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

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3434-3439
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• 2015

As a criterion of information theoretic learning, the Euclidean distance (ED) of two error probability distribution functions (minimum ED of error, MEDE) has been adopted in nonlinear (decision feedback, DF) supervised equalizer algorithms and has shown significantly improved performance in severe channel distortion and impulsive noise environments. However, the MEDE-DF algorithm has the problem of heavy computational complexity. In this paper, the recursive ED for MEDE-DF algorithm is derived first, and then the feed-forward and feedback section gradients for weight update are estimated recursively. To prove the effectiveness of the recursive gradient estimation for the MEDE-DF algorithm, the number of multiplications are compared and MSE performance in impulsive noise and underwater communication environments is compared through computer simulation. The ratio of the number of multiplications between the proposed DF and the conventional MEDE-DF algorithm is revealed to be $2(9N+4):2(3N^2+3N)$ for the sample size N with the same MSE learning performance in the impulsive noise and underwater channel environment.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.115-122
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• 2024

Multi-object tracking (MOT) is a vital component in understanding the surrounding environments. Previous research has demonstrated that MOT can successfully detect and track surrounding objects. Nonetheless, inaccurate classification of the tracking objects remains a challenge that needs to be solved. When an object approaching from a distance is recognized, not only detection and tracking but also classification to determine the level of risk must be performed. However, considering the erroneous classification results obtained from the detection as the track class can lead to performance degradation problems. In this paper, we discuss the limitations of classification in tracking under the classification uncertainty of the detector. To address this problem, a class update module is proposed, which leverages the class uncertainty estimation of the detector to mitigate the classification error of the tracker. We evaluated our approach on the VisDrone-MOT2021 dataset,which includes multi-class and uncertain far-distance object tracking. We show that our method has low certainty at a distant object, and quickly classifies the class as the object approaches and the level of certainty increases.In this manner, our method outperforms previous approaches across different detectors. In particular, the You Only Look Once (YOLO)v8 detector shows a notable enhancement of 4.33 multi-object tracking accuracy (MOTA) in comparison to the previous state-of-the-art method. This intuitive insight improves MOT to track approaching objects from a distance and quickly classify them.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.370-378
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• 2007

In wireless sensor networks (WSNs), thousands of sensors are often deployed in a hostile environment. In such an environment, WSNs can be applied to various applications by using the absolute or relative location information of the sensors. Until now, the time-of-arrival (TOA) based localization method has been considered most accurate. In the TOA method, however, inaccuracy in distance estimation is caused by clock drift and clock skew between sensor nodes. To solve this problem, several numbers of periodic time synchronization methods were suggested while these methods introduced overheads to the packet traffic. In this paper, we propose a new localization method based on multiple round-trip times (RTOA) of a signal which gives more accurate distance and location estimation even in the presence of clock skew between sensor nodes. Our experimental results show that the Proposed RTOA method gives up to 93% more accurate location estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.243-257
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• 2010

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.5
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• pp.461-470
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• 2018

In this study, the leak signal was measured by using an accelerometer to analyze the basic data and methodology for the development of the leak point estimation method in the water supply pipe. The measured results were analyzed by frequency analysis and cross-correlation analysis for leakage signals, and the error range was compared and analyzed with the actual leak point distance. As a result, it was confirmed that the vibration intensity due to leakage from the water leakage point was attenuated according to the distance. In the case of the ductile iron casting used in the experiment, the intensity of the signal at the 945 Hz, 1,500 Hz, 2,300 Hz band was increased with the change of the pressure in the pipe at 4mm of leakage hole. Also, it was confirmed that as the water pressure increases, the intensity of the leak signal increases but the similarity of the signal decreases. The results of this study confirm that the accelerometer sensor can be used efficiently for leak detection and it can be used as a basic data for the analysis for the development of leak point estimation method in the future.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.87-96
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• 2010

The impact speed estimation practice used in the car-bicycle accident analysis practice in Korea was mainly dependent on foreign study results which were tested with limited speed ranges and vehicle types, but the characteristics of roadway, human body, and vehicle performance were quite different. This study developed an impact speed estimation model using the car-bicycle accident field data. For this, a regression analysis was performed using the impact speed and bicycle throw distance collected from 23 real accident data, and statistical test was also conducted. For the verification of the induced model, the impact speeds derived from the model were compared with the true impact speeds estimated from skid marks of two accident cases. The result showed that the two speeds were very close to each other. It is believed that the model could be included in the car-bicycle accident analysis practice.

• Journal of Radiation Protection and Research
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• v.28 no.1
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• pp.59-63
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• 2003

Purpose : Measurement of transmission dose is useful for in vivo dosimetry of QA purpose. The objective of this study is to develope an algorithm for estimation of tumor dose using measured transmission dose for open radiation field. Materials and Methods : Transmission dose was measured with various field size (FS), phantom thickness (Tp), and phantom chamber distance (PCD) with a acrylic phantom for 6 MV and 10 MV X-ray Source to chamber distance (SCD) was set to 150 cm. Measurement was conducted with a 0.6 cc Farmer type ion chamber. Using measured data and regression analysis, an algorithm was developed for estimation of expected reading of transmission dose. Accuracy of the algorithm was tested with flat solid phantom with various settings. Results : The algorithm consisted of quadratic function of log(A/P) (where A/P is area-perimeter ratio) and tertiary function of PCD. The algorithm could estimate dose with very high accuracy for open square field, with errors within ${\pm}0.5%$. For elongated radiation field, the errors were limited to ${\pm}1.0%$. Conclusion : The developed algorithm can accurately estimate the transmission dose in open radiation fields with various treatment settings.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.452-457
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• 2016

In this paper, we propose a taxi safety support system using the beacon device to reduce the anxiety and increase the satisfaction of taxi passengers. At first, we design a USB-type low power beacon device that can be easily installed inside a taxi and propose a distance and estimation method using beacon signal strength. Mobile applications for passengers and drivers based on beacon signals are developed. The server operation program for situation recognition, position estimation, risk management and notification of the taxi passenger is also developed. An accident risk management method is proposed using the recognition of getting on and off of the taxi passenger. The proposed methods are verified for applicability and usefulness through practical experiments.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.302-307
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• 2019

In modern Anti-Submarine Warfare, there are various ways to locate a submarine in a two-dimensional space. For more effective tracking and attack against a submarine the depth of the target is a critical factor. However, it has been difficult to find out the depth of a submarine until now. In this paper a possible solution to the depth estimation of submarines is proposed utilizing DIFAR (Directional Frequency Analysis and Recording) sonobuoy information such as contact bearings at or prior to CPA (Closest Point of Approach) and the target's Doppler signals. The relative depth of the target is determined by applying the Pythagorean theorem to the slant range and horizontal range between the target and the hydrophone of a DIFAR sonobuoy. The slant range is calculated using the Doppler shift and the target's velocity. the horizontal range can be obtained by applying a simple trigonometric function for two consecutive contact bearings and the travel distance of the target. The simulation results show that the algorithm is subject to an elevation angle, which is determined by the relative depth and horizontal distance between the sonobuoy and target, and that a precise measurement of the Doppler shift is crucial.