• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.3
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• pp.461-469
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• 2010

In this paper, we have proposed an improved fusion method of detection features which can enhance the detection probability under the given false alarm rate in the prescreening stage of SAR ATR(Synthetic Aperture Radar Automatic Target Recognition) system. Since the detection features have the positive correlation, the detection performance can be improved if the joint probability distribution of detection features is considered in the fusion process. The detection region is designed as a simple piecewise linear function which can be represented by few parameters. The parameters for the detection region can be derived by training the sample SAR images to maximize the detection probability with the given false alarm rate. Simulation result shows that the detection performance of the proposed method is improved for all combinations of detection features.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.63-68
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• 2017

In this paper, we propose a bounding box prediction algorithm using multiple probability maps to improve object detection result of object detector. Although the performance of object detectors has been significantly improved, it is still not perfect due to technical problems and lack of learning data. Therefore, we use the result correction method to obtain more accurate object detection results. In the proposed algorithm, the preprocessed bounding box created as a result of object detection by the object detector is clustered in various form, and a conditional probability is given to each cluster to make multiple probability map. Finally, multiple probability map create new bounding box of object using morphological elements. Experiment results show that the newly predicted bounding box reduces the error in ground truth more than 45% on average compared to the previous bounding box.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.77-85
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• 2012

Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center's managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system's detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system's overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability's frequency in the real accident.

• Journal of Ocean Engineering and Technology
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• v.8 no.1
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• pp.62-70
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• 1994

In order to estimate the detection range of a active SONAR system, the SONAR equation is commonly used. In this paper, an algorithm to calculate detection range in active SONAR system as function of SONAR depth and target depth is presented. For given SONAR parameters and environment, the transmission loss and background level are found, signal excess is computed. Using log-normal distribution, signal excess is converted to detection probability at each range. Then, the detection range is obtained by integrating the detection probability as function of range for each depth. The proposed algorithm have been applied to the case of omni-directional source with center frequency 30Hz for summer and winter sound profiles. It is found that the optimal search depth is the source depth since the detection range increase at source depth where the signal excess is maximized.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.140-146
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• 2024

Active electronically scanning antennas are faster and more flexible in beam-scheduling than mechanical antennas. Thus, they require an advanced resource management or detection methods to operate efficiently. In a surveillance radar performing periodic detection, alert-confirm detection is an excellent method to improve the cumulative detection probability by reducing the period while maintaining the detection probability. This paper proposes a design method for alert-confirm detection based on the parameters of the conventional design. We developed a simulator based on simulink@matworks and verified the result through Monte Carlo simulation.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.285-292
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• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.70-76
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• 2012

We compare the detection probabilities of the time-reversal(TR) detection system and the conventional radar system. The target is assumed to be hidden inside a random medium such as a forest. We propose a TR detection system based on the SAR(Synthetic Aperture Radar) algorithm. Unlike the conventional SAR images, the proposed TR-SAR system has an interesting property. Specifically, the target-related signal components due to the time-reversal refocusing characteristics, as well as some of clutter-related signal components are concentrated at the time-reversal reference point. The remaining clutter-related signal components are scattered around that reference point. In this paper, we model the random media as a collection of point scatterers to avoid unnecessary complexities. We calculate the detection probability of the TR radar system based on the proposed simple random media model.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.633-641
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• 2016

Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.411-419
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• 2012

This paper proposes a new FDI(Fault Detection and Isolation) method, which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with one faulty sensor or two faulty sensors. In the system with two faulty sensors, the fault detection and isolation probability may be decreased when two faults are occurred between the sensors related to the large fault direction angle. Nonetheless, the previously suggested FDI methods to treat the two-faults problem do not consider the effect of the large fault direction angle. In order to solve this problem, this paper analyzes the effect of the large fault direction angle and proposes how to increase the fault detection and isolation probability. For the increase the detection probability, this paper additionally considers the fault type that is not detected because of the cancellation of the fault biases by the large fault direction angle. Also for the increase the isolation probability, this paper suggests the additional isolation procedure in case of two-faults. EPSA helps that the user can know the exact fault situation. The proposed FDI method is verified through Monte Carlo simulation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.147-150
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• 1996

A homing torpedo's performance can be expressed a function of many variables, i.e. technical and tactical variables. When designing a homing torpedo, these variables have to be decided upon. The system effectiveness of a homing torpedo can be determined by analyzing of these variables. This paper describes a procedure of simulation metamodelling using a Factor Analysis methodology. A simulation model was used in order to obtain the data base for analyzing detection probability of torpedo. By analyzing the main and interaction effects these variables on the analysis of detection probability, we will show the importance of certain variables, of a homing torpedo.