• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.5
• /
• pp.94-104
• /
• 2000

The accuracy and reliability of the target tracking is very critical issue in the design of automotive collision warning radar A significant problem in multi-target tracking (MTT) is the target-to-measurement data association If an incorrect measurement is associated with a target, the target could diverge the track and be prematurely terminated or cause other targets to also diverge the track. Most methods for target-to-measurement data association tend to coalesce neighboring targets Therefore, many algorithms have been developed to solve this data association problem. In this paper, a new multi-target data association method based on order statistics is described The new approaches. called the order statistics probabilistic data association (OSPDA) and the order statistics joint probabilistic data association (OSJPDA), are formulated using the association probabilities of the probabilistic data association (PDA) and the joint probabilistic data association (JPDA) filters, respectively Using the decision logic. an optimal or near optimal target-to-measurement data association is made A computer simulation of the proposed method in a heavy cluttered condition is given, including a comparison With the nearest-neighbor CNN). the PDA, and the JPDA filters, Simulation results show that the performances of the OSPDA filter and the OSJPDA filter are superior to those of the PDA filter and the JPDA filter in terms of tracking accuracy about 18% and 19%, respectively In addition, the proposed method is implemented using a developed digital signal processing (DSP) board which can be interfaced with the engine control unit (ECU) of car engine and with the d?xer through the controller area network (CAN)

• Journal of Internet Computing and Services
• /
• v.21 no.4
• /
• pp.117-126
• /
• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Journal of KIISE
• /
• v.44 no.2
• /
• pp.213-222
• /
• 2017

The Internet of Things (IoT) technology is rapidly developing in recent years, and is applicable to various fields. A smart factory is one wherein all the components are organically connected to each other via a WSN, using an intelligent operating system and the IoT. A smart factory technology is used for flexible process automation and custom manufacturing, and hence needs adaptive network management for frequent network fluctuations. Moreover, ensuring the timeliness of the data collected through sensor nodes is crucial. In order to ensure network timeliness, the power consumption for information exchange increases. In this paper, we propose an IEEE 802.15.4e DSME-based distributed scheduling algorithm for mobility support, and we evaluate various performance metrics. The proposed algorithm adaptively assigns communication slots by analyzing the network traffic of each node, and improves the network reliability and timeliness. The experimental results indicate that the throughput of the DSME MAC protocol is better than the IEEE 802.15.4e TSCH and the legacy slotted CSMA/CA in large networks with more than 30 nodes. Also, the proposed algorithm improves the throughput by 15%, higher than other MACs including the original DSME. Experimentally, we confirm that the algorithm reduces power consumption by improving the availability of communication slots. The proposed algorithm improves the power consumption by 40%, higher than other MACs.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.17 no.8 s.111
• /
• pp.773-787
• /
• 2006

An airborne radar is an essential aviation electronic system for the aircraft to perform various civil and/or military missions in all weather environments. This paper presents the design, development, and test results of the multi-mode X-band pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRUs(Line-Replacement Unit), which include antenna unit, transmitter and receiver unit, radar signal & data processing unit and display Unit. The developed core technologies include the planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, MTI, DSP based Doppler FFT filter, adaptive CFAR, moving clutter compensation, platform motion stabilizer, and tracking capability. The design performance of the developed radar system is verified through various ground fixed and moving vehicle test as well as helicopter-borne field tests including MTD(Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.45 no.9
• /
• pp.794-806
• /
• 2017

It is essential to protect the national space assets and space environment safely as a space development country from the continuously increasing space debris. And Active Debris Removal(ADR) is the most active way to solve this problem. In this paper, we studied the Artificial Neural Network(ANN) for a stable recognition model of vision-based space debris tracking system. We obtained the simulated image of the space environment by the KARICAT which is the ground-based space debris clearing satellite testbed developed by the Korea Aerospace Research Institute, and created the vector which encodes structure and color-based features of each object after image segmentation by depth discontinuity. The Feature Vector consists of 3D surface area, principle vector of point cloud, 2D shape and color information. We designed artificial neural network model based on the separated Feature Vector. In order to improve the performance of the artificial neural network, the model is divided according to the categories of the input feature vectors, and the ensemble technique is applied to each model. As a result, we confirmed the performance improvement of recognition model by ensemble technique.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.75-84
• /
• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.8
• /
• pp.74-85
• /
• 2015

PCI Express is a well-known and widely used de-facto system bus standard for connecting among a processor and IO devices. PCI Express is originated from old PCI standard, and its most of applications are limited to be used within a PC or server system. But, because of its fast speed, low power consumption, and good protocol efficiency, it is considered as one of a good candidate for an alternate system interconnect for many years. In this paper, we present design, implementation and early evaluation of an alternate system interconnect by utilizing PCI Express. The developed alternate system interconnect using PCI Express (named PCIeLINK) utilizes non-transparent bridging (NTB) technic which generally used in fail-over system in PCI and PCI Express. By using NTB technic, PCI Express device can be extended to outside of a system without electrical and logical problems arising during system boot and enumeration. To build up an alternate system interconnect, we designed and implemented a network interface card having multiple PCI Express ${\times}4$ connections (theoretically 20 Gbps) and tested, The early test results revealed that an ${\times}4$ port in the card showed 8.6 Gbps peak performance for bulk transmission and 5.1 Gbps peak for normal TCP/IP transfer.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.34 no.5
• /
• pp.491-498
• /
• 2010

Humidification of PEM fuel cells is necessary for enhancing their performance and lifetime. In this study, a humidification system was designed and tested; the system includes an air-supply tube (inner diameter: 75 mm) through which a nozzle can be directly inserted and a cyclonic separator for the removal of water droplets. Three types of nozzles were employed to study the influence of injection pressure, air flow rate, and spray direction on the humidification performance. To evaluate the humidification performance, the concept of humidification efficiency was defined. In the absence of an external heat source, latent heat for evaporation will be supplied by the own enthalpies of water and air. Thus, the amount of water sprayed from the nozzle is the most critical factor affecting the humidification efficiency. Water droplets were efficiently removed by a cyclonic separator, but re-entrainment occurred at high air flow rates. The absolute humidity and humidification efficiency were $21.29\;kJ/kg_{da}$ and 86.57%, respectively, under the following conditions: nozzle type PJ24; spray direction angle $90^{\circ}$; injection pressure 1200 kPa; air flow rate 6000 Nlpm.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.6
• /
• pp.10-21
• /
• 2010

In the cluster-tree network which covers wide area network and has many nodes for monitoring purpose traffic is concentrated around the sink. There are long transmit delay and high data loss due to the intensive traffic when IEEE 802.15.4 is adapted to the cluster-tree network. In this paper we propose Dynamic Channel Allocation algorithm which dynamically allocates channels to increase the channel usage and the transmission success rate. To evaluate the performance of DCA, we assumed the monitoring network that consists of a cluster-tree in which sensing data is transmitted to the sink. Analysis uses the traffic data which is generated around the sink. As a result, DCA is superior when much traffic is generated. During the experiment assuming the least amount of traffic, IEEE 802.15.4, has the minimum length of active period and 90% data transmission success rate. However DCA maintains 11.8ms of active period length and results in 98.9% data transmission success rate.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.1
• /
• pp.36-41
• /
• 2011

Configuration space(C-space) including configuration obstacle(C-obstacle) is one of the most important concepts in mobile robot path planning. Using C-space and C-obstacles, the robot with different shapes and moving mechanisms can be considered as a point in the C-space. And, as a result, the collision-free path for the robot can be easily achieved. To make C-space including C-obstacle, many researchers used circular approximation method for the efficient caluculation time. This method can help us to save our time by approximating the shape of a robot as the minimum sized circle which can cover all the area of robot. But, by using the circle larger than the robot, more space are considered as the part of robot and, as a result, some obstacles which are very near each other may be considered as a combined one obstacle. To solve this problem, multi-level configuration space is proposed by this paper. This multi-level method also use the circular approximation method as the initial step. But, after finding the initial path, it will check how many obstacles are combined. And then, for each combined obstacle, more accurate C-space generation will be continued. To check the efficiency of the proposed algorithm, time for c-space generation are compared with the well-known accurate C-space generation method using various types of robot shape.