• 응용통계연구
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• 제18권3호
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• pp.655-660
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• 2005

두 그룹 판별분석에서 자주 사용되는 Rao의 추가정보경정법의 적용에서 변수들의 모든 조합중에 일부분만을 고려하여 변수를 선택하는 방법을 제시하고, 예를 들어 제시된 방법의 효용성을 살펴본다.

• 한국전자파학회논문지
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• 제29권10호
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• pp.791-798
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• 2018

CFAR(Constant False Alarm Rate)는 레이다 시스템에서 표적 탐지에 주요 사용된다. 그 중에서 OS(Ordered Statistic) CFAR는 비균일 잡음환경에서 사용된다. 그러나 OS CFAR는 참조 셀을 오름차순으로 정렬하여 임계값을 계산하므로 많은 연산량이 필요하다. 이로 인하여 실시간 적용에 어려움이 있다. 본 논문에서는 OS CFAR의 연산량을 줄이는 방안을 서술한다. 단순 표적 유무만 판단하기 위하여 참조 셀들을 오름차순 정렬하는 대신 참조 셀과 크기 비교하는 방식으로 수행하였다. 그리고 3개의 테스트 셀을 묶어 구역을 나누고, 구역 내에서 공통 참조 셀을 구하였다. 공통 참조 셀과 테스트 셀과의 크기 비교를 우선 수행함으로써 연산시간을 단축한다.

• Journal of Positioning, Navigation, and Timing
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• 제6권4호
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• pp.167-179
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• 2017

In this paper, a simplified Cubature Kalman Filter (SCKF) is proposed to reduce the computation load of CKF, which is then used as a filter for transfer alignment of shipboard INS. CKF is an approximate Bayesian filter that can be applied to non-linear systems. When an initial estimation error is large, convergence characteristic of the CKF is more stable than that of the Extended Kalman Filter (EKF), and the reliability of the filter operation is more ensured than that of the Unscented Kalman Filter (UKF). However, when a system degree is large, the computation amount of CKF is also increased significantly, becoming a burden on real-time implementation in embedded systems. A simplified CKF is proposed to address this problem. This filter is applied to shipboard inertial navigation system (INS) transfer alignment. In the filter design for transfer alignment, measurement type and measurement update rate should be determined first, and if an application target is a ship, lever-arm problem, flexure of the hull, and asynchronous time problem between Master Inertial Navigation System (MINS) and Slave Inertial Navigation System (SINS) should be taken into consideration. In this paper, a transfer alignment filter based on SCKF is designed by considering these problems, and its performance is validated based on simulations.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.87-94
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• 2013

UKF (Unscented Kalman Filter) has been used in the nonlinear systems without initial accurate state estimates instead of EKF (Extended Kalman Filter) of the last decade because the UKF has robustness to the large initial estimation error. In the multirate integrated system such as INS (Inertial Navigation System)/GPS (Global Positioning System) integrated navigation system, however, it is difficult to implement the UKF based navigation algorithm in the mid-grade micro-processor due to the large computational burden. To overcome this problem, this paper proposes a MUKF (Modified UKF) that has a reduced computation burden using the basic idea that the change of the provability distribution for the state variables between measurement updates is small in the multi-rate INS/GPS integrated navigation filter. The performance of the proposed MUKF is verified by numerical simulations.

• 한국군사과학기술학회지
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• 제14권5호
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• pp.904-912
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• 2011

In this paper, we have proposed a M&S tool for analyzing detection coverage and target localization in bistatic radar system. The detection coverage determined by radar parameters is meaningful when it satisfies the clear line-of-sight condition. We improved the method to find the minimum altitudes of transmitter and receiver for meeting the condition by considering three-dimensional coverage. Its computational burden is not problematic because the calculation is for maximizing the performance of the radar and does not demand a real-time operation. In addition, target localization on three-dimensional earth model based on the information of the height, longitude, and latitude is proposed instead of the previous unpractical calculation on two-dimensional bistatic plane. Its precalculated result can reduce its computation burden and it is suitable for real-time estimation of target location.

• International Journal of Aeronautical and Space Sciences
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• 제15권2호
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• pp.173-182
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• 2014

The structured singular value (${\mu}$) analysis based method has many advantages for the robust stability analysis of missiles with uncertain parameters. Nevertheless, the present linear fractional transformation (LFT) modeling process, which is the basis of ${\mu}$ analysis, is complex, and not suitable for automatic implementation; on the other hand, ${\mu}$ analysis requires a large amount of computation, which is a burden for large-scale application. A constructive procedure, which is computationally more efficient, and which may lead to a lower order realization than existing algorithms, is proposed for LFT modeling. To reduce the calculation burden, an analysis method is developed, based on skew ${\mu}$. On this basis, calculation of the supremum of ${\mu}$ over a fixed frequency range converts into a single skew ${\mu}$ value calculation. Two algorithms are given, to calculate the upper and lower bounds of skew ${\mu}$, respectively. The validity of the proposed method is verified through robust stability analysis of a missile with real uncertain parameters.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.140-145
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• 2013

This paper proposes an efficient integration method for GPS (Global Positioning System) and INS (Inertial Navigation System). To obtain accuracy and computational conveniency at the same time with low cost global positioning system receivers and micro mechanical inertial sensors, a new mechanization method and a new filter architecture are proposed. The proposed mechanization method simplifies velocity and attitude computation by eliminating the need to compute complex transport rate related to the locally-level frame which continuously changes due to unpredictable vehicle motions. The proposed filter architecture adopts two heterogeneous filters, i.e. position-domain Hatch filter and velocity-aided Kalman filter. Due to distict characteristics of the two filters and the distribution of computation into the two hetegrogeneous filters, it eliminates the cascaded filter problem of the conventional loosly-coupled integration method and mitigates the computational burden of the conventional tightly-coupled integration method. An experiment result with field-collected measurements verifies the feasibility of the proposed method.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 추계학술대회 논문집
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• pp.163-167
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• 2009

Although the domestic electric power consumption of lighting have shared 20${\sim}$30 % of the national electric power consumption, the spread of lighting control system which can reduce the electric power consumption have been insignificant. The government have set the demonstration project and given the incentive to promote the spread of lighting control system since 2008. The M&V (Measurement and Verification) methodology for lighting control system have not been set yet in our country, but the direct measurement was suggested in US. The direct measurement methodology can increase the accuracy of measurement, but it cost much money to burden a customer. This study have suggested a new M&V methodology which cost low and is simple relatively. I had measured the amount of electric consumption through both the direct measurement and the new M&V program computation, and have analyzed the deviation. The amount of electric consumption measured by the new M&V program computation have agreed with one by the direct measurement within the error range of the instrumentation in case of lab scale test, and the 4${\sim}$8 % deviation have existed in case of field evaluation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2532-2537
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• 2005

FIR(Finite Impulse Response) filter is well known to be ideal for the finite time state-space model, but it requires much computation due to its inherent non-recursive structure especially when the measurement interval grows to a large extent. And often a fixed-lag smoother based on the finite time interval is needed to monitor the soundness of the system model and the measurement model, but the computation burden of FIR-type smoother imposes much restriction of its usage for real-time application. Conventional recursive forms of FIR estimator[1]-[4] could not be used for real time applications, since they are numerically unstable in their recursive equations. To cope with this problem, we suggest a stable recursive form FIR estimator(SRFIR) and its usefulness is demonstrated for designing the real-time fixed-lag smoother on the finite time window through an example of detection of rate bias in the anti-aircraft gun fire control system.

• ETRI Journal
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• 제42권5호
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• pp.658-668
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• 2020

In edge computing, most procedures, including data collection, data processing, and service provision, are handled at edge nodes and not in the central cloud. This decreases the processing burden on the central cloud, enabling fast responses to end-device service requests in addition to reducing bandwidth consumption. However, edge nodes have restricted computing, storage, and energy resources to support computation-intensive tasks such as processing deep neural network (DNN) inference. In this study, we analyze the effect of models with single and multiple local exits on DNN inference in an edge-computing environment. Our test results show that a single-exit model performs better with respect to the number of local exited samples, inference accuracy, and inference latency than a multi-exit model at all exit points. These results signify that higher accuracy can be achieved with less computation when a single-exit model is adopted. In edge computing infrastructure, it is therefore more efficient to adopt a DNN model with only one or a few exit points to provide a fast and reliable inference service.