• Title/Summary/Keyword: radar data

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An Artificial Intelligence Research for Maritime Targets Identification based on ISAR Images (ISAR 영상 기반 해상표적 식별을 위한 인공지능 연구)

  • Kim, Kitae;Lim, Yojoon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.2
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    • pp.12-19
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    • 2022
  • Artificial intelligence is driving the Fourth Industrial Revolution and is in the spotlight as a general-purpose technology. As the data collection from the battlefield increases rapidly, the need to us artificial intelligence is increasing in the military, but it is still in its early stages. In order to identify maritime targets, Republic of Korea navy acquires images by ISAR(Inverse Synthetic Aperture Radar) of maritime patrol aircraft, and humans make out them. The radar image is displayed by synthesizing signals reflected from the target after radiating radar waves. In addition, day/night and all-weather observations are possible. In this study, an artificial intelligence is used to identify maritime targets based on radar images. Data of radar images of 24 maritime targets in Republic of Korea and North Korea acquired by ISAR were pre-processed, and an artificial intelligence algorithm(ResNet-50) was applied. The accuracy of maritime targets identification showed about 99%. Out of the 81 warship types, 75 types took less than 5 seconds, and 6 types took 15 to 163 seconds.

Quality Enhancement of MIROS Wave Radar Data at Ieodo Ocean Research Station Using ANN

  • Donghyun Park;Kideok Do;Miyoung Yun;Jin-Yong Jeong
    • Journal of Ocean Engineering and Technology
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    • v.38 no.3
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    • pp.103-114
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    • 2024
  • Remote sensing wave observation data are crucial when analyzing ocean waves, the main external force of coastal disasters. Nevertheless, it has limitations in accuracy when used in low-wind environments. Therefore, this study collected the raw data from MIROS Wave and Current Radar (MWR) and wave radar at the Ieodo Ocean Research Station (IORS) and applied the optimal filter by combining filters provided by MIROS software. The data were validated by a comparison with South Jeju ocean buoy data. The results showed it maintained accuracy for significant wave height, but errors were observed in significant wave periods and extreme waves. Hence, this study used an artificial neural network (ANN) to improve these errors. The ANN was generalized by separating the data into training and test datasets through stratified sampling, and the optimal model structure was derived by adjusting the hyperparameters. The application of ANN effectively improved the accuracy in significant wave periods and high wave conditions. Consequently, this study reproduced past wave data by enhancing the reliability of the MWR, contributing to understanding wave generation and propagation in storm conditions, and improving the accuracy of wave prediction. On the other hand, errors persisted under high wave conditions because of wave shadow effects, necessitating more data collection and future research.

Fast Coordinate Conversion Method for Real-time Weather Radar Data Processing

  • Jang, Bong-Joo;Lim, Sanghun;Kim, Won
    • Journal of Multimedia Information System
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    • v.5 no.1
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    • pp.1-8
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    • 2018
  • The coordinate system conversion of weather radar data is a basic and important process because it can be a factor to measure the accuracy of radar precipitation rate by comparison with the ground rain gauge. We proposed a real-time coordinate system conversion method that combines the advantages of the interpolation masks of SPRINT and REORDER to use tables of predetermined radar samples for each interpolated object coordinate and also distance weights for each precomputed sample. Experimental results show that the proposed method improves the computation speed more than 20~30 times compared with the conventional method and shows that the deterioration of image quality is hardly ignored.

Target-to-Clutter Ratio Enhancement of Images in Through-the-Wall Radar Using a Radiation Pattern-Based Delayed-Sum Algorithm

  • Lim, Youngjoon;Nam, Sangwook
    • Journal of electromagnetic engineering and science
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    • v.14 no.4
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    • pp.405-410
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    • 2014
  • In this paper, we compare the quality of images reconstructed by a conventional delayed-sum (DS) algorithm and radiation pattern-based DS algorithm. In order to evaluate the quality of images, we apply the target-to-clutter ratio (TCR), which is commonly used in synthetic aperture radar (SAR) image assessment. The radiation pattern-based DS algorithm enhances the TCR of the image by focusing the target signals and preventing contamination of the radar scene. We first consider synthetic data obtained through GprMax2D/3D, a finite-difference time-domain (FDTD) forward solver. Experimental data of a 2-GHz bandwidth stepped-frequency signal are collected using a vector network analyzer (VNA) in an anechoic chamber setup. The radiation pattern-based DS algorithm shows a 6.7-dB higher TCR compared to the conventional DS algorithm.

Displaying Multiple Maritime Surveillance Radar Data (다수의 해안감시 레이더자료 전시 기법)

  • Hwang, Gyu-Hwan;Kim, Moon-Ki;Kang, Do-Keun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.7
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    • pp.1041-1048
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    • 2012
  • We display important test information from radar, telemetry in real time for monitoring and control of guided missile flight test. Clearing test area is the most important thing for safety. Thus, we have to constantly monitor and control ships around the test area. Several maritime surveillance radars are deployed around the test area for that purpose. However, multiple points are displayed for the same target when using multiple surveillance radars and this confuses the test personnel during the mission. In this paper, we suggested a method to solve this problem by analyzing error factor of surveillance radar and comparing the correlation of each radar data.

A General Radar Scattering Model for Earth Surfaces

  • Jung, Goo-Jun;Lee, Sung-Hwa;Oh, Yi-Sok
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.41-43
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    • 2003
  • A radar scattering model is developed based on an empirical rough surface scattering model, the radiative transfer model (RTM), a numerical simulation algorithm of radar scattering from particles, and experimental data obtained by ground-based scatterometers and SAR systems. At first, the scattering matrices of scattering particles such as a leaf, a branch, and a trunk, have been modeled using the physical optics (PO) model and the numerical full-wave analysis. Then, radar scattering from a group of mixed particles has been modeled using the RTM, which leads to a general scattering model for earth surfaces. Finally, the scattering model has been verified with the experimental data obtained by scatterometers and SAR systems.

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Correction of Radar Reflectivity over Beam Blocking Area by Accumulated Radar Reflectivity (레이더 반사도 누적 방법을 이용한 지형에 의한 부분차폐영역의 레이더 반사도 보정)

  • Park, Sung-Hwan;Jung, Sung-Hwa;Lee, Jung-Hoon;Kim, Kyeong-Eak
    • Journal of Korea Water Resources Association
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    • v.42 no.8
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    • pp.607-617
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    • 2009
  • Radar beam blocking which is partially or entirely interrupted by obstacles like a mountain causes underestimation of the rainfall. In this paper, partially blocked radar reflectivity is retrieved using the ARM(Accumulated Reflectivity Map). ARM is made by accumulation of the radar reflectivity and very useful product to analyze the beam blockage. The blockage correcting map could be obtained by assuming the spatially uniform reflectivity field in the ARM. This method is applied to the cases of typhoon and Changma, and we obtain the MFE(Mean Fractional Error) from two radar data, the one is objective radar data which is affected by blockage and the other is comparative radar data which is not affected by blockage. Before blocking correction, MFE is 20-35%. However, after correction, MFE decreases to 7-10%.

A spatiotemporal adjustment of precipitation using radar data and AWS data (레이더와 지상관측소 강우자료를 이용한 시공간 강우 조정 모형)

  • Shin, Tae Sung;Lee, Gyuwon;Kim, Yongku
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.39-47
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    • 2017
  • Precipitation is an important component for hydrological and water control study. In general, AWS data provides more accurate but low dense information for precipitation while radar data gives less accurate but high dense information. The objective of this study is to construct adjusted precipitation field based on hierarchical spatial model combining radar data and AWS data. Here, we consider a Bayesian hierarchical model with spatial structure for hourly accumulated precipitation. In addition, we also consider a redistribution of hourly precipitation to 2.5 minute precipitation. Through real data analysis, it has been shown that the proposed approach provides more reasonable precipitation field.

Quality Enhancement of Wave Data Observed by Radar at the Socheongcho Ocean Research Station (소청초 종합해양과학기지 Radar 파랑 관측 데이터의 신뢰도 향상)

  • Min, Yongchim;Jeong, JinYong;Shim, Jae-Seol;Do, Kideok
    • Journal of Coastal Disaster Prevention
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    • v.4 no.4
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    • pp.189-196
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    • 2017
  • Ocean Research Stations (ORSs) is the ocean platform type observation towers and measured oceanic, atmospheric and environmental data. These station located on the offshore area far from the coast, so they can produce the data without land effect. This study focused to improve the wave data quality of ORS station. The wave observations at ORSs are used by the C-band (5.8 GHz, 5.17 cm) MIROS Wave and Current Radar (MWR). MWR is convenient to maintenance and produce reliability wave data under bad weather conditions. MWR measured significant wave height, peak wave period, peak wave direction and 2D wave spectrum, so it's can provide wave information for researchers and engineers. In order to improve the reliability of MWR wave data, Datawell Waverider Buoy was installed near the one ORS (Socheoncho station) during 7 months and validate the wave data of MWR. This study found that the wave radar tend to be overestimate the low wave height under wind condition. Firstly, this study carried out the wave Quality Control (QC) using wind data, however the quality of wave data was limited. So, this study applied the four filters (Correlation Check, Direction Filter, Reduce White Noise and Phillips Check) of MWR operating software and find that the filters effectively improve the wave data quality. After applying 3 effective filters in combination, the RMSE of significant wave height decreased from 0.81m to 0.23m, by 0.58m and Correlation increased from 0.66 to 0.96, by 0.32, so the reliability of MWR significant wave height was significantly improved.

Tracking of ARPA Radar Signals Based on UK-PDAF and Fusion with AIS Data

  • Chan Woo Han;Sung Wook Lee;Eun Seok Jin
    • Journal of Ocean Engineering and Technology
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    • v.37 no.1
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    • pp.38-48
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    • 2023
  • To maintain the existing systems of ships and introduce autonomous operation technology, it is necessary to improve situational awareness through the sensor fusion of the automatic identification system (AIS) and automatic radar plotting aid (ARPA), which are installed sensors. This study proposes an algorithm for determining whether AIS and ARPA signals are sent to the same ship in real time. To minimize the number of errors caused by the time series and abnormal phenomena of heterogeneous signals, a tracking method based on the combination of the unscented Kalman filter and probabilistic data association filter is performed on ARPA radar signals, and a position prediction method is applied to AIS signals. Especially, the proposed algorithm determines whether the signal is for the same vessel by comparing motion-related components among data of heterogeneous signals to which the corresponding method is applied. Finally, a measurement test is conducted on a training ship. In this process, the proposed algorithm is validated using the AIS and ARPA signal data received by the voyage data recorder for the same ship. In addition, the proposed algorithm is verified by comparing the test results with those obtained from raw data. Therefore, it is recommended to use a sensor fusion algorithm that considers the characteristics of sensors to improve the situational awareness accuracy of existing ship systems.