• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.108-113
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• 1991

In this paper, an improved method for tracking maneuvering target is proposed. The proposed tracking filter is constructed by combining the input estimation approach with the variable dimension filtering approach. In this approach, the filter also provides the estimated time instant at which target starts maneuver, when the target maneuver is detected. Using this estimated maneuvering time, the maneuver input is estimated and the tracking system changes to the maneuver model. Simulations are performed to demonstrate the efficiency of the proposed tracking filter.

• 한국항공우주학회지
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• 제30권8호
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• pp.87-93
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• 2002

일반적으로 궤도재배치는 주어진 시간동안 현재 경도에서 목표 경도로 옮기는 작업이며, 궤도재배치 기동은 표류제도 기동과 목표제도 기동으로 나누어진다. 정지궤도 위성은 지구비대칭에 의한 중력장 때문에 동서방향의 표류에 끊임없이 영향을 받는다. 따라서 기동을 계획할 때, 이러한 영향을 고려하지 않는다면 위성은 성공적으로 궤도재배치 되지 않을 수 있다. 본 연구에서는 기동시각과 delta-V를 구하기 위해서 선형화된 궤도전이 방정식을 사용하여 구하였으며, 궤도재배치를 수행할 경우 위성들간의 접근여부를 확인하기 위하여 비선형 시뮬레이션을 수행하였다.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.976-983
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• 2002

We presents a modified variable dimension filter with input estimation for maneuvering target tracking. The conventional variable dimension filter with input estimation(VDIE) consists of the input estimation(IE) technique and the variable dimension(VD) filter. In the VDIE, the IE technique is used for estimation of a maneuver onset time and its magnitude in the least square sense. The detection of the maneuver is declared according to the estimated magnitude of the maneuver. The VD filter structure is applied for the adaptation to the maneuver of the target after compensating the filter parameter with respect to the estimated maneuver when the detection of the maneuver is declared. The VDIE is known as one of the best maneuvering target tracking filter based on a single filter. However, it requires too much computational burden since the IE technique is performed at every sampling instance and thus it is computationally inefficient. We propose another variable dimension filter with input estimation named 'Modified VDIE' which combines VD filter with If technique. Modified VDIE has less computational load than the original one by separating maneuver detection and input estimation. Simulation results show that the proposed VDIE is more efficient and outperforms in terms of computational load.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.496-499
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• 1995

In this paper, a new detection scheme, the detectable maneuver set (DMS) scheme, is proposed by incorporating the trade-off property between target maneuver magnitude and detection time delay. With this new detection scheme, small maneuvers can be effectively detected without enlarging window size. Simulation results show that the proposed DMS scheme gives better tracking performance.

• 전기의세계
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• 제31권2호
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• pp.119-125
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• 1982

A new approach to the maneuvering target tracking problem is proposed. Its basic concept is to take the maneuver variable from the measurements. Tracking scheme based on the Kalman filter estimates the maneuver varieble from the residual and uses the estimates to update the Kalman filter. The estimation process is independent of target types and a model of the maneuver characteristics. All the filtering algorithms are processed in polor coordinate. Simulation results are presented and compared to that of the extended Kalman filter.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.680-688
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• 2004

This paper proposes an observer-based method for adaptive nonlinear guidance. Previously, adaptive nonlinear guidance law is proposed considering target maneuver and control loop dynamics. However, several information of this guidance law is not available, and therefore needs to be estimated for more practical application. Accordingly, considering the unavailable information as bounded time-varying uncertainties, an integrated guidance and control model is re-formulated in normal form with respect to available states including target uncertainties and control loop dynamics. Then, a nonlinear observer is designed based on the integrated guidance and control model. Finally, using the estimates for states and uncertainties, an observer-based adaptive guidance law is proposed to guarantee the desired interception performance against maneuvering target. The proposed approach can be effectively used against target maneuver and the limited performance of control loop. The stability analyses and simulations of the proposed observer and guidance law are included to demonstrate the practical application of our scheme.

• 제어로봇시스템학회논문지
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• 제20권8호
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• pp.882-889
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• 2014

This paper deals with a filterbank based on the IMM (Interacting Multiple Model) that combines data from a sensor and uses them selectively depending on a level of maneuver. Furthermore, within the maneuver interval, the existing IMM filter has disadvantages such as unnecessary target estimation errors caused by using a constant velocity model and an increase of computation load because of a fixed structure. On the other hand, the proposed IMM filterbank overcomes these disadvantages by using three model groups and designs a filterbank to cope with a wideband-maneuvering target. The performances of the IMM filterbank was evaluated through comparison with the existing IMM via computer simulations. The results show good performances for a wideband-maneuvering target.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.499-501
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• 2005

When the target maneuver occurs, the estimate of the standard Kalman filter is biased and its performance may be seriously degraded. To solve this problem, this paper proposes a new intelligent estimation algorithm for a maneuvering target. This algorithm is to estimate the unknown target maneuver by a fuzzy system using the relation between the filter residual and its variation. The detected acceleration input is regarded as an additive process noise. To optimize the employed fuzzy system, the genetic algorithm (GA) is utilized. And then, the modified filter is corrected by the new update equation method using the fuzzy system. The tracking performance of the proposed method is compared with those of an interacting multiple model (IMM).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.541-547
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• 1992

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three-dimensional adaptive tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track update illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver detector. A detailed simulation is conducted to test the validity of our tracking algorithm for encounter geometries under various conditions of maneuver.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.53.6-53
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• 2001

In this paper, we are concerned with a tracking filter algorithm which can track a maneuvering target. Among the novel tracking filter algorithms, the input estimation (IE) filter can be summarized as estimating the unknown maneuver input and compensating the state according to the estimated input, and the variable dimension filter (VDF) can be summarized as detecting the maneuver of target and changing the dimension of the target dynamics to accomodate the maneuver of target They have some goods and bads with respect to each other. The variable dimension filter with input estimation (VDIEF) is constructed by combining the two filtering algorithms. However, it requires too much computational burden while it has good performance. We propose another variable dimension with input estimation ...