• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.1
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• pp.96-106
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• 2002

Many modern guided weapon systems employ sophisticated target sensors as well as powerful computing systems. Due to such advanced features, they are required to achieve better guidance accuracy, and at the same time other guidance objectives for better weapon effectiveness and survivability. In this paper, we overview some of the technical considerations in such advanced guidance algorithm development, and briefly look at some related research works. More specifically, we discuss impact angle control, time-varying nature of the guidance system, time-to-go estimation, guidance loop stability, effect of autopilot lag and physical limitations in control variables, parasitic paths in guidance loops, etc. We also briefly look at some advanced concepts such as integrated guidance and control loop design, target adaptive guidance, guidance law development based on dual control concept, and terminal evasive maneuver.

• Journal of Ocean Engineering and Technology
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• v.35 no.3
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• pp.238-246
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• 2021

The survivability of a naval ship is the ability of the ship and its onboard systems to remain functional and continue a designated mission in man-made hostile environments. A passive decoy system is primarily used as a weapon system for improving the survivability of a naval ship. In this study, an engagement scenario-based simulation program was developed for decoy effectiveness assessments against an anti-ship missile (ASM), which tracks a target with sea-skimming and active radar homing. The program can explain the characteristics of a target ship, such as the radar cross section and evasive maneuvers, as well as the operational performance of the onboard decoy system, the guidance method of the ASM, and the engagement environment's wind speed and direction. This paper describes the theory and formulations, configuration, and user interface of the developed program. Numerical examples of a decoy effect assessment of a virtual naval ship against an ASM are presented.

• Journal of Advanced Navigation Technology
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• v.4 no.2
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• pp.162-170
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• 2000

Maneuvering targets are difficult for the Kalman filter to track since the target model of tracking filter might not fit the real target trajectory and the statistical characteristics of the target maneuver are unknown in advance. In order to track such a wildly maneuvering target, several schemes had been proposed and improved the tracking performance in some extent. In this paper a Kalman filter-based scheme is proposed for maneuvering target tracking. The proposed scheme estimates the target acceleration input vector directly from the feature of maneuvering target trajectories and updates the simple Kalman tracker by use of the acceleration estimates. Simulation results for various target profiles are analyzed for a comparison of the performances of our proposed scheme with that of conventional trackers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.7
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• pp.600-609
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• 2017

We designed a target management integration system that enables us to select the final target manually or automatically from seeker's sensor image. The integrated system was developed separately for the air vehicle system and the ground system. The air vehicle system simulates the motion dynamics and the sensor image of the air vehicle, and the ground system is composed of the target template image module and the ground control center module. The flight maneuver of the air vehicle is based on pseudo 6-degree of freedom motion equation and the proportional navigation guidance. The sensor image module was developed using the known infrared(IR) image rendering method, and was verified by comparing the rendered image to that of a commercial software. The ground control center module includes an user interface that can display as much information to meet user needs. Finally, we verified the integrated system with simulated impact target mission of the air vehicle, by confirming the final target change and the shot down result of the user's intervention.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.202-210
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• 2017

For the target tracking in cluttered environment using a bistatic sonar whose transmitter and receiver are separately positioned, it is necessary to use data association algorithm via applying a proper measurement modelling to the bistatic sonar. The measurements obtained from the interval of ownship's maneuver have an increased error due to uncertainty of the position of transmitter and receiver. Using the measurements from this interval results in poor target tracking performance. In this paper, an improved tracking performance for the proposed data association based multiple model algorithm is validated by a monte carlo simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.966-980
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• 2011

Radar receiving echo signal provides target information - range, velocity and position by signal magnitude and Doppler shift, which are determined by target reflection characteristics and target maneuver. Target angle error is extracted from the magnitude ratio of difference channel to sum channel. In this paper, we introduce a radar Return Signal Simulation Equipment(RSSE) which is implemented for the purpose of performance analysis and evaluation of phased array multi-function radar(MFR). It generates multi-target environment with jamming signals using MC-DDS (Multi-Channel Direct Digital Synthesis), and has scalability by using the efficient hardware configuration. The performance of the developed RSSE has been evaluated under various test environments. Especially, we proved that required target detection performance is achieved by RSP(Radar Signal Processor) interfaced RSSE configuration.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.131-136
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• 2003

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the states of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.136-142
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• 2007

This paper proposes a new approach on nonlinear maneuvering target tracking. In this paper, proposed algorithm is the Kalman filter based on the adaptive interactive multiple model using the concept of predicted impact point and utilize modified Kalman filter regarding the error between measurement position and predicted impact point. The unknown target acceleration is regarded as an additional process noise to the target model, and each sub-model is characterized in accordance with the valiance of the overall process noise which is obtained on the basis of each acceleration interval. To compensate the decreasing performance of Kalman filter in nonlinear maneuver, we construct optional algorithm to utilize proposed method or Kalman filter selectively. To effectively estimate the acceleration during the target maneuvering, the rapid increase of the noise scale is recognized as the acceleration to be used in maneuvering target's movement equation. And a few examples are presented to show suggested algorithm's executional potential.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.297-302
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• 2017

The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel's position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity ${\alpha}-{\beta}$ filter, the ${\alpha}-{\beta}-{\gamma}$ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The ${\alpha}-{\beta}-{\gamma}$ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter's performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, ${\alpha}-{\beta}-{\gamma}-{\eta}$ algorithm as compared to the constant acceleration model, ${\alpha}-{\beta}-{\gamma}$ in terms of error reduction and stability of the filter during target maneuver.

• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.387-395
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• 2019

TMA (Target Motion Analysis) in passive sonar is generally conducted with the bearing only or the bearing frequency. In order to conduct TMA fast and accurately, it is essential to estimate a initial target maneuver precisely. The accuracy of TMA can be improved by using SNR (Signal to Noise Ratio) information and acoustic propagation model additionally. This method assumes that the radiated noise level of the target is known, but the accuracy of TMA can be degraded due to a mismatch between the assumed radiated noise level and the actual radiated noise level. In this paper, TMA with the acoustic propagation model, bearing measurements, and SNR information is conducted in the ocean environment of South Korea (East Sea/ Yellow Sea/ South Sea). And the performance analysis of TMA for the mismatch in the radiated noise is presented.