• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.125-130
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• 1991

This paper presents a tracking filter using pseudomeasurements in an estimated line-of-sight Cartesian coordinate system(ELCCS) whose x-axis is on the line-of-sight to an estimated target position. A target dynamics model and a measurement equation in the ELCCS are derived first and then a tracking filter in the ELCCS named moving coordinate tracking filter(MCTF) is proposed. It is shown that this MCTF is equivalent to a Kalman filter in the inertial Cartesian coordinate system which is widely used in the target tracking system. By approximating the MCTF for a pseudomeasurement noise and an error covariance matrix in the ELCCS, decoupling of three axes can be achieved. In this case, named decoupled moving coordinate tracking filter(DMCTF), computation time can be drastically reduced by utilizing its parallel structure. Finally, the stochastic properties of the MCTF and DMCTF are presented. Especially, a sufficient condition of nondestabilizing deviation for the DMCTF is proposed. The performance of the MCTF and DMCTF are compared with a conventional Kalman tracking filter.

• 제어로봇시스템학회논문지
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• 제22권7호
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• pp.536-542
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• 2016

To enhance tracking efficiency, a target-tracking filter with a resource management algorithm is required. One of the resource management algorithms chooses or evaluates the proper sampling time using cost functions which are related to the target tracking filter. We propose a resource management algorithm for bearing only tracking environments. Since the tracking performance depends on the system observability, the bearing-only tracking is one of challenging target-tracking fields. The proposed algorithm provides the adaptive sampling time using the variation rate of the error covariance matrix from the target-tracking filter. The simulation verifies the efficiency performance of the proposed algorithm.

• 한국음향학회지
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• 제33권5호
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• pp.326-334
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• 2014

논문은 MVDR 빔 형성 기법을 위한 새로운 공분산 행렬 예측을 제안한다. 오디오-비디오 센서를 이용하여 음원의 방향 정보를 정확히 추적함으로써, 공분산 행렬은 가변 적응 망각율을 적용하여 효과적으로 예측된다. 가변 적응 망각율은 신호 대 방해 신호 비를 고려하여 결정된다. 실험 결과에서는 제안하는 방법의 성능이 방해신호/잡음 감소 및 음성 왜곡의 면에서 기존의 방법의 성능보다 더 우수하다는 것을 보여준다.

• 한국군사과학기술학회지
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• 제26권1호
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• pp.10-21
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• 2023

For various target tracking applications, it is well known that the Kalman filter is the optimal estimator(in the minimum mean-square sense) to predict and estimate the state(position and/or velocity) of linear dynamical systems driven by Gaussian stochastic noise. In the case of nonlinear systems, Extended Kalman filter(EKF) and/or Unscented Kalman filter(UKF) are widely used, which can be viewed as approximations of the(linear) Kalman filter in the sense of the conditional expectation. However, to implement EKF and UKF, the exact dynamical model information and the statistical information of noise are still required. In this paper, we propose the recurrent neural-network based Kalman filter, where its Kalman gain is obtained via the proposed GRU-LSTM based neural-network framework that does not need the precise model information as well as the noise covariance information. By the proposed neural-network based Kalman filter, the state estimation performance is enhanced in terms of the tracking error, which is verified through various linear and nonlinear tracking problems with incomplete model and statistical covariance information.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.153-156
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• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

• 제어로봇시스템학회논문지
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• 제5권6호
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• pp.764-776
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• 1999

In this paper, a tracking algorithm for a maneuvering single target in the presence of multiple data from multiple sensors is investigated. Allowing individual sensors to function by themselves, the estimates from individual sensors on the same target are fused for the purpose of improving the state estimate. The filtering method adopted in the local sensors is the variable dimensional filter with input estimatio technique, which consists of a constant velocity model and a constant acceleration model. A posteriori probability for the maneuvering hypothesis is newly derived. It is shown that the relation function of the a posteriori probability is a function of only the covariance of the fused estimates. Simulation results are provided.

• 한국멀티미디어학회논문지
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• 제21권5호
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• pp.545-557
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• 2018

The Global Positioning System (GPS) has become popular and widely used in many fields from military to civilian applications. However, GPS signals are suffered from interference due to its weak signal over wireless channel. There are many types of interference, such as jamming, blocking multipath, and spoofing, which can mislead the operation of GPS receiver. In this paper, vector-based tracking loop model with integrity check is proposed to detect and mitigate the harmful effect of interference on GPS receiver operation. The suggested methods are implemented in the tracking loop of GPS receiver. As a first method, integrity check with carrier-to-noise ratio (C/No) monitoring technique is applied to detect the presence of interference and prevent contaminated channels out of tracking channels to calculate position. As a second method, a vector-based tracking loop using Extended Kalman Filter with adaptive noise covariance according to C/No monitoring results. The proposed methods have been implemented on simulated dataset. The results demonstrates that the suggested methods significantly mitigate interference of Additive White Gaussian Noise (AWGN) and improve position calculation by 44%.

• 대한의용생체공학회:의공학회지
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• 제31권6호
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• pp.427-433
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• 2010

Although tracking methods are efficient and popular for vessel segmentation, they require a seed to initiate an instance of tracking. In this paper, a new method to detect new seeds for tracking of arterial segments from CT angiography (CTA) and to construct a vascular structure is proposed. The proposed algorithm is based on shape analysis of connected components in a volume of interest around a vessel segment which was already extracted by tracking. The eigenvalues of the covariance matrix are used as the shape features for detection. The experimental results on actual clinical data showed that the results totally revealed the arterial tree not hindered by bone or veins. In visual comparison to a method which combines registration and subtraction of both pre-contrast and post-contrast CT volumes, the proposed method produced comparable results to the reference method and were confirmed of its feasibility for clinical use of reducing the cost and burden of patients.

• 항공우주기술
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• 제11권2호
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• pp.19-25
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• 2012

정지궤도복합위성은 천리안위성에 비하여 고품질의 영상품질을 요구하며 지구센서 대신 별센서의 사용으로 인하여 고정밀의 탑재용 궤도정보생성이 요구된다. 이는 고정밀의 궤도 결정이 바탕이 되어야 한다. 천리안위성의 경우는 항공우주연구원에 설치된 추적 안테나를 이용하여 레인징을 수행하고 이를 바탕으로 궤도결정을 수행하였다. 정지궤도복합위성의 정밀한 궤도결정을 위하여 항공우주연구원에서는 축섬에 새로운 추적장비를 준비중에 있다. 본 논문에서는 대전과 축섬에 위치한 정지궤도복합위성을 가정하여 궤도결정을 수행했을 경우 궤도결정 및 예측 오차와 테이블 방식의 탑재용궤도정보 생성기의 궤도정밀도를 분석하였다. 본 논문에서는 공분산해석과 수치적인 방법을 통하여 궤도정밀도를 해석하였다. 두 해석결과를 종합하여 최종적인 궤도오차를 산출하였다.