非高斯环境下的GPS自适应多径抑制技术

为解决非高斯环境下的全球定位系统(GPS)信号多径抑制,尤其是短延迟多径抑制问题,推导出一种具有权值修正更新能力的改进最小平均p范数(LMP)算法。该算法通过对权值变化趋势项的预测可有效减小算法的收敛时间,通过对其参数变化影响的理论分析和仿真,证实在所设实验条件下算法的收敛时间最大可减少50%。为在自适应多径参数估计时应对非高斯噪声环境的影响,同时获得更大的处理增益,设计了改进的自适应多径估计方案,将算法应用于方案的权值更新,并对更新后的权值引入均值滤波,仿真证明所提多径抑制方案在非高斯和高斯环境下均能表现出很好的稳定性和有效性。     

基于小波域贝叶斯估计模糊萎缩的SAR图像降斑算法

提出了基于小波域高斯混合模型贝叶斯估计模糊萎缩的SAR图像降斑算法.该算法分析了SAR图像在平稳小波变换(SWT)域中的统计模型,并用高斯混合模型对其进行描述,推导出基于贝叶斯估计的信号最小均方误差(MMSE)的模糊萎缩因子.籍此再根据小波域相邻尺度间小波系数的相关性,采用分区域模糊萎缩思想,很好地得到无斑点真实信号小波系数的估计值.仿真结果表明该算法在大大抑制斑点噪声的同时,有效地保持了边缘,其性能优于改进Lee滤波、小波软阈值和SWT萎缩降斑算法.     

多自由度非高斯随机振动控制

在振动试验台上进行多自由度(MDOF)随机振动激励时,传统的控制方法生成的驱动信号及试验台的响应信号都是高斯信号。但真实的振动干扰信号多是超高斯的;而相比于高斯激励,亚高斯激励可降低驱动信号的最大幅值。为实现多自由度亚高斯和超高斯振动控制,提出一种多自由度非高斯随机振动控制方法,该方法采用系统辨识解决系统耦合问题,而后通过选择特殊的相位生成非高斯伪随机驱动信号,再经过时域随机化得到真随机非高斯驱动信号。基于Hexapod平台的多自由度微振动试验台的亚高斯和超高斯实验表明,在试验台的响应功率谱(PSD)满足工程中常用的±3dB精度的同时,亚高斯驱动信号的最大幅值相比于高斯驱动信号的最大幅值降低了20%以上;超高斯响应信号的峭度与参考峭度的误差在0.2之内。实验结果验证了所提方法的有效性。     

基于自适应粒子滤波的涡扇发动机故障诊断

针对涡扇发动机非线性、非高斯的特点,提出了一种自适应的粒子滤波算法用于涡扇发动机气路部件突变故障的诊断.为了减小算法的计算量并且保证滤波精度,分析了滤波精度和样本数目的关系,提出根据滤波过程中状态的方差自适应地调整粒子数,在保证一定的滤波精度下可以有效地减少滤波过程中使用的粒子数,提高了算法的实时性.同时,引入扩展卡尔曼滤波(EKF)用于更新粒子,产生重要概率密度函数,在一定程度上避免了粒子的退化.通过某型涡扇发动机的仿真分析表明:改进的算法相比标准粒子滤波算法用于涡扇发动机气路部件故障诊断时,参数估计的方均根误差减小了50%左右,且算法的计算量减小了30%.     

改进的ICCP地磁匹配算法

本文在分析等值线约束迭代最近点(ICCP)匹配算法基本原理的基础上,针对ICCP算法在非刚性变换情形下,就难以取得理想匹配效果的情况,提出了改进的ICCP算法。该算法首先用ICCP匹配算法修正初始位置误差和航向误差,然后采用逐点匹配,再迭代该过程的方法,逐点修正位置误差。仿真实验表明,改进的ICCP算法能够实现准确定位,定位精度在一个网格精度以内。     

基于模糊自适应滤波的水下INS/DVL组合导航研究

由于水下环境的复杂性,多普勒测速(DVL)误差的均值和噪声方差等统计特性均存在跳变现象,影响了INS/DVL组合导航精度。为此提出了一种基于模糊自适应滤波的水下INS/DVL组合导航算法,通过实时监测滤波残差的均值变化以及滤波残差方差与理论滤波残差方差的不一致程度,利用隶属度函数在线修正多普勒测速偏差以及量测噪声的统计特性。本文改进了已有模糊自适应滤波算法未考虑观测误差均值跳变以及对残差方差变化过于敏感的问题,并对DVL零偏跳变进行了修正。试验表明,所提出算法对多普勒测速误差的均值和噪声方差跳变具有较强的适应性,能够有效提高水下INS/DVL组合导航精度。     

GHQF精度分析及其在组合导航中的应用

针对非线性滤波算法在组合导航系统中的应用问题,利用泰勒级数展开对无味卡尔曼滤波(UKF)、容积卡尔曼滤波(CKF)和高斯厄米特积分滤波(GHQF)三种非线性高斯滤波算法的性能进行了比较分析;基于泰勒展开的精度分析表明,UKF和CKF从四阶项开始出现截断误差,而GHQF可以逼近任意阶精度的非线性系统的后验均值;以CNS/SAR/SINS非线性组合导航系统为应用背景,对三种滤波算法的精度进行了仿真验证。数学仿真结果表明,与UKF和CKF相比,GHQF具有更高的滤波估计精度。     

光电探测系统指向误差分析、建模与修正

针对光电探测系统(EODS)的高精度指向要求,提出一种基于半参数同归模型(SPRM)的改进算法.全面分析了误差来源,如光学系统的光轴一致性误差、机械框架的垂直度和回转误差、控制系统的稳定跟踪误差等,采用多体系统运动学理论,建立了具有明确物理意义的指向误差线性模型.同时,针对系统中的非线性误差因素,提出了半参数回归模型改...     

基于零均值特性的箕舌线变步长 LMS算法

针对基于箕舌线变步长LMS算法步长更新公式易受噪声干扰的问题，根据高斯自噪声的零均值特性，提出基于零均值特性的箕舌线变步长LMS算法，使算法的抗噪声干扰能力增强。若2算法选取相同参数α、β，则基于零均值特性的箕舌线变步长LMS算法相对于箕舌线变步长LMS算法具有小的稳态误差。在保证算法收敛的条件下，基于零均值特性的箕舌线变步长LMS算法相对箕舌线变步长LMS算法具有较快的收敛速度。     

基于改进容积卡尔曼滤波的惯性/光流组合自主测速方法

针对容积卡尔曼滤波算法在惯性/光流组合测速数据融合时出现由于各系统输出数据频率不一致导致融合精度有限的问题,提出了一种基于多速率残差校正的改进容积卡尔曼滤波算法.通过当前时刻误差估算组合导航系统残差,再使用估算后的残差对速度估计值进行补偿,最终实现惯性/光流组合系统速度测量值的数据融合.实验结果表明,通过提出的改进容积卡尔曼滤波对惯性/光流数据进行融合后,东向速度均方根误差为0.2964m/s,北向速度均方根误差为0.06m/s,与现有其他卡尔曼滤波算法相比,此方法可显著提高惯性/光流组合系统的速度测量精度.     

Sigma-mean monitoring for the local area augmentation of GPS

The local area augmentation system (LAAS) is a ground-based differential GPS system being developed to support aircraft precision approach and landing navigation with guaranteed integrity. To quantitatively appraise navigation integrity, an aircraft computes vertical and lateral protection levels using the standard deviation of pseudo-range correction errors, /spl sigma//sub pr/spl I.bar/gnd/, broadcast by the LAAS ground facility (LGF). Thus, one significant integrity risk is that the true standard deviation (sigma) of the pseudo-range correction error distribution may grow to exceed the broadcast correction error sigma or that the true mean of the correction error distribution becomes excessive during LAAS operation. This event may occur due to unexpected anomalies of GPS measurements. To insure that the true error distribution is bounded by a zero-mean Gaussian distribution with the broadcast sigma value, real-time sigma and mean monitoring is necessary. Both direct estimation and cumulative sum (CUSUM) methods are useful to detect violations with acceptable residual integrity risk. For sigma monitoring, the estimation method more rapidly detects small violations of /spl sigma//sub pr/spl I.bar/gnd/ but the fast initial response (FIR) CUSUM variant more promptly detects significant violations that would pose a larger threat to user integrity. For the purposes of mean monitoring, the FIR CUSUM variant is superior to the estimation method in detecting any mean violations. The results demonstrate that real-time protection is achievable against all sizes of sigma/mean failures that can threaten navigation integrity.     

A novel LAAS pseudo-range error over-bound method based on improved pseudo-range error distribution model

The high level of safety demand of civil aviation requests local area augmentation system (LAAS) extremely high navigation integrity performance. A new LAAS pseudo-range error overbound method is proposed in this paper to improve the integrity of LAAS. Firstly, a more practical pseudo-range error distribution model is established. Then, by calculating the relationship between the statistical uncertainty of the model parameter and the integrity risk, a new method is proposed to calculate the pseudo-range error over-bound model. This method can effectively reduce the inflation factor and the resulting conservativeness of the over-bound model. Comparative experiments show that the method proposed in this paper performs better and satisfies the requirements of real applications.     

Adaptive robust cubature Kalman filtering for satellite attitude estimation

This paper is concerned with the adaptive robust cubature Kalman filtering problem for the case that the dynamics model error and the measurement model error exist simultaneously in the satellite attitude estimation system. By using Hubel-based robust filtering methodology to correct the measurement covariance formulation of cubature Kalman filter, the proposed filtering algorithm could effectively suppress the measurement model error. To further enhance this effect and reduce the impact of the dynamics model error, two different adaptively robust filtering algorithms, one with the optimal adaptive factor based on the estimated covariance matrix of the predicted residuals and the other with multiple fading factors based on strong tracking algorithm, are developed and applied for the satellite attitude estimation. The quaternion is employed to represent the global attitude parameter, and three-dimensional generalized Rodrigues parameters are introduced to define the local attitude error. A multiplicative quaternion error is derived from the local attitude error to maintain quaternion normalization constraint in the filter. Simulation results indicate that the proposed novel algorithm could exhibit higher accuracy and faster convergence compared with the multiplicative extended Kalman filter, the unscented quaternion estimator, and the adaptive robust unscented Kalman filter.     

Sigma inflation for the local area augmentation of GPS

The Local Area Augmentation System (LAAS) is the differential satellite navigation architectural standard for civil aircraft precision approach and landing. While the system promises great practical benefit, a number of key technical challenges have been encountered in the definition of the architecture. Perhaps chief among these has been the need to ensure compliance with stringent requirements for navigation Integrity. In this context, this research investigates the sensitivity of integrity risk to statistical uncertainties in the knowledge of reference receiver error standard deviation (σ_{pr_gnd} ) and error correlation across the multiple reference receivers to be used in the LAAS ground segment. A new, detailed approach toward mitigating the integrity risk due to parameter statistical uncertainty is presented     

Formulation of a time-varying maximum allowable error for ground-based augmentation systems

Ground-based augmentation systems (GBAS), such as the federal aviation administration's local area augmentation system (LAAS), protect GPS users against signal anomalies by monitoring for rare satellite faults. This paper introduces a new, time-varying MERR (maximum-allowable error in range) formulation that enables proof of integrity for ground-based fault monitoring. The time-varying MERR supersedes earlier MERR methods which relied on a static integrity test. The utility of these earlier methods was limited in that they neglected GBAS time-to-alert (TTA) requirements and restricted the choice of the monitor filter, requiring its impulse response to match that of the user ranging-error filter. By contrast, the time-varying MERR explicitly incorporates TTA and places no restrictions on monitor filter design. These attributes are critical for correctly evaluating system integrity and for crediting the integrity benefits of GBAS systems with aggressive filter designs and process timing.     

局域增强系统级联双频平滑技术研究(英文)

针对电离层误差时间梯度和空间梯度对局域增强系统的不利影响,提出使用级联双频平滤波方法解决此问题。级联双频平滤波先使用一个双频平滑滤波器精确估计电离层误差,利用得到的估计值修正码伪距观测量中的电离层误差,再使用一个双频平滑滤波器削弱噪声。这样,电离层误差被完全从平滑过程中移出,由L2码观测量引入的附加的噪声也被压制。基于中国民航新航行系统实验室的局域增强系统测试平台所采集的数据对级联双频平滤波的有效性和基于级联双频平滤波的局域增强系统的精度进行了分析。结果表明级联双频平滤波技术可以同时消除电离层误差时间梯度和空间梯度导致的平滑滤波残差和差分校正残差,并具有较低的滤波噪声。     

A novel optimal data fusion algorithm and its application for the integrated navigation system of missile

For Inertial Navigation System(INS)/Celestial Navigation System(CNS)/Global Navigation Satellite System(GNSS) integrated navigation system of the missile, the performance of data fusion algorithms based on the Cubature Kalman Filter(CKF) is seriously degraded when there are non-Gaussian noise and process-modeling errors in the system model. Therefore, a novel method is proposed, which is called Optimal Data Fusion algorithm based on the Adaptive Fading maximum Correntropy generalized high-degree...     

时钟模型辅助的惯性/卫星紧组合导航算法研究

针对卫星信号受到遮挡或者干扰、卫星接收机收星数不足的问题,提出了一种时钟模型辅助的惯性/卫星紧组合导航算法。通过正常紧组合状态下的钟差、钟漂估计值建立钟差和钟漂的数学模型,在可见卫星少于4颗时,用时钟模型计算得到的钟差和钟漂作为系统钟差、钟漂的真实值引入观测信息中,并省去状态变量中的钟差和钟漂项,增加了系统的可观测性。最后,通过采集跑车试验数据进行了离线数据仿真试验。试验结果表明,提出的时钟模型辅助的惯性/卫星紧组合导航算法在可见卫星不足的情况下取得了良好的效果。     

时钟模型辅助的惯性/卫星紧组合导航算法研究

针对卫星信号受到遮挡或者干扰、卫星接收机收星数不足的问题,提出了一种时钟模型辅助的惯性/卫星紧组合导航算法。通过正常紧组合状态下的钟差、钟漂估计值建立钟差和钟漂的数学模型,在可见卫星少于4颗时,用时钟模型计算得到的钟差和钟漂作为系统钟差、钟漂的真实值引入观测信息中,并省去状态变量中的钟差和钟漂项,增加了系统的可观测性。最后,通过采集跑车试验数据进行了离线数据仿真试验。试验结果表明,提出的时钟模型辅助的惯性/卫星紧组合导航算法在可见卫星不足的情况下取得了良好的效果。     

基于气压高度辅助的机载自主完好性监测算法

卫星接收机自主完好性监测是指根据用户接收机的多余观测值监测用户定位结果的完好性,其目的是在导航过程中检测出发生故障的卫星,并保障导航定位精度。针对卫星接收机自主完好性监测算法可用性不足的问题,结合机载实际导航系统配置,提出了一种基于气压高度表辅助的机载自主完好性监测算法。综合利用卫星导航系统及气压高度表观测信息,建立联合系统的观测模型,推导了基于多解分离的完好性监测及保护级别计算方法。仿真结果表明,相比于传统的接收机自主完好性监测算法,该算法在可见星为5颗时仍能识别故障卫星。该算法具有更好的故障检测能力及可用性,能有效提高卫星导航系统的完好性监测性能,从而保证卫星导航系统的精度和可靠性。