• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.13-21
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• 2010

The Optimal results of Kalman Filtering on the Inverted Pendulum System requires an effective factor such as the noise covariance matrix Q, the measurement noise covariance matrix R and the initial error covariance matrix $P_0$. We present a special case where the optimality of the filter is not destroyed and not sensitive to scaling of these covariance matrix because these factors are unknown or are known only approximately in the practical situation. Moreover, the error covariance matrices issued by this method predict errors in the state estimate consistent with the scaled covariance matrices and not the issued state estimates. Various results using the scalar gain $\delta$ are derived to described the relations among the three covariance matrices, Kalman Gain and the error covariance matrices. This paper is described as follows: Section III a brief overview of the Inverted Pendulum system. Section IV deals with the mathematical dynamic model of the system used for the computer simulation. Section V presents a various simulation results using the scalar gain.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.40-47
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• 2013

GEO-KOMPSAT2 shall be designed to produce higher quality of image than that of COMS, and this requires the ground system to provide orbit data with high accuracy; better than 2km which is sort of high accuracy when it comes to geostationary satellite. For GEO-KOMPSAT2, KARI is planning to use ranging data for orbit determination, obtained from two ranging stations located in KARI and oversea country with long longitudinal baseline. This paper estimated achievable orbit determination accuracy using covariance analysis under assumption of using two ranging stations; SOC and available secondary tracking stations located in oversea countries. In addition to covariance analysis, in order to validate the analysis, the Monte-Carlo simulation has been performed and compared to the covariance analysis.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.147-152
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• 2005

본 논문에서는 k개의 포아송 확률변수가 서로 종속 되어 있는 다변량 포아송 분포를 따를 때, 주어진 분산-공분산 행렬 구조를 유지하는 다변량 포아송 확률난수 생성방법에 대해 다루었다. 특히, 확률난수를 생성하기 위해 선형방정식을 푸는 두 가지 수치해석 알고리즘을 제안하였으며, Park 등 (1996)의 다변량 베르누이 확률난수 생성에 활용된 알고리즘과의 연관성을 다루었다.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.19-25
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• 2012

GEO-KOMPSAT2 shall provide higher quality of image than the COMS and uses star tracker instead of earth sensor, which requires precise onboard orbit information. This requires precise on-ground orbit determination. For COMS, orbit determination is performed using the ranging data obtained from tracking system located in DAEJON. For accurate orbit determination of GEO-KOMPSAT2, KARI is building a secondary tracking station in CHUUK Islands. In this paper, the achievable accuracy of table based onboard orbit parameter generator which interpolates orbit data obtained from on-ground orbit determination using tracking data collected from two ground stations. Two types of approaches have been applied; covariance analysis and numerical analysis. By combining two analysis results, total orbit error has been estimated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.11
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• pp.42-46
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• 2006

As an application of SDINS/GPS integration for its synergistic results, the SDINS alignments utilizing GPS carrier phase rate measurements. A measurement model of GPS carrier phase rate is derived in order to be used with SDINS alignment process. For in-flight alignment, the performance of the suggested SDINS/GPS integration method is analyzed using the covariance analysis and its results are confirmed by those of van test. Consequently, it is shown that all states of the SDINS integrated system by utilizing GPS carrier phase rate measurements can be estimated more efficiently than a general SDINS/GPS during in-flight alignment.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.34-39
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• 1996

Target state estimation is a fundamental problem of the sonar signal processing. In this paper, the covariance analysis techniques are applied to enhance the performance of the target state estimation of a monopulse sonar system. MOST, the artificial target signal generator based on the highlight model is used to generate signals in various target states. The performance of the developed method has been evaluated by applying it to the various S/N. The enhanced performance of the covariance analysis method presented in this paper is discussed.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2034-2036
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• 2003

본 논문에서는 21차 상태변수를 갖는 칼만필터 형태의 비행시험용 데이터 융합필터 알고리듬의 성능을 분석하였다. 실측 데이터에 대한 분석을 통하여 상태변수 선택의 적절성을 검증하였다. 공분산 해석기법을 통하여 기 개발된 데이터 융합 알고리듬의 추정값의 오차범위를 구하였다. 수치적인 성능값을 구하고자 간단한 시뮬레이터를 설계하였다. 20회 몬테칼로 시뮬레이션과 공분산 해석결과에 기반하여 필터 계수를 튜닝하였고 이를 기설계된 분산형 칼만필터에 적용하였다. 실시간 소프트웨어 모듈의 수행결과를 동일한 실측데이터를 적용한 후처리 실험결과와 비교하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.166-175
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• 2002

In this paper. we predict tracking performance of the probabilistic strongest neighbor filter (PSNF). The PSNF is known to be consistent and superior to the probabilistic data association filter (PDAF) in both performance and computation. The PSNF takes into account the probability that the measurement with the strongest intensity in the neighborhood of the predicted target measurement location is not target-originated. The tracking performance of the PSNF is quantified in terms of its estimation error covariance matrix. The estimation error covariance matrix is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.25-34
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• 2005

We had research to conduct interrelationships between sensors using postprocessing analysis with the Fuzzy-Kalman Filtering Auto-Correlation about Real Time Simulator data of the NaroSC LCS in case of a fully blind situation scenario. The conducted interrelations are same harmony with relations in scenario. We had analyzed signals of sensors reverse-using a optimization character of Fuzzy-Kalman Filter. As our research conclusion, We had recognized possibilities of signal processing about the KSLV-1, on-board payloads, general equipments of ground support which apply to multi sensor systems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.734-745
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• 2017

The navigation system of lunar lander are composed of various navigation sensors which have a complementary characteristics such as inertial measurement unit, star tracker, altimeter, velocimeter, and camera for terrain relative navigation to achieve the precision and autonomous navigation capability. The required performance of sensors has to be determined according to the landing scenario and mission requirement. In this paper, the specifications of navigation sensors are investigated through covariance analysis. The reference error model with 77 state vector and measurement model are derived for covariance analysis. The mission requirement is categorized as precision exploration with 90m($3{\sigma}$ ) landing accuracy and area exploration with 6km($3{\sigma}$ ), and the landing scenario is divided into PDI(Powered descent initiation) and DOI(Deorbit initiation) scenario according to the beginning of autonomous navigation. The required specifications of the navigation sensors are derived by analyzing the performance according to the sensor combination and landing scenario.