scholarly journals Inertial-Navigation-Aided Single-Satellite Highly Dynamic Positioning Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4196 ◽  
Author(s):  
Lingling Zhang ◽  
Chengkai Tang ◽  
Yi Zhang ◽  
Houbing Song
Keyword(s):  
Target Location ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Satellite System ◽  
Global Navigation Satellite Systems ◽  
Positioning System ◽  
Position Change ◽  
Satellite Positioning ◽  
Initial Location ◽  
Positioning Algorithm

Nowadays, research on global navigation satellite systems (GNSS) has reached a certain level of maturity to provide high-precision positioning services in many applications. Nonetheless, there are challenging GNSS-denial environments where a temporarily deployed single-satellite positioning system is a promising choice. To further meet the emergency call of highly dynamic targets in such situations, an augmented single-satellite positioning algorithm is proposed in this paper. First, the initial location of the highly dynamic target is found by real-time displacement feedback from the inertial navigation system (INS). Then, considering the continuity of position change, and taking advantage of the high accuracy and robustness of the unscented Kalman filter (UKF), target location is through iteration and fusion. Comparing this proposed method with the least-squares Newton-iterative Doppler single-satellite positioning system and the pseudorange rate-assisted method under synthetic error conditions, the positioning error of our algorithm was 10 % less than the other two algorithms. This verified the validation of our algorithm in the single-satellite system with highly dynamic targets.

scholarly journals Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1055
Author(s):  
Qingyun Zhang ◽  
Jian Yang ◽  
Panpan Huang ◽  
Xin Liu ◽  
Shanpeng Wang ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
System Model ◽  
Degree Of Polarization ◽  
Positioning System ◽  
Integration Model ◽  
Position Errors ◽  
Model Combining ◽  
Polarization Compass

In this paper, to address the problem of positioning accumulative errors of the inertial navigation system (INS), a bionic autonomous positioning mechanism integrating INS with a bioinspired polarization compass is proposed. In addition, the bioinspired positioning system hardware and the integration model are also presented. Concerned with the technical issue of the accuracy and environmental adaptability of the integrated positioning system, the sun elevation calculating method based on the degree of polarization (DoP) and direction of polarization (E-vector) is presented. Moreover, to compensate for the latitude and longitude errors of INS, the bioinspired positioning system model combining the polarization compass and INS is established. Finally, the positioning performance of the proposed bioinspired positioning system model was validated via outdoor experiments. The results indicate that the proposed system can compensate for the position errors of INS with satisfactory performance.

scholarly journals A square root unscented Kalman filter for multiple view geometry based stereo cameras/inertial navigation

2016 ◽  
Vol 13 (5) ◽  
pp. 172988141666485 ◽  
Author(s):  
Zhiwen Xian ◽  
Junxiang Lian ◽  
Mao Shan ◽  
Lilian Zhang ◽  
Xiaofeng He ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Square Root ◽  
Multiple View Geometry ◽  
Multiple View ◽  
Stereo Cameras

scholarly journals Measurements and Accuracy Evaluation of a Strapdown Marine Gravimeter Based on Inertial Navigation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3902 ◽  
Author(s):  
Wei Wang ◽  
Jinyao Gao ◽  
Dongming Li ◽  
Tao Zhang ◽  
Xiaowen Luo ◽  
...  
Keyword(s):  
Coupling Effect ◽  
Inertial Navigation ◽  
Satellite System ◽  
Gravity Survey ◽  
Accuracy Evaluation ◽  
Earth’S Gravity Field ◽  
Marine Gravity ◽  
Global Navigation Satellite ◽  
Measuring Unit ◽  
Rough Sea

The strapdown gravimetry system uses the combination of an Inertial Measuring Unit (IMU) and a Global Navigation Satellite System (GNSS) to measure the Earth’s gravity field. Due to limited accuracies of IMU and GNSS, early strapdown gravimetry systems were more often used in airborne surveys, but less used in marine surveys. We developed a strapdown inertial navigation system (SINS), the Sea-Air Gravimeter-2Marine (SAG-2M), using novel IMU components, whose accuracy was further improved with the application of Precise Point Positioning (PPP) and enhanced algorithm, making it possible to be used in marine gravity survey. The testing results of the SAG-2M were compared to those of the Lacoste and Romberg S-129 gravimeter on the same ship in the South China Sea basin. The cruise lasted for 50 days, during which 134 effective gravity profiles were measured, resulting in 174 crossover points. The results showed that, for the SAG-2M, the root mean square (RMS) crossover points were 1.35 mGal before difference adjustment and 0.69 mGal after difference adjustment; for the S-129 gravimeter, they were 5.62 mGal and 0.95 mGal, correspondingly. In calm sea conditions, the results of the two systems were relatively consistent at all wavelengths. However, in rough sea conditions, since the SAG-2M was not affected by the cross-coupling effect, its data demonstrated less high-frequency jump. A physical platform adopted in SAG-2M can further make the transition data effective when the ship is turning around. Therefore, SAG-2M was able to improve the proportion of valid data and the efficiency of data post-processing for measurements taken during the cruise. The testing results indicate that in terms of accuracy and efficiency in the marine gravity survey, SAG-2M is better than S-129. In addition, as the miniaturization and precision of inertial components are developing continuously, SAG-2M also shows great potential in miniaturization.

scholarly journals Performance Evaluation of GPS Auto-Surveying Techniques

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7374
Author(s):  
João Manito ◽  
José Sanguino
Keyword(s):  
Kalman Filter ◽  
Least Squares ◽  
Unscented Kalman Filter ◽  
Weighted Least Squares ◽  
Base Station ◽  
Global Navigation Satellite Systems ◽  
Precise Position ◽  
Satellite Systems ◽  
Global Navigation Satellite ◽  
Position Estimate

With the increase in the widespread use of Global Navigation Satellite Systems (GNSS), increasing numbers of applications require precise position data. Of all the GNSS positioning methods, the most precise are those that are based in differential systems, such as Differential GNSS (DGNSS) and Real-Time Kinematics (RTK). However, for absolute positioning, the precision of these methods is tied to their reference position estimates. With the goal of quickly auto-surveying the position of a base station receiver, four positioning methods are analyzed and compared, namely Least Squares (LS), Weighted Least Squares (WLS), Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), using only pseudorange measurements, as well as the Hatch Filter and position thresholding. The research results show that the EKF and UKF present much better mean errors than LS and WLS, with an attained precision below 1 m after about 4 h of auto-surveying. The methods that presented the best results are then tested against existing implementations, showing them to be very competitive, especially considering the differences between the used receivers. Finally, these results are used in a DGNSS test, which verifies a significant improvement in the position estimate as the base station position estimate improves.

scholarly journals Low-Power Indoor Positioning Algorithm Based on iBeacon Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaona Zhang ◽  
Shufang Zhang ◽  
Shuaiheng Huai
Keyword(s):  
Low Power ◽  
Performance Improvement ◽  
General Framework ◽  
Logical Structure ◽  
Indoor Positioning ◽  
Positioning System ◽  
Depth Analysis ◽  
Communication Distance ◽  
Positioning Algorithm ◽  
Indoor Positioning System

In this article, we use a low-power iBeacon network to conduct an in-depth analysis and research on the principle of indoor positioning and adopt an efficient and fast positioning algorithm. Secondly, based on the obtained analysis, an iBeacon-based indoor positioning system is proposed to analyze how to use iBeacon for accurate positioning and whether it can effectively compensate for the current mainstream positioning system. We analyze the requirements of the iBeacon-based indoor positioning system and propose the design of this positioning system. We analyze the platform and environment for software development, design the general framework of the positioning system, and analyze the logical structure of the whole system, the structure of data flow, and the communication protocols between each module of the positioning system. Then, we analyze the functions of the server module and the client module of the system, implement the functions of each module separately, and debug the functions of each module separately after each module is implemented. The feasibility of the algorithm and the performance improvement are confirmed by the experimental data. Our results show that the communication distance is improved by approximately 20.25% and the accuracy is improved by 5.62% compared to other existing results.

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