Keynote: A Common Framework for Inertial Sensor Error Modeling

2017 ◽  
Author(s):  
Juan D. Jurado ◽  
John F. Raquet
Keyword(s):  
Inertial Sensor ◽  
Error Modeling ◽  
Sensor Error ◽  
Common Framework

Wavelet-Based Improvements for Inertial Sensor Error Modeling

2016 ◽  
Vol 65 (12) ◽  
pp. 2693-2700 ◽  
Author(s):  
Stephane Guerrier ◽  
Roberto Molinari ◽  
Yannick Stebler
Keyword(s):  
Inertial Sensor ◽  
Error Modeling ◽  
Sensor Error

scholarly journals Performance Criteria for the Identification of Inertial Sensor Error Models

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1997 ◽  
Author(s):  
Oleg Stepanov ◽  
Andrei Motorin
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
Identification Problem ◽  
Performance Criteria ◽  
Problem Solution ◽  
Error Models ◽  
Sensor Error ◽  
Joint Problem ◽  
Suboptimal Algorithms ◽  
The Bayesian Approach

This paper considers performance criteria for the identification of sensor error models and the procedure for their calculation. These criteria are used to investigate the efficiency of the identification problem solution, depending on the initial data, and to carry out a comparative analysis of various suboptimal algorithms. The calculation procedure is based on an algorithm that solves the joint problem of hypothesis recognition and parameter estimation within the Bayesian approach. A performance analysis of the models traditionally used to describe errors of inertial sensors is given to illustrate the application of the procedure for the calculation of performance criteria.

scholarly journals Inertial Sensor Error Reduction through Calibration and Sensor Fusion

Sensors ◽  
2016 ◽  
Vol 16 (2) ◽  
pp. 235 ◽  
Author(s):  
Stefan Lambrecht ◽  
Samuel Nogueira ◽  
Magdo Bortole ◽  
Adriano Siqueira ◽  
Marco Terra ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Inertial Sensor ◽  
Error Reduction ◽  
Sensor Error

Robust wavelet-based inertial sensor error mitigation for tightly coupled GPS/BDS/INS integration during signal outages

Survey Review ◽  
2016 ◽  
Vol 49 (357) ◽  
pp. 419-427 ◽  
Author(s):  
Jian Wang ◽  
Houzeng Han ◽  
Xiaolin Meng ◽  
Lihui Yao ◽  
Zengke Li
Keyword(s):  
Inertial Sensor ◽  
Sensor Error ◽  
Error Mitigation ◽  
Tightly Coupled

Optimisation-based Transfer Alignment and Calibration Method for Inertial Measurement Vector Integration Matching

2016 ◽  
Vol 70 (3) ◽  
pp. 595-606 ◽  
Author(s):  
Lili Xie ◽  
Jiazhen Lu
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Prior Information ◽  
Inertial Sensor ◽  
Inertial Navigation ◽  
Inertial Measurement ◽  
Transfer Alignment ◽  
Sensor Error ◽  
Vector Integration ◽  
Measurement Vector

The traditional Kalman filtering-based transfer alignment methods largely depend on prior information for initialisation. However, the initialisation process is hard to fulfil on a moving base. In this paper, a type of inertial measurement vector integration matching for optimisation-based transfer alignment and calibration is proposed to estimate the misalignment between the Master Inertial Navigation System (MINS) and Slave Inertial Navigation System (SINS), and main inertial sensor error parameters of SINS, including bias and scale factor error. In contrast to filter techniques, the proposed method has the capability of self-initialisation and provides a new idea to solve the alignment and calibration problem. No prior information is needed. Moreover, the integration time interval for the matching inertial measurement vector is selected by considering both the observation degree of inertial sensor error parameters and the noise effect. Simulation results demonstrate that the proposed method has faster convergence and is more accurate than Kalman filter techniques.

scholarly journals Conservative Sensor Error Modeling Using a Modified Paired Overbound Method and its Application in Satellite-Based Augmentation Systems

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2826
Author(s):  
Yan Zhang ◽  
Zhibin Xiao ◽  
Pengpeng Li ◽  
Xiaomei Tang ◽  
Gang Ou
Keyword(s):  
Interval Estimation ◽  
Original Method ◽  
Error Modeling ◽  
Maximum Deviation ◽  
Data Loss ◽  
Sensor Error ◽  
Confidence Interval Estimation ◽  
Integrity Risk ◽  
Non Gaussian ◽  
Improved Algorithm

Conservative sensor error modeling is of great significance in the field of safety-of-life. At present, the overbound method has been widely used in areas such as satellite-based augmentation systems (SBASs) and ground-based augmentation systems (GBASs) that provide integrity service. It can effectively solve the difficulties of non-Gaussian and non-zero mean error modeling and confidence interval estimation of user position error. However, there is still a problem in that the model is too conservative and leads to the lack of availability. In order to further improve the availability of SBASs, an improved paired overbound method is proposed in this paper. Compared with the traditional method, the improved algorithm no longer requires the overbound function to conform to the characteristics of the probability distribution function, so that under the premise of ensuring the integrity of the system, the real error characteristics can be more accurately modeled and measured. The experimental results show that the modified paired overbound method can improve the availability of the system with a probability of about 99%. In view of the fact that conservative error modeling is more sensitive to large deviations, this paper analyzes the robustness of the improved algorithm in the case of abnormal data loss. The maximum deviation under a certain integrity risk is used to illustrate the effectiveness of the improved paired overbound method compared with the original method.

scholarly journals The Optimal Design of Modulation Angular Rate for MEMS-Based Rotary Semi-SINS

Micromachines ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 111 ◽  
Author(s):  
Jiayu Zhang ◽  
Jie Li ◽  
Xiaorui Che ◽  
Xi Zhang ◽  
Chenjun Hu ◽  
...  
Keyword(s):  
Rotation Speed ◽  
Inertial Sensor ◽  
Design Method ◽  
Angular Rate ◽  
Sensor Error ◽  
Speed Error ◽  
Rotation Scheme ◽  
Navigation Error ◽  
Roll Axis ◽  
Motion Characteristics

In previous studies, the semi-strapdown inertial navigation system (SSINS), based on microelectromechanical system (MEMS) sensors, had realized cross-range measurement of attitude information of high-spinning projectiles through construction of a “spin reduction” platform of the roll axis. However, further improvement of its measurement accuracy has been difficult, due to the inertial sensor error. In order to enhance the navigational accuracy, a periodically rotating method is utilized to compensate for sensor error, which is called rotation modulation. At present, the rotation scheme, as one of the core technologies, has been studied by a lot of researchers. It is known that the modulation angular rate is the main factor affecting the effectiveness of error modulation. Different from the long-endurance and low-dynamic motion characteristics of ships, however, the short-endurance and high-dynamic characteristics of the high-spinning projectile not only require the modulation angular rate to be as fast as possible but, also, the influence of the rotation speed error caused by rotating mechanism errors cannot be ignored. Combined with the rotation speed error of the rotating mechanism, this paper explored the relationship between modulation angular rate, device error, and the navigation error, and then proposed a design method for optimal modulation angular rate. Experiments were carried out to validate the performance of the method. In addition, the proposed method is applicable for rotation modulation systems with different types of motors as the rotating mechanism.

Sign in / Sign up

Export Citation Format

Share Document