• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.6
• /
• pp.251-257
• /
• 2021

An underwater platform operating a passive sonar needs to acquire the target position to perform its mission. In an environment where sea-floor reflections exist, the position of a target can be estimated using the difference in the arrival time between the signals received through multipaths. In this paper, a method of localization for passive sonar is introduced, based on the EKF (Extended Kalman Filter) using the multipath time difference of arrival in underwater environments. TMA (Target Motion Analysis) requires accumulated measurements for long periods and has limitations on own-ship movement, allowing it to be used only in certain situations. The proposed method uses an EKF, which takes measurements of the time differences of the signal arrival in multipath environments. The method allows for target localization without restrictions on own-ship movement or the need for an observation time. To analyze the performance of the proposed method, simulation according to the distance and depth of the target was performed repeatedly, and the localization error according to the distance and water depth were analyzed. In addition, the correlation with the estimated position error was assessed by analyzing the arrival time difference according to the water depth.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1352-1355
• /
• 1997

This paper presents the algorithm for estimating the attitude of an underwater vehicle using EFK. The system model is designed by linerizing the nonlinear Euler angle differential equation and the measurements is a speed logger output. The simulation result shows that the estimation lagorithm is adequate for decreasing attitude errors that grow abruptly during the motion with acceleration and rotation. It also shows that we can adapt the algorithm for compensating initial attitude errors generated after initial leveling.

• Proceedings of the KOR-KST Conference
• /
• 1996.12a
• /
• pp.17-40
• /
• 1996

본 연구에서는 거시적 연속교통류 모형에 바탕을 둔 도시고속도로로 시뮬레이션모형의 개발이 시도되었다. 이 모형은 simple continuum model에 통행수요모형 기능을 강화시킨 것으로서 기존 연속교통류 시뮬레이션모형의 단점을 개선하였다. 제안된 시뮬레이션모형은 정산과정을 거쳐 미국 도시고속도로에서 수집한 현장자료에 의해 평가되었다. 특히 링크의 목적지별 차량대수 추정, 실시간 O-D추정의 문제가 확장칼만필터의 형태로 접근되었으며, 개발된 시뮬레이션모형을 ATMS전략에 활용하는 방안이 개발·평가되었다. 이들 전 과정을 통합한 모수적응적 모형(Parameter Adaptive Model)에 의해 교통량을 실시간으로 예측(Real time traffic prediction)하는 방법을 제안하였으며 현장자료에 의해서 평가되었다.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.611-615
• /
• 1991

A technique for estimation of the hydrodynamic parameter of an underwater vehicle is presented. An extended, augmented Kalman Filter is used to extract the hydrodynamic parameter. Computer generated data were used for the measurement information in lieu of actual run data. The feasibility of identifying values of the hydrodynamic parameter of an underwater vehicle is studied. Computer simulation are done in order to validate the performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.457-462
• /
• 1990

Lately, at an epock of full-scale satellite ranching plan of Korea, T.T.C (Tracking, Telemetery & Command) is a indispensable part. In this paper, particular attention is given to orbit determination problem of role of T.T.C. Orbit determination, which is applied to Kalman Filter and Smoothing Filter, use the observation data which is given by satellite tracking radar system, and then the simulation is accomplished. As a result, it shows effectiveness.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.43 no.7
• /
• pp.609-618
• /
• 2015

This paper discusses the attitude determination of the CNUSAIL-1 cube-satellite. The primary mission of the CNUSAIL-1 is sail deployment and operation in low Earth orbit, and the secondary mission is to look into influence of the sail deployment on satellite attitude and orbit. The attitude determination strategy is proposed depending on three mission phases, and its performance and applicability are verified through numerical simulations. This study considers the following sensors: Sun sensors and a three-axis magnetometer as attitude reference sensors, and a three-axis MEMS gyroscope as an inertial attitude sensor. Because sensors used for cube satellites have relatively low performances and worse noise characteristics, an Extended Kalman filter (EKF) is applied to attitude determination. Additionally, it has the merits to deal with the Gaussian noises and to predict the attitude even with no measurements from reference attitude sensors, especially in the eclipse of the cube satellite. The performance of the EKF is compared to a deterministic attitude determination technique, QUEST(QUaternion ESTimation).

• Journal of Advanced Navigation Technology
• /
• v.3 no.2
• /
• pp.97-107
• /
• 1999

Passive sensors such as Laser Range Finder(LRF) and Forward Looking Infrared(FLIR) camera frequently used for tracking aircraft landing produce the measurements of elevation angle contaminated by large noise due to the exhaust plume disturbance. This results in poor tracking performance if the extended Kalman filter is used for estimation of the range and elevation which are corrupted by the non-Gaussian noise such as plume disturbance. In this paper, an adaptive estimation filter and the extended Kalman filter is combined to produce a combination-type filter. In this approach the adaptive filter is used for the plume-type disturbance noise and the extended Kalman filter is utilized for the measurement of Gaussian type. The proposed combination filter is effective for the trajectory estimation of landing aircraft under the influence of unknown bias and numerical simulations illustrate the performance of the proposed filter.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.9
• /
• pp.208-214
• /
• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.5
• /
• pp.418-422
• /
• 2013

This paper has considered the location estimation problem in two dimension space by using a non-linear filter under non-Gaussian noise in underwater acoustic sensor networks(UASNs). Recently, the extended Kalman filter (EKF) is widely used in location estimation. However, the EKF has a lot of problems in the non-linear system under the non-gaussian noise environment like underwater environment. In this paper, we propose the improved Two-Dimension Particle Filter (TDPF) using the re-interpretation distribution techniques based on the maximum likelihood (ML). Through the simulation, we compared and analyzed the proposed TDPF with the EKF under the non-Gaussian underwater sensor networks. Finally, we determined that the TDPF's result shows more accurate localization than EKF's result.

• The Journal of the Acoustical Society of Korea
• /
• v.15 no.6
• /
• pp.104-109
• /
• 1996

In passive sonar system, frequency lines generated by underwater target are very important for detection, tracking and classification. In this paper, the extraction method of unstable frequency line from the time samples of the radiated noise of underwater target is studied. As unstable frequency line is time varying, an extended Kalman filter algorithm which is desirable for nonlinear system is applied to extract unstable frequency line. The proposed method shows good extraction of unstable frequency line by application of simulated signal and real target.