arXiv subjects

Seong-Ook Park

Publications and source records attributed to Seong-Ook Park.

6 recordsLinked to original sources

arXiv2023

Dynamic Geometry-Based Stochastic Channel Modeling for Polarized MIMO Systems with Moving Scatterers

This paper introduces a four-dimensional (4D) geometry-based stochastic model (GBSM) for polarized multiple-input multiple-output (MIMO) systems with moving scatterers. We propose a novel motion path model with high degrees of freedom based on the Brownian Motion (BM) random process for randomly moving scatterers. This model is capable of analyzing the effect of both deterministically and randomly moving scatterers on channel properties. The mixture of Von Mises Fisher (VMF) distribution is considered for scatterers resulting in a more general and practical model. The proposed motion path model is applied to the clusters of scatterers with the mixture of VMF distribution, and a closed form formula for calculating space time correlation function (STCF) is achieved, allowing the study of the behavior of channel correlation and channel capacity in the time domain with the presence of stationary and moving scatterers. To obtain numerical results for channel capacity, we employed Monte Carlo simulation method for channel realization purpose. The impact of moving scatterers on the performance of polarized MIMO systems is evaluated using 2 by 2 MIMO configurations with various dual polarizations, i.e. V/V, V/H, and slanted 45° polarizations for different signal-to-noise (SNR) regimes. The proposed motion path model can be applied to study various dynamic systems with moving objects. The presented process and achieved formula are general and can be applied to polarized MIMO systems with any arbitrary number of antennas and polarizations.

eess.SY↗

arXiv2020

Internal Calibration Process Using Chirp Pulses with Application of the Adam Learning Algorithm

We propose a new internal calibration process using chirp pulses. Our method is utilized to mitigate thermal drift, which is unwanted changes and usually occurs in active elements such as a high power amplifier and low noise amplifier. The proposed method has advantages from two distinct aspects: calibration signal and algorithm. In respect to the calibration signal, our method does not contain an additional signal source because chirp pulses, which are normally used for remote sensing, are used as calibration signals. Moreover, our methods solve the ambiguity problem of analyzing a phase shift which occurs when sinusoidal signals are used as calibration signals. In regards to the algorithm, the Adam learning algorithm avoids learning in the wrong direction, unlike the conventional gradient descent. Using our method, mathematical forms of received signals are acquired successfully. Our method shows better effectivity compared to the conventional gradient descent algorithm. After compensation, the maximum differences of gain and phase become 0.06 dB and 2.42 degrees, respectively.

eess.SP↗

arXiv2020

FMCW SAR with New Synthesis Method Based on A-SPC Technique

Frequency modulated continuous wave (FMCW) radar is emerging as a trendy radar system for synthetic aperture radar (SAR). This letter proposes a novel method for the extraction of the SAR image with the FMCW radar. The proposed method can improve the quality of the SAR image. For the verification, we built an automobile SAR (AutoSAR) system and conducted experiments to extract the SAR map by using the AutoSAR system. Then, we synthesized SAR images through both the conventional method and the proposed method to demonstrate the performance of the proposed method. The experimental results show that the SAR image has been successfully improved by the proposed method.

eess.SP↗

arXiv2020

Small Drone Classification with Light CNN and New Micro-Doppler Signature Extraction Method Based on A-SPC Technique

As the threats of small drones increase, not only the detection but also the classification of small drones has become important. Many recent studies have applied an approach to utilize the micro-Doppler signature (MDS) for the small drone classification by using frequency modulated continuous wave (FMCW) radars. In this letter, we propose a novel method to extract the MDS images of the small drones with the FMCW radar. Moreover, we propose a light convolutional neural network (CNN) whose structure is straightforward, and the number of parameters is quite small for fast classification. The proposed method contributes to increasing the classification accuracy by improving the quality of MDS images. We classified the small drones with the MDS images extracted by the conventional method and the proposed method through the proposed CNN. The experimental results showed that the total classification accuracy was increased by 10.00 % due to the proposed method. The total classification accuracy was recorded at 97.14 % with the proposed MDS extraction method and the proposed light CNN.

eess.SP↗

arXiv2020

Advanced Stationary Point Concentration Technique for Leakage Mitigation and Small Drone Detection with FMCW Radar

As the threats of small drones have grown, developing radars to detect the small drones has become an important issue. In earlier studies, we proposed the stationary point concentration (SPC) technique for the small drone detection with frequency-modulated continuous-wave (FMCW) radar. The SPC technique is a new approach to mitigate the leakage that is an inherent problem in the FMCW radar. The SPC technique improves the signal-to-noise ratio of the small drones by reducing the noise floor and provides accurate distance and velocity information of the small drones. However, the SPC technique has shortcomings in realizing it. In this paper, we present the drawbacks of the SPC technique clearly and propose an advanced SPC (A-SPC) technique. The A-SPC technique can overcome the drawbacks of the SPC technique while taking all the good effects of the SPC technique. The experimental results verify the proposed A-SPC technique and show its robustness and usefulness.

eess.SP↗

arXiv2018

Leakage Mitigation and Internal Delay Compensation in FMCW Radar for Small Drone Detection

One of the notorious problems of frequency modulated continuous-wave (FMCW) radar is leakage between the transmitter and the receiver. The phase noise of the leakage is expressed as a skirt around the leakage signal on power spectrum. It causes the deterioration of the dynamic range, especially, in the near-distance region. Therefore, although FMCW radar has an advantage over pulse radar in terms of near-distance target detection due to its way of operation, the advantage of FMCW radar can be lost because of the leakage. Another problem of FMCW radar is internal delay in the radar system. It leads to the decrease of the maximum detectable range. In this paper, a novel down-conversion technique which resolves these problems is proposed. Detailed theory and procedures to implement the proposed technique are explained. Then, performances of it are verified with the experiment results. The proposed technique can be implemented through frequency planning and digital signal processing without additional parts. The results show that the proposed technique lowers the noise floor about 7.0 dB in the near-distance region and 2.1 dB even in the far-distance region. Also, the results demonstrate the proposed technique recover the reduced maximum detectable range by compensating the internal delay.

eess.SP↗