A Hybrid Intelligent Algorithm DGP-MLP for GNSS/INS Integration during GNSS Outages

2018 ◽  
Vol 72 (2) ◽  
pp. 375-388 ◽  
Author(s):  
Yuexin Zhang ◽  
Lihui Wang
Keyword(s):  
Satellite System ◽  
Micro Electro Mechanical System ◽  
Real Field ◽  
Prediction Errors ◽  
Integrated Navigation ◽  
Intelligent Algorithm ◽  
Position Information ◽  
Hybrid Intelligent Algorithm ◽  
Global Navigation Satellite ◽  
Adaptively Adjusting

The performance of Global Navigation Satellite System (GNSS) and Micro-Electro-Mechanical System (MEMS)-based Inertial Navigation System (INS) integrated navigation is reduced during GNSS outages. To bridge the period during GNSS outages, a novel hybrid intelligent algorithm incorporating a Discrete Grey Predictor (DGP) and a Multilayer Perceptron (MLP) neural network (DGP-MLP) is proposed. The DGP-MLP is used to provide a pseudo-GNSS position to correct the INS errors during GNSS outages; the DGP uses the GNSS position information of the latest few moments to predict the position of future moments; in the process of DGP-MLP, the MLP is used to modify the prediction errors of DGP, and the MLP is improved by adding momentum terms and adaptively adjusting the learning rate and momentum factor. To evaluate the effectiveness of the proposed methodology, four GNSS outages in different cases over a real field test data were employed. The experimental results demonstrate that the proposed methodology can significantly improve positioning accuracy during GNSS outages.

scholarly journals Robustly Adaptive EKF PDR/UWB Integrated Navigation Based on Additional Heading Constraint

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4390
Author(s):  
Debao Yuan ◽  
Jian Zhang ◽  
Jian Wang ◽  
Ximin Cui ◽  
Fei Liu ◽  
...  
Keyword(s):  
Dead Reckoning ◽  
Wide Band ◽  
Satellite System ◽  
Line Of Sight ◽  
Indoor Environments ◽  
Integrated Navigation ◽  
Position Information ◽  
Positioning Systems ◽  
Global Navigation Satellite ◽  
Non Line Of Sight

At present, GNSS (Global Navigation Satellite System) positioning technology is widely used for outdoor positioning services because of its high-precision positioning characteristics. However, in indoor environments, effective position information cannot be provided, because of the signals being obscured. In order to improve the accuracy and continuity of indoor positioning systems, in this paper, we propose a PDR/UWB (Pedestrian Dead Reckoning and Ultra Wide Band) integrated navigation algorithm based on an adaptively robust EKF (Extended Kalman Filter) to address the problem of error accumulation in the PDR algorithm and gross errors in the location results of the UWB in non-line-of-sight scenarios. First, the basic principles of UWB and PDR location algorithms are given. Then, we propose a loose combination of the PDR and UWB algorithms by using the adaptively robust EKF. By using the robust factor to adjust the weight of the observation value to resist the influence of the gross error, and by adjusting the variance of the system adaptively according to the positioning scene, the algorithm can improve the robustness and heading factor of the PDR algorithm, which is constrained by indoor maps. Finally, the effectiveness of the algorithm is verified by the measured data. The experimental results showed that the algorithm can not only reduce the accumulation of PDR errors, but can also resist the influence of gross location errors under non-line-of-sight UWB scenarios.

scholarly journals TDMA Datalink Cooperative Navigation Algorithm Based on INS/JTIDS/BA

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 782
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Satellite System ◽  
Time Of Arrival ◽  
Military Operations ◽  
Position Information ◽  
Cooperative Navigation ◽  
Navigation Algorithm ◽  
Geometric Dilution Of Precision ◽  
Global Navigation Satellite

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.

scholarly journals Constrained Unscented Particle Filter for SINS/GNSS/ADS Integrated Airship Navigation in the Presence of Wind Field Disturbance

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 471 ◽  
Author(s):  
Zhaohui Gao ◽  
Dejun Mu ◽  
Yongmin Zhong ◽  
Chengfan Gu
Keyword(s):  
Wind Speed ◽  
Particle Filter ◽  
State Estimation ◽  
Wind Field ◽  
Satellite System ◽  
Integrated Navigation ◽  
Unscented Particle Filter ◽  
Field Disturbance ◽  
Global Navigation Satellite ◽  
Optimal State Estimation

Due to the disturbance of wind field, it is difficult to achieve precise airship positioning and navigation in the stratosphere. This paper presents a new constrained unscented particle filter (UPF) for SINS/GNSS/ADS (inertial navigation system/global navigation satellite system/atmosphere data system) integrated airship navigation. This approach constructs a wind speed model to describe the relationship between airship velocity and wind speed using the information output from ADS, and further establishes a mathematical model for SINS/GNSS/ADS integrated navigation. Based on these models, it also develops a constrained UPF to obtain system state estimation for SINS/GNSS/ADS integration. The proposed constrained UPF uses the wind speed model to constrain the UPF filtering process to effectively resist the influence of wind field on the navigation solution. Simulations and comparison analysis demonstrate that the proposed approach can achieve optimal state estimation for SINS/GNSS/ADS integrated airship navigation in the presence of wind field disturbance.

A Novel GNSS Attitude Determination Method Based on Primary Baseline Switching for A Multi-Antenna Platform

2020 ◽  
Vol 12 (5) ◽  
pp. 747
Author(s):  
Peng Zhang ◽  
Yinzhi Zhao ◽  
Huan Lin ◽  
Jingui Zou ◽  
Xinzhe Wang ◽  
...  
Keyword(s):  
Attitude Determination ◽  
Low Cost ◽  
Satellite System ◽  
Poor Quality ◽  
Integrated Navigation ◽  
Determination Method ◽  
Integrated Navigation System ◽  
Determination System ◽  
Vehicle Test ◽  
Global Navigation Satellite

The global navigation satellite system (GNSS)-based attitude determination system has attracted more and more attention with the advantages of having simplified algorithms, a low price and errors that do not accumulate over time. However, GNSS signals may have poor quality or lose lock in some epochs with the influence of signal fading and the multipath effect. When the direct attitude determination method is applied, the primary baseline may not be available (ambiguity is not fixed), leading to the inability of attitude determination. With the gradual popularization of low-cost receivers, making full use of spatial redundancy information of multiple antennas brings new ideas to the GNSS-based attitude determination method. In this paper, an attitude angle conversion algorithm, selecting an arbitrary baseline as the primary baseline, is derived. A multi-antenna attitude determination method based on primary baseline switching is proposed, which is performed on a self-designed embedded software and hardware platform. The proposed method can increase the valid epoch proportion and attitude information. In the land vehicle test, reference results output from a high-accuracy integrated navigation system were used to evaluate the accuracy and reliability. The results indicate that the proposed method is correct and feasible. The valid epoch proportion is increased by 16.2%, which can effectively improve the availability of attitude determination. The RMS of the heading, pitch and roll angles are 0.52°, 1.25° and 1.16°.

A new method for underwater dynamic gravimetry based on multisensor integrated navigation

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. G69-G80
Author(s):  
Zhiming Xiong ◽  
Juliang Cao ◽  
Kaixun Liao ◽  
Meiping Wu ◽  
Shaokun Cai ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Finite Impulse Response ◽  
Gravity Data ◽  
Satellite System ◽  
New Method ◽  
Integrated Navigation ◽  
Oil And Gas Exploration ◽  
Half Wavelength ◽  
Marine Gravity ◽  
Global Navigation Satellite

Underwater gravity information plays a major role in deepwater oil and gas exploration. To realize underwater dynamic gravimetry, we have developed a strapdown gravimeter mounted in a pressure capsule for adaption to the underwater environment and we adopted a two-stage towed underwater gravimetry scheme. An improved strapdown gravimeter and other underwater sensors were installed in a towed vessel to form an underwater dynamic gravimetry system. Because the global navigation satellite system cannot be used for underwater dynamic gravimetry, we developed a new method based on underwater multisensor integrated navigation, in which a federal Kalman filter was applied for error estimation. This new method allowed us to obtain the accurate attitude, velocity, and position necessary for gravity estimation. In addition, the gravity data can then be extracted from the noisy data through finite impulse response low-pass filtering. We acquired the underwater gravity data at a depth of 300 m to test the validity of the new method and evaluate the accuracy of the underwater gravity system. The results indicated a repeatability from 0.85 to 0.96 mGal at a half wavelength of approximately 0.2 km and also indicated good consistency with the marine gravity data.

scholarly journals Semantic VPS for Smartphone Localization in Challenging Urban Environments

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6137
Author(s):  
Max Jwo Lem Lee ◽  
Li-Ta Hsu ◽  
Hoi-Fung Ng
Keyword(s):  
Smart Cities ◽  
Satellite System ◽  
Urban Environments ◽  
Position Estimation ◽  
Information Modeling ◽  
Position Information ◽  
Precise Position ◽  
Segmented Images ◽  
Building Information ◽  
Global Navigation Satellite

Accurate smartphone-based outdoor localization systems in deep urban canyons are increasingly needed for various IoT applications. As smart cities have developed, building information modeling (BIM) has become widely available. This article, for the first time, presents a semantic Visual Positioning System (VPS) for accurate and robust position estimation in urban canyons where the global navigation satellite system (GNSS) tends to fail. In the offline stage, a material segmented BIM is used to generate segmented images. In the online stage, an image is taken with a smartphone camera that provides textual information about the surrounding environment. The approach utilizes computer vision algorithms to segment between the different types of material class identified in the smartphone image. A semantic VPS method is then used to match the segmented generated images with the segmented smartphone image. Each generated image contains position information in terms of latitude, longitude, altitude, yaw, pitch, and roll. The candidate with the maximum likelihood is regarded as the precise position of the user. The positioning result achieved an accuracy of 2.0 m among high-rise buildings on a street, 5.5 m in a dense foliage environment, and 15.7 m in an alleyway. This represents an improvement in positioning of 45% compared to the current state-of-the-art method. The estimation of yaw achieved accuracy of 2.3°, an eight-fold improvement compared to the smartphone IMU.

scholarly journals Application of Inertial and GNSS Integrated Navigation to Seabird Biologging

2021 ◽  
Vol 33 (3) ◽  
pp. 526-536
Author(s):  
Masaru Naruoka ◽  
Yusuke Goto ◽  
Henri Weimerskirch ◽  
Takashi Mukai ◽  
Taichi Sakamoto ◽  
...  
Keyword(s):  
Power Consumption ◽  
High Performance ◽  
Feasible Solution ◽  
Satellite System ◽  
Integrated Navigation ◽  
Guidance And Control ◽  
Marine Vehicles ◽  
Navigation Algorithm ◽  
Global Navigation Satellite ◽  
And Control

The study demonstrates the versatility of integration of inertial navigation and global navigation satellite system (GNSS) with its unique application to seabird biologging. Integrated navigation was originally developed in the field of aerospace engineering, which requires accurate and reliable position, velocity, and attitude information for the guidance and control of aircraft and spacecraft. Due to its high performance and recent progress of sensor development, integrated navigation has been widely used not only in aerospace but also in many fields represented by land and marine vehicles. One of its ultimate applications under the constraint on the size and power consumption of devices is this study. Seabird biologging involves attaching a logging device onto a seabird for scientific purposes to understand its biomechanics, behavior, and so on. Design restrictions for the device include several tens of grams mass, several tens of millimeters in length, and several tens of milliamperes of power consumption. It is more difficult to maintain the accuracy of such a device than applications to an artificial vehicle. This study has shown that integrated navigation is a feasible solution for such extreme applications with two examples: biologging for wandering albatrosses and great frigatebirds. Furthermore, it should be stressed that the navigation captured the world’s first data of their detailed trajectories and attitudes in their dynamic and thermal soarings. For completeness, the navigation algorithm, simulation results to show the effectiveness of the algorithm, and the logging devices attached to bird are also described.

scholarly journals Determination of Cultivated Area, Field Boundary and Overlapping for A Plowing Operation Using ISO 11783 Communication and D-GNSS Position Data

Agriculture ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 38 ◽  
Author(s):  
Andreas Heiß ◽  
Dimitrios Paraforos ◽  
Hans Griepentrog
Keyword(s):  
Crop Production ◽  
Low Cost ◽  
Satellite System ◽  
Position Information ◽  
Cost Differential ◽  
Main Challenge ◽  
Wide Range ◽  
Position Data ◽  
Machine Speed ◽  
Global Navigation Satellite

Easily available and detailed area-related information is very valuable for the optimization of crop production processes in terms of, e.g., documentation and invoicing or detection of inefficiencies. The present study dealt with the development of algorithms to gain sophisticated information about different area-related parameters in a preferably automated way. Rear hitch position and wheel-based machine speed were recorded from ISO 11783 communication data during plowing with a mounted reversible moldboard plow. The data were georeferenced using the position information from a low-cost differential global navigation satellite system (D-GNSS) receiver. After the exclusion of non-work sequences from continuous data logs, single cultivated tracks were reconstructed, which represented as a whole the cultivated area of a field. Based on that, the boundary of the field and the included area were automatically detected with a slight overestimation of 1.4%. Different field parts were distinguished and single overlaps between the cultivated tracks were detected, which allowed a distinct assessment of the lateral and headland overlapping (2.05% and 3.96%, respectively). Incomplete information about the work state of the implement was identified as the main challenge to get precise results. With a few adaptions, the used methodology could be transferred to a wide range of mounted implements.

Integrated Navigation Models of a Mobile Fodder-Pushing Robot Based on a Standardized Cow Husbandry Environment

2020 ◽  
Vol 63 (2) ◽  
pp. 221-230
Author(s):  
Shenghui Yang ◽  
Shenghao Liang ◽  
Yongjun Zheng ◽  
Yu Tan ◽  
Zhang Xiao ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Time Course ◽  
Satellite System ◽  
Integrated Navigation ◽  
Multiple Sensors ◽  
Motion Models ◽  
Outdoor Environments ◽  
Global Navigation Satellite ◽  
Smart Mobile

HighlighIntegrated navigation models for a two-wheel robot were specifically developed for a semi-enclosed environment.A combination of Kalman filter and fuzzy control system was developed with mathematical models.Real-time pose estimate and adjustment of perturbances due to feeding cows and fodder resistance were achieved.Abstract. As part of welfare feeding, standardized feeding is commonly used for cows in confined operations. Due to the strict facility requirements, smart mobile robots have been specifically developed to address these semi-enclosed environments. Their navigation is based on electromagnetic sensors with magnetic tapes, which does not easily allow route changes and other abilities afforded by the newer integrated sensors and Global Navigation Satellite System (GNSS) guidance packages available on large agricultural machinery in outdoor environments. This article proposes a system of integrated navigation using multiple sensors, which was used for a two-wheel-drive robot operating in the standardized environment of a cow husbandry facility. The developed system combined incremental encoders, ultrasonic sensors, and a gyroscope to determine parameters such as course angle and covered distance. A fuzzy self-adaption Kalman filter was applied to integrate these parameters and estimate the robot pose, so that the robot could achieve real-time course adjustment during operation. Experimental trials indicated that the real-world route was highly consistent with the set route. Moreover, the cross-track error was =0.10 m at a travel velocity of 0.2 m s-1, indicating that perturbances due to feeding cows and fodder resistance had little interference on the movement of the robot, and the models were robust and accurate. This novel integrated sensing system with a fuzzy self-adaption Kalman filter and derived models was able to guide real-time robot operations in a modern cow husbandry environment without the need for magnetic tapes. Keywords: Kalman filter, Integrated navigation, Motion models, Pose estimate, Welfare feeding.

scholarly journals Polar Region Integrated Navigation Method Based on Covariance Transformation

2021 ◽  
Vol 11 (20) ◽  
pp. 9572
Author(s):  
Yongjian Zhang ◽  
Lin Wang ◽  
Guo Wei ◽  
Chunfeng Gao
Keyword(s):  
Navigation System ◽  
Physical Simulation ◽  
Inertial Navigation ◽  
Satellite System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Global Navigation Satellite ◽  
Relationship Of ◽  
The Relationship ◽  
Navigation Method

Aircraft flying the trans-arctic routes usually apply inertial navigation mechanization in two different navigation frames, e.g., the local geographic frame and the grid frame. However, this change of navigation frame will cause filter overshoot and error discontinuity. To solve this problem, taking the inertial navigation system/global navigation satellite system (INS/GNSS) integrated navigation system as an example, an integrated navigation method based on covariance transformation is proposed. The relationship of the system error state between different navigation frames is deduced as a means to accurately convert the Kalman filter’s covariance matrix. The experiment and semi-physical simulation results show that the presented covariance transformation algorithm can effectively solve the filter overshoot and error discontinuity caused by the change of navigation frame. Compared with non-covariance transformation, the system state error is thereby reduced significantly.

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