一种低动态高抖动环境下的GPS/INS紧组合方法

针对低动态高抖动环境下,GPS/INS紧组合精度的重要因素之一——惯性测量单元(IMU)数据中的噪声,该文提出利用小波降噪方法分离IMU数据中的噪声和有用信号以提高GPS/INS紧组合的精度。首先对IMU数据进行小波分解后得到的高频系数进行阈值量化处理,然后将GPS观测数据与降噪后的IMU数据进行GPS/INS紧组合解算,最终得到载体的导航信息。实例结果表明,该方法可以大幅提升GPS/INS紧组合的精度和稳定可靠性。     

一种低动态高抖动环境下的GPS/INS紧组合方法

针对低动态高抖动环境下,GPS/INS紧组合精度的重要因素之一——惯性测量单元(IMU)数据中的噪声,该文提出利用小波降噪方法分离IMU数据中的噪声和有用信号以提高GPS/INS紧组合的精度。首先对IMU数据进行小波分解后得到的高频系数进行阈值量化处理,然后将GPS观测数据与降噪后的IMU数据进行GPS/INS紧组合解算,最终得到载体的导航信息。实例结果表明,该方法可以大幅提升GPS/INS紧组合的精度和稳定可靠性。     

一种低动态高抖动环境下的GPS/INS紧组合方法

针对低动态高抖动环境下,GPS/INS紧组合精度的重要因素之一——惯性测量单元(IMU)数据中的噪声,该文提出利用小波降噪方法分离IMU数据中的噪声和有用信号以提高GPS/INS紧组合的精度。首先对IMU数据进行小波分解后得到的高频系数进行阈值量化处理,然后将GPS观测数据与降噪后的IMU数据进行GPS/INS紧组合解算,最终得到载体的导航信息。实例结果表明,该方法可以大幅提升GPS/INS紧组合的精度和稳定可靠性。     

基于低通滤波的GPS/INS组合导航模型研究

惯导系统中惯性元件误差是影响惯性导航及组合导航精度的重要因素。本文首先分析了INS加速度计及陀螺仪在不同方向上的原始观测数据误差源及其相关作用,并给出低通滤波及GPS/INS(Global Positioning System/Inertial Navi-gation System)组合导航模型。在此基础上,提出采用低通滤波器消除INS原始数据中的高频随机误差,提高GPS/INS组合导航精度的技术路线。模拟INS的线速度及角加速度原始观测数据,对本文模型进行INS自主导航测试,导航精度得到明显提高。进一步采用实测数据进行组合导航分析,滤波前后计算的位置误差比较可以看出滤波后的导航解要优于滤波前,X、Y、Z三个方向上导航精度分别提高了15.1%、28.3%、28.1%。在残差最大值的比较上,三个方向上都有所减小,说明本文模型可有效提高导航精度。     

基于高阶AR模型的陀螺随机漂移模型

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。首先用周期函数拟合和小波变换两种方法分别对随机漂移中的周期噪声进行分析和处理;然后对相关噪声建立高阶AR模型;最后将该模型应用在GPS／INS组合导航Kalman滤波中,并对结果进行分析和比较。结果表明,相比于周期函数拟合,小渡变换不仅能够更好地削弱周期噪声的影响,还能够削弱高频白噪声的影响;相比于一阶马尔科夫过程,高阶AR模型能够更好地描述随机漂移中的相关噪声;基于小渡变换和高阶AR模型的GPS／INS组合导航具有明显的优势。     

多普勒平滑伪距在GPS/INS紧耦合导航中的应用

针对GPS/INS紧耦合导航中GPS伪距观测值精度较低的问题,提出了一种多普勒平滑伪距在GPS/INS紧耦合导航的应用算法。首先给出了GPS/INS紧耦合导航详细的动力学模型和观测模型,在载波相位平滑伪距的基础上推导了多普勒平滑伪距的具体算法和方差-协方差计算公式,并引入遗传算法对平滑因子进行最优估计;然后利用实测数据验证了新算法的有效性。结果表明,平滑算法能够有效提高伪距观测值的精度,从而提高组合导航的定位精度,相对于载波相位平滑伪距,多普勒平滑伪距的精度略有提高,而且多普勒平滑伪距不受周跳的影响,算法的效率更高。与此同时,伪距观测值精度的提高使其与伪距率观测值精度相当,增强了滤波系统的稳定性。     

一种GPS/GLONASS/INS数据融合算法

针对卫星导航系统和惯性导航系统(INS)的不同特性,提出了一种GPS/GLONASS/INS数据融合算法。采用差分自适应检测算法、改进码平均相位算法以及位置联合解算方法实现了GPS/GLONASS数据融合,借助于改进的粒子滤波器、INS误差模型建立系统状态方程和观测方程,完成GPS/GLONASS系统速度值和INS系统速度值数据融合,提高组合导航系统精度和可靠性。使用真实数据对数据融合算法性能进行仿真分析,结果表明所设计算法是有效的,能够处理非线性非高斯条件下的滤波估计,提高滤波精度和系统可靠性。     

基于伪距和多普勒观测值的DGPS/INS紧组合导航算法研究

GPS/INS组合导航具备数据更新率高、抗干扰、能够提供包括姿态在内的全部导航信息等优点,因此在测绘领域得到了广泛应用。但是目前国内GPS/INS组合导航研究主要集中在单GPS接收机与INS的组合模式,针对此问题,本文研究基于伪距和多普勒观测值的DGPS/INS紧组合导航算法,给出组合导航扩展卡尔曼滤波的状态方程和量测方程。实测数据解算表明,该组合模式下的导航精度得到显著提高。     

UKF在GPS/INS组合导航系统中的应用

扩展卡尔曼滤波(EKF)是GPS/INS组合导航系统工程实现中常用的一种数据融合方式。但EKF线性化误差在一定程度上影响了GPS/INS组合导航系统精度的提高。Unscented卡尔曼滤波器(UKF)是一种非线性滤波器,它能有效地减小线性化误差对GPS/INS组合导航系统精度的影响。基于四元数法建立了GPS/INS组合导航系统的非线性误差方程模型;最后通过数字仿真验证了UKF组合导航系统应用中的性能。     

应用EKF平滑算法提高GPS/INS定位定姿精度

为了提高城市遮挡环境下GPS较长时间(60s)无法单独定位情况下GPS/INS组合定位定姿精度,研究了扩展卡尔曼滤波及其RTS(Rauch Tung Striebel)平滑算法;同时给出了基于ψ角惯导误差模型的GPS/INS组合系统状态方程和基于位置、速度更新的量测方程。实验中模拟GPS信号失锁60s,应用RTS后处理算法进行了GPS/INS组合数据处理。结果表明,扩展卡尔曼滤波EKF平滑算法可以有效地提高城市遮挡环境下GPS/INS组合定位定姿精度,特别是对GPS失锁的情况。从而很大程度上降低对高成本惯导的依赖。     

基于小波阈值消噪自适应滤波的GPS/INS组合导航

惯导系统中惯性元件误差是影响惯性导航及其组合导航精度的重要因素.在GPS/INS组合导航自适应滤波的基础之上,提出利用小波进行阈值消噪以提高组合导航精度.首先对惯性元件输出信号进行频谱分析,确定相应的多分辨分析尺度以及不同尺度下对高频系数采取的相应措施.对噪声占主要成分的尺度将其高频系数全部置零,对噪声和有用信号共同占有的尺度将其高频系数作阈值处理.利用实测数据进行验证,结果表明这种方法能够有效地削弱惯性元件误差的影响,提高GPS/INS组合导航系统的精度和可靠性.     

BDS RTK／MEMS-INS组合数学模型研究与性能分析

卫星导航系统和惯性导航系统（INS）具有极强的互补性,两者组合能有效提高导航定位结果的可用性、连续性和可靠性. 随着北斗卫星导航系统（BDS）的快速发展和低成本惯导元件（IMU）性能的不断提高,进行基于BDS和低成本IMU的组合导航系统相关理论和技术研究具有很强的研究意义和实用价值. 本文首先对BDS RTK／M-EMS INS组合理论模型进行推导,并利用实测车载数据对组合系统的性能进行分析. 实验结果表明,在BDS中引入低成本IMU,可以在不损失定位精度的同时有效改善测速精度. 组合后在车载动态中定位精度影响为mm级,而速度误差改善在北、东、地方向达到了75.8％、79.5％、66.7％. 此外,在BDS+INS紧组合中使用双频数据可以改善测速定姿精度,速度误差改善为18.2％、33.3％、33.3％,姿态误差改善为41.1％、26.7％、59.0％.      

Design of a low-cost attitude determination GPS/INS integrated navigation system

Due to their complementary features of GPS and INS, the GPS/INS integrated navigation system is increasingly being used for a variety of commercial and military applications. An attitude determination GPS (ADGPS) receiver, with multiple antennas, can be more effectively integrated with a low-cost IMU since the receiver gives not only position and velocity data but also attitude data. This paper proposes a low-cost attitude determination GPS/INS integrated navigation system. The proposed navigation system comprises an ADGPS receiver, a navigation computer unit (NCU), and a low-cost commercial MEMS IMU. The navigation software includes a fault detection and isolation (FDI) algorithm for integrity. In order to evaluate the performance of the proposed navigation system, two flight tests have been performed using a small aircraft. The first flight test confirmed the fundamental operation of the proposed navigation system and the effectiveness of the FDI algorithm. The second flight test evaluated the performance of the proposed navigation system and demonstrated the benefit of GPS attitude information in a high dynamic environment. The flight test results show that the proposed ADGPS/INS integrated navigation unit gives reliable navigation performance even when anomalous GPS data is provided and gives better navigation performance than a conventional GPS/INS unit.     

惯性导航与卫星导航紧耦合技术发展现状

对紧耦合方案、最优估计滤波算法和硬件开发等几方面进行了总结分析。分析了传统的INS／GPS松组合系统和INS／GPS紧耦合系统的区别；给出了INS／GPS紧耦合系统国内外的发展状况；指出INS／GPS紧耦合系统所涉及的关键技术。     

Hybrid derivative-free extended Kalman filter for unknown lever arm estimation in tightly coupled DGPS/INS integration

Differential carrier phase observations from GPS (Global Positioning System) integrated with high-rate sensor measurements, such as those from an inertial navigation system (INS) or an inertial measurement unit (IMU), in a tightly coupled approach can guarantee continuous and precise geo-location information by bridging short outages in GPS and providing a solution even when less than four satellites are visible. However, to be efficient, the integration requires precise knowledge of the lever arm, i.e. the position vector of the GPS antenna relative to the IMU. A previously determined lever arm by direct measurement is not always available in real applications; therefore, an efficient automatic estimation method can be very useful. We propose a new hybrid derivative-free extended Kalman filter for the estimation of the unknown lever arm in tightly coupled GPS/INS integration. The new approach takes advantage of both the linear time propagation of the Kalman filter and the nonlinear measurement propagation of the derivative-free extended Kalman filter. Compared to the unscented Kalman filter, which in recent years is typically used as a superior alternative to the extended Kalman filter for nonlinear estimation, the virtue of the new Kalman filter is equal estimation accuracy at a significantly reduced computational burden. The performance of the new lever arm estimation method is assessed with simulated and real data. Simulations show that the proposed technique can estimate the unknown lever arm correctly provided that maneuvers with attitude changes are performed during initialization. Field test results confirm the effectiveness of the new method.     

A wavelet-extreme learning machine for low-cost INS/GPS navigation system in high-speed applications

The combined navigation system consisting of both global positioning system (GPS) and inertial navigation system (INS) results in reliable, accurate, and continuous navigation capability when compared to either a GPS or an INS stand-alone system. To improve the overall performance of low-cost micro-electro-mechanical systems (MEMS)-based INS/GPS by considering a high level of stochastic noise on low-cost MEMS-based inertial sensors, a highly complex problems with noisy real data, a high-speed vehicle, and GPS signal outage during our experiments, we suggest two approaches at different steps: (1) improving the signal-to-noise ratio of the inertial sensor measurements and attenuating high-frequency noise using the discrete wavelet transform technique before data fusion while preserving important information like the vehicle motion information and (2) enhancing the positioning accuracy and speed by an extreme learning machine (ELM) which has the characteristics of quick learning speed and impressive generalization performance. We present a single-hidden layer feedforward neural network which is employed to optimize the estimation accuracy and speed by minimizing the error, especially in the high-speed vehicle and real-time implementation applications. To validate the performance of our proposed method, the results are compared with an adaptive neuro-fuzzy inference system (ANFIS) and an extended Kalman filter (EKF) method. The achieved accuracies are discussed. The results suggest a promising and superior prospect for ELM in the field of positioning for low-cost MEMS-based inertial sensors in the absence of GPS signal, as it outperforms ANFIS and EKF by approximately 50 and 70%, respectively.     

GPS/INS navigation precision and its effect on airborne radio occultation retrieval accuracy

An airborne radio occultation (RO) system has been developed to retrieve atmospheric profiles of refractivity, moisture, and temperature. The long-term objective of such a system is deployment on commercial aircraft to increase the quantity of moisture observations in flight corridors in order to improve weather forecast accuracy. However, there are several factors important to operational feasibility that have an impact on the accuracy of the airborne RO results. We investigate the effects of different types of navigation system noise on the precision of the retrieved atmospheric profiles using recordings from the GNSS Instrument System for Multistatic and Occultation Sensing (GISMOS) test flights, which used an Applanix POS/AV 510 Global Positioning System (GPS)/Inertial Navigation System (INS). The data were processed using a carrier phase differential GPS technique, and then the GPS position and inertial measurement unit data were combined in a loosely coupled integrated inertial navigation solution. This study quantifies the velocity precision as a function of distance from GPS reference network sites, the velocity precision with or without an inertial measurement unit, the impact of the quality of the inertial measurement unit, and the compromise in precision resulting from the use of real-time autonomous GPS positioning. We find that using reference stations with baseline lengths of up to 760?km from the survey area has a negligible impact on the retrieved refractivity precision. We also find that only a small bias (less than 0.5% in refractivity) results from the use of an autonomous GPS solution rather than a post-processed differential solution when used in an integrated GPS/INS system. This greatly expands the potential range of an operational airborne radio occultation system, particularly over the oceans, where observations are sparse.     

新型组合导航定位技术在机场抢建中的应用

在机场抢修抢建中,对测量系统的作业时间、定位精度、可靠性具有较高的要求,本文提出了一种新型高精度IMU/TS组合定位导航方法,引入激光跟踪定位/惯性组合导航理念,分析了系统组成以及各传感器的误差项,将系统时间延迟作为新的状态估计参数,采用卡尔曼滤波器将IMU和TS数据进行数据融合处理,并在车载动态应用条件下同IMU/GPS组合定位导航系统进行了实验数据比对,验证了在无GNSS信号环境下IMU/TS组合定位导航系统的位置测量精度。     

Strapdown INS/DGPS airborne gravimetry tests in the Gulf of Mexico

Combining data from a Strapdown Inertial Navigation System and a Differential Global Positioning System (SINS/DGPS) has shown great promise in estimating gravity on moving platforms. Previous studies on a ground-vehicle system obtained 1–3 mGal precision with 2 km spatial resolution. High-accuracy Inertial Measurement Units (IMU) and cm-level positioning solutions are very important in obtaining mGal-level gravity disturbance estimates. However, these ideal configurations are not always available or achievable. Because the noise level in the SINS/DGPS gravimetric system generally decreases with an increase of speed and altitude of the platform, the stringent constraints on the IMU and GPS may be relieved in the airborne scenario. This paper presents an investigation of one navigation-grade and one tactical-grade IMU for the possibility of low-cost INS/GPS airborne gravimetry. We use the data collected during the Gravity-Lidar Study of 2006 (GLS06), which contains aerogravity, GPS, and INS along the northern coastline of the Gulf of Mexico. The gravity disturbance estimates from the navigation-grade IMU show 0.5–3.2 mGal precision compared with the onboard gravimeter’s measurements and better than 3 mGal precision compared with the upward continued surface control data. Due to relatively large (240 s) smoothing window, the results have about 34 km along-track resolution. But the gravity estimates from the tactical-grade IMU have much poorer precisions. Nonetheless, useful contributions from the tactical-grade IMU could be extracted for longer wavelengths.