• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.955-958
• /
• 1998

This paper describes the algorithm which extracts moving vehicles from sequential images and tracks those vehicles using Kalman filter. This work is composed of a motion segmentation stage which extracts moving objects from sequential images and gets features of objects, and a motion estimation stage which estimates the position and the motion of moving objects using Kalman filter. In the motion estimation stage, applying to affine motion model we divided the Kalman filter into position filter and velocity filter to employ linear Kalman filter. Multi-target tracking requires a data association component that decides which measurement to use for updating the state of which object. We use pattern recognition method to solve this problem.

• Transactions on Electrical and Electronic Materials
• /
• v.14 no.4
• /
• pp.187-192
• /
• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.

• Journal of Advanced Navigation Technology
• /
• v.26 no.5
• /
• pp.319-324
• /
• 2022

If radio interference occurs or there is no navigation device, radio navigation of high-speed moving object becomes impossible. Nevertheless, if there are multiple ground stations and precise range measurement between the high-speed moving object and the ground station can be secured, it is possible to estimate the position of moving object. This paper proposes a position estimation method using high-precision TDOA measurement generated using TLM signal. In the proposed method, a common error of moving object is removed using the TDOA measurements. The measurements is generated based on TLM signal including SOQPSK PN symbol capable of precise timing synchronization. Therefore, since precise timing synchronization of the system has been performed, the timing error between ground stations has a very small value. This improved the position estimation performance by increasing the accuracy of the measured values. The proposed method is verified through software-based simulation, and the performance of estimated position satisfies the target performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.6 no.3
• /
• pp.148-151
• /
• 2013

A new direction of arrival estimation method using effects of model errors and sensitivity analysis is proposed. Since a desired signal is obtained after interference rejection through correction effects of model error, the effect of channel interference on the estimation is significantly reduced. Through simulation, we show that the proposed method offers significantly improved estimation resolution and accuracy relative to existing method.

• Journal of Advanced Marine Engineering and Technology
• /
• v.39 no.2
• /
• pp.187-194
• /
• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• International Journal of Ocean System Engineering
• /
• v.1 no.1
• /
• pp.52-59
• /
• 2011

A prototype radar display unit was implemented using inexpensive off-the-shelf components, including a nonlinear estimation algorithm for the target tracking in a clutter environment. Two custom designed boards; an analog signal processing board and a DSP board, can be plugged into an expansion slot of a personal computer (PC) to form a maritime radar display unit. Our system provided all the functionality specified in the International Maritime Organization (IMO) resolution A422(XI). The analog signal processing board was used for A/D conversion as well as rain and sea clutter suppression. The main functions of the DSP board were scan conversion and video overlay operations. A host PC was used to run the tracking algorithm of targets in clutter, using the discrete-time Bayes optimal (nonlinear, and non-Gaussian) estimation method, and the graphic user interface (GUI) software for Automatic Radar Plotting Aid (ARPA). The proposed tracking method recursively found the entire probability density function of the target position and velocity by converting into linear convolution operations.

• Journal of Astronomy and Space Sciences
• /
• v.36 no.4
• /
• pp.293-306
• /
• 2019

In this study, the observational arc-length effect on orbit determination (OD) for the Korea Pathfinder Lunar Orbiter (KPLO) in the Earth-Moon Transfer phase was investigated. For the OD, we employed a sequential estimation using the extended Kalman filter and a fixed-point smoother. The mission periods, comprised between the perigee maneuvers (PM) and the lunar orbit insertion (LOI) maneuver in a 3.5 phasing loop of the KPLO, was the primary target. The total period was divided into three phases: launch-PM1, PM1-PM3, and PM3-LOI. The Doppler and range data obtained from three tracking stations [included in the deep space network (DSN) and Korea Deep Space Antenna (KDSA)] were utilized for the OD. Six arc-length cases (24 hrs, 48 hrs, 60 hrs, 3 days, 4 days, and 5 days) were considered for the arc-length effect investigation. In order to evaluate the OD accuracy, we analyzed the position uncertainties, the precision of orbit overlaps, and the position differences between true and estimated trajectories. The maximum performance of 3-day OD approach was observed in the case of stable flight dynamics operations and robust navigation capability. This study provides a guideline for the flight dynamics operations of the KPLO in the trans-lunar phase.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.3
• /
• pp.315-327
• /
• 2017

In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).

• Journal of the Korean Society for Precision Engineering
• /
• v.29 no.9
• /
• pp.986-994
• /
• 2012

This paper is concerned with the application of the vision control algorithm with weighting matrix in robot point placement task. The proposed vision control algorithm involves four models, which are the robot kinematic model, vision system model, the parameter estimation scheme and robot joint angle estimation scheme. This proposed algorithm is to make the robot move actively, even if relative position between camera and robot, and camera's focal length are unknown. The parameter estimation scheme and joint angle estimation scheme in this proposed algorithm have form of nonlinear equation. In particular, the joint angle estimation model includes several restrictive conditions. For this study, the weighting matrix which gave various weighting near the target was applied to the parameter estimation scheme. Then, this study is to investigate how this change of the weighting matrix will affect the presented vision control algorithm. Finally, the effect of the weighting matrix of robot vision control algorithm is demonstrated experimentally by performing the robot point placement.

• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.4
• /
• pp.305-310
• /
• 2002

The measured rate of the tracking sensor becomes biased under some operational situation. For a highly maneuverable aircraft in 3D space, the target dynamics changes from time to time, and the Kalman filter using position measurement only can not be used effectively to reject the rate measurement bias error. To cope with this problem, we present a new algorithm which incorporate FIR-type filter and FIR-type fixed-lag smoother, and demonstrate that it has the optimal performance in terms of both estimation accuracy and response time through an application example to the anti-aircraft gun fire control system(AAGFCS).