• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.9
• /
• pp.820-827
• /
• 2014

One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).

• Journal of Space Technology and Applications
• /
• v.4 no.1
• /
• pp.74-85
• /
• 2024

As the limitations of conventional radio communications between satellites and the ground become apparent, various experiments are being conducted around the world to overcome them with space laser communication. In this study, we address the development of our own optical communications terminal (OCT) and optical ground station (OGS) and the experiments of free-space optical communication (FSOC) using them. Using a 30 mm-diameter OCT and a 250 mm-diameter portable OGS telescope, as well as commercial 10 Gbps SFP+ modules and media converters, we successfully transmitted and received 4K high-definition multimedia interface (HDMI) signals through 1,550 nm optical laser beam. The transmission and reception distances of the experiment were 3, 9, and 20 km, respectively, and the received signal strength at each distance was +6.1, -2.8, and -10.9 dBm, respectively. It was demonstrated that the 4K HDMI video lasted for over 10 minutes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.1
• /
• pp.119-133
• /
• 2009

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.857-860
• /
• 2008

In this paper, we proposed cooperative based localization algorithm for wireless sensor networks, which can estimate to unknown node position using received signal strength table set. The unknown nodes are monitor to RSS from neighbor nodes and exclude existence possibility area of sensor node in sensor field. Finally, we can calculate the centroid position for each unknown node with cooperative localization algorithm. Furthermore, these processes are applied iteratively about all nodes which is recorded to RSS table and can estimate for unknown nodes.

• ETRI Journal
• /
• v.38 no.4
• /
• pp.634-644
• /
• 2016

Channel-based radio-frequency fingerprinting such as a channel impulse response (CIR), channel transfer function (CTF), and frequency coherence function (FCF) have been recently proposed to improve the accuracy at the physical layer; however, their empirical performance, advantages, and limitations have not been well reported. This paper provides a comprehensive empirical performance evaluation of RF location fingerprinting, focusing on a comparison of received-signal strength, CIR-, CTF-, and FCF-based fingerprinting using the weighted k-nearest neighbor pattern recognition technique. Frequency domain channel measurements in the IEEE 802.11 band taken on a university campus were used to evaluate the accuracy of the fingerprinting types and their robustness to human-induced motion perturbations of the channel. The localization performance was analyzed, and the results are described using the spatial and temporal radio propagation characteristics. In particular, we introduce the coherence region to explain the spatial properties and investigate the impact of the Doppler spread in time-varying channels on the time coherence of RF fingerprint structures.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.6
• /
• pp.589-594
• /
• 2015

In this paper, we described the Cramer-Rao Lower Bound (CLRB) performances of Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) methods when there are multiple emitters. The TDOA and FDOA values between two receivers can be simultaneously estimated by using the so-called Complex Ambiguity Function (CAF). In the case of multiple emitters, there exist Inter Symbol Interferences (ISIs) in the measurement data. Therefore, it is required to reduce the effect of ISI and provide a performance evaluation method of TDOA and FDOA estimations. In order to eliminate the ISIs, using of a filter bank before calculating CAF is proposed when the carrier frequencies of the emitters are different to one another. Angle of Arrival (AOA) or Received Signal Strength (RSS) methods before calculating CAF were proposed to reduce the ISIs when the carrier frequencies are the same. In order to evaluate the CRLB of TDOA and FDOA estimations, we employed the conditional probability distribution method and described the numerical comparison results.

• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.2
• /
• pp.109-116
• /
• 2017

In this paper, we propose an Internet of Things (IoT) platform for ocean observation buoys. The proposed system consists of various sensor modules, a gateway, and a remote monitoring site. In order to integrate sensor modules with various communications interfaces, we propose a controller area network (CAN)-based sensor data packet and a protocol for the gateway. The proposed scheme supports the registration and management of sensor modules so as to make it easier for the buoy system to manage various sensor modules. Also, in order to extend communication coverage between ocean observation buoys and the monitoring site, we implement a multi-hop relay network based on a mesh network that can provide greater communication coverage than conventional buoy systems. In addition, we verify the operation of the implemented multi-hop relay network by measuring the received signal strength indication between buoy nodes and by observing the collected data from the deployed buoy systems via our monitoring site.

• Journal of Information Technology Applications and Management
• /
• v.12 no.4
• /
• pp.93-104
• /
• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.11
• /
• pp.2657-2675
• /
• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

• Industrial Engineering and Management Systems
• /
• v.16 no.1
• /
• pp.92-102
• /
• 2017

In this paper, we consider a typical health care system via the help of Wireless Sensor Network (WSN) for wireless patient tracking. The wireless patient tracking module of this system performs localization out of samples of Received Signal Strength (RSS) variations and tracking through a Particle Filter (PF) for WSN assisted by multiple transmit-power information. We propose a modified PF, Kullback-Leibler Distance (KLD)-resampling PF, to ameliorate the effect of RSS variations by generating a sample set near the high-likelihood region for improving the wireless patient tracking. The key idea of this method is to approximate a discrete distribution with an upper bound error on the KLD for reducing both location error and the number of particles used. To determine this bound error, an optimal algorithm is proposed based on the maximum gap error between the proposal and Sampling Important Resampling (SIR) algorithms. By setting up these values, a number of simulations using the health care system's data sets which contains the real RSSI measurements to evaluate the location error in term of various power levels and density nodes for all methods. Finally, we point out the effect of different power levels vs. different density nodes for the wireless patient tracking.