scholarly journals Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4432
Author(s):  
Minghao Wang ◽  
Juliang Cao ◽  
Shaokun Cai ◽  
Meiping Wu ◽  
Kaidong Zhang ◽  
...  
Keyword(s):  
Field Data ◽  
Flight Test ◽  
Attitude Measurement ◽  
Integrated Navigation ◽  
Accuracy Improvement ◽  
Forward Algorithm ◽  
Navigation Algorithm ◽  
Improvement Method ◽  
Vector Gravimetry ◽  
No Sensor

Strapdown airborne gravimetry is an efficient way to obtain gravity field data. A new method has been developed to improve the accuracy of airborne vector gravimetry. The method introduces a backward strapdown navigation algorithm into the strapdown gravimetry, which is the reverse process of forward algorithm. Compared with the forward algorithm, the backward algorithm has the same performance in the condition of no sensor error, but has different error characteristics in actual conditions. The differences of the two algorithms in the strapdown gravimetry data processing are presented by simulations, which show that the two algorithms have different performance in the horizontal attitude measurement and convergence of integrated navigation filter. On the basis of detailed analysis, the procedures of accuracy improvement method are presented. The result of this method is very promising when applying to an actual flight test carried out by a SGA-WZ02 strapdown gravimeter. After applying the proposed method, the repeatability of two gravity disturbance horizontal components were 1.83 mGal and 1.80 mGal under the resolution of 6 km, which validate the effectiveness of the method. Furthermore, the wavenumber correlation filter is also discussed as an alternative data fusion method.

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.

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.

Mobile robot integrated navigation algorithm based on template matching VO/IMU/UWB

2021 ◽  
pp. 1-1
Author(s):  
Yuhong Zheng ◽  
Qingxi Zeng ◽  
Chade Lv ◽  
Haonan Yu ◽  
Bangjun Ou
Keyword(s):  
Mobile Robot ◽  
Template Matching ◽  
Integrated Navigation ◽  
Navigation Algorithm
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