• 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%.

• Journal of Internet Computing and Services
• /
• v.10 no.1
• /
• pp.159-173
• /
• 2009

Locations of positioned nodes as well as gathered data from nodes are very important because generally multiple nodes are deployed randomly and data are gathered in wireless sensor network. Since the nodes composing wireless sensor network are low cost and low performance devices, it is very difficult to add specially designed devices for positioning into the nodes. Therefore in wireless sensor network, technology positioning nodes precisely using low cost is very important and valuable. This research proposes Cooperative Positioning System, which raises accuracy of location positioning and also can find positions on multiple sensors within limited times. And this research verifies this technology is excellent in terms of performance, accuracy, and scalability through simulation.

• ETRI Journal
• /
• v.38 no.3
• /
• pp.560-567
• /
• 2016

To solve the problem of parameter optimization in image sensor-based visible light positioning systems, theoretical limits for both the location and the azimuth angle of the image sensor receiver (ISR) are calculated. In the case of a typical indoor scenario, maximum likelihood estimations for both the location and the azimuth angle of the ISR are first deduced. The Cramer-Rao Lower Bound (CRLB) is then derived, under the condition that the observation values of the image points are affected by white Gaussian noise. For typical parameters of LEDs and image sensors, simulation results show that accurate estimates for both the location and azimuth angle can be achieved, with positioning errors usually on the order of centimeters and azimuth angle errors being less than $1^{\circ}$. The estimation accuracy depends on the focal length of the lens and on the pixel size and frame rate of the ISR, as well as on the number of transmitters used.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.5
• /
• pp.339-348
• /
• 2017

Due to recent improvements in computer processing speed and image processing technology, researches are being actively carried out to combine information from a camera with existing GNSS (Global Navigation Satellite System) and dead reckoning. In this study, the mathematical model based on SPR (Single Photo Resection) is derived for image-based assistant algorithm for vehicle positioning. Simulation test is performed to analyze factors affecting SPR. In addition, GNSS/on-board vehicle sensor/image based positioning algorithm is developed by combining image-based positioning algorithm with existing positioning algorithm. The performance of the integrated algorithm is evaluated by the actual driving test and landmark's position data, which is required to perform SPR, based on simulation. The precision of the horizontal position error is 1.79m in the case of the existing positioning algorithm, and that of the integrated positioning algorithm is 0.12m at the points where SPR is performed. In future research, it is necessary to develop an optimized algorithm based on the actual landmark's position data.

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.343-349
• /
• 2011

Now, for the continuous location detection of train, the method that the moving distance of a vehicle is detected using an wheel sensor(odometer) mounted within a train, is generally used. It has a problem that the positioning errors of a train can be accumulated as the moving distance increases. To solve this problem, it is required to apply a variety of positioning sensors and to integrate with sensor data. In this paper, we develop the train-borne positioning system applicable to the conventional railway and high-speed railway, and verify the performance of the train-borne positioning system through a vehicle test.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.10
• /
• pp.141-147
• /
• 2003

This paper represents an absolute positioning system using a light navigation path for mobile robot. The absolute positioning system is composed of the projector unit which generates a laser beam using laser diode and mobile robot with the optical detector which has some optical sensors. The projector unit is fixed over the navigating plane of mobile robot to generate the light navigation path, and the optical detector located upper part of mobile robot detects the generated laser beam from the projector. The navigation of mobile robot is controlled by the micro-processor which compares the detected present position from the detector with the previously programmed navigation path. And experimental results show that our sensor system can be used for the absolute positioning system of the mobile robot.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.2
• /
• pp.405-423
• /
• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

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

• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.6
• /
• pp.323-334
• /
• 2014

In this paper, we proposed indoor positioning system with improved accuracy. The proposed indoor location measurement system is based pedestrian location measurement method that use the embedded sensor of smartphone. So, we do not need wireless external resources, such as GPS or WiFi signals. The conventional methods measure indoor location by generating a movement route of pedestrian by step and direction recognition. In this paper, to correct the direction sensor error, we use the common feature of the normal indoor floor map that the indoor path is lattice-structured. And we quantize moving directions depending on the direction of indoor path. In addition, we propose moving direction measuring method using geomagnetic sensor and gyro sensor to improve the accuracy. Also, the proposed step detection method uses angle and accelerometer sensors. The proposed step detection method is not affected by the posture of the smartphone. Direction errors caused by direction sensor error is corrected due to proposed moving direction measuring method. The proposed location error correction method corrects location error caused by step detection error without the need for external wireless signal resources.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.1
• /
• pp.27-35
• /
• 2022

In the most IPS (Indoor Positioning System), it is available to specify the user's movement by sending a specific signal from a tag such as a beacon to multiple receivers. This method is very efficiently used in places where the number of people is limited. On the other hand, in large commercial facilities, it is nearly difficult to apply the existing IPS method because it is necessary to attach a tag to each customer. In this paper, we propose a system that uses an external sensor grid to identify people's movement without using tags. Each sensor node uses both an ultrasonic sensor and an infrared sensor to monitor people's movements and sends collected data to the main server through wireless transmission for easy system maintenance. The operation was verified using the FPGA board, and we designed a VLSI circuit in 180nm process.