Adaptive GPS/INS integration for relative navigation

Relative navigation based on GPS receivers and inertial measurement units is required in many applications including formation flying, collision avoidance, cooperative positioning, and accident monitoring. Since sensors are mounted on different vehicles which are moving independently, sensor errors are more variable in relative navigation than in single-vehicle navigation due to different vehicle dynamics and signal environments. In order to improve the robustness against sensor error variability in relative navigation, we present an efficient adaptive GPS/INS integration method. In the proposed method, the covariances of GPS and inertial measurements are estimated separately by the innovations of two fundamentally different filters. One is the position-domain carrier-smoothed-code filter and the other is the velocity-aided Kalman filter. By the proposed two-filter adaptive estimation method, the covariance estimation of the two sensors can be isolated effectively since each filter estimates its own measurement noise. Simulation and experimental results demonstrate that the proposed method improves relative navigation accuracy by appropriate noise covariance estimation.     

Web-based resources on software GPS receivers

This column provides the Web-based GPS resources and their technical background information. Its purpose is to inform the reader about the data, software, electronic documents that are available online. This column is coordinated by Dr. Jinling Wang, The University of New South Wales, Sydney. Comments and suggestions are appreciated (jinling.wang@unsw.edu.au). In this issue’s column, Mr. Ravindra Babu introduces the online resources on software GPS receivers.     

GPS/Pseudolite/INS integration: concept and first tests

This paper discusses the introduction of pseudolites (ground-based GPS-like signal transmitters) into existing integrated GPS/INS systems in order to provide higher availability, integrity, and accuracy in a local area. Even though integrated GPS/INS systems can overcome inherent drawbacks of each component system (line-of-sight requirement for GPS, and INS errors that grow with time), performance is nevertheless degraded under adverse operational circumstances. Some typical examples are when the duration of satellite signal blockage exceeds an INS bridging level, resulting in large accumulated INS errors that cannot be calibrated by GPS. Such a scenario, unfortunately, is a common occurrence for certain kinematic applications. To address such shortcomings, both pseudolite/INS and GPS/pseudolite/INS integration schemes are proposed here. Typically, the former is applicable for indoor positioning where the GPS signal is unavailable for use. The latter would be appropriate for system augmentation when the number and geometry of visible satellites is not sufficient for accurate positioning or attitude determination. In this paper, some technical issues concerned with implementing these two integration schemes are described, including the measurement model, and the appropriate integration filter for INS error estimation and correction through GPS and pseudolite (PL) carrier phase measurements. In addition, the results from the processing of simulated measurements, as well as field experiments, are presented in order to characterize the system performance. As a result, it has been established that the GPS/PL/INS and PL/INS integration schemes would make it possible to ensure centimeter-level positioning accuracy even if the number of GPS signals is insufficient, or completely unavailable. Electronic Publication     

An integer ambiguity resolution procedure for GPS/pseudolite/INS integration

In order to achieve a precise positioning solution from GPS, the carrier-phase measurements with correctly resolved integer ambiguities must be used. Based on the integration of GPS with pseudolites and Inertial Navigation Systems (INS), this paper proposes an effective procedure for single-frequency carrier-phase integer ambiguity resolution. With the inclusion of pseudolites and INS measurements, the proposed procedure can speed up the ambiguity resolution process and increase the reliability of the resolved ambiguities. In addition, a recently developed ambiguity validation test, and a stochastic modelling scheme (based on-line covariance matrix estimation) are adapted to enhance the quality of ambiguity resolution. The results of simulation studies and field experiments indicate that the proposed procedure indeed improves the performance of single-frequency ambiguity resolution in terms of both reliability and time-to-fix-ambiguity.     

Reliable partial ambiguity resolution for single-frequency GPS/BDS and INS integration

GPS Solutions - Correctly fixing carrier phase integer ambiguities is a prerequisite to achieve high-precision positioning solutions from global navigation satellite system (GNSS). However, for the...     

Ultra-tight GPS/INS/PL integration: a system concept and performance analysis

The architecture of the ultra-tight GPS/INS/PL integration is the key to its successful performance; the main feature of this architecture is the Doppler feedback to the GPS receiver tracking loops. This Doppler derived from INS, when integrated with the carrier tracking loops, removes the Doppler due to vehicle dynamics from the GPS/PL signal thereby achieving a significant reduction in the carrier tracking loop bandwidth. The bandwidth reduction provides several advantages such as: improvement in anti-jamming performance, and increase in post correlated signal strength which in turn increases the dynamic range and accuracy of measurements. Therefore, any degradation in the derived Doppler estimates will directly affect the tracking loop bandwidth and hence its performance. The quadrature signals from the receiver correlator, I (in-phase) and Q (quadrature), form the measurements, whereas the inertial sensor errors, position, velocity and attitude errors form the states of the complementary Kalman filter. To specify a reliable measurement model of the filter for this type of integrated system, a good understanding of GPS/PL signal characteristics is essential. It is shown in this paper that phase and frequency errors are the variables that relate the measurements and the states in the Kalman filter. The main focus of this paper is to establish the fundamental mathematical relationships that form the measurement model, and to show explicitly how the system error states are related to the GPS/PL signals. The derived mathematical relationships encapsulated in a Kalman filter, are tested by simulation and shown to be valid.

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Robust GPS/BDS/INS tightly coupled integration with atmospheric constraints for long-range kinematic positioning

GPS Solutions - The combination of new global navigation satellite system (GNSS) has brought great benefits to reliable positioning and ambiguity resolution (AR), especially in restricted...     

Adaptive Kalman Filtering for INS/GPS

After reviewing the two main approaches of adaptive Kalman filtering, namely, innovation-based adaptive estimation (IAE) and multiple-model-based adaptive estimation (MMAE), the detailed development of an innovation-based adaptive Kalman filter for an integrated inertial navigation system/global positioning system (INS/GPS) is given. The developed adaptive Kalman filter is based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors. Results from two kinematic field tests in which the INS/GPS was compared to highly precise reference data are presented. Results show that the adaptive Kalman filter outperforms the conventional Kalman filter by tuning either the system noise variance–covariance (V–C) matrix `Q' or the update measurement noise V–C matrix `R' or both of them. Received: 14 September 1998 / Accepted: 21 December 1998     

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。     

GPS/INS支持下的机载干涉SAR定标试验

干涉定标技术是机载InSAR获取高精度DEM的关键技术,根据GPS高精度定位数据支持下的机载SAR定标模型,通过一定数量的地面定标点校正干涉SAR系统参数,InSAR与高精度GPS/INS技术的结合进一步提高了InSAR测图的精度。文中对GPS支持下的干涉定标技术进行仿真试验,基于机载SAR正侧视模型的成像几何关系,建立关于干涉参数和地面定标点的定标模型,采用基于敏感度方程的干涉定标方法,对地面定标点的测量高程值上加入不同的随机误差,分析该测量误差对干涉定标结果的影响,结果表明,高精度的GPS定位数据提高了机载InSAR测图的精度。     

GPS／INS组合导航系统的Matlab／Simulink仿真

首先系统研究了GPS／INS组合导航系统的仿真原理，然后以Matlab／Simulink为平台，在对GPS、INS进行单独仿真的基础上，对GPS／INS组合导航系统进行了实时的扩展Kalman滤波仿真试验，试验结果不仅证明组合导航具有较高的导航精度，而且为进一步研究组合导航系统开辟了一条比较实用的道路。     

GPS/INS组合导航系统的Matlab/Simulink仿真

首先系统研究了GPS/INS 组合导航系统的仿真原理,然后以Matlab/Simulink为平台,在对GPS、INS进行单独仿真的基础上,对GPS/INS组合导航系统进行了实时的扩展Kalman滤波仿真试验,试验结果不仅证明组合导航具有较高的导航精度,而且为进一步研究组合导航系统开辟了一条比较实用的道路.     

New jump trajectory determination method using low-cost MEMS sensor fusion and augmented observations for GPS/INS integration

Objective information on athletic maneuvers for performance evaluation has become highly desired in sports such as skiing, snowboarding, and mountain biking. Body-mounted devices, incorporating low-cost microelectromechanical, inertial navigation units, and global positioning system (GPS) receivers, to calculate sport-specific key performance variables (KPVs) and provide real-time feedback, are now commercially available. However, algorithms implemented for such purposes still lack accuracy and power efficiency. A new GPS/INS (inertial navigation system) integration algorithm is proposed to determine the trajectory of an athlete executing jumps while skiing, snowboarding, mountain biking etc. KPVs, such as jump horizontal distance, vertical height, and drop, are calculated from the trajectory. A new sensor error compensation scheme is developed using sensor fusion and linear Kalman filters (LKF). The LKF parameters are varied to address the fluctuating dynamics of the athlete during a jump. The extended Kalman filter used for GPS/INS integration has an observation vector augmented with sensor error measurements derived from sensor fusion. The performance of the proposed algorithm is evaluated through experimental field tests. For the determination of jump horizontal distance, height, and drop, the proposed algorithm has errors of 14.3 cm (5.5 %), 1.6 cm (38 %), and 6.7 cm (9.4 %), respectively. Errors in KPVs for a set of jumps were first determined with respect to the true KPVs, and then the errors for all the jumps were averaged to calculate the absolute and percentage errors. The accuracy achieved is deemed to fulfill the expectations of both recreational and professional athletes.     

Double-filter model with modified Kalman filter for baseband signal pre-processing with application to ultra-tight GPS/INS integration

In federated design of ultra-tight GPS/INS integrated system, the baseband signal pre-processing is completed in a single pre-filter assigned for each channel. As the state space model of this single pre-filter includes the code tracking errors coupled with carrier tracking errors, ionospheric errors and normalized signal amplitude, the carrier tracking process may be destroyed. Also, the measurement noises are not independent any longer after passing through the code and carrier discriminators. Therefore, we propose a double-filter-based pre-filter model that distributes the carrier and code tracking into two independent filters: a conventional pre-filter, where the normalized signal amplitude is excluded from the state space and tracks only the code signal, and a 3-dimension state filter, tracking the carrier signal. The measurement information from both filters is a scalar quantity, which removes most of the noise correlation. To further improve the performance of the double-filter-based pre-filter model, we propose a modified Kalman filter algorithm. Simulation and field tests have been conducted, and the performance analysis has been done for the following configurations in a vector-tracking mode: double-filter model with modified Kalman filter, double-filter model with conventional Kalman filter and traditional single-filter model. The preliminary analysis indicates that the double-filter model with modified Kalman filter shows the best performance in tracking and navigation domains, while the traditional single-filter model shows a sub-optimal performance.     

基于GPS/INS的高光谱影像几何粗校正

高光谱影像,较之全色、多光谱影像在地物分类识别方面具有巨大的优势,为了检验现有高光谱相机的空间定位精度,使用基于GPS/INS的POS系统获取航空飞行中高光谱相机的位置与姿态参数,在无地面控制点的情况下,实现几何粗校正.     

GPS/INS组合系统数据处理方法

在介绍国际和国内GPS／INS组合系统研究动态和热点的基础上，提出采用一个低价格单频伪距差分GPS／INS系统，辅以相位平滑伪距差分，同时施用模拟的多路径效应和多普勒改正，使定位精度达到分米级，运用联邦卡尔曼滤波，可提高系统的可靠性，大大减少计算量。     

GPS／INS直接定向精度分析

近年来,GPS／INS融合技术在国内逐渐被应用于航空摄影测量中,利用其直接获得外方位元素,从而减少外业控制点。通过试验,在DMC数码相机同高精度的GPS／INS系统联结下,直接获取了试验区的外方位元素,并对GPS／INS数据直接定向的精度进行分析和总结,得出了一些有益的结论。     

GPS/INS组合系统中姿态参数估计准确性检验方法探讨

从滤波的关键矩阵——增益阵入手进行分析,发现机动条件下经典组合模型受状态预报模型不准的影响,姿态参数滤波估值及其更新方差阵偏离准确值,指出常用的姿态参数精度衡量指标不合理。提出了利用组合系统输出的载体系中某些方向速度为0的条件对姿态参数估值的准确性进行检验的思想。新的检验方法不需要增加任何额外设备,经济、方便、简单。     

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。     

一种低成本GPS/INS紧耦合组合导航系统

描述了一种低成本的GPS/INS组合导航系统,经过理论推导得到了系统具体的实现方法,并通过市场上大量使用的低成本GPS模块和MEMS陀螺和加速度计实现了该系统。实际路测数据结果显示,该系统基本达到了理论预期。