• Journal of Positioning, Navigation, and Timing
• /
• v.8 no.3
• /
• pp.107-117
• /
• 2019

When a vehicle moves with a high rotation rate, it is not easy to measure the angular velocity using an off-the-shelf gyroscope. If the angular velocity is estimated using the extended Kalman filter in the gyro-free inertial navigation system, the effect of the accelerometer error and initial angular velocity error can be reduced. In this paper, in order to improve the navigation performance of the gyro-free inertial navigation system, an angular velocity estimation method is proposed based on an extended Kalman filter with an accelerometer random bias error model. In order to show the validity of the proposed estimation method, angular velocities and navigation outputs of a vehicle with 3 rev/s rotation rate are estimated. The results are compared with estimates by other methods such as the integration and an extended Kalman filter without an accelerometer random bias error model. The proposed method gives better estimation results than other methods.

• Journal of Korean Port Research
• /
• v.10 no.2
• /
• pp.61-68
• /
• 1996

The main problems in structural analysis by Finite Eelement Method are difficulty in making data file and error estimation. For decreasing these problems' pays. have been suggesting the adaptive mesh refinement and error estimation method. Posteriory error estimation methods suggested by Jang[1], Babuska[2,3], Ohtsubo[8,9], and this paper. Comparing these methods and examine their properties. According this paper, In the problem supposed having singularity, the method suggested by this paper is good, But the problem supposed having no singularity, the method suggested by Jang[1] is good. For decreasing the effect of initial mesh in p-refinement, make application h-refinement at first and apply p-refinement, and confine polynomial's degree to two, for making program simply by plural mesh models are not needed.

• Journal of Integrative Natural Science
• /
• v.5 no.3
• /
• pp.157-162
• /
• 2012

Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES III) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.

• 전자공학회논문지 IE
• /
• v.48 no.1
• /
• pp.30-35
• /
• 2011

In this paper, we propose a method to improve the performance of initial channel estimation (CE) for the multiband-OFDM (MB-OFDM) UWB. The performance of the initial CE can be generally improved as increasing the number of the used preamble symbols. The MB-OFDM specification presents two CE symbols per band in preamble format. The performance of CE estimation with two CE symbols may be satisfied in relatively high sensitivity -77.5 and -72.5 dBm for 200 Mbps and 480 Mbps data rate, respectively, but can not be enough in the degraded 55 Mbps and 110 Mbps sensitivities such as -83.5 and -80.5 dBm, respectively. A method proposed in this paper achieves the performance improvement by extending CE estimation region to packet synchronization (PS) symbols and frame synchronization (FS) symbols including two CE symbols. This can improve the CE performance in the degraded SNR and increase the link-margin by reducing the error rate in physical-layer header. The link-margin improvement obtained by the proposed CE preamble can induce the decrease of error-rate in physical-layer header and increase of communication throughput. Simulation results for the proposed initial method show that the performance is improved by about 0.7 dB at 10-4 bit-error-rate using '4' symbols than initial method using only two CE symbols.

• Proceedings of the KIEE Conference
• /
• 2005.04a
• /
• pp.207-209
• /
• 2005

Recently, the use of IPMSM is coming to be active, in many industrial applications. In sensorless drive of IPMSM, it is important to know the exact information of the initial rotor position, because the wrong estimation of the initial rotor position brings about the decrease of the starting torque, or a temporary reverse revolution, In addition, PMSM is necessary to use the accurate information of the inductance for the precise torque control owing to the reluctance torque. In this paper presents initial rotor position estimation method and, measure method of the each-axis inductance. And to minimize the speed estimations error, the estimated speeds are compensated by using an instantaneous reactive power in synchronously rotating reference frame.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.4
• /
• pp.468-473
• /
• 2014

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.2
• /
• pp.93-100
• /
• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

• ETRI Journal
• /
• v.29 no.5
• /
• pp.596-606
• /
• 2007

It is well known that an OFDM receiver is vulnerable to synchronization errors. Despite fine estimations used in the initial acquisition, there are still residual synchronization errors. Though these errors are very small, they severely degrade the bit error rate (BER) performance. In this paper, we propose a residual error elimination scheme for the digital OFDM baseband receiver aiming to improve the overall BER performance. Three improvements on existing schemes are made: a pilot-aided recursive algorithm for joint estimation of the residual carrier frequency and sampling time offsets; a delay-based timing error correction technique, which smoothly adjusts the incoming data stream without resampling disturbance; and a decision-directed channel gain update algorithm based on recursive least-squares criterion, which offers faster convergence and smaller error than the least-mean-squares algorithms. Simulation results show that the proposed scheme works well in the multipath channel, and its performance is close to that of an OFDM system with perfect synchronization parameters.

• Journal of Astronomy and Space Sciences
• /
• v.36 no.4
• /
• pp.249-264
• /
• 2019

In this study, the precise orbit determination (POD) software is developed for optical observation. To improve the performance of the estimation algorithm, a nonlinear batch filter, based on the unscented transform (UT) that overcomes the disadvantages of the least-squares (LS) batch filter, is utilized. The LS and UT batch filter algorithms are verified through numerical simulation analysis using artificial optical measurements. We use the real optical observation data of a low Earth orbit (LEO) satellite, Cryosat-2, observed from optical wide-field patrol network (OWL-Net), to verify the performance of the POD software developed. The effects of light travel time, annual aberration, and diurnal aberration are considered as error models to correct OWL-Net data. As a result of POD, measurement residual and estimated state vector of the LS batch filter converge to the local minimum when the initial orbit error is large or the initial covariance matrix is smaller than the initial error level. However, UT batch filter converges to the global minimum, irrespective of the initial orbit error and the initial covariance matrix.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.6
• /
• pp.545-550
• /
• 2009

Generally, the smoothing pre-filter of sensor's raw measurement(accelerometer and gyroscope) is used for INS's fast alignment. When the pre-filter is abruptly removed at Navigation-mode entry in vibration environment, INS's initial attitude error can be largely generated. So that we propose initial attitude error reducing methods(monotone increasing of cutoff-frequency, real-time attitude estimation), these are proved by simulation.