• Journal of IKEEE
• /
• v.11 no.4
• /
• pp.137-144
• /
• 2007

Fire Control System(FCS) errors can be classified as hardware errors and software errors, and one of the software errors is from target tracking filter which estimates target's location, velocity, acceleration, and so on. It affects function of ballistic calculation equipment significantly. For gun to form predicted hitting point accurately and enhance hitting rate, we need status information of target's future location. Target tracking filter algorithms consist of Single Singer Model, Fixed Gain filter algorithm, IMM, PBIMM and so on. This paper will design IMM tracking filer, which is going to be! applied to domestic warship. Target tracking filter using CV model, Song model and CRT model for IMM tracking filter is made, and tracking ability is analyzed through Monte-Carlo simulation.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.4
• /
• pp.474-481
• /
• 2017

This paper presents a multiple target tracking system using Normalized Rayleigh likelihood of amplitude information of target. Although many studies of Radar systems using amplitude information have been studied, they are focused on single target tracking. This paper proposes the multiple target tracking using amplitude information as well as kinematic information from Radar sensor. The amplitude information are applied in generating the association probability of joint probabilistic data association(JPDA) algorithm through the normalized Rayleigh likelihood. It is verified that the proposed system can enhance the track maintenance and tracking accuracy, especially, in the target crossing case.

• 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 Marine Engineering and Technology
• /
• v.29 no.5
• /
• pp.560-570
• /
• 2005

In this paper, we discuss the tracking system for a wheelchair which can follow the path of a human target such as a nurse in hospital. The problem of human tracking is that it requires recognition of feature as well as the tracking of human positions. For this purpose the use of a high cost visual sensor such as laser finder or streo camera makes the tracking a high cost additional expense. This paper proposes the tracking system uses a low cost infrared range-finder and CCD camera, The Infrared range-finder and CCD camera can create a target candidate through each target recognition algorithm. and this information is fused in order to reduce the uncertainties of a target decision and correct the positional error of the human. The effectiveness of the proposed system is verified through experiments.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.8 no.3 s.22
• /
• pp.24-32
• /
• 2005

This paper describes the tracking filter performance for Naval Gun Ballistic Computation Unit(BCU). BCU needs tracing filter for gun firing. Using data of tracking sensor, BCU calculates the future position of Target and Gun order in the time of flight. In this paper, tracing filter is designed with interacting multiple model(IMM). The tracking algorithm based on the IMM requirers a considerable number of sub-model for the various maneuvering target in order to have a good performance. But, in the case of ship target, the maneuvering is restricted compared with the air target. Considering the maneuvering properties and adjusting the mode transition probabilities and the process noise of sub-model, We designed the IMM3 algorithm for Naval tracking filter with three sub-model.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.6
• /
• pp.549-558
• /
• 2020

In this paper, the method is discussed such that the robustness of automatic initiated narrowband target tracking is improved in passive sonar. In the case of automatic tracking initiation as target in passive sonar, due to a number of clutter, the clutter is initiated as target and tracked which prohibits the operation capability. The associated probability and information entropy of measurements, extracted from detection data, is calculated to keep going on automatic target initiation and tracking of true target, but reduce the automatic initiation and tracking of clutter. If the association probability and information entropy of the extracted measurements is satisfied for the predefined conditions, the procedure of automatic initiation begins. Using sea-trial data, simulations are executed and the results from the proposed method indicate that it keeps the automatic target initiation and tracking of true target and suppresses the automatic target initiation and tracking of clutters in contrary to the conventional method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.5
• /
• pp.450-456
• /
• 2013

This paper suggests the target tracking method improved for the collaboration of the quad rotor type UAV (Unmanned Aerial Vehicle) and omnidirectional Unmanned Ground Vehicle. If UAV shakes or UGV moves rapidly, the existing method generates a phenomenon that the tracking object loses the tracking target. To solve the problems, we propose an algorithm that can track continually when they lose the target. The proposed algorithm stores the vector of the landmark. And if the target was lost, the control signal was inputted so that the landmark could move continuously to the direction running out. Prior to the experiment, Proportional and integral control were used in 4 motors in order to calibrate the Heading value of the omnidirectional mobile robot. The landmark of UGV was recognized as the camera adhered to UAV and the target was traced through the proportional-integral-derivative control. Finally, the performance of the target tracking controller and proposed algorithm was evaluated through the experiment.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.17 no.5
• /
• pp.703-710
• /
• 2014

An Image-Based Target Tracker maintains LOS(Line Of Sight) to a target by controlling azimuth and elevation gimbals of an ISS(Inertially Stabilized System). Its controller produces the gimbals commands of the ISS using tracking errors provided by an image tracker. The control performance of the target tracker with PI controller generally used for tracking controller is limited because of bandwidth limitation by time delay yielded by image capture and processing of the image tracker. In this paper, tracking controller using target states estimator is proposed which can enhance the tracking performance under the highly dynamic maneuvering conditions of the ISS and the target. Simulation results show that the proposed method can improve the tracking performance than that with only PI controller.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.3
• /
• pp.1377-1389
• /
• 2016

This paper presents a target model update scheme for the mean-shift tracking with background weighted histogram. In the scheme, the target candidate histogram is corrected by considering the back-projection weight of each pixel in the kernel after the best target candidate in the current frame image is chosen. In each frame, the target model is updated by the weighted average of the current target model and the corrected target candidate. We compared our target model update scheme with the previous ones by applying several test sequences. The experimental results showed that the object tracking accuracy was greatly improved by using the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.7
• /
• pp.536-542
• /
• 2016

To enhance tracking efficiency, a target-tracking filter with a resource management algorithm is required. One of the resource management algorithms chooses or evaluates the proper sampling time using cost functions which are related to the target tracking filter. We propose a resource management algorithm for bearing only tracking environments. Since the tracking performance depends on the system observability, the bearing-only tracking is one of challenging target-tracking fields. The proposed algorithm provides the adaptive sampling time using the variation rate of the error covariance matrix from the target-tracking filter. The simulation verifies the efficiency performance of the proposed algorithm.