• International Journal of Control, Automation, and Systems
• /
• v.6 no.5
• /
• pp.767-775
• /
• 2008

Methods used for exploring marine resources and spaces include positioning a probe under water and then recalling it after a specified time. Hydro-acoustic Releasers are commonly used for positioning and retrieving of such exploration equipment. The most important factor in this kind of system is the reliability for recalling the instruments. The frequently used ultrasonic signal detection method can detect ultrasonic signals using a fixed comparator, but because of increased rates of errors due to outside interferences, information is repetitively acquired. This study presents an effective ultrasonic signal detection algorithm using the characteristics of a resonance and adaptive comparator Combined with the FSK+ASK modulator. As a result, approximately 8.8% of ultrasonic wave communication errors caused by background noise and transmission losses were reduced for effectively detecting ultrasonic waves. Furthermore, the resonance circuit's quality factor was enhanced (Q = 120 to 160). As such, the bias voltage of the transistor (Vb= 3.3 to 6.8V) was increased thereby enhancing the frequency's selectivity.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.10 no.2
• /
• pp.101-108
• /
• 2015

In this paper, a robust traffic light detection method is proposed by using vision sensor and DGPS(Difference Global Positioning System). The conventional vision-based detection methods are very sensitive to illumination change, for instance, low visibility at night time or highly reflection by bright light. To solve these limitations in visual sensor, DGPS is incorporated to determine the location and shape of traffic lights which are available from traffic light database. Furthermore the geometric relationship between traffic light and vision sensor is used to locate the traffic light in the image by using DGPS information. The empirical results show that the proposed method improves by 51% in detection rate for night time with marginal improvement in daytime environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.2
• /
• pp.723-743
• /
• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.1
• /
• pp.71-78
• /
• 2024

In indoor environments, since global positioning system (GPS) signals can be blocked by obstacles, such as building structure. the performance of GPS-based positioning methods can be degraded because of the loss of GPS signals. To solve this problem, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope, accelerometer, and magnetometer, have been proposed to enhance the positioning accuracy in indoor environments. IMU-based positioning methods can estimate the location of the user by calculating the velocity and heading angle of the user without the help of GPS. However, low-cost MEMS IMUs may lead to drift error and large bias. In addition, positioning errors in IMU-based positioning approaches can be caused by the irrelevant motion of the pedestrian. In this study, we propose an enhanced indoor positioning method that provides more reliable localization results by using the camera, light detection and right (LiDAR), and ARKit framework on the iPhone. Through reliable positioning results and augmented reality (AR) experiences, our indoor positioning system can provide indoor space guidance services.

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.671-679
• /
• 2011

Now, for the continuous location detection of train, The method which the moving distance and speed of vehicles are detected using an odometer mounted within railway vehicle, is used in railway domain generally. There are some problems that the train's positioning errors are accumulated as the moving distances increase. To solve this problems, The Train-borne Positioning System is being developed at Korea Railroad Research Institute. It is required to evaluate exactly a positioning performance of The Train-borne Positioning System for improvement of performance. Therefore, in this paper, we review the CDGPS methods to acquire reference position for performance evaluation of Train-borne Positioning System and verify the accuracy of the reference position through the static test and the vehicle test.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.10
• /
• pp.991-996
• /
• 2010

In this paper, a new indoor positioning system based on incident angle measurement of infrared sensor has been suggested. Though there have been various researches on indoor positioning systems using vision sensor or ultrasonic sensor, they have not only advantages, but also disadvantages. In a new positioning system, there are three infrared emitters on fixed known positions. An incident angle sensor measures the angle differences between each two emitters. Mathematical problems to determine the position with angle differences and position information of emitters has been solved. Simulations and experiments have been implemented to show the performance of this new positioning system. The results of simulation were good. Since there existed problems of noise and signal conditioning, the experimented has been implemented in limited area. But the results were acceptable. This new positioning method can be applied to any indoor systems that need absolute position information.

• ETRI Journal
• /
• v.40 no.1
• /
• pp.101-110
• /
• 2018

In wireless positioning systems using range measurements non-line-of-sight (NLOS) links cause estimation errors. Several studies have attempted to improve the positioning performance by mitigating these NLOS errors. These studies, however, have focused on the performance of a dataset consisting of three or more links. Therefore, measurement errors induced by links are averaged, and a reliable link is not fully utilized in the dataset. This paper proposes a Link Reliability based on Range Measurement (LRRM) scheme, which specifies the relative reliability of each link using residuals. The link reliability becomes the input to a Link Residual Weighting (LRW) scheme, which is also proposed as a weighted positioning scheme. Moreover, LRRM and LRW constitute new turbo positioning, where the estimation errors are reduced considerably by iterative updates.

• Journal of Digital Convergence
• /
• v.11 no.11
• /
• pp.321-326
• /
• 2013

GPS reception rate in the room has less features. To overcome these shortcomings, the AP positioning using RSS technology research and development is being done. If we use positioning technology and signal strength in order to detect a obstacles, it has the advantage of no-cost in terms of utilization and efficiency when we do this applied service. In this paper, We are presented method to determine the obstacles using RSS(Received Signal Strength).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10A
• /
• pp.784-795
• /
• 2009

An accurate positioning estimation in the wireless sensor networks (WSN) is very important in which each sensor node is aware of neighbor conditions. The multi-hop positioning estimation technique is considered as one of the suitable techniques for the WSN with many low power devices. However geographical holes, where there is no sensor node, may severely decrease the positioning accuracy so that the positioning error can be beyond the tolerable range. Therefore in this paper, we analyze error factors of DV-hop and hole effect to obtain node's accurate position. The proposed methods include boundary node detection, distance level adjustment, and unreliable anchor elimination. The simulation results show that the proposed method can achieve higher positioning accuracy using the hole detection and enhanced distance calculation methods compared with the conventional DV-hop.

• Imaging Science in Dentistry
• /
• v.48 no.4
• /
• pp.245-254
• /
• 2018

Purpose: To assess the effects of object position in the field of view (FOV) and application of a metal artifact reduction (MAR) algorithm on the diagnostic accuracy of cone-beam computed tomography (CBCT) for the detection of vertical root fractures(VRFs). Materials and Methods: Sixty human single-canal premolars received root canal treatment. VRFs were induced in 30 endodontically treated teeth. The teeth were then divided into 4 groups, with 2 groups receiving metal posts and the remaining 2 only having an empty post space. The roots from different groups were mounted in a phantom made of cow rib bone, and CBCT scans were obtained for the 4 different groups. Three observers evaluated the images independently. Results: The highest frequency of correct diagnoses of VRFs was obtained with the object positioned centrally in the FOV, using the MAR algorithm. Peripheral positioning of the object without the MAR algorithm yielded the highest sensitivity for the first observer (66.7%). For the second and third observers, a central position improved sensitivity, with or without the MAR algorithm. In the presence of metal posts, central positioning of the object in the FOV significantly increased the diagnostic sensitivity and accuracy compared to peripheral positioning. Conclusion: Diagnostic accuracy was higher with central positioning than with peripheral positioning, irrespective of whether the MAR algorithm was applied. However, the effect of the MAR algorithm was more significant with central positioning than with peripheral positioning of the object in the FOV. The clinical experience and expertise of the observers may serve as a confounder in this respect.