• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2107-2113
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• 2014

Particle filtering (PF) has shown its outperforming results compared to that of classical Kalman filtering (KF), particularly for highly nonlinear problems. However, PF may not be universally superior to the extended KF (EKF) although the case (i.e. an example that the EKF outperforms PF) is seldom reported in the literature. Particularly, PF approaches show degraded performance for problems where the state noise is very small or zero. This is because particles become identical within a few iterations, which is so called particle impoverishment (PI) phenomenon; consequently, no matter how many particles are employed, we do not have particle diversity regardless of if the impoverished particle is close to the true state value or not. In this paper, we investigate this PI phenomenon, and show an example problem where a classical KF approach outperforms PF approaches in terms of mean squared error (MSE) criterion. Furthermore, we compare the processing speed of the EKF and PF approaches, and show the better speed performance of classical EKF approaches. Therefore, PF approaches may not be always better option than the classical EKF for nonlinear problems. Specifically, we show the outperforming result of unscented Kalman filter compared to that of PF approaches (which are shown in Fig. 7(c) for processing speed performance, and Fig. 6 for MSE performance in the paper).

• 한국지능시스템학회논문지
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• 제25권1호
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• pp.70-77
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• 2015

본 논문은 수중 로봇 위치추정을 위하여 무향 칼만 필터 방법을 제안한다. 이 방법은 해저 지형 정보와 로봇으로부터 수심측정을 비교한다. 해저 수심 범위의 측정을 위해, DVL 센서를 이용한다. 일반적으로 DVL은 로봇의 속도 정보와 4개의 거리 데이터를 획득한다. 확장 칼만 필터는 지형 수심 범위 측정을 위해 자코비안을 유도하기가 가능하지 않기 때문에 지형정보를 이용한 방법에는 유용하지가 않는다. 파티클 필터는 자코비안을 필요로하지 않고, 비선형 및 비 가우시안 시스템에 좋은 해결책이지만 연산량이 많은 단점이 있다. 본 논문에서는 무향 칼만 필터와 파티클 필터의 위치추정 성능과 처리 속도를 비교한다. 수중 네비게이션에 사용되는 무향 칼만 필터 방법은 일부 있지만 해저 지형 정보를 이용한 방법은 극히 드물다. 특히, 제안된 방법은 수백개의 스캔 범위 데이터를 사용하지 않고 4개의 범위 데이터만을 이용한다. 본 논문에서는 4개의 거리 데이터를 가지고 해저 지형을 기반을 둔 위치추정을 위한 무향 칼만 필터 방법의 접근 가능성을 보인다.

• Journal of Astronomy and Space Sciences
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• 제35권3호
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• pp.163-173
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• 2018

This paper presents relative navigation using intermittent laser-based measurement data for spacecraft flying formation that consist of two spacecrafts; namely, chief and deputy spacecrafts. The measurement data consists of the relative distance measured by a femtosecond laser, and the relative angles between the two spacecrafts. The filtering algorithms used for the relative navigation are the extended Kalman filter (EKF), unscented Kalman filter (UKF), and least squares recursive filter (LSRF). Numerical simulations reveal that the relative navigation performances of the EKF- and UKF-based relative navigation algorithms decrease in accuracy as the measurement outage period increases. However, the relative navigation performance of the UKF-based algorithm is 95 % more accurate than that of the EKF-based algorithm when the measurement outage period is 80 sec. Although the relative navigation performance of the LSRF-based relative navigation algorithm is 94 % and 370 % less accurate than those of the EKF- and UKF-based navigation algorithms, respectively, when the measurement outage period is 5 sec; the navigation error varies within a range of 4 %, even though the measurement outage period is increased. The results of this study can be applied to the design of a relative navigation strategy using the developed algorithms with laser-based measurements for spacecraft formation flying.

• Smart Structures and Systems
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• 제20권5호
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• pp.619-636
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• 2017

Magnetorheological (MR) damper is a type of controllable device widely used in vibration mitigation. This device is highly nonlinear, and exhibits strongly hysteretic behavior that is dependent on both the motion imposed on the device and the strength of the surrounding electromagnetic field. An accurate model for understanding and predicting the nonlinear damping force of the MR damper is crucial for its control applications. The MR damper models are often identified off-line by conducting regression analysis using data collected under constant voltage. In this study, a MR damper model is integrated with a model for the power supply unit (PSU) to consider the dynamic behavior of the PSU, and then a real-time nonlinear model updating technique is proposed to accurately identify this integrated MR damper model with the efficiency that cannot be offered by off-line methods. The unscented Kalman filter is implemented as the updating algorithm on a cyber-physical model updating platform. Using this platform, the experimental study is conducted to identify MR damper models in real-time, under in-service conditions with time-varying current levels. For comparison purposes, both off-line and real-time updating methods are applied in the experimental study. The results demonstrate that all the updated models can provide good identification accuracy, but the error comparison shows the real-time updated models yield smaller relative errors than the off-line updated model. In addition, the real-time state estimates obtained during the model updating can be used as feedback for potential nonlinear control design for MR dampers.

• Smart Structures and Systems
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• 제32권1호
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• pp.9-21
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• 2023

The parameters of civil engineering structures have time-variant characteristics during their service. When extremely large external excitations, such as earthquake excitation to buildings or overweight vehicles to bridges, apply to structures, sudden or gradual damage may be caused. It is crucially necessary to detect the occurrence time and severity of the damage. The unscented Kalman filter (UKF), as one efficient estimator, is usually used to conduct the recursive identification of parameters. However, the conventional UKF algorithm has a weak tracking ability for time-variant structural parameters. To improve the identification ability of time-variant parameters, an adaptive UKF with forgetting factor (AUKF-FF) algorithm, in which the state covariance, innovation covariance and cross covariance are updated simultaneously with the help of the forgetting factor, is proposed. To verify the effectiveness of the method, this paper conducted two case studies as follows: the identification of time-variant parameters of a simply supported bridge when the vehicle passing, and the model updating of a six-story concrete frame structure with field test during the Yangbi earthquake excitation in Yunnan Province, China. The comparison results of the numerical studies show that the proposed method is superior to the conventional UKF algorithm for the time-variant parameter identification in convergence speed, accuracy and adaptability to the sampling frequency. The field test studies demonstrate that the proposed method can provide suggestions for solving practical problems.

• 한국항행학회논문지
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• 제15권4호
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• pp.536-542
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• 2011

본 논문에서는 GPS/INS 강결합 시스템에서 다중경로 오차에 대한 EKF와 total-state UKF 두 가지 필터의 성능을 비교 분석하였다. 도심 빌딩숲에서 많이 발생하는 다중경로 오차가 없는 경우와 있는 경우에 대하여 시뮬레이션을 수행하였고, 위성이 3개만 보이는 경우에 두 필터의 추정 성능을 비교하였다. 다중경로 오차가 없을 경우보다 있는 경우에 total-state UKF가 EKF에 비하여 더 좋은 추정 성능을 보여서 total-state UKF의 성능이 더 강인함을 확인할 수 있었다.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2004년도 한국우주과학회보 제13권2호
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• pp.296-299
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• 2004

KARI precision attitude determination system has been developed for high accurate geo-coding of KOMPSAT-2 image. Sensor data from two star trackers and a IRU are used as measurement and dynamic data. Sensor data from star tracker are composed of QUEST and unit vector filter. Filter algorithms consists of extended Kalman filter, unscented Kalman filter, and least square batch filter. The type of sensor data and filter algorithm can be chosen by user options. Estimated parameters are Euler angle from 12000 frame to optical bench frame, gyro drift rate bias, gyro scale factor, misalignment angle of star tracker coordinate frame with respect to optical bench frame, and misalignment angle of gyro coordinate frame with respect to optical bench frame. In particular, ground control point data can be applied for estimating misalignment angle of star tracker coordinate frame. Through the simulation, KPADS is able to satisfy the KOMPSAT-2 mission requirement in which geo-location accuracy of image is 80 m (CE90) without ground control point.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

• ETRI Journal
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• 제42권1호
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• pp.108-117
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• 2020

This study proposes a robust range-only beacon mapping method for registering the locations of range-only beacons automatically. The proposed method deals with the multipath propagation of signals from range-only beacons using the range-only measurement association (RoMA) and an unscented Kalman filter (UKF). The RoMA initially predicts the candidate positions of a range-only beacon. The location of the range-only beacon is then updated using the UKF. With the proposed method, the locations of range-only beacons are accurately estimated in a multipath environment. The proposed method also provides the location uncertainty of each range-only beacon. Simulation results using the model for multipath propagation and experimental results in a real indoor environment verify the performance of the proposed method.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2011년도 추계학술대회
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• pp.191-192
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• 2011

MEMS 기반 관성 센서를 이용한 항법장치를 개발하는 경우, 칼만 필터(Kalman Filter, KF) 구축 여부에 따라 그 성능이 결정된다. 특히 해상에서 이러한 MEMS 기반 관성항법 장치를 사용하는 경우에는, 육상과 달리 다양한 제약조건이 따르게 된다. KF는 선형과 비선형으로 구분되고, 비선형은 다시 확장 KF와 Unscented KF, Particle KF 등 다양한 것이 연구 개발되어 있는데, 해상에 적용하기 위해서는 이러한 다양한 필터들의 특징과 추가 요청사항 등을 사전 조사할 필요가 있다. 본 연구에서는 기존 개발된 KF를 조사하여 해상용 MEMS 기반 관성 항법장치를 개발하는 경우 필요한 필터 구성 방법을 조사하여 문제점을 살펴보고, 이 문제 해결을 위한 방안을 검토하였다.