• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.30 no.3
• /
• pp.236-242
• /
• 2019

Ultra-wideband(UWB) is a technology that can transmit and receive signals at high speeds using a very short signal of wideband of several GHz, and has been recently used in the field of radar technology. Impulse radio(IR)-UWB radar is used in the field of motion recognition with high resolution. In this work, we studied motion recognition using IR-UWB radar. We constructed a development environment to acquire data about motion and implemented a signal processing algorithm for performance enhancement. Based on the signal processing result, the performance was verified through feature extraction and learning of motion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.837-839
• /
• 2014

In radar systems, information of three-dimensional (3D) trajectory is necessary for tracking targets. The information of 3D trajectory for a 3D radar can be obtained by estimating the azimuth angle, the elevation angle, and the distance. The estimated information of the angles and the distance has errors according to received signals. Since these errors affect performances of 3D radar systems, performance analysis of 3D radar for the angles and the distance errors is required. In this paper, the performance of 3D radar systems is analyzed by root mean square error (RMSE) between true trajectory information and the estimated trajectory information according to the angles and the distance errors.

• Journal of Navigation and Port Research
• /
• v.28 no.4
• /
• pp.305-309
• /
• 2004

The problem for parameters estimation of the received signals impinging on array sensors has long been of great research Interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.11 no.4
• /
• pp.36-45
• /
• 2008

LYNX ESM system operates digital receiver for analyzing radar of intrapulse modulation signal. This paper contains DC offset compensation method of IQ channels, imbalancing comensation method of amplitude and phase, precisional PW measurement using adaptive threshold set, analyzing algorithm of intrapulse modulation signals. Its effectiveness was proven by technical and operational test.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.9
• /
• pp.1986-1995
• /
• 2013

The ELINT system which derives intelligence from electromagnetic radiations plays an important role in modern electric warfares. Among radar characteristics inferred from the signals, intra-pulse modulation scheme is a useful feature to identify modern radars. This paper proposes the method to classify intra-pulse modulation schemes such as UM, PSK, BFSK, QFSK, LFM and NLFM based on the fuzzy algorithm. The proposed method defines fuzzy membership functions to characterize input signals, and then it calculates accordance rates for each modulation scheme with fuzzy inference rules. The experimental results show that the probability of correct recognition is more than 95% for SNR > 10dB.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.25 no.4
• /
• pp.467-475
• /
• 2014

In this paper, we introduce a sparse recovery algorithm applied to a radar signal model, based on the compressive sensing(CS), for the formulation of the radar signatures, such as high-resolution range profile(HRRP) and ISAR(Inverse Synthetic Aperture Radar) image. When there exits missing data in observed RCS data samples, we cannot obtain correct high-resolution radar signatures with the traditional IDFT(Inverse Discrete Fourier Transform) method. However, high-resolution radar signatures using the sparse recovery algorithm can be successfully recovered in the presence of data missing and qualities of the recovered radar signatures are nearly comparable to those of radar signatures using a complete RCS data without missing data. Therefore, the results show that the sparse recovery algorithm rather than the DFT method can be suitably applied for the reconstruction of high-resolution radar signatures, although we collect incomplete RCS data due to unwanted interferences or jamming signals.

• International Journal of Highway Engineering
• /
• v.18 no.2
• /
• pp.37-42
• /
• 2016

PURPOSES : The objective of this study is to determine the optimal frequency of ground penetrating radar (GPR) testing for detecting the voids under the pavement. METHODS : In order to determine the optimal frequency of GPR testing for void detection, a full-scale test section was constructed to simulate the actual size of voids under the pavement. Voids of various sizes were created by inserting styrofoam at varying depths under the pavement. Subsequently, 250-, 500-, and 800-MHz ground-coupled GPR testing was conducted in the test section and the resulting GPR signals were recorded. The change in the amplitude of these signals was evaluated by varying the GPR frequency, void size, and void depth. The optimum frequency was determined from the amplitude of the signals. RESULTS: The capacity of GPR to detect voids under the pavement was evaluated by using three different ground-coupled GPR frequencies. In the case of the B-scan GPR data, a parabolic shape occurred in the vicinity of the voids. The maximum GPR amplitude in the A-scan data was used to quantitatively determine the void-detection capacity. CONCLUSIONS: The 250-MHz GPR testing enabled the detection of 10 out of 12 simulated voids, whereas the 500-MHz testing allowed the detection of only five. Furthermore, the amplitude of GPR detection associated with 250-MHz testing is significantly higher than that of 500-MHz testing. This indicates that 250-MHz GPR testing is well-suited for the detection of voids located at depths ranging from 0.5~2.0 m. Testing at frequencies lower than 250 MHz is recommended for void detection at depths greater than 2 m.

• Korean Journal of Remote Sensing
• /
• v.26 no.3
• /
• pp.297-304
• /
• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.25 no.1
• /
• pp.92-102
• /
• 2017

For an automotive surveillance radar system, fast-chirp train based FMCW (Frequency Modulated Continuous Wave) radar is a very effective method, because clutter and moving targets are easily separated in a 2D range-velocity map. However, pedestrians with low echo signals may be masked by strong clutter in actual field. To address this problem, we proposed in the previous work a clutter cancellation and moving target indication algorithm using the coherent phase method. In the present paper, we initially composed the test set-up using a 24 GHz FMCW transceiver and a real-time data logging board in order to verify this algorithm. Next, we created two indoor test environments consisting of moving human and stationary targets. It was found that pedestrians and strong clutter could be effectively separated when the proposed method is used. We also designed and implemented these algorithms in FPGA (Field Programmable Gate Array) in order to analyze the hardware and time complexities. The results demonstrated that the complexity overhead was nearly zero compared to when the typical method was used.

• Journal of Advanced Navigation Technology
• /
• v.25 no.5
• /
• pp.426-432
• /
• 2021

Continuous wave (CW) Doppler radar has the advantage of being able to solve the privacy problem unlike camera and obtains signals in a non-contact manner. Therefore, this paper proposes a human activity recognition (HAR) system using CW Doppler radar, and presents the hardware design and implementation results for acceleration. CW Doppler radar measures signals for continuous operation of human. In order to obtain a single motion spectrogram from continuous signals, an algorithm for counting the number of movements is proposed. In addition, in order to minimize the computational complexity and memory usage, binarized neural network (BNN) was used to classify human motions, and the accuracy of 94% was shown. To accelerate the complex operations of BNN, the FPGA-based BNN accelerator was designed and implemented. The proposed HAR system was implemented using 7,673 logics, 12,105 registers, 10,211 combinational ALUTs, and 18.7 Kb of block memory. As a result of performance evaluation, the operation speed was improved by 99.97% compared to the software implementation.