• 한국음향학회지
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• 제40권5호
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• pp.401-407
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• 2021

연속 송수신 소나 기술은 표적 탐지 시간간격이 짧아 표적을 탐지하고 추적하는 데 효과적인 기술이다. 연속 송수신 소나 시스템에 적합한 Generalized Sinusoidal Frequency Modulation(GSFM)펄스는 펄스 간 직교성을 유지하면서 높은 시간-주파수 곱을 얻을 수 있는 것으로 알려져 있다. 그러나 가속도를 갖는 표적이 존재할 경우 수신된 GSFM 펄스를 상관처리하는 적정한 시간 길이를 산출하는 방법에 대해서는 알려진 바가 없다. 본 논문에서는 GSFM 펄스를 사용하는 연속 송수신 소나 시스템에서 수신신호를 정합처리할 때 적합한 시간 길이를 상관도에 근거하여 산출하는 방법을 제안한다. 제안된 방법은 표적의 가속도에 따른 상관도를 계산하고 상관도에 따른 신호처리 길이를 산출한다. 부엽의 준위를 통해 제안된 방법으로 산출된 신호처리 길이를 적용할 경우 안정적인 탐지 성능을 얻을 수 있음을 보인다.

• 한국군사과학기술학회지
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• 제9권3호
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• pp.95-100
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• 2006

The pulse compression technique using Linear FM signal is commonly used for improving the performance of both the detection range and range resolution in radar system. In general, the compressed LFM waveform has relatively large sidelobe level which may prevent a target from being detected when strong jammer or clutter signal is near the target signal. In this paper, we propose a new weighting method which uses the square-root weight to suppress the sidelobe level. Typical applications are missile seekers and tracking radar systems where target tracking range is available prior to the signal processing. By computer simulation, we show that the performance of the proposed method is better than that of the conventional weighting methods in terms of sidelobe suppression.

• 한국군사과학기술학회지
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• 제20권4호
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• pp.482-490
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• 2017

The radar signal processing procedure is divided into the pre-processing such as frequency down converting, down sampling, pulse compression, and etc, and the post-processing such as doppler filtering, extracting target information, detecting, tracking, and etc. The former is generally designed using FPGA because the procedure is relatively simple even though there are large amounts of ADC data to organize very quickly. On the other hand, in general, the latter is parallel processed by multiple DSPs because of complexity, flexibility and real-time processing. This paper presents the radar signal processor design using FPGA which includes not only the pre-processing but also the post-processing such as doppler filtering, bore-sight error, NCI(Non-Coherent Integration), CFAR(Constant False Alarm Rate) and etc.

• Journal of electromagnetic engineering and science
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• 제9권3호
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• pp.130-140
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• 2009

The design theory and experimental results of a true random noise radar system are presented in this paper. Target range information can be extracted precisely by correlation processing between the delayed reference and the signal received from a target, and the velocity information by the Doppler processing with successive correlation data. A K-band noise radar system was designed using random FM noise signal, and the characteristics of the fabricated system were examined with laboratory and outdoor experiments. A C-band random FM noise signal was generated by applying a low-frequency white Gaussian noise source to VCO(Voltage Controlled Oscillator), and a K-band Tx noise signal with 100 MHz bandwidth was obtained by using a following frequency multiplier. Two modified wave-guide horn arrays were designed and fabricated, and used for the Tx and Rx antennas. The required amount of Tx/Rx isolation was attained by using a coupling cancellation circuit as well as keeping them apart with predetermined spacing. A double down-conversion scheme was used in the Rx and reference channels, respectively, for easy post processing such as correlation and Doppler processing. The implemented noise radar performance was examined with a moving bicycle and a very high-speed target with a velocity of 150 m/s. The results extracted by the Matlab simulation using the logging data were found to be in a reasonable agreement with the expected results.

• 전기전자학회논문지
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• 제22권3호
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• pp.532-538
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• 2018

본 논문은 자성센서 기반 지뢰탐지기를 개발하는 과정에서 필요한 신호처리 알고리즘을 제안한다. 탐지신호의 세기는 탐지 코일에 수신된 자기장의 변화량을 이용하여 얻는다. 표적이 없을 때 대비 표적이 있을 때의 상대적인 신호세기를 계산하기 때문에 표적이 없는 상태에서 calibration data를 만든다. 자기장은 장비 자체의 전기적인 잡음 또는 주변 환경의 영향을 받으므로 calibration을 지속적으로 수행하고 갱신하는 것이 중요하다. 마지막으로 표적에 의해 발생하는 신호크기의 변화량, 즉 단위 시간 당 그래프의 기울기 값이 일정 수준 이상 도달하는지 감시하여 정확한 탐지지점과 신호크기를 판별한다.

• 대한전자공학회논문지SP
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• 제49권1호
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• pp.119-127
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• 2012

본 논문은 밀리미터파 탐색기 신호처리장치의 개발 및 시험에 대하여 기술한다. 지대공미사일은 표적의 종류 및 상황에 따라 다양한 송신파형이 요구되기 때문에 유연성을 고려한 하드웨어, 소프트웨어 설계를 하였다. 본 신호처리장치는 ADC, FPGA, DSP 및 기타 소자들로 구성된다. FPGA는 DSP에 연동 인터페이스를 제공하고, 중간주파수 신호를 기저대역신호로 변환한다. DSP는 신호처리, 표적정보계산 및 장치제어를 수행한다. 각 부품은 하드웨어적으로 직렬로 연결되며, 다양한 송신파형에 대한 신호처리 알고리즘은 병렬로 연결되어있다.

• 전기학회논문지
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• 제64권4호
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• pp.573-577
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• 2015

In this paper, we propose a signal processing board suitable for a semi-active laser tracking to detect an optical signal generated from the laser target designator by applying an analog trigger signal, the quadrant photodetector and a high speed ADC(analog-digital converter) sampling technique. We improved the stability by applying the averaging method to minimize the measurement error of a gaussian pulse. To evaluate the performances of the proposed methods, we implemented a prototype board and performed experiments. As a result, we implemented a frequency counter with an error 14.9ns in 50ms. PRF error code has a stability of less than 1.5% compared to the NATO standard. Applying the three point averaging method to ADC sampling, the stability of 28% in X-axis and 22% in Y-axis than one point sampling was improved.

• 대한임베디드공학회논문지
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• 제12권5호
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• pp.267-275
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• 2017

Time of difference of arrival (TDOA) method using passive sonar sensor array has normally been used to estimate the location of a concealed moving target in underwater environment. Particle filter has been introduced for effective target estimation for non-Gaussian and nonlinear systems. In this paper, we propose a GPU-based acceleration of target position estimation using particle filter and propose efficient embedded system and software architecture. For the TDOA measurement from the passive sonar sensor, we use the generalized cross correlation phase transform (GCC-PHAT) method to obtain the correlation coefficient of the signal using FFT and we try to accelerate the calculation of GCC-PHAT based TDOA measurements using FFT with GPU CUDA. We also propose parallelization method of the target position estimation algorithm using the GPU CUDA to update the state of each particle for the target position estimation using the measured values. The target estimation algorithm was verified using Matlab and implemented using GPU CUDA. Then, we realized the proposed signal processing acceleration system using NVIDIA Jetson TX1 as the target board to analyze in terms of the execution time. The execution time of the algorithm is reduced by 55% to the CPU standalone-operation on the target board. Experiment results show that the proposed architecture is a feasible solution in terms of high-performance and area-efficient architecture.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.76-81
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• 2021

This study proposes a method to reduce the phase error of the received signal to detect the object bearing. The phase shift of the received signal occurs due to the multipath of the signal by natural structure or artificial structures. When detecting the direction of the object using radio waves, the phase of the received signal cannot be accurately detected because of the phase bearing error in the object detection direction. The object detection direction estimation depends on the phase difference, antenna installation distance, signal source wavelength, frequency band and bearing angle. This study reduces the error of the phase bearing by using the phase delay of the relative phase difference for the signals incident on the two antennas. Through simulation, we analyzed the object direction detection performance of the proposed method and the existing method. Three targets are detected from the [-15°, 0°, 15°] direction. The existing method detects the target at [-13°, 3°, 17°], and the proposed method detects the at [-15°, 0°, 15°]. As a result of the simulation, the target detection direction of the proposed method is improved by 2 degrees compared to the existing method.

• 한국멀티미디어학회논문지
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• 제19권10호
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• pp.1775-1781
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• 2016

Generally, in the underwater target recognition, feature vectors are extracted from the target signal utilizing spatial information according to target shape/material characteristics. In addition, various signal processing techniques have been studied to extract feature vectors which are less sensitive to the location of the receiver. In this paper, we synthesized active echo signals using 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to echo signals to extract signal features. For the performance verification, classification experiments were performed using backpropagation and probabilistic neural network classifiers based on single aspect and multi-aspect method. As a result, we obtained a better recognition result using proposed feature extraction and multi-aspect based method.