• Journal of electromagnetic engineering and science
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• v.12 no.4
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• pp.234-239
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• 2012

This paper presents a compact K-band Doppler radar sensor for human vital signal detection that uses a radar configuration with only single coupler. The proposed radar front-end configuration can reduce the chip size and the additional RF power loss. The radar front-end IC is composed of a Lange coupler, VCO, and single balanced mixer. The oscillation frequency of the VCO is from 27.3 to 27.8 GHz. The phase noise of the VCO is -91.2 dBc/Hz at a 1 MHz offset frequency, and the output power is -4.8 dBm. The conversion gain of the mixer is about 11 dB. The chip size is $0.89{\times}1.47mm^2$. The compact Ka-band Doppler radar system was developed in order to demonstrate remote human vital signal detection. The radar system consists of a Ka-band Doppler radar module with a $2{\times}2$ patch array antenna, baseband signal conditioning block, DAQ system, and signal processing program. The front-end module size is $2.5{\times}2.5cm^2$. The proposed radar sensor can properly capture a human heartbeat and respiration rate at the distance of 50 cm.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.425-428
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• 2001

In this paper, FMCW radar signal processing technique for the vehicle detection system are studied. And FMCW radar sensor is used as a equipment for vehicle detection. To test the performance of developed algorithm, the evaluation of the algorithm is done by simulation for signal processing technique of vehicle detection system. RADAR signal of a driving vehicle is generated by using the Matlab. Distance and velocity of vehicles are calculated with developed a1gorithm. Also the signal processing procedure is done for the virtual data with FM-AM converted noise.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1064-1066
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• 2003

In this paper, ground penetrating radar (GPR), which has the capability to detect non metal and plastic mines, is proposed to detect and discriminate antipersonnel (AP) landmines. The time domain GPR - Impulse radar and frequency domain GPR - SFCW (Stepped Frequency Continuous Wave) radar is utilized for metal and non-metal landmine detection and its performance is investigated. Since signal processing is vital for target reorganization and clutter rejection, we implemented the MUSIC (Multiple Signal Classification) algorithm for the signal processing of SFCW radar data and SAR (Synthetic Aperture Radar) processing method for the signal processing of Impulse radar data.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.353-357
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• 2006

The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We propose the pulse radar signal processing algorithm in which we devide the trace. data from pulse radar into segments by using SSC concept, and then construct the sectors in accordance with period and amplitude of segments, and finally decide the vehicle detection probability by applying the SSC parameters of each sectors into the discriminant function. We also improve the signal processing time by reducing the quantities of processing data and processing routines.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.134-141
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• 2019

Radar systems are divided into the pulse Doppler (PD) radar and the frequency modulated continuous wave (FMCW) radar depending on the transmission waveform. In particular, the PD radar is advantageous for long-range target detection, and the FMCW radar is suitable for short-range target detection. In this paper, we present design and implementation results for a multi-mode radar signal processor (RSP) that can support both PD and FMCW radar systems to detect unmanned aerial vehicles (UAVs) at short distances as well as long distances. The proposed radar signal processor can be implemented based on Altera Cyclone-IV FPGA with 19,623 logic elements, 9,759 registers, and 25,190,400 memory bits. The logic elements and registers of the proposed radar signal processor are reduced by approximately 43% and 30%, respectively, compared to the sum of logic elements and registers of the conventional PD radar and FMCW radar signal processor.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.79-87
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• 2019

Radar detection range is decreased with an increase in the noise levels and detection thresholds in adaptive CFAR of a radar signal processor to the weather clutter reflection signal in the rain. When a high-velocity plot is generated in weather clutter, what are detected are not targets but false plots. Detection opportunity is reduced by radar time resource consumption from additional confirmations regarding the false plots. In this paper, the received signals are saved using a radar-received signal storage device. Based on the analysis of the received signals from weather clutter, the influence of the rainfall reflection has been mitigated by front-end attenuation of the signal processor. The improvement in the detection performance is verified through received signal and simulation results.

• 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 Astronomy and Space Sciences
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• v.35 no.4
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• pp.279-286
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• 2018

Radar sensors are used for space situational awareness (SSA) to determine collision risk and detect re-entry of space objects. The capability of SSA radar system includes radar sensitivity such as the detectable radar cross-section as a function of range and tracking capability to indicate tracking time and measurement errors. The time duration of the target staying in a range cell is short; therefore, the signal-to-noise ratio cannot be improved through the pulse integration method used in pulse-Doppler signal processing. In this study, a method of improving the signal-to-noise ratio during range migration is presented. The improved detection performance from signal processing gains realized in this study can be used as a basis for comprehensively designing an SSA radar system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.982-984
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• 2017

In time domain, a radar signal is divided into two segments: one is for a transmitted pulse and the other is for receiving possible returns from radar targets. Also the received signal is relatively weak and consists of background noise except for the reflected signals from radar targets. In this Letter, we present an energy detection based spectrum sensing for a radar signal in the presence of noise power uncertainty exploiting this characteristics.