• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.775-778
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• 2016

In this paper, we propose a new method to automatically recognize PRI modulation type of radar signal at ES(Electronic Support) in electronic singal environment. The propose method stores pattern of PRI(Pulse Repetition Interval) of radar signal and uses statistic data, which firstly classifies into 2 classes. Then the proposed method recognizes each PRI signal using statistic characteristic of PRI. We apply various 5 kinds of PRI signal such as constant PRI, jitter PRI, D&S(dwell & switch) PRI, stagger PRI, sliding PRI, etc. The result shows the proposed method correctly identifies various PRI signals.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.144-150
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• 2022

The on-board processor of satellite synthetic aperture radar(SAR) generates transmission signal by digital signal processing, converts it into an analog signal. At this time, the transmission signal generated from the baseband requires the frequency modulation to convert it to the high-frequency band in order to improve the stability. General frequency modulation method using local oscillator(LO) causes IQ imbalance due to phase error/magnitude error and these error reduce performance of SAR. To generate transmission signal without phase/magnitude error, this paper suggests design method of the frequency modulation method using digital to analog converter(DAC) at on-board SAR. For design, this paper analyzes the characteristic of DAC mode and uses pre-compensation filter. To analyze the proposed method performance, performance index are compared with IQ imbalance signals. This method is suitable for on-board SAR using fast sampling DAC and has the advantage of being able to solve IQ imbalances.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.347-354
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• 2022

The synthetic aperture radar(SAR) is an equipment that can acquire images in all weathers day and night based on radar signals. The on-board processor of satellite SAR generates transmission signal by digital signal processing, converts it into an analog signal and transmits to antenna. Until the transmission signal generated by on-board processor is output, the signal passes the transmission cables and analog devices. At this time, these hardware distort the signal and makes SAR performance worse. To improve the performance, pre-distortion technique is used. But, general pre-distortion using taylor series is not sufficient to compensate for the distortion. This paper suggests transmit signal design method with improved pre-distortion. This paper uses envelop sampling method and interpolation filter for frequency domain compensation. The proposed method accurately compensates the hardware distortion and reduces resource usage of FPGA. To analyze proposed method's performance, IRF characteristics are compared when the proposed method applies to signal with errors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.59-64
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• 2024

The small tracking radar randomly changes the transmission period to avoid deceptive signals such as RGPO (Range Gaet Pull Off) operated on the target. Since the code repeats after a specific section, it becomes difficult to avoid a deceptive signal when the repetition is exposed. In this paper, a more realistic transmission pulse code is generated by adding random code generation through FPGA and system white noise. We present the research results of code generation that generates PRF that can avoid repetition while using pseudo-random code in EPROM using FPGA. Also, the result of designing random PRF pulse was confirmed by applying it to tracking radar.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3761-3779
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• 2022

The performance of existing recognition algorithms for binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals degrade under conditions of low signal-to-noise ratios (SNR). Hence, a novel recognition algorithm based on features in the graph domain is proposed in this study. First, the power spectrum of the squared candidate signal is truncated by a rectangular window. Thereafter, the graph representation of the truncated spectrum is obtained via normalization, quantization, and edge construction. Based on the analysis of the connectivity difference of the graphs under different hypotheses, the sum of degree (SD) of the graphs is utilized as a discriminate feature to classify BPSK and QPSK signals. Moreover, we prove that the SD is a Schur-concave function with respect to the probability vector of the vertices (PVV). Extensive simulations confirm the effectiveness of the proposed algorithm, and its superiority to the listed model-driven-based (MDB) algorithms in terms of recognition performance under low SNRs and computational complexity. As it is confirmed that the proposed method reduces the computational complexity of existing graph-based algorithms, it can be applied in modulation recognition of radar or communication signals in real-time processing, and does not require any prior knowledge about the training sets, channel coefficients, or noise power.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.9
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• pp.1244-1249
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• 1995

Wavelet transform technique is applied to two important electromagnetic problems:1) to analyze the frequency-domain radar echo from finite-size targets and 2) to the integral solution of two- dimensional electromagnetic scattering problems. Since the frequency- domain radar echo consists of both small-scale natural resonances and large-scale scattering center information, the multiresolution property of the wavelet transform is well suited for analyzing such ulti-scale signals. Wavelet analysis examples of backscattered data from an open- ended waveguide cavity are presented. The different scattering mechanisms are clearly resolved in the wavelet-domain representation. In the wavelet transform domain, the moment method impedance matrix becomes sparse and sparse matrix algorithms can be utilized to solve the resulting matrix equationl. Using the fast wavelet transform in conjunction with the conjugate gradient method, we present the time performance for the solution of a dihedral corner reflector. The total computational time is found to be reduced.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1671-1675
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• 2012

In this paper, we fabricate multi-channel receiver for radar system. This receiver at X-band can be received 8 signal of an identical characteristic, dynamic range has more than 80[dB]. To process direct received signals, this system has the built-in two digital de-modulators which offer the minimum loss on the receiving signal path and has high stability by adding Built-In Test. The gain, noise figure, difference of amplitude and phase on the signal path is respectively $14{\pm}2$[dB], 19[dB], ${\pm}2$[dB], $10^{\circ}$ and below.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1407-1413
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• 1994

To obtain accurate target information in a radar system, clutter or interference signals must first be effectively removed for target detection. In this paper, the signal is projected onto a constrained orthogonal subspace, so that a minimum variance optimal detector is transformed into an unconstrained detector. The proposed algorithm is equivalent to the conventional optimal detector algorithm, and th algorithm structure shows that the Gram-Schmidt orthogonalization can be achieved to obtain the fast convergence. The performance of the proposed method was observed by simulation experiments.

• ETRI Journal
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• v.41 no.6
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• pp.750-759
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• 2019

Presently, the extraction of hand-crafted features is still the dominant method in radar emitter recognition. To solve the complicated problems of selection and updation of empirical features, we present a novel automatic feature extraction structure based on deep learning. In particular, a convolutional neural network (CNN) is adopted to extract high-level abstract representations from the time-frequency images of emitter signals. Thus, the redundant process of designing discriminative features can be avoided. Furthermore, to address the performance degradation of a single platform, we propose the construction of an ensemble learning-based architecture for multi-platform fusion recognition. Experimental results indicate that the proposed algorithms are feasible and effective, and they outperform other typical feature extraction and fusion recognition methods in terms of accuracy. Moreover, the proposed structure could be extended to other prevalent ensemble learning alternatives.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.369-377
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• 2005

This paper describes the realization of a coordinates tracking algorithm for an EOTS (Electro-Optical Tracking System). The EOTS stabilizes the image sensors, tracks targets automatically, and provides navigation capability for vehicles. The coordinates tracking algorithm calculates the azimuth and the elevation angle of an EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which are generated by a Radar. In the error analysis, the unexpected behaviors of an EOTS due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. The application of this algorithm to an EOTS will improve the operational capability by reducing the time which is required to find the target and support flight especially in the night time flight and the poor weather condition.