scholarly journals An INS/Geomagnetic Integrated Navigation Algorithm Based on Matching Strategy and Hierarchical Filtering

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 460
Author(s):  
Xiusheng Duan ◽  
Jing Xiao ◽  
Xiaohui Qi ◽  
Yifei Liu
Keyword(s):  
Magnetic Measurements ◽  
Inertial Navigation ◽  
State Equation ◽  
Integrated Navigation ◽  
Matching Algorithm ◽  
Filtering Algorithm ◽  
Navigation Algorithm ◽  
Physical Experiments ◽  
Matching Strategy ◽  
Navigation Information

To improve the positioning accuracy of an inertial/geomagnetic integrated navigation algorithm, a combined navigation method based on matching strategy and hierarchical filtering is proposed. First, the PDA-ICCP geomagnetic matching algorithm is improved. On basis of evaluating the distribution of magnetic measurements, a number of controllable magnetic values are regenerated to participate in the geomagnetic matching algorithm (GMA). As a result, accuracy of the matching algorithm is ensured and its efficiency is improved. Secondly, the integrated navigation filter is designed based on the hierarchical filtering strategy, in which the navigation information of the geomagnetic matching module and inertial navigation module are respectively filtered and fused in the main filter. In this way, the shortcoming that GMA is unable to provide continuous and real-time navigation information is overcome. Meanwhile, precision of the inertial/geomagnetic integrated navigation algorithm is improved. Finally, the feasibility and validity of the proposed algorithm are verified by simulation and physical experiments. Compared with the integrated filtering algorithm which directly uses the error equation of inertial navigation system (INS) as the state equation, the proposed hierarchical filtering algorithm can achieve higher positioning precision.

scholarly journals Tightly Coupled Integrated Navigation Algorithm for Hypersonic Boost-Glide Vehicles in the LCEF Frame

Aerospace ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 124
Author(s):  
Kai Chen ◽  
Sensen Pei ◽  
Fuqiang Shen ◽  
Shangbo Liu
Keyword(s):  
Inertial Navigation ◽  
State Equation ◽  
Integrated Navigation ◽  
Loosely Coupled ◽  
Navigation Algorithm ◽  
Tightly Coupled ◽  
Measurement Equations ◽  
Range Rate ◽  
Better Than ◽  
Strapdown Inertial Navigation

According to the trajectory characteristics of hypersonic boost-glide vehicles, a tightly coupled integrated navigation algorithm for hypersonic vehicles based on the launch-centered Earth-fixed (LCEF) frame is proposed. First, the strapdown inertial navigation mechanization algorithm and discrete update algorithm in the LCEF frame are introduced. Subsequently, the attitude, velocity, and position error equations of strapdown inertial navigation in the LCEF frame are introduced. The strapdown inertial navigation system/global positioning system (SINS/GPS) pseudo-range and pseudo-range rate measurement equations in the LCEF frame are derived. Further, the tightly coupled SINS/GPS integrated navigation filter state equation and the measurement equation are presented. Finally, the tightly coupled SINS/GPS integrated navigation algorithm is verified in the hardware-in-the-loop (HWIL) simulation environment. The simulation results indicate that the precision of tightly coupled integrated navigation is better than that of loosely coupled integrated navigation. Moreover, even when the number of effective satellites is less than four, tightly coupled integrated navigation functions well, thus verifying the effectiveness and feasibility of the algorithm.

scholarly journals Relatively-Integrated Ship Navigation by H¥ Fusion Filters

2021 ◽  
Vol 15 (4) ◽  
pp. 1-12
Author(s):  
Yanping Yang ◽  
Ruiguang Li
Keyword(s):  
Automatic Identification ◽  
Integrated Navigation ◽  
Sequential Method ◽  
Filtering Algorithm ◽  
System Noise ◽  
Statistical Property ◽  
Observation Noise ◽  
Navigation Information ◽  
Fusion Framework ◽  
Navigation Method

For the system with unknown statistical property noises, the property that the energies of the system noise and the observation noise are limited is utilized in this paper. On this basis, two novel fusion algorithms are proposed for ship integrated navigation with the relative navigation information, broadcasted by the Automatic Identification Systems (AISs) in the adjacent ships. Firstly, an H∞ fusion filtering algorithm is given to deal with the navigation observation messages, under the centralized fusion framework. The integrated navigation method based on this algorithm cannot deal with the asynchronous navigation messages in real time. Therefore, a sequential H∞ fusion filtering algorithm is also given to sequentially deal with the asynchronous navigation messages, secondly. Finally, a computer simulation is employed to illustrate the validity and feasibility of the sequential method.

scholarly journals Relatively Integrated Ship Navigation by H∞ Fusion Filters

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Automatic Identification ◽  
Integrated Navigation ◽  
Sequential Method ◽  
Filtering Algorithm ◽  
System Noise ◽  
Statistical Property ◽  
Observation Noise ◽  
Navigation Information ◽  
Fusion Framework ◽  
Navigation Method

For the system with unknown statistical property noises, the property that the energies of the system noise and the observation noise are limited is utilized in this paper. On this basis, two novel fusion algorithms are proposed for ship integrated navigation with the relative navigation information, broadcasted by the Automatic Identification Systems (AISs) in the adjacent ships. Firstly, an H∞ fusion filtering algorithm is given to deal with the navigation observation messages, under the centralized fusion framework. The integrated navigation method based on this algorithm cannot deal with the asynchronous navigation messages in real time. Therefore, a sequential H∞ fusion filtering algorithm is also given to sequentially deal with the asynchronous navigation messages, secondly. Finally, a computer simulation is employed to illustrate the validity and feasibility of the sequential method.

scholarly journals An Improved Method of Geomagnetic Aided Inertial Navigation Algorithm with Gyro and Accelerometer Error Corrected Online

2018 ◽  
Vol 198 ◽  
pp. 02007
Author(s):  
Song ZhongGuo ◽  
Gao Jiuxiang ◽  
Zhang Jinsheng ◽  
Xi Xiaoli
Keyword(s):  
Affine Transformation ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Procrustes Analysis ◽  
Improved Method ◽  
Matching Algorithm ◽  
Navigation Algorithm ◽  
Reference Information ◽  
Gyro Drift ◽  
Navigation Method

In consideration of the problem that traditional geomagnetic aided navigation method cannot reduce the scaling error of indication track in inertial navigation system (INS), which will further limit the error correction precision of gyro and accelerometer, an improved geomagnetic matching algorithm based on affine transformation is proposed in this paper. A geomagnetic matching algorithm led to the optimal affine transformation solution by Procrustes analysis is presented and develops latitude and longitude reference information. Then a 13-dimensional-state extended Kalman filter which estimates the attitude misalignment angles, the position error, the velocity error, the Gyro drift, and accelerometer error is introduced to continuously update the output of INS and remove the accumulative error. The results show that geomagnetic aided navigation based on improved algorithm has better location accuracy and correction accuracy of INS than the traditional method.

scholarly journals The Inertial Integrated Navigation Algorithms in the Polar Region

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Li-Jun Song ◽  
Guang-Qiao Yang ◽  
Wang-Liang Zhao ◽  
You-Jun Ding ◽  
Feng Wu ◽  
...  
Keyword(s):  
Navigation System ◽  
Polar Region ◽  
Inertial Navigation ◽  
Integrated Navigation ◽  
Simulation Experiments ◽  
Integrated Navigation System ◽  
Existing Problems ◽  
Navigation Algorithm ◽  
Low Latitudes ◽  
Safety And Reliability

Because the accuracy of the existing airborne navigation is lacking in the polar region, it is difficult to ensure the safety and reliability of the aircraft when it is flying over the polar region. The integrated navigation system based on the inertial navigation technology uses multi-information fusion to assist collaborative navigation and obtain an indirect grid navigation algorithm that combines the azimuth navigation algorithm and the grid navigation algorithm to solve the existing problems. This paper analyzes the principle of the inertial navigation system in the polar region, the semiphysical simulation experiments are carried out by using the navigation theory and the background engineering, and the accuracies of the integrated navigation system of the indirect grid frame in the polar region and the integrated navigation system in the middle and low latitudes are consistent, which verifies the feasibility and effectiveness of the SINS/CNS/GPS integrated navigation system in the polar region. In addition, the paper provides the theoretical basis and the application of engineering to achieve the SINS/CNS/GPS integrated navigation system in the polar region.

scholarly journals Dual-Satellite Alternate Switching Ranging/INS Integrated Navigation Algorithm for Broadband LEO Constellation Independent of Altimeter and Continuous Observation

2021 ◽  
Vol 13 (16) ◽  
pp. 3312
Author(s):  
Lvyang Ye ◽  
Yikang Yang ◽  
Xiaolun Jing ◽  
Hengnian Li ◽  
Haifeng Yang ◽  
...  
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
State Equation ◽  
Low Earth Orbit ◽  
Integrated Navigation ◽  
Continuous Observation ◽  
Noise Interference ◽  
Location Service ◽  
Navigation Algorithm ◽  
Alternate Switching

In challenging environments such as forests, valleys and higher latitude areas, there are usually fewer than four visible satellites. For cases with only two visible satellites, we propose a dual-satellite alternate switching ranging integrated navigation algorithm based on the broadband low earth orbit (LEO) constellation, which integrates communication and navigation (ICN) technology. It is different from the traditional dual-satellite integrated navigation algorithm: the difference is that it can complete precise real-time navigation and positioning without an altimeter and continuous observation. First, we give the principle of our algorithm. Second, with the help of an unscented Kalman filter (UKF), we give the observation equation and state equation of our algorithm, and establish the mathematical model of multipath/non-line of sight (NLOS) and noise interference. Finally, based on the SpaceX constellation, for various scenarios, we analyze the performance of our algorithm through simulation. The results show that: our algorithm can effectively suppress the divergence of the inertial navigation system (INS), in the face of different multipath/NLOS interference and various noise environments it still keeps good robustness, and also has great advantages in various indicators compared with the traditional dual-satellite positioning algorithms and some existing 3-satellite advanced positioning algorithms. These results show that our algorithm can meet the real-time location service requirements in harsh and challenging environments, and provides a new navigation and positioning method when there are only two visible satellites.

A new visual/inertial integrated navigation algorithm based on sliding-window factor graph optimisation

2020 ◽  
pp. 1-17
Author(s):  
Haiying Liu ◽  
Jingqi Wang ◽  
Jianxin Feng ◽  
Xinyao Wang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Prior Information ◽  
Sliding Window ◽  
Factor Graph ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Sliding Windows ◽  
Navigation Algorithm ◽  
Almost All

Abstract Visual–Inertial Navigation Systems (VINS) plays an important role in many navigation applications. In order to improve the performance of VINS, a new visual/inertial integrated navigation method, named Sliding-Window Factor Graph optimised algorithm with Dynamic prior information (DSWFG), is proposed. To bound computational complexity, the algorithm limits the scale of data operations through sliding windows, and constructs the states to be optimised in the window with factor graph; at the same time, the prior information for sliding windows is set dynamically to maintain interframe constraints and ensure the accuracy of the state estimation after optimisation. First, the dynamic model of vehicle and the observation equation of VINS are introduced. Next, as a contrast, an Invariant Extended Kalman Filter (InEKF) is constructed. Then, the DSWFG algorithm is described in detail. Finally, based on the test data, the comparison experiments of Extended Kalman Filter (EKF), InEKF and DSWFG algorithms in different motion scenes are presented. The results show that the new method can achieve superior accuracy and stability in almost all motion scenes.

scholarly journals Single-Satellite Integrated Navigation Algorithm Based on Broadband LEO Constellation Communication Links

2021 ◽  
Vol 13 (4) ◽  
pp. 703
Author(s):  
Lvyang Ye ◽  
Yikang Yang ◽  
Xiaolun Jing ◽  
Jiangang Ma ◽  
Lingyu Deng ◽  
...  
Keyword(s):  
Real Time ◽  
Satellite Communication ◽  
The State ◽  
Earth Orbit ◽  
Integrated Navigation ◽  
Location Services ◽  
The Real ◽  
Navigation Algorithm ◽  
Communication Links ◽  
Leo Satellite

With the rapid development of satellite technology and the need to satisfy the increasing demand for location-based services, in challenging environments such as indoors, forests, and canyons, there is an urgent need to improve the position accuracy in these environments. However, traditional algorithms obtain the position solution through time redundancy in exchange for spatial redundancy, and they require continuous observations that cannot satisfy the real-time location services. In addition, they must also consider the clock bias between the satellite and receiver. Therefore, in this paper, we provide a single-satellite integrated navigation algorithm based on the elimination of clock bias for broadband low earth orbit (LEO) satellite communication links. First, we derive the principle of LEO satellite communication link clock bias elimination; then, we give the principle and process of the algorithm. Next, we model and analyze the error of the system. Subsequently, based on the unscented Kalman filter (UKF), we model the state vector and observation vector of our algorithm and give the state and observation equations. Finally, for different scenarios, we conduct qualitative and quantitative analysis through simulations, and the results show that, whether in an altimeter scenario or non-altimeter scenario, the performance indicators of our algorithm are significantly better than the inertial navigation system (INS), which can effectively overcome the divergence problem of INS; compared with the medium earth orbit (MEO) constellation, the navigation trajectory under the LEO constellation is closer to the real trajectory of the aircraft; and compared with the traditional algorithm, the accuracy of each item is improved by more than 95%. These results show that our algorithm not only significantly improves the position error, but also effectively suppresses the divergence of INS. The algorithm is more robust and can satisfy the requirements of cm-level real-time location services in challenging environments.

Research on outdoor AGV precise navigation based on BDS/INS data fusion

2021 ◽  
pp. 1-12
Author(s):  
Yongwei Tang ◽  
Huijuan Hao ◽  
Jun Zhou ◽  
Yuexiang Lin ◽  
Zhenzhen Dong
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Navigation System ◽  
Integrated Navigation ◽  
Complex Environments ◽  
Assisted Navigation ◽  
Precise Control ◽  
Bee Colony ◽  
Navigation Algorithm ◽  
Navigation Error

AGV (Automated Guided Vehicle) technology has attracted increasing attention. Precise control of AGV position and attitude information in complex operating environment is a key part of smart factories. With outdoor AGV as a platform, this study uses BDS/INS combined navigation system combining Beidou positioning system and inertial navigation system and takes the velocity and position difference between BDS and INS as a model. An integrated navigation method is proposed to improve bee colony algorithm and optimize the BP neural network-assisted Kalman filtering to achieve accurate positioning. Moreover, the optimization of BP neural network navigation using INS navigation, network-assisted navigation and bee colony algorithm is simulated. Results demonstrate that the integrated navigation algorithm has effectiveness and feasibility, and can solve the problems of BDS misalignment and large INS navigation error in complex environments.

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