• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.83-90
• /
• 2020

A commercial flow measurement radar sensor estimates a quantity of flowed water using surface flow rate. In this way, the amount of water flowing per unit time cannot be measured accurately because of using an estimation result and it can't response environmental changes. For more accurate flow measurements we need width of waterway, water level and distance that water moved per unit time. Commonly two sensors are used to measure water level and flow rate. In this paper, we propose a method to simultaneously measure the water level and surface flow velocity using a single FMCW radar sensor and design the transmission waveform. In order to verify the waveform design, received signal is modelled based on transmission waveform. In addition, we consider phenomenons and problems that may occur in signal processing.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.22 no.3
• /
• pp.123-129
• /
• 2014

SCC (Smart Cruise Control) and AEBS (Autonomous Emergency Braking System) are using various types of sensors data, so it is important to consider about sensor data reliability. In this paper, data from radar and vision sensor is fused by applying a Bayesian sensor fusion technique to improve the reliability of sensors data. Then, it presents a sensor fusion verification tool developed to monitor acquired sensors data and to verify sensor fusion results, efficiently. A parallel computing method was applied to reduce verification time and a series of simulation results of this method are discussed in detail.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.8
• /
• pp.783-789
• /
• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• Proceedings of the KSR Conference
• /
• 1999.05a
• /
• pp.307-314
• /
• 1999

The potential use of ranging sensors for reducing the occurrence of accidents in real environment is explored by many companies and laboratories. Most of the sensors under investigation utilize the FMCW(Frequency Modulated Continuous Wave) waveforms. The automotive environment presents to the FMCW radar sensor a multitude of moving and fixed targets and the sensor must detect and track only the targets which may pose a threat of collision or passengers accident. The sensor must function accurately in the presence of background echoes generated by moving and fixed targets, ground reflections, atmospheric noises, including rains, fog, and, snow and noise generated within the receiver. False detection of the desired target in this environment may issue false alarms. That may be dangerous to the passenger and the vehicle. A high false alarm rate is totally unacceptable. The false alarm mechanism consists of noise peaks, crossing the threshold and the undesired response of the system to off lane targets which are not potentially hazardous to the radar equipped vehicle. This paper presents an improve technique safety performance for driver-less operation using FMCW radar sensors.

• Proceedings of the KIEE Conference
• /
• 2000.07b
• /
• pp.1368-1370
• /
• 2000

The automotive environment presents to the FMCW radar sensor a multitude of moving and fixed targets and the sensor must detect and track only the targets which may pose a threat of collision or passengers accident. The sensor must function accurately in the presence of background echoes generated by moving and fixed targets, ground reflections, atmospheric noises, including rains, fog, and, snow and noise generated within the receiver. False detection of the desired target in this environment may issue false alarms. That may be dangerous to the passenger and the vehicle. A high false alarm rate is totally unacceptable. The false alarm mechanism consists of noise peaks, crossing the threshold and the undesired response of the system to off lane targets which are not potentially hazardous to the radar equipped vehicle. This paper presents an improve technique safety performance for driver-less operation using FMCW radar sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.552-554
• /
• 2021

We propose a fall recognition system using a deep learning algorithm using motion data acquired by a Doppler radar sensor. Among the deep learning algorithms, an RNN that has an advantage in time series data is used to recognize falls. The fall data of the Doppler radar sensor has a temporal characteristic as time series data, and the structure of the RNN is sequenced because the result only determines whether a fall or not It is designed in a structure that outputs a fixed size to the input.

• Journal of IKEEE
• /
• v.24 no.1
• /
• pp.232-237
• /
• 2020

In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.3
• /
• pp.307-315
• /
• 2014

Existing level crossing obstruction detecting system occurs section of not detecting an obstruction by line detecting. Due to installation of decentralized equipment, it has become a problem in terms of safety and maintenance costs. accordingly, We have developed level crossing obstruction detecting system using laser radar sensor in order to solve these problems. In this paper, Describe results of functional test for the developed level crossing obstruction detecting system. functional tests are normal operation test(control unit and sensor unit) and test to display the fault information in event of a failure(control unit and sensor unit). It was confirmed that it works properly all according to functional test of level crossing obstruction detecting system using laser radar sensor.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.7
• /
• pp.1009-1014
• /
• 2018

In this paper, we have designed and implemented a system that utilizes a radar sensor to measure distance between a sensor and objects. The sensor module creates raw data and uploads the data on the distance measuring system, which detects the presence of objects by using standard deviation and average filters. The experiment found that an algorithm using average filters measured people with error rates of up to 9.7 meters and a maximum error rate of 0.02 meters or less. While in an algorithm using standard deviations, it was found that an object is measured at an error rate of up to a maximum distance of 9.7 meters and a maximum error rate of 0.15 meters. Therefore, we have concluded that if a distance was measured by using a radar sensor, algorithms using average filters resulted in a higher accuracy than standard deviations filters.

• International Journal of Safety
• /
• v.9 no.2
• /
• pp.35-40
• /
• 2010

Many casualties are being occurred due to many misses the railway platform, and the accident occurrence is being increased. Recently in Korea, efforts to prevent casualties fundamentally are being made by installing and operating the PSD(Passenger Screen Door) as to prevent these casualties of passengers. However, in case of the PSD system, although it can solve the problem of public casualties at platform fundamentally, it is impossible to install it at whole railway platforms. This paper proposes the safety equipment using LaserRadar sensor for the prevention against casualties of passengers at platform. The safety equipment using novel sensor is the safety equipment making an approaching train stopped if the falling object is a person by detecting the obstacle at platform, and it has the merit possible to apply it to platform since it may detect accurately under ambient environmental elements such as the snow, rain and yellow dust, etc. also. We manufactured a prototype of the safety equipment to reduce public casualties at platform by using LaserRadar sensor and carried out its performance test, and the result is presented in this paper.