scholarly journals Cooperative localisation with hybrid inertial navigation system/pedestrian dead reckoning tracking for GPS-denied environments

2016 ◽  
Author(s):  
Panagiotis Agis ◽  
Kai-Kit Wong ◽  
Zhongbin Zheng ◽  
Yangyang Zhang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Pedestrian Dead Reckoning

scholarly journals In-Motion Iterative Fine Alignment Algorithm for On-Board Vehicular Odometer-Aided SINS

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Baichun Gong ◽  
Chenglong He ◽  
Xiaoyue Wang ◽  
Xin Li
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Alignment Algorithm ◽  
Map Matching ◽  
Error Angle ◽  
Landmark Point ◽  
Principle Of Similarity ◽  
Digital Simulations

This research proposes a novel in-motion fine alignment algorithm for vehicular dead reckoning (DR) with odometer-aided strapdown inertial navigation system (SINS) while the map matching result is used for a group of landmark points to estimate misalignment angles. The proposed algorithm is designed based on principle of similarity, that is, trajectory of DR is similar to the true trajectory that the main difference between these two trajectories is rotation and scale. Further, the results from map matching are introduced as a group of landmark points to estimate the residual of azimuth error angle after coarse alignment and the scale factor error of the odometer. It is theoretically proved that the alignment effectiveness based on the results from map matching is equivalent to that on single zero error landmark point. Finally, digital simulations are conducted to verify the presented algorithm and test the performance.

scholarly journals Accurate integrated position and orientation method for vehicles based on strapdown inertial navigation system /Doppler radar

2018 ◽  
Vol 51 (9-10) ◽  
pp. 431-442 ◽  
Author(s):  
Yang Bo ◽  
Wang Yue-gang ◽  
Xue Liang ◽  
Shan Bin ◽  
Wang Bao-cheng
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Doppler Radar ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Strapdown Inertial Navigation System ◽  
Orientation Method ◽  
Integration Mode ◽  
Position And Orientation ◽  
Strapdown Inertial Navigation

In order to realize maneuver combat in the modern warfare, some special military vehicles require the ability of determining their position and orientation rapidly and accurately, and the position and orientation system should be highly autonomous and have strong anti-jamming capability. So a high-accuracy independent position and orientation method for vehicles that utilizes strapdown inertial navigation system/Doppler radar is presented in this article. Laser gyroscopes in strapdown inertial navigation system and Doppler radar are adopted to develop a dead-reckoning system for vehicles. Subsequently, the attitude, velocity,and position-updating algorithms of dead-reckoning system are designed. The error sources of dead-reckoning system are analyzed to establish the system error model, including the attitude error equations of the mathematical platform, velocity error equations, and position error equations. The errors of strapdown inertial navigation system and deadreckoning system are selected as system states of the integrated position and orientation method. The difference between the attitude output of strapdown inertial navigation system and that of dead-reckoning system, and the difference between the position output of strapdown inertial navigation system and that of dead-reckoning system are chosen as the measurements of integrated position and orientation. Then, Kalman filter is adopted to design the filtering algorithm of integrated position and orientation. In the end, the integrated position and orientation method is validated by simulation experiment and vehicular experiment. The experimental results show that strapdown inertial navigation system/Doppler radar integration can realize accurate positioning and orientation for a long time, and the accuracy of attitude/position integration mode is significantly higher than that of velocity/position integration mode. Therefore, the former integration mode is more suitable for accurate position and orientation for vehicles.

scholarly journals An Alignment Method for Strapdown Inertial Navigation Systems Assisted by Doppler Radar on a Vehicle-Borne Moving Base

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4577 ◽  
Author(s):  
Bo Yang ◽  
Jianxiang Xi ◽  
Jian Yang ◽  
Liang Xue
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Doppler Radar ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Vertical Direction ◽  
Strapdown Inertial Navigation System ◽  
Moving Base ◽  
The Dead ◽  
Strapdown Inertial Navigation

In this study, we investigated a novel method for high-accuracy autonomous alignment of a strapdown inertial navigation system assisted by Doppler radar on a vehicle-borne moving base, which effectively avoids the measurement errors caused by wheel-slip or vehicle-sliding. Using the gyroscopes in a strapdown inertial navigation system and Doppler radar, we calculated the dead reckoning, analyzed the error sources of the dead reckoning system, and established an error model. Then the errors of the strapdown inertial navigation system and dead reckoning system were treated as the states. Besides velocity information, attitude information was cleverly introduced into the alignment measurement to improve alignment accuracy and reduce alignment time. Therefore, the first measurement was the difference between the output attitude and velocity of the strapdown inertial navigation system and the corresponding signals from the dead reckoning system. In order to further improve the alignment accuracy, more measurement information was introduced by using the vehicle motion constraint, that is, the velocity output projection of strapdown inertial navigation system along the transverse and vertical direction of the vehicle body was also used as the second measurement. Then the corresponding state and measurement equations were established, and the Kalman filter algorithm was used for assisted alignment filtering. The simulation results showed that, with a moving base, the misalignment angle estimation accuracy was better than 0.5’ in the east direction, 0.4’ in the north direction, and 3.2’ in the vertical direction.

On In Situ Calibration of SINS and Doppler Dead Reckoning Navigation System

2012 ◽  
Vol 479-481 ◽  
pp. 2610-2615
Author(s):  
Kai Yao ◽  
Qi Dan Zhu ◽  
Bo Zhang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Strapdown Inertial Navigation System ◽  
Doppler Velocity ◽  
Navigation Algorithm ◽  
Calibration Algorithm ◽  
Strapdown Inertial Navigation

This paper addresses a practical problem arising in the calibration of bottom-lock doppler velocity log for the navigation of surface ships. Firstly, a dead reckoning navigation algorithm and briefly error analyze are proposed. Then, employing ship’s true trajectory and calculated trajectory, the rotational alignment offset between a bottom-lock doppler velocity log and a strapdown inertial navigation system as well as the scale factor error of the doppler velocity log can be experimentally determined using sensors commonly deployed with a vehicle in the field. It requires velocity values from the vehicle's doppler log and strapdown inertial navigation system, and absolute vehicle position fixes from a GPS receiver. Lake experiment results show that the calibration algorithm can calibrate the error parameters effectively, thus the position error decreases significantly after compensating the error parameters.

INS/Odometer Integration: Positional Approach

2021 ◽  
Vol 29 (2) ◽  
pp. 110-125
Author(s):  
A.A. Golovan ◽  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Strapdown Inertial Navigation System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Zero Velocity ◽  
Strapdown Inertial Navigation

The problem of a strapdown inertial navigation system (SINS) integration with an odometer as part of an integrated navigation system is considered. The odometer raw measurement is considered as an increment of the distance traveled along the odometer ‘measuring’ axis. Models of the integration solution components for the case of threedimensional navigation are presented, among which are the models of inertial autonomous and kinematic odometer dead reckoning (DR), models of relevant error equations, the model of SINS position aiding based on the odometer DR data and using GNSS position and velocity, wherever possible. The models comprise objective components, which do not depend on the type of the inertial sensors used and their accuracy grade, and variable components, which take into account the properties of the navigation sensors used. The integration does not require zero velocity updates, known as ZUPT correction, which are commonly used in navigation application.

scholarly journals Analysis and Improvement of Attitude Output Accuracy in Rotation Inertial Navigation System

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Kui Li ◽  
Pengyu Gao ◽  
Lei Wang ◽  
Qian Zhang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Angular Rate ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Measurement Unit ◽  
Short Term ◽  
High Attitude ◽  
Navigation Accuracy ◽  
Accelerometer Biases

Inertial navigation system (INS) measures vehicle’s angular rate and acceleration by orthogonally mounted tri-axis gyroscopes and accelerometers and then calculates the vehicle’s real-time attitude, velocity, and position. Gyroscope drifts and accelerometer biases are the key factors that affect the navigation accuracy. Theoretical analysis and experimental results show that the influence of gyroscope drifts and accelerometer biases can be restrained greatly in rotation INS (RINS) by driving the inertial measurement unit (IMU) rotating regularly, thus improving navigation accuracy significantly. High accuracy in position and velocity should be matched with that in attitude theoretically since INS is based on dead reckoning. However, the marine and vehicle experiments show that short-term attitude output accuracy of RINS is even worse compared with that of nonrotation INS. The loss of attitude accuracy has serious impacts on many task systems where high attitude accuracy is required. This paper researched the principle of attitude output accuracy loss in RINS and then proposed a new attitude output accuracy improvement algorithm for RINS. Experiment results show that the proposed attitude compensation method can improve short-term pitch and roll output accuracy from 20~30 arc seconds to less than 5 arc seconds and azimuth output accuracy improved from 2~3 arc minutes to less than 0.5 arc minutes in RINS.

scholarly journals A Gyroscope Bias Estimation Algorithm Based on Map Specific Information

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2534 ◽  
Author(s):  
Tian Tan ◽  
Ao Peng ◽  
Junjun Huang ◽  
Lingxiang Zheng ◽  
Gang Ou
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Dead Reckoning ◽  
Estimation Algorithm ◽  
Experimental Results ◽  
Specific Information ◽  
Euler Angles ◽  
Bias Estimation ◽  
Positioning Accuracy ◽  
Pedestrian Dead Reckoning

In an inertial navigation system, especially in a pedestrian dead-reckoning system, gyroscope bias can demonstrably reduce positioning accuracy. A novel gyroscope bias estimation algorithm is proposed, which estimates the bias of a gyroscope under any set of angle observations. Moreover, a method for obtaining Euler angles using map corridor information is proposed. The heading information obtained from a map is used to estimate the bias, and the estimated bias is used to correct the trajectories. Experimental results show that it is feasible for the algorithm to estimate the bias of the gyroscope.

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