Navigation Kalman Filter Design for Pipeline Pigging

2005 ◽  
Vol 58 (2) ◽  
pp. 283-295 ◽  
Author(s):  
Eun-Hwan Shin ◽  
Naser El-Sheimy
Keyword(s):  
Kalman Filter ◽  
Natural Gas ◽  
Filter Design ◽  
Measurement Model ◽  
Velocity Measurements ◽  
Adaptive Kalman Filter ◽  
Holonomic Constraints ◽  
Measurement Models ◽  
The Past ◽  
Natural Gas Pipeline

The paper discusses the development of an adaptive Kalman filter for pipeline surveying applications. Various measurement models are developed and numerically tested using a real natural gas pipeline dataset. Since, for tactical-grade IMUs, odometer-derived velocity measurements alone cannot yield good results, two non-holonomic constraints are augmented to make the three-direction measurement model. Smoothing computation is also applied to yield the best trajectory using all the information contained in the past, current and future measurements. The trajectory errors are within 10–20 m for extreme cases, and within 10 m for most cases. RMS of the trajectory errors is expected to be about 2·5 m.

scholarly journals An Evaluation of Caucasian Countries with respect to Eurasian Natural Gas Pipeline Projects

2013 ◽  
Author(s):  
Nuri Gökhan Toprak
Keyword(s):  
Natural Gas ◽  
Regional Cooperation ◽  
Gas Pipeline ◽  
European Countries ◽  
Eastern European ◽  
Political Situation ◽  
The Past ◽  
Natural Gas Pipeline ◽  
Relative Stabilization ◽  
Gas Consumption

Breaking down the natural gas export monopoly of Russia against to the European countries is one the very challenging issues of European authorities in the past thirty years. Despite the introduction of the Norwegian and Algerian gas to the European market in recent years, European countries are still in search of the alternative gas exporter countries to meet their increasing gas consumption. When the expectations of European countries were combined with the relative stabilization of political structure in both South Eastern European and Caucasian countries, the alternative Eurasian natural gas pipeline projects came to the European agenda gradually. In this study, it will be analyzed that both the economic and political situation of Azerbaijan, Georgia and Armenia in terms of their participation to the ongoing Eurasian natural gas projects that plans to deliver natural gas resources of the Caspian Basin to Europe. Within this context, after the brief introduction to explain what those Eurasian natural gas projects are, it will be given information, analyzed and discussed that the current positions of the Caucasian countries against these projects. It is important that the evaluation of the Eurasian Natural Gas Pipeline Projects in the case of the Caucasian countries makes the final step more reliable which will strengthen the economic integration and regional cooperation of Caucasian countries.

scholarly journals Multiple Adaptive Fading Schmidt-Kalman Filter for Unknown Bias

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Tai-Shan Lou ◽  
Zhi-Hua Wang ◽  
Meng-Li Xiao ◽  
Hui-Min Fu
Keyword(s):  
Kalman Filter ◽  
Dynamic Systems ◽  
Measurement Model ◽  
Covariance Matrices ◽  
The State ◽  
Negative Effects ◽  
Measurement Models ◽  
Initial Values ◽  
Kalman Filter Algorithm ◽  
Unknown Bias

Unknown biases in dynamic and measurement models of the dynamic systems can bring greatly negative effects to the state estimates when using a conventional Kalman filter algorithm. Schmidt introduces the “consider” analysis to account for errors in both the dynamic and measurement models due to the unknown biases. Although the Schmidt-Kalman filter “considers” the biases, the uncertain initial values and incorrect covariance matrices of the unknown biases still are not considered. To solve this problem, a multiple adaptive fading Schmidt-Kalman filter (MAFSKF) is designed by using the proposed multiple adaptive fading Kalman filter to mitigate the negative effects of the unknown biases in dynamic or measurement model. The performance of the MAFSKF algorithm is verified by simulation.

scholarly journals A Kalman filter application for rainfall estimation using radar reflectivity measurements

2019 ◽  
pp. 1198-1212
Author(s):  
ENGİN MAŞAZADE ◽  
ALİ KEMAL BAKIR ◽  
PINAR KIRCI
Keyword(s):  
Kalman Filter ◽  
Process Model ◽  
Measurement Model ◽  
Rainfall Amount ◽  
Radar Reflectivity ◽  
Measurement Models ◽  
Weather Radars ◽  
Filter Process ◽  
The Mean ◽  
Weather Observation

The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed at each AWOS location. For the execution of the Kalman filter, a number of rainfall amount and radar reflectivity value pairs are first required to learn the process and measurement models of the Kalman filter. The estimation performance of the proposed Kalman filter is then compared with empirical reflectivity (Z) - rainfall (R) relationships. Numerical results show that when the Kalman filter is executed with radar reflectivity measurements observed around a large number of AWOS locations, the mean squared errors of the Kalman filter rainfall estimates are smaller than the ones obtained with empirical ZR relationships.

scholarly journals Autonomous Positioning of Satellite Constellations via X-ray Pulsar Measurements

2013 ◽  
Vol 66 (5) ◽  
pp. 671-682 ◽  
Author(s):  
Li Liu ◽  
Wei Zheng ◽  
Guojian Tang
Keyword(s):  
Numerical Simulation ◽  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Measurement Model ◽  
Orbital Dynamics ◽  
Satellite Constellations ◽  
X Ray ◽  
Measurement Models ◽  
Measurement Scheme ◽  
Dynamics Models

A novel autonomous positioning approach based on X-ray pulsars is proposed in this paper. First, the principles of the pulsar–based measurement model and the inter-satellite range model in the autonomous positioning of satellite constellations are presented. The observability of the pulsar-based measurement model is then shown. Second, the autonomous positioning algorithms, including measurement models and orbital dynamics models, are formulated using an unscented Kalman filter to estimate the position vectors of satellites. Finally, the feasibility of the proposed measurement scheme compared with an inter-satellite range scheme is illustrated by numerical simulation. The results show that the proposed approach can keep the satellite state convergent, and achieve position accuracies of 2 m. The proposed scheme provides a promising approach for autonomous absolute positioning of constellation systems by using X-ray pulsars.

Fuzzy adaptive Kalman filter for the drive system with an elastic coupling

2013 ◽  
Vol 62 (2) ◽  
pp. 251-265 ◽  
Author(s):  
Piotr J. Serkies ◽  
Krzysztof Szabat
Keyword(s):  
Kalman Filter ◽  
Control Structure ◽  
Experimental Tests ◽  
Drive System ◽  
Adaptive Kalman Filter ◽  
State Matrix ◽  
State Controller ◽  
Kalman Gain ◽  
Robust Adaptive ◽  
Fuzzy Adaptive

Abstract In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and experimental tests.

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