′分辨率数据的测量精度优于2×10-5 m/s2。利用交叉点平差和泊松积分法、点质量法对渤海区域的航空重力测量进行了内部交叉点平差和外部精度评估,结果表明,内部评估精度与外部评估精度存在一定的差异,以外部评估为准则,CHAGS测量系统在渤海区域5′分辨率的航空重力数据精度优于3.5×10-5 m/s2。综合国内外试验情况分析得到,在近海区域,航空重力数据的分辨率和精度受测量仪器的性能而不同,整体上对于5′分辨率数据而言,可以达到或优于3×10-5 m/s2的精度。     

New results in airborne vector gravimetry using strapdown INS/DGPS

A method for airborne vector gravimetry has been developed. The method is based on developing the error dynamics equations of the INS in the inertial frame where the INS system errors are estimated in a wave estimator using inertial GPS position as update. Then using the error-corrected INS acceleration and the GPS acceleration in the inertial frame, the gravity disturbance vector is extracted. In the paper, the focus is on the improvement of accuracy for the horizontal components of the airborne gravity vector. This is achieved by using a decoupled model in the wave estimator and decorrelating the gravity disturbance from the INS system errors through the estimation process. The results of this method on the real strapdown INS/DGPS data are promising. The internal accuracy of the horizontal components of the estimated gravity disturbance for repeated airborne lines is comparable with the accuracy of the down component and is about 4–8 mGal. Better accuracy (2–4 mGal) is achieved after applying a wave-number correlation filter (WCF) to the parallel lines of the estimated airborne gravity disturbances.     

基于Allan方差和SVR的MEMS陀螺仪随机误差分析与预测

为了使低成本MEMS陀螺仪数据的精度更高，本文提出了一种混合核函数支持向量回归（SVR）的MEMS陀螺仪随机误差预测模型，并通过粒子群优化（PSO）算法对模型参数和核函数参数进行优化；同时通过Allan方差法对SVR预测前后的MEMS陀螺仪随机误差数据进行分析。试验结果表明：混合核函数SVR对MEMS陀螺仪随机误差的预测准确度可达99.99%；当MEMS陀螺仪所处状态不同，但噪声特性相同时，可采用统一的SVR预测模型预测随机误差，研究结果为进一步用于MEMS陀螺仪的实时误差补偿中提供依据。     

Error analysis of satellite attitude determination using a vision-based approach

Improvements in communication and processing technologies have opened the doors to exploit on-board cameras to compute objects’ spatial attitude using only the visual information from sequences of remote sensed images. The strategies and the algorithmic approach used to extract such information affect the estimation accuracy of the three-axis orientation of the object.This work presents a method for analyzing the most relevant error sources, including numerical ones, possible drift effects and their influence on the overall accuracy, referring to vision-based approaches. The method in particular focuses on the analysis of the image registration algorithm, carried out through on-purpose simulations. The overall accuracy has been assessed on a challenging case study, for which accuracy represents the fundamental requirement. In particular, attitude determination has been analyzed for small satellites, by comparing theoretical findings to metric results from simulations on realistic ground-truth data. Significant laboratory experiments, using a numerical control unit, have further confirmed the outcome.We believe that our analysis approach, as well as our findings in terms of error characterization, can be useful at proof-of-concept design and planning levels, since they emphasize the main sources of error for visual based approaches employed for satellite attitude estimation. Nevertheless, the approach we present is also of general interest for all the affine applicative domains which require an accurate estimation of three-dimensional orientation parameters (i.e., robotics, airborne stabilization).