scholarly journals Compensation of time-varying clock-offset in a LBL navigation

2020 ◽  
Vol 9 (4) ◽  
pp. 1364-1372
Author(s):  
Yohannes S. M. Simamora ◽  
Harijono A. Tjokronegoro ◽  
Edi Leksono ◽  
Irsan S. Brodjonegoro
Keyword(s):  
The State ◽  
Time Varying ◽  
State Estimator ◽  
Clock Rate ◽  
Long Baseline ◽  
Clock Offset

This paper presents compensation of the clock-offset in a long baseline (LBL)navigation. It departs from the existing literature mainly in dealing with a time-varyingclock-offset, i.e. the clock-rate drifts over the time. Specifically, the clock-offsetdynamics are introduced to the ToFs as an autoregressive filter.Subsequently,interactions among the now biased ToFs and the kinematics of an autonomousunderwater vehicle (AUV)–the navigation subject–are represented in a state-spaceform. Implementing the so-called graphic approach, minimum sensor requirementfor this system’s observability is then explicated. Finally, a standard discrete Kalmanfilter is deployed as the state estimator. By simulation, it is demonstrated that theestimator manages to compensate the offset and to provide localization with less than1 m accuracy

scholarly journals Influence of Adopted Nutation Model on VLBI NEOS-Intensives Analysis

2000 ◽  
Vol 180 ◽  
pp. 259-262 ◽  
Author(s):  
Oleg Titov
Keyword(s):  
Very Long Baseline Interferometry ◽  
Parametric Model ◽  
Universal Time ◽  
Reference Station ◽  
Earth’S Rotation ◽  
Clock Rate ◽  
Long Baseline ◽  
Vlbi Data ◽  
Intensive Program ◽  
Clock Offset

Very Long Baseline Interferometry (VLBI) provides information about the Earth’s rotation. Various observational programs have operated for different specific purposes since 1983. The purpose of the NEOS-Intensive program is to make observations of Universal Time (UT1–UTC). Short observational sessions (1-2 hours) include only the transcontinental baseline (Wettzell - NRAO20). 20–30 individual scans are performed during the observational time. Only five parameters, wet delay for the reference station, wet delay for the second station, clock offset for the second station, clock rate for the second station, and UT1–UTC are considered in the parametric model.The purpose of this paper is to investigate the influence of the adopted nutation model on the UT1–UTC estimates. VLBI data from the NEOS-Intensives have been analyzed using the OCCAM 3.4 software. All reduction calculations are in accordance with the IERS Conventions 1996 (McCarthy, 1996).

State Estimation Using Randomly Delayed Measurements

1993 ◽  
Vol 115 (1) ◽  
pp. 19-26 ◽  
Author(s):  
A. Ray ◽  
L. W. Liou ◽  
J. H. Shen
Keyword(s):  
State Estimation ◽  
Minimum Variance ◽  
The State ◽  
Sensor Data ◽  
State Estimator ◽  
Uniform Asymptotic Stability ◽  
Simulation Experiments ◽  
State Estimate ◽  
Sampling Instant ◽  
Recursive Relations

This paper presents a modification of the conventional minimum variance state estimator to accommodate the effects of randomly varying delays in arrival of sensor data at the controller terminal. In this approach, the currently available sensor data is used at each sampling instant to obtain the state estimate which, in turn, can be used to generate the control signal. Recursive relations for the filter dynamics have been derived, and the conditions for uniform asymptotic stability of the filter have been conjectured. Results of simulation experiments using a flight dynamic model of advanced aircraft are presented for performance evaluation of the state estimation filter.

scholarly journals State Estimation for Cooperative Lateral Vehicle Following Using Vehicle-to-Vehicle Communication

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 651
Author(s):  
Wouter Schinkel ◽  
Tom van der Sande ◽  
Henk Nijmeijer
Keyword(s):  
State Estimation ◽  
Cooperative Control ◽  
The State ◽  
State Estimator ◽  
Estimation Process ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Control Schemes ◽  
Input Signals ◽  
Vehicle To Vehicle Communication

A cooperative state estimation framework for automated vehicle applications is presented and demonstrated via simulations, the estimation framework is used to estimate the state of a lead and following vehicle simultaneously. Recent developments in the field of cooperative driving require novel techniques to ensure accurate and stable vehicle following behavior. Control schemes for the cooperative control of longitudinal and lateral vehicle dynamics generally require vehicle state information about the lead vehicle, which in some cases cannot be accurately measured. Including vehicle-to-vehicle communication in the state estimation process can provide the required input signals for the practical implementation of cooperative control schemes. This study is focused on demonstrating the benefits of using vehicle-to-vehicle communication in the state estimation of a lead and following vehicle via simulations. The state estimator, which uses a cascaded Kalman filtering process, takes the operating frequencies of different sensors into account in the estimation process. Simulation results of three different driving scenarios demonstrate the benefits of using vehicle-to-vehicle communication as well as the attenuation of measurement noise. Furthermore, in contrast to relying on low frequency measurement data for the input signals of cooperative control schemes, the state estimator provides a state estimate at every sample.

Prognostics Health Management Model for LED Package Failure Under Contaminated Environment

2015 ◽  
Author(s):  
Pradeep Lall ◽  
Hao Zhang ◽  
Lynn Davis
Keyword(s):  
Health Management ◽  
Luminous Flux ◽  
The State ◽  
Remaining Useful Life ◽  
Integrating Sphere ◽  
State Estimator ◽  
Acceptable Error ◽  
Color Shift ◽  
Useful Life ◽  
The Impact

The reliability consideration of LED products includes both luminous flux drop and color shift. Previous research either talks about luminous maintenance or color shift, because luminous flux degradation usually takes very long time to observe. In this paper, the impact of a VOC (volatile organic compound) contaminated luminous flux and color stability are examined. As a result, both luminous degradation and color shift had been recorded in a short time. Test samples are white, phosphor-converted, high-power LED packages. Absolute radiant flux is measured with integrating sphere system to calculate the luminous flux. Luminous flux degradation and color shift distance were plotted versus aging time to show the degradation pattern. A prognostic health management (PHM) method based on the state variables and state estimator have been proposed in this paper. In this PHM framework, unscented kalman filter (UKF) was deployed as the carrier of all states. During the estimation process, third order dynamic transfer function was used to implement the PHM framework. Both of the luminous flux and color shift distance have been used as the state variable with the same PHM framework to exam the robustness of the method. Predicted remaining useful life is calculated at every measurement point to compare with the tested remaining useful life. The result shows that state estimator can be used as the method for the PHM of LED degradation with respect to both luminous flux and color shift distance. The prediction of remaining useful life of LED package, made by the states estimator and data driven approach, falls in the acceptable error-bounds (20%) after a short training of the estimator.

Output Control by Linear Time-Varying Systems using Parametric Identification Methods

2020 ◽  
Vol 21 (7) ◽  
pp. 387-393
Author(s):  
V. Q. Dat ◽  
A. A. Bobtsov
Keyword(s):  
Differential Equation ◽  
Initial Conditions ◽  
Control Object ◽  
The State ◽  
Time Varying ◽  
State Variables ◽  
Matrix Differential Equation ◽  
Matrix Differential ◽  
Uniform Observability ◽  
Riccati Matrix

In this paper the problem of control for time-varying linear systems by the output (i.e. without measuring the vector of state variables or derivatives of the output signal) was considered. For the control design, the well-known online procedure for solving the Riccati matrix differential equation is chosen. This procedure involves the synthesis of linear static feedbacks on state variables in the case of known parameters of the plant. If state variables are not measured, then for the observer design using the matrix Riccati differential equation, using the dual scheme, which provides for the transposition of the state matrix and the replacement of the input matrix by the output matrix. It is well known that an observer of state variables built on the basis of a solution of the Riccati matrix differential equation ensures the exponential stability of a closed loop system in the case of uniform observability. Despite the fact that this type of observer can be classified as universal, its have a number of significant drawbacks. The main problem of such observers is the need for accurate knowledge of the parameters and the requirement for uniform observability, which in practice cannot always be realized. Thus, the problem of the new methods design for constructing observers of state variables of linear non-stationary systems is still relevant. Some time ago, a number of methods for the adaptive observers design of state variables for nonlinear systems were proposed. The main idea of the synthesis of observers was based on the transformation of the original dynamic system to a linear regression model containing unknown parameters, which in turn were functions of the initial conditions of the state variables of the control object. This approach in the English language literature is called PEBO. This paper, based on the PEBO method, proposes a new approach for the observers design of state for non-stationary systems. This approach provides the possibility of obtaining monotonic convergence estimates with transient time tuning.

Orbit Determination of Geostationary Earth Orbit Satellite by Transfer with Differenced Ranges between Slave-Slave Stations

2013 ◽  
Vol 67 (1) ◽  
pp. 163-175 ◽  
Author(s):  
Cao Fen ◽  
Yang XuHai ◽  
Su MuDan ◽  
Li ZhiGang ◽  
Feng ChuGang ◽  
...  
Keyword(s):  
Orbit Determination ◽  
Very Long Baseline Interferometry ◽  
Baseline Length ◽  
Positioning System ◽  
Orbit Error ◽  
Long Baseline ◽  
Data Volume ◽  
Clock Offset ◽  
Range Observation

In order to more restrict the transverse orbit error, a new method named “differenced ranges between slave stations by transfer”, similar to Very Long Baseline Interferometry (VLBI) observation, has been developed in the Chinese Area Positioning System (CAPS). This method has the number of baselines added, the baseline length increased and the data volume enlarged. In this article, the principle of “differenced ranges between slave stations by transfer” has been described in detail, with the clock offset between slave stations and system error which affects the precision of the differenced ranges observation being discussed. Using this method, the differenced observation of the SINOSAT-1 satellite with C-band between slave stations from 6 to 13 June 2005 was conducted. Then a comparison was made between the accuracy of orbit determination and orbit prediction. A conclusion can be drawn that the combination of pseudo-range receiving the own-station-disseminated signal and the differenced range observation between slave-slave stations has a higher orbit determination and prediction accuracy than using only the former.

scholarly journals Parameter and State Estimator for State Space Models

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Ruifeng Ding ◽  
Linfan Zhuang
Keyword(s):  
State Space ◽  
State Equation ◽  
The State ◽  
Parameter Estimates ◽  
Identification Algorithm ◽  
State Variables ◽  
Input Output ◽  
State Estimator ◽  
Output Data ◽  
Canonical State

This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

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