共查询到20条相似文献，搜索用时 957 毫秒
1.
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
2.
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
3.
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. 相似文献
4.
Adaptive GPS/INS integration for relative navigation 总被引：1，自引：0，他引：1
Je Young Lee Hee Sung Kim Kwang Ho Choi Joonhoo Lim Sebum Chun Hyung Keun Lee 《GPS Solutions》2016,20(1):63-75
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. 相似文献
5.
目前GPS／INS制导控制技术已成为精确制导武器的核心技术。根据GPS导航的特点及GPS／INS制导机理,对压制式干扰对GPS接收机的影响进行了分析,并分析了采用自适应调零天线技术来提高GPS／INS组合式导航抗干扰能力的有效性。 相似文献
6.
7.
In the complex urban environments, land vehicle navigation purely relying on GNSS cannot satisfy user needs due to the loss of satellite signals caused by obstructions such as buildings, tunnels, and trees. To solve this problem, we introduce a GPS-/MSINS-/magnetometer-integrated urban navigation system based on context awareness. In this system, the data from the Micro Strapdown Inertial Navigation System (MSINS) are used to analyze and detect the context knowledge of vehicles, whose sensor errors can be compensated by the heuristic drift reduction algorithm for different motion situations. When GPS is available, the vehicle position can be estimated by unscented Kalman Filter, whereas in the case of GPS outages, the vehicle attitude is provided by an attitude and heading reference system and the motion constraints-aided algorithm is used to complete the positioning. In the experiment validation, the integrated navigation system is set up by low-cost inertial sensors. The result shows that the proposed system can achieve high accuracy when GPS is available. For most of the time without GPS, the system can guarantee the positioning precision of 10 m and compensate the errors of MSINS effectively, which fully satisfies positioning needs in complex urban environments. 相似文献
8.
GPS/INS navigation precision and its effect on airborne radio occultation retrieval accuracy 总被引：1，自引：1，他引：0
Paytsar Muradyan Jennifer S. Haase Feiqin Xie James L. Garrison Justin Voo 《GPS Solutions》2011,15(3):207-218
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. 相似文献
9.
基于GPS的汽车稳定性控制系统研究 总被引：1，自引：0，他引：1
介绍GPS测姿原理,利用双天线GPS接收机直接测量车身侧偏角等汽车状态参数,采用卡尔曼滤波器融合GPS与INS测量数据。运用滑模控制理论,设计汽车稳定性控制器。运用Matlab/simulink软件仿真在变换车道等各种工况下控制器的控制效果。 相似文献
10.
Xiaopeng Li 《Journal of Geodesy》2011,85(9):597-605
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. 相似文献
11.
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
12.
M. S. Senobari 《Journal of Geodesy》2010,84(5):277-291
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. 相似文献
13.
Attitude estimation based on fusion of gyroscopes and single antenna GPS for small UAVs under the influence of vibration 总被引：4，自引：2，他引：2
An attitude estimation method is presented for small unmanned aerial vehicles (UAVs) powered by a piston engine which is the
major source of vibration. Vibration of the engine significantly degrades the accuracy of the inertial measurement unit, especially
for low-cost sensors that are based on micro electro-mechanical system. Therefore, a vibration model for a small UAV is proposed
in order to examine the influence of vibration on attitude estimation with different sensors. The model is derived based on
spectrum analysis with short-time Fourier transform. The vibration is compared with the drift of the gyroscope in order to
examine the impact on attitude estimation. An attitude estimation method that fuses the gyroscopes and single antenna global
positioning system (GPS) is proposed to mitigate the influence of engine vibration and gyroscope drift. The quaternion-based
extended Kalman filter is implemented to fuse the sensors. This filter fuses the angular rates measured by the gyroscopes
and the pseudo-attitude derived from the GPS velocity to estimate the attitude of the UAV. Simulations and experiment results
indicate that the proposed method performs well both in short-term and long-term accuracy even though the gyroscopes are affected
by drift and vibration noise, while the pseudo-attitude contains severe noise. 相似文献
14.
CNS+GNSS+INS船载高精度实时定位定姿算法改进研究 总被引：2，自引：1，他引：1
天文导航(CNS)、卫星导航(GNSS)和惯性导航(INS) 3种系统组合可提供高精度的定位定姿结果。实际工程中因INS长时间误差累积,以及系统硬件传输存在不可忽略的时间延迟,导致INS提供给CNS的预报粗姿态误差较大,恶劣海况下难以保障快速搜星,造成天文导航可靠性下降、姿态测量精度较低的问题。为此,本文提出了一种CNS+GNSS+INS高精度信息融合实时定位定姿框架,引入了等角速度外推措施,有效地解决了惯导信息延迟问题。通过高精度转台模拟恶劣海况下载体大角速度摇摆,验证了本文提出的改进算法的有效性。试验结果表明,该算法架构简单,性能可靠,显著提高了恶劣环境下星敏感器的快速、准确搜星能力,保障了三组合姿态测量的精度和可用性。 相似文献
15.
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
16.
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
17.
18.
David M. Gleason 《Journal of Geodesy》1996,70(5):263-275
A current pursuit of the geodetic community is the optimal integration of differential GPS (DGPS) and inertial navigation system (INS) data streams for precise and efficient position and gravity vector surveying. Therein a complete INS and multiple-antenna GPS receiver payload, mounted on a moving platform, is used in conjunction with a network of ground-fixed single antenna GPS receivers. This paper presents a complete, GPS-based, external updating measurement model for the applicable Kalman filter. The model utilizes four external observation types for every GPS satellite in-view: DGPS range differences, single phase differences, and single phase-rate differences; as well as the mobile, multipleantenna GPS receiver's measurement of theerrors in the INS's estimate of the phase difference between any two vehicle-borne GPS antennae. Although not widely conveyed in the geodetic world, the inertial navigation community has long known that traditional Kalman filter covariance propagation recurrences are inherently unstable when such highly accurate external updates are repeatedly applied (every 1 second) over long time durations. A hybrid square root covariance/U — D covariance factorization approach is a numerically stable alternative and is reviewed herein. The hybrid makeup of the algorithm is necessitated by the correlated nature of the fourth type of GPS external measurement listed above (each vehicle-borne GPS antenna formstwo baselines). Such measurement correlations require a functional transformation of the overall external updating model to permit the multiple updates (simultaneously available at each updating epoch) to be sequentially (and efficiently) processed. An appropriate transformation is given. Stable covariance propagation relationships are presented and the transformed Kalman gain is also furnished and its use in the determination of the externally updated error states is discussed. Specific DGPS/INS instabilities produced by the traditional recurrences are displayed. The stable alternative method requires about 25% more CPU time than the traditional Kalman recurrences. With the ever-increasing computational speeds of microprocessors, this added CPU time is of no real concern. 相似文献
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20.
机载GPS、姿态和激光扫描测距集成定位系统的精确定位方程、误差分析与精度评估 总被引：4，自引：0，他引：4
全球定位系统（GPS），姿态测量（惯性导航系统（INS））和激光扫描测距技术集成的直接空对地定位系统是近年来遥感与测绘领域发展起来的新型定位技术，是定量化三维遥感中获取地面几何信息和生成数字高程模型的主要新技术手段之一。该文给出了该系统的精确定位方程，分析了误差源对定位精度的影响，并给出了数量级评估。结果对实际应用具有重要的参考价值。 相似文献