• Journal of the Korea Institute of Military Science and Technology
• /
• v.18 no.1
• /
• pp.1-7
• /
• 2015

In this paper, we have described target positioning of automatic survey system. Target positioning error analysis shows target positioning errors are mainly dependent on the vertical angle of the triangle configured by target and two measurement points. Suggested target positioning error formula are confirmed by simulation using the Gaussian distribution.

• Journal of Positioning, Navigation, and Timing
• /
• v.7 no.1
• /
• pp.25-35
• /
• 2018

This paper describes the measurement of pulse positioning (input time) to calculate a time of arrival (TOA) that takes from transmitting a signal from the target of multilateration (MLAT) system to receiving the signal at the receiver. In this regard, this paper analyzes performances of simple threshold method and level adjust system (LAS) method, which is one of the adaptive threshold detector (ATD) methods, among many methods to calculate pulse positioning of signal received at the receiver. To this end, Cramer-rao lower bound (CRLB) with regard to pulse positioning, which was measured when signals transmitted from a transponder mounted at the target were received at the receiver, was induced and then deviation sizes with regard to pulse positioning, which was measured with simple threshold and LAS methods through MATLAB simulations, were compared. Next, problems occurring according to a difference in amplitude of signals inputted to each receiver are described when pulse positioning is measured at multiple receivers located at a different distance from the target as is the case in the MLAT system. Furthermore, LAS method to resolve the problems is explained. Lastly, this study analyzes whether a pulse positioning error occurring due to the signal noise satisfies the requirement (6 nsec. or lower) recommended for the MLAT system when using these two methods.

• Journal of Positioning, Navigation, and Timing
• /
• v.10 no.1
• /
• pp.49-54
• /
• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• Journal of the Semiconductor & Display Technology
• /
• v.22 no.2
• /
• pp.112-119
• /
• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.349-352
• /
• 2005

The telematics positioning testbed is an infrastructure to test and verify positioning technology, the sub-component of telernatics system. The positioning testbed provides the environment of performance analysis for acquisition of static and dynamic positioning information using telematics vehicle. This testbed consists of onboard positioning system, positioning reference station and lab positioning server. The onboard positioning system equipped in telematics vehicle, consists of target positioning system, reference positioning system, and analysis tool. A equipment acquiring high precision positioning data obtained from GPS combined with IMU was set as a reference positioning system. Analysis tool compares observed positioning data with high precision positioning information from a reference positioning system, and processes positioning information. Positioning reference station is RTK system used for reducing atmosphere error, and it transmits corrected information to reference positioning system. Positioning server which is located at laboratory manages positioning database and provides monitoring data to integrated testbed operating system. It is expected that the testbed supports commercialization of telernatics technology and services, integrated testing among component technology and verification.

• Journal of Positioning, Navigation, and Timing
• /
• v.6 no.2
• /
• pp.53-57
• /
• 2017

eLoran refers to a terrestrial navigation system using high-power low-frequency signals. Thus, it can be regarded as a positioning, navigation and timing (PNT) system to back up a global navigation satellite system (GNSS) or an alternative to GNSS. South Korea is vulnerable to interference such as GNSS jamming in particular. Therefore, South Korea has made an effort to develop an independent navigation system through eLoran system. More particularly, an eLoran testbed has been developed to be used in the northwest sea area and research on applicability of eLoran in South Korea has been underway. The present study analyzes expected performance of eLoran according to locations of newly built eLoran transmitting stations as part of the eLoran testbed research. The performance of eLoran is analyzed in terms of horizontal position accuracy, and horizontal dilution of precision (HDOP) information was used since it affects accuracy significantly. The target service areas of the eLoran testbed are Incheon and Pyeongtaek Ports, and the required target performance is positioning accuracy of 20 m position within 30 km coverage of the target service area.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.212-217
• /
• 1993

In this paper, characteristics of the motions of a human arm are investigated experimentally. When the conditions of the target point are restricted, human adjusts its trajectory and velocity pattern of the arm to fit the conditions skillfully. The purpose of this work is to examine the characteristics of the trajectory, velocity pattern, and the size of the duration in the following cases. First, we examine the case of point-to-point motion. The results are consistent with the minimum jerk theory. However, individual differences in the length of the duration can be observed in the experiment. Second, we examine the case which requires accuracy of positioning at the target point. It is found that the velocity pattern differs from the bell shaped pattern explained by the minimum jerk theory, and has its peak in the first half of the duration. When higher accuracy of the positioning is required, learning effects can be observed. Finally, to examine the case which requires constraint of the arm posture at the target point, we conduct experiments of a human trying to grasp a cup. It is considered that this motion consists of two steps : one is the positioning motion of the person in order to start the grasping motion, the other is the grasping motion of the human's hand approaching toward the cup and grasping it. In addition, two representative velocity patterns are observed : one is the similar velocity pattern explained in the above experiment, the other is the velocity pattern which has its relative maximum in the latter half of the duration.

• Journal of Sensor Science and Technology
• /
• v.28 no.6
• /
• pp.414-419
• /
• 2019

An ultrasonic based magnetostrictive position sensor (MPS) provides an indication of real target position. It determines the real target position by multiplying the propagation speed of ultrasonic wave and the time-of-flight between the receiving signals; one is the initial signal by an excitation current and the other is the reflection signal by the ultrasonic wave. The propagation speed of the ultrasonic wave depends on the temperature of the waveguide. Hence, the change of the propagation speed in various environments is a critical factor in terms of the positioning accuracy in the MPS. This means that the influence of the changes in the waveguide temperature needs to be compensated. In this paper, we presents a novel way to improve the positioning accuracy of MPSs using temperature compensation for waveguide. The proposed method used the inherent measurement blind area for the structure of the MPS, which can simultaneously measure the position of the moving target and the temperature of the waveguide without any additional devices. The average positional error was approximately -23.9 mm and -1.9 mm before and after compensation, respectively. It was confirmed that the positioning accuracy was improved by approximately 93%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.159-162
• /
• 2002

This paper deals with target positioning performance according to active sonar formation and measurement error. Generally, active sonar can be categorized into Monostatic, Bistatic and Multistatic cases and their error characteristics are different each other. In this paper, on the assumption that each receiver has two kinds of measurements； sum of distances, and a angle between receiver and target, we suggest least square(LS) method that combines the two measurements in Multistatic formation, and compare Multistatic case with Monostatic and Bistatic cases. Experimental results show that target positioning RMSE in Multistatic sonar is superior to those in Monostatic and Bistatic sonar by approximately 57％.

• Progress in Medical Physics
• /
• v.24 no.4
• /
• pp.290-294
• /
• 2013

Stereotactic Radiosurgery require high accuracy and precision of patient positioning and target localization. We evaluate the real time positioning accuracy of isocenter using optic guided patient positioning system, ExacTrac (BrainLab, Germany), during spinal radiosurgery procedure. The system is based on real time detect multiple body markers attached on the selected patient skin landmarks. And a custom designed patient positioning verification tool (PPVT) was used to check the patient alignment and correct the patient repositioning before radiosurgery. In this study, We investigate the selected 8 metastatic spinal tumor cases. All type of tumors commonly closed to thoracic spinal code. To evaluate the isocenter positioning, real time patient alignment and positioning monitoring was carried out for comparing the current 3-dimensional position of markers with those of an initial reference positions. For a selected patient case, we have check the isocenter positioning per every 20 millisecond for 45 seconds during spinal radiosurgery. In this study, real time average isocenter positioning translation were $0.07{\pm}0.17$ mm, $0.11{\pm}0.18$ mm, $0.13{\pm}0.26$ mm, and $0.20{\pm}0.37$ mm in the x (lateral), y (longitudinal), z (vertical) directions and mean spatial error, respectively. And body rotations were $0.14{\pm}0.07^{\circ}$, $0.11{\pm}0.07^{\circ}$, $0.03{\pm}0.04^{\circ}$ in longitudinal, lateral, table directions and mean body rotation $0.20{\pm}0.11^{\circ}$, respectively. In this study, the maximum mean deviation of real time isocenter positioning translation during spinal radiosurgery was acceptable accuracy clinically.