• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.59-65
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• 2020

Many technologies are being studied to reduce the RCS(Radar Cross Section) of stealth aircraft. Most RCS-reduction technlogies correspond to platforms. It is important to identify factors that RCS performance through simulation analysis of aircraft Mounted equipment. In particular, there are no studies of RCS performance in the radar frequency band when antenna transmit signals are applied. In this paper, the RCS performance variation on the transmit signal on/off of antennas mounted on a stealth aircraft was verified. Antennas were selected for each frequency band and simulated analysis to the RCS performance changes during antenna transmitting signal. Finally, to verify the characteristics of the change in RCS performance, RCS test measurements on the low-profile antenna transmit signal on/off were performed. In addintion, antenna RCS test measurement was performed according to the change of transmit signal power output. As a result, it was confirmed that there is no change in RCS performance when an antenna transmit signal is applied.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.23-28
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• 2021

In this paper, we analyze the tracking errors of monopulse radar according to the JSR of retrodirective cross-eye and radar skin return signals. The cross-eye jammer gain(G_c) is used to calculate the radar tracking errors, and the relationship between the jammer gain and the JSR is represented mathematically. We analyze the radar tracking errors by varying the tracking angle and JSR. Analysis results of the phase difference(ϕ) and amplitude ratio(a) between the two jammer signals and the changing JSR show that the closer the phase difference of the two jammer signals is to 180, the greater the tracking error and it shows that if the JSR is above 20dB, the tracking errors no longer increase. This work presents an effective utilization of retrodirective cross-eye jammers through various tracking error analyses based on the JSR, tracking angles, two-jammer phase differences and amplitude ratios of two-jammer signals.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.7
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• pp.625-630
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• 2009

In this paper, we introduce the analysis and counter-measure of signal distortion of search radar equipped on the ship. Using ShipEDF program, the search radar's main antenna and ship structures are modeled in the view of electromagnetism. Ray tracing method is used for analysis of the search radar's radiation patterns in free space and ship condition. From analyzed radiation patterns, we can conclude that the search radar's signal distortion is due to radiation pattern distortion. We also analyze the surface current distribution of the mast to propose the counter-measure to reduce electro-magnetic field reflection of mast.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.732-737
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• 2016

A pulse radar signal exhibits periodic appearance of pulses in time. So it leads to a high correlation between two samples separated in time by multiples of its period. In this paper, we present a spectrum sensing technique for a radar signal which exploits the periodicity of its autocorrelation function and a radar pulse interval estimation scheme in order to address the case that the radar pulse interval is not known a priori. Finally, we evaluate the sensing performance of the proposed scheme through computer simulation and compare its performances with those of energy detection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.10
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• pp.1188-1195
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• 2012

The trend for the development of radar is the active phased-array radar system. The trade-off between the processing speed and the number of the signal process board for the real time signal processing has to be optimized particularly in multichannel radar system. This paper introduces a transmission technique in order to transmit a large amount of received data from an Antenna Part to Signal Process Part. As a result, the number of the S/L board(COTS board) is reduced to one half, and the margin of the data transmission rate is about 2 times higher than the original method.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.491-498
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• 2015

Recognition of radar emitter signals is one of core elements in radar reconnaissance systems. A novel method based on singular value decomposition (SVD) and the main ridge slice of ambiguity function (AF) is presented for attaining a higher correct recognition rate of radar emitter signals in case of low signal-to-noise ratio. This method calculates the AF of the sorted signal and ascertains the main ridge slice envelope. To improve the recognition performance, SVD is employed to eliminate the influence of noise on the main ridge slice envelope. The rotation angle and symmetric Holder coefficients of the main ridge slice envelope are extracted as the elements of the feature vector. And kernel fuzzy c-means clustering is adopted to analyze the feature vector and classify different types of radar signals. Simulation results indicate that the feature vector extracted by the proposed method has satisfactory aggregation within class, separability between classes, and stability. Compared to existing methods, the proposed feature recognition method can achieve a higher correct recognition rate.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1279-1284
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• 2000

This study introduces a simulation model of radar responses with frequencies on subsurface voids in concrete. In this model, the resolution and the attenuation according to radar frequencies in each interface which has different electromagnetic property are analyzed. This model aims to select the best frequency of radar which can analyze the thickness of voids in concrete from radar response. It also can be applied to estimate the limitation of propagation depth of radar on subsurface voids in concrete. The computed results show the radar images based on radar signal processing using convolution technique.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.114-117
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• 2002

The airborne tracking radar is located in front of aircraft or missile and measures and tracks a target motion. The signal processor receives target signals from a receiver using A/D converters, and calculates the target motion, and transfers the data to the aircraft or missile control unit. Since the signal processing system is required to be lightweight and small size as well as high performance to calculate and analyze the received signal, we use high speed DSPs and SMD type components having low power consumption. In this paper, we describe the design concept of signal processing system of the airborne tracking radar.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.890-893
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• 2014

In this paper, we present a signal processing algorithm for a marine radar system, in which the evaluation of probability of collision as well as target detection and tracking are performed. Moreover, the digital signal processor that implements the algorithm is proposed. As simulation environment, a mechanically scanning antenna utilizing FMCW signal is used, conducting the beamforming operation with 1 degrees intervals. Test board consists of DSP chips and FPGA, which enable the implemented system to operate in real-time.

• Journal of IKEEE
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• v.22 no.1
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• pp.162-167
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• 2018

In this paper, we propose a method to classify radar signals according to the jamming technique by applying the machine learning to parameter data extracted from received radar signals. In the present army, the radar signal is classified according to the type of threat based on the library of the radar signal parameters mostly built by the preliminary investigation. However, since radar technology is continuously evolving and diversifying, it can not properly classify signals when applying this method to new threats or threat types that do not exist in existing libraries, thus limiting the choice of appropriate jamming techniques. Therefore, it is necessary to classify the signals so that the optimal jamming technique can be selected using only the parameter data of the radar signal that is different from the method using the existing threat library. In this study, we propose a method based on machine learning to cope with new threat signal form. The method classifies the signal corresponding the new jamming method for the new threat signal by learning the classifier composed of the hidden Markov model and the neural network using the existing library data.