• Journal of IKEEE
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• v.24 no.4
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• pp.1034-1038
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• 2020

In order to effectively process target recognition using radar, accurate signal information for the target is required. However, such a target signal is usually mixed with noise, and this part of the study is continuously carried out. Especially, image processing, target signal processing and target recognition for the target are examples. Since the field of target recognition is important from a military point of view, this paper carried out research on target recognition of aircraft using a tree-structured fuzzy neural networks. Fuzzy neural networks are learned by using reflected signal data for an aircraft to optimize the model, and then test data for the target are used for the optimized model to perform an experiment on target recognition. The effectiveness of the proposed method is verified by the simulation results.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.257-260
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• 2000

In modern battlefield situation, radar and infrared sensors may be located on aircraft having limited computational resources available for real-time computer processing. Hence sensor images are transmitted typically to central stations for processing and automatic target recognition/detection. Owing to the limited bandwidth channels that are typically available between the aircraft and processing stations, images are compressed prior to transmission to facilitate rapid transfer. In this paper we examine the problem of compressing sensor data for transmission, given that target recognition is the end goal. Performance result shows that the front-end target recognition system achieves a relatively high level of performance as well as a high compression ratio.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.795-808
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• 2020

Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.7
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• pp.717-722
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• 2007

Inverse synthetic aperture radar(ISAR) images represent two-dimensional(2-D) spatial distribution of electromagnetic scattering phenomenology against a target. Hence, they are usually used in the areas of automatic target recognition (ATR) or non-cooperative target recognition(NCTR), identifying a target using radar in a long distance. This paper makes use of Korea Miniature Synthetic Aperture Radar(KOMSAR) to generate ISAR images of a real and maneuvering aircraft. The data obtained from KOMSAR are processed to eliminate phase errors due to motion of a target, with the use of entropy-based ISAR autofocusing technique. Results show that we can successfully obtain ISAR images of a real aircraft, and the success of experiments implies that a significant step toward ATR using radar has been established.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.8
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• pp.777-782
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• 2002

The range profile is easily obtainable and promising feature vector in the aspect of real-time radar target recognition system. However, the range profile is highly dependent on a aspect angle of a target and this dependence make it difficult the recognition over wide-angular region. In this paper, we propose the classifier with subclass concept in order to solve this dependence problem. Recognition results using six aircraft models measured at compact range facility are presented to show the effectiveness of this proposed classifier over wide-angular region.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1173-1180
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• 2013

High Resolution Range Profile-Jet Engine Modulation imagery first introduced in 2005 carries out radar target recognition by localizing the position of the jet engine installed on the aircraft target. This paper presents a new approach for estimating the jet engine position in the HRRP-JEM image based on the eccentricity of a complex signal. It can effectively evaluate the contribution of the JEM component to the radar received signal in a range bin of the HRRP-JEM image. Therefore, the localization is expected to be performed more quantitatively and reliably by pinpointing the range bin corresponding to the jet engine position where the JEM contribution is maximized. The simulation results of realistic aircraft models validated the effectiveness of the proposed concept.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.501-506
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• 2017

An infrared seeking missile does not emit any signal by itself as it is guided by passive heat signature from an aircraft. Therefore, it is difficult for the target aircraft to notice the existence of incoming missile, making it a serious threat. The usage of MAW(missile approach warning) that can notify the approaching infrared seeking missile is currently limited due to its high cost. Furthermore, effectiveness of MAW against infrared seeking missile is not available in open literature. Therefore, effect of evasive maneuver by MAW on the survivability of the aircraft is simulated to evaluate the benefit of the MAW in this research. The lethal range is used as a measure of aircraft survivability. An aircraft flying at an altitude of 5km with Mach 0.9 being tracked by air-launched AIM-9 infrared seeking missile is considered in this research. As a variable for the evasive maneuver, the MAW recognition distance of 5~7km and the G-force of 3~7G that limits maximum directional change of the aircraft are considered. Simulation results showed that the recognition of incoming missile by MAW and following evasive maneuver can reduce the lethal range considerably. Maximum reduction in lethal range is found to be 29.4%. Also, the MAW recognition distance have a greater importance than the aircraft maneuverability that is limited by structural limit of the aircraft.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.388-393
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• 1992

An infrared range finder using a self-mixing laser diode (SM-LD), which has been proposed and developed by the Authors, can measure not only a range of a moving target but its velocity simultaneously. In this paper, described is that the precise mode-hop pulse train can be obtained by employing a new signal processing circuit even when the backscattered light returning into the SM-LD is much more weaker. As a result, the distance to a tilted square sheet made from aluminium or white paper, which is placed 10 cm through 60 cm from the SM-LD, is measured with accuracy of a few percent even when the tilting angle is less than 75 degrees or 85 degrees, respectively. And in this paper, described is the range-image recognition of a plane object under the condition of standstill. The output laser beam is scanned by scanning two plane mirrors-equipped with each stepping motor. And we succeeded in the acquisition of the range-image of a plane object in a few tens of seconds. Furthermore, described is a feasibility study about the range-image recognition of a slowly moving plane object.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.6
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• pp.579-589
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• 2004

The radar signals are generally very sensitive to relative orientations between radar and target. Thus, the performance of a target recognition system significantly deteriorates as the region of aspect angles becomes broader. To address this difficulty, in this paper, we propose a method based on the multi-aspect information in order to improve the classification capability ever for a wide angular region. First, range profiles are used to extract feature vectors based on the central moments and principal component analysis(PCA). Then, a classifier with the use of multi-aspect information is applied to them, yielding an additional improvement of target recognition capability. There are two different strategies among the classifiers that can fuse the information from multi-aspect radar signals: independent methodology and dependent methodology. In this study, the performances of the two strategies are compared within the frame work of target recognition. The radar cross section(RCS) data of six aircraft models measured at compact range of Pohang University of Science and Technology are used to demonstrate and compare the performances of the two strategies.