• 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.

• 한국군사과학기술학회지
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• 제11권3호
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• pp.40-49
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• 2008

In this paper, we have described a Simulated Radar Target Generation Equipment(SRTGE) for evaluating the performance of a developed radar system. In order to change a simulated target range(or time delay), the variable optical delay line structure is used in SRTGE, In addition, SRTGE is required to generate a target return signal which is composed of variable amplitude and Doppler velocity. The interference such as noise jamming and clutter is also produced from SRTGE for evaluating ECCM(Electronic-Counter-Counter Measure) capability of radar.

• 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 ...

• The Journal of the Acoustical Society of Korea
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• 제22권1E호
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• pp.19-25
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• 2003

Ryu et al. recently proposed a multiple target angle-tracking algorithm without a data association problem. This algorithm, however, shows the degraded performance on evasive maneuvering targets, because the estimated signal subspace is d,:graded in the algorithm. In this Paper, we proposed a new algorithm, in which VFF-PASTd (Variable Forgetting Factor PASTd) algorithm is applied to Ryu's algorithm to effectively handle the evasive target tracking with better time-varying signal subspace.

• 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.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• 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.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1131-1140
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• 2019

Characteristics of fruit tree canopies are important target information for adjusting the pesticide application rate in variable rate spraying in orchards. Therefore, the target detection of the canopy characteristics is very important. In this study, a canopy volume measurement method for peach trees was presented and a variable rate spraying system based on canopy volume measurement was developed using the ultrasonic sensing, one of the most effective target detection method. Ten ultrasonic sensors and two flow control units were mounted on the orchard air-assisted sprayer. The ultrasonic sensors were used to detect the canopy diameters and the flow controls were used to modify the flow rate of the nozzles in real time. Two treatments were established: a constant application rate of $300Lha^{-1}$ was set as the control treatment for the comparison with the variable rate application at a $0.095Lm^{-3}$ canopy. The tracer deposition at different parts of peach trees and the tracer losses to the ground (between rows and within rows) were analyzed in detail under constant rate and variable rate application. The results showed that there were no significant differences between two treatments in the liquid distribution and the capability to reach the inner parts of the crop canopies.

• 품질경영학회지
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• 제22권4호
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• pp.28-39
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• 1994

This study is concerned with determination of an optimal target value in a filling process. Complete inspection procedures are widely used to improve outgoing quality of products. In many cases, however, it may be impossible or noneconomical to measure the quality characteristic, performance variable, directly. In such cases, it is a common practice to select an easily measurable variable which is highly correlated with the performance variable and perform screening products for the variable. This study proposes a model to determine the target value and the inspection rule based on the screening variable. This, study deals with the cases in which rejected products would be scrapped and sold at a reduced price in secondary markets.

• 대한교통학회지
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• 제27권6호
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• pp.157-166
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• 2009

교통망설계문제(network design problem, NDP)는 교통체계(transportation system)을 최적화시키는 설계변수(design parameter, design variable)를 구하는 문제이다. 본 연구에서는 교통망설계문제를 조금 변환시킨 목표지향 교통망설계문제(target-oriented network design problem, target-oriented NDP)를 제시하고 이를 풀기 위한 기법도 제시한다. 목표지향 교통망설계는 교통운영자(traffic operator) 또는 관리자(travel manager)가 특정 교통정책 목표(target)를 미리 설정하고 이를 달성하기 위한 최적 설계변수를 찾는 문제이다. 즉, 일반적인 교통망설계문제(general NDP)는 총통행비용이나 순편익 등 특정목적함수를 최적화시키는 설계변수를 찾는데 반해, 목표지향 교통망설계(target NDP)는 사전에 설정된 목표수준(target level)을 달성하기 위한 설계변수를 구하는 문제이다. 본 연구에서 제시된 목표지향 교통망설계모형을 교통수단분담문제에 적용하여 모형을 평가한다.