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1.
Dong-Hwan Hwang Sang Heon Oh Sang Jeong Lee Chansik Park Chris Rizos 《GPS Solutions》2005,9(4):294-311
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. 相似文献
2.
Performance improvement of integrated Inertial Measurement Units (IMU) utilizing micro-electro-mechanical-sensors (MEMS) and
GPS is described in this paper. An offline pre-defined Fuzzy model is employed to improve the system performance. The Fuzzy
model is used to predict the position and velocity errors, which are the inputs to a Kalman Filter (KF) during GPS signal
outages. The proposed model has been verified on real MEMS inertial data collected in a land vehicle test. A number of 30-s
GPS outages were simulated during the data processing at different times and under different vehicle dynamics. Performance
of the suggested Fuzzy model was compared to that of the traditional KF particularly during the simulated GPS outages. The
test results indicate that the proposed Fuzzy model can efficiently compensate for GPS updates during short outages. 相似文献
3.
A GPS-aided Inertial Navigation System (GAINS) is used to determine the orientation? position and velocity of ground and aerial vehicles. The data measured by Inertial Navigation System (INS) and GPS are commonly integrated through an Extended Kalman Filter (EKF). Since the EKF requires linearized models and complete knowledge of predefined stochastic noises? the estimation performance of this filter is attenuated by unmodeled nonlinearity and bias uncertainties of MEMS inertial sensors. The Attitude Heading Reference System (AHRS) is applied based on the quaternion and Euler angles methods. A moving horizon-based estimator such as Model Predictive Observer (MPO) enables us to approximate and estimate linear systems affected by unknown uncertainties. The main objective of this research is to present a new MPO method based on the duality principle between controller and observer of dynamic systems and its implementation in AHRS mode of a low-cost INS aided by a GPS. Asymptotic stability of the proposed MPO is proven by applying Lyapunov’s direct method. The field test of a GAINS is performed by a ground vehicle to assess the long-time performance of the MPO method compared with the EKF. Both the EKF and MPO estimators are applied in AHRS mode of the MEMS GAINS for the purpose of real-time performance comparison. Furthermore? we use flight test data of the GAINS for evaluation of the estimation filters. The proposed MPO based on both the Euler angles and quaternion methods yields better estimation performances compared to the classic EKF. 相似文献
4.
针对车载全球导航卫星系统/惯性导航系统（global navigation satellite system/inertial navigation system,GNSS/INS）组合导航中卫星信号中断,惯性导航系统单独导航误差积累较大的问题,提出了附加载体运动条件约束的卡尔曼（Kalman）滤波解算方法。通过利用载体固有的运动约束,包括近似高程约束、近似速度约束和近似姿态约束,减少载体自由度和模型参数;通过引入新的观测类型,增加观测冗余,可以加强Kalman滤波解,提高在GNSS信号中断时组合导航系统的定位精度,实现无缝导航。 相似文献
5.
Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications 总被引：3，自引：3，他引：3
Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies, which has widespread usage
in industry, is also regarded as an ideal solution for automated agriculture because it fulfils the accuracy, reliability
and availability requirements of industrial and agricultural applications. Agriculture applications use position, velocity
and heading information for automated vehicle guidance and control to enhance the yield and quality of the crop, and in order
to vary the application of fertilizer and herbicides according to soil heterogeneity at sub-field level. A loosely coupled
GPS/INS integration algorithm known as “AhrsKf” is introduced for automated agriculture vehicle guidance and control utilizing
MEMS inertial sensors and GPS. The AhrsKf can produce high-frequency attitude solutions for the vehicle’s guidance and control
system, by using inputs from a single survey grade L1/L2 antenna, eliminating the need for the previous two antenna solutions.
Given its agricultural application, the AhrsKf has been implemented with some specific design features to improve the accuracy
of the attitude solution including, temperature compensation of the inertial sensors, and the aid of plough lines of farm
lands. To evaluate the AhrsKf solution, two benchmarking tests have been conducted by using a three-antenna GPS system and
NovAtel’s SPAN-CPT. The results have demonstrated that the AhrsKf solution is stable and can correctly track the movement
of the farming vehicle. 相似文献
6.
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. 相似文献
7.
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％. 相似文献
8.
介绍了一种低成本微小型惯性测量组件(inertialmeasurementunit,IMU)和双天线GPS构成的组合定位定向系统。为确保组合系统的实时性和滤波稳定性,提出了一种基于UD分解的快速卡尔曼滤波算法,给出了IMU/GPS组合系统的软硬件设计和实验结果。该组合系统应用于炮兵测地车,具有成本低、精度高等优点,能够提高炮兵测地保障的精度和速度。 相似文献
9.
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。 相似文献
10.
A dual-rate Kalman Filter (DRKF) has been developed to integrate the time-differenced GPS carrier phases and the GPS pseudoranges with INS measurements. The time-differenced GPS carrier phases, which have low noise and millimeter measurement precision, are integrated with INS measurements using a Kalman Filter with high update rates to improve the performance of the integrated system. Since the time-differenced GPS carrier phases are only relative measurements, when integrated with INS, the position error of the integrated system will accumulate over time. Therefore, the GPS pseudoranges are also incorporated into the integrated system using a Kalman Filter with a low update rate to control the accumulation of system errors. Experimental tests have shown that this design, compared to a conventional design using a single Kalman Filter, reduces the coasting error by two-thirds for a medium coasting time of 30?s, and the position, velocity, and attitude errors by at least one-half for a 45-min field navigation experiment. 相似文献
11.
Hung Lee Jinling Wang Chris Rizos Dorota Grejner-Brzezinska Charles Toth 《GPS Solutions》2002,6(1-2):34-46
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 相似文献
12.
里程计通常被用于辅助车载GNSS/INS组合导航系统,以解决当遇到高楼、密林、隧道等信号干扰和遮蔽严重情景时导致精度下降的问题,而里程计辅助需要获取准确的里程计杆臂和安装角。鉴于此,本文提出了一种基于预积分的IMU/ODO外参估计算法,使用由里程计观测和GNSS/INS组合导航解算得到的一段时间内的里程增量差异构建代价函数,通过非线性优化器进行标定参数求解。仿真与实际测试均表明了本文标定方法的有效性,里程计观测在经过标定外参补偿后,可为车载GNSS/INS组合导航系统提供厘米级的精度辅助。 相似文献
13.
An enhanced MEMS-INS/GNSS integrated system with fault detection and exclusion capability for land vehicle navigation in urban areas 总被引：2，自引：2，他引：0
We describe an enhanced quality control algorithm for the MEMS-INS/GNSS integrated navigation system. It aims to maintain the system’s reliability and availability during global navigation satellite system (GNSS) partial and complete data loss and disturbance, and hence to improve the system’s performance in urban environments with signal obstructions, tunnels, bridges, and signal reflections. To reduce the inertial navigation system (INS) error during GNSS outages, the stochastic model of the integration Kalman filter (KF) is informed by Allan variance analysis and the application of a non-holonomic constraint. A KF with a fault detection and exclusion capability is applied in the loosely and tightly coupled integration modes to reduce the adverse influence of abnormal GNSS data. In order to evaluate the performance of the proposed navigation system, road tests have been conducted in an urban area and the system’s reliability and integrity is discussed. The results demonstrate the effectiveness of different algorithms for reducing the growth of INS error. 相似文献
14.
15.
简要介绍了GPS/INS松组合导航系统状态方程和观测方程。针对标准Kalman滤波算法存在的状态方程截断误差、噪声统计特性的不确定性以及状态扰动异常的影响,给出了一种应用于GPS/INS组合导航系统的迭代滤波算法。该算法采用迭代策略,不断利用观测信息实时修正状态预报值。实测数据计算结果表明,通过对状态预报值的实时修正,该算法能够很好地抑制状态预报信息的不确定性和扰动异常等对导航解的影响。其滤波解精度明显优于标准Kalman滤波。 相似文献
16.
Dead reckoning techniques such as inertial navigation and odometry are integrated with GPS to avoid interruption of navigation
solutions due to lack of visible satellites. A common method to achieve a low-cost navigation solution for land vehicles is
to use a MEMS-based inertial measurement unit (IMU) for integration with GPS. This integration is traditionally accomplished
by means of a Kalman filter (KF). Due to the significant inherent errors of MEMS inertial sensors and their time-varying changes,
which are difficult to model, severe position error growth happens during GPS outages. The positional accuracy provided by
the KF is limited by its linearized models. A Particle filter (PF), being a nonlinear technique, can accommodate for arbitrary
inertial sensor characteristics and motion dynamics. An enhanced version of the PF, called Mixture PF, is employed in this
paper. It samples from both the prior importance density and the observation likelihood, leading to an improved performance.
Furthermore, in order to enhance the performance of MEMS-based IMU/GPS integration during GPS outages, the use of pitch and
roll calculated from the longitudinal and transversal accelerometers together with the odometer data as a measurement update
is proposed in this paper. These updates aid the IMU and limit the positional error growth caused by two horizontal gyroscopes,
which are a major source of error during GPS outages. The performance of the proposed method is examined on road trajectories,
and results are compared to the three different KF-based solutions. The proposed Mixture PF with velocity, pitch, and roll
updates outperformed all the other solutions and exhibited an average improvement of approximately 64% over KF with the same
updates, about 85% over KF with velocity updates only, and around 95% over KF without any updates during GPS outages. 相似文献
17.
GPS／INS组合导航系统的Matlab／Simulink仿真 总被引：7，自引：1，他引：7
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。 相似文献
18.
A combined algorithm of improving INS error modeling and sensor measurements for accurate INS/GPS navigation 总被引：1，自引：1，他引：1
Although the integrated system of a differential global positioning system (DGPS) and an inertial navigation system (INS)
had been widely used in many geodetic navigation applications, it has sometimes a major limitation. This limitation is associated
with the frequent occurrence of DGPS outages caused by GPS signal blockages in certain situations (urban areas, high trees,
tunnels, etc.). In the standard mechanization of INS/DGPS navigation, the DGPS is used for positioning while the INS is used
for attitude determination. In case of GPS signal blockages, positioning is provided using the INS instead of the GPS until
satellite signals are obtained again with sufficient accuracy. Since the INS has a very short-time accuracy, the accuracy
of the provided INS navigation parameters during these periods decreases with time. However, the obtained accuracy in these
cases is totally dependent on the INS error model and on the quality of the INS sensor data. Therefore, enhanced navigation
parameters could be obtained during DGPS outages if better inertial error models are implemented and better quality inertial
measurements are used. In this paper, it will be shown that better INS error models are obtained using autoregressive processes
for modeling inertial sensor errors instead of Gauss–Markov processes that are implemented in most of the current inertial
systems and, on the other hand, that the quality of inertial data is improved using wavelet multi-resolution techniques. The
above two methods are discussed and then a combined algorithm of both techniques is applied. The performance of each method
as well as of the combined algorithm is analyzed using land-vehicle INS/DGPS data with induced DGPS outage periods. In addition
to the considerable navigation accuracy improvement obtained from each single method, the results showed that the combined
algorithm is better than both methods by more than 30%. 相似文献
19.
20.
The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) technologies is a very useful navigation option for high-accuracy positioning in many applications. However, its performance is still limited by GNSS satellite availability and satellite geometry. To address such limitations, a non-GNSS-based positioning technology known as “Locata” is used to augment a standard GNSS/INS system. The conventional methods for multi-sensor integration can be classified as being either in the form of centralized Kalman filtering (CKF), or decentralized Kalman filtering. However, these two filtering architectures are not always ideal for real-world applications. To satisfy both accuracy and reliability requirements, these three integration algorithms—CKF, federated Kalman filtering (FKF) and an improved decentralized filtering, known as global optimal filtering (GOF)—are investigated. In principle, the GOF is derived from more information resources than the CKF and FKF algorithms. These three algorithms are implemented in a GPS/Locata/INS integrated navigation system and evaluated using data obtained from a flight test. The experimental results show that the position, velocity and attitude solution derived from the GOF-based system indicate improvements of 30, 18.4 and 20.8% over the CKF- and FKF-based systems, respectively. 相似文献