• Title, Summary, Keyword: RSSI

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A Study on Distance Calculation Revision Algorithm using the Filtering of RSSI Measurement Results (RSSI 측정결과 필터링을 이용한 거리계산 보정 알고리즘에 관한 연구)

  • Kim, Ji-seong;Kim, Yong-kab
    • The Journal of The Institute of Internet, Broadcasting and Communication
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    • v.17 no.1
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    • pp.25-31
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    • 2017
  • The indoor location based service proposed in the study was assigned to target a moving user. Positioning in the outdoor environment is accurate while using GPS. However, in an indoor environment, positioning is inaccurate and difficult. In order to overcome this, studies of various techniques for positioning based on wireless communication such as Wi-Fi, Zigbee and Bluetooth are being performed. The RSSI value and the delivery signal of the bluetooth beacon are measured according to the distance, and to a database. It was applied calculating the value for the average RSSI and the RSSI filtering feedback. Filtering is used to reduce the error of the RSSI values that are measured at long distance. When average and feedback filtering coefficient are set with 0.5, irregular and highly RSSI values are decreased. As the distance increases, the range of error is confirmed to have a reduction when using a distance calculation correction algorithm. Finally, when using the RSSI measurement results filtering, it corrects an unstable signal. Also, the distance correction algorithm is used to reduce a range of errors.

Wireless Sensor Node Location Management By Regression Analysis of RSSI (RSSI 측정값의 회귀분석을 이용한 무선센서노드의 위치관리)

  • Choi, Jun-Young;Kim, Hyun-Joong;Yang, Hyun-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.308-311
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    • 2008
  • One of the key technical elements of wireless sensor network (WSN) is location management of sensor nodes. Typical node location management methods use GPS, ultrasonic sensors or RSSI. In this paper we propose a new location management method which adopts regression analysis of RSSI measurement to improve the accuracy of sensor node position estimation. We also evaluated the performance of proposed method by comparing the experimental results with existing scheme. According to the results, our proposed method showed better accuracy than existing location management scheme using RSSI and Firis' equation.

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RSSI Stabilization for Measuring Position using Beacon (위치 측정을 위한 비콘의 RSSI 안정화)

  • Kim, Woo-Chan;Lee, Cherng-Ghill;Kwak, Ho-Young
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.13-14
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    • 2019
  • 비콘을 이용해서 위치를 측정하기 위해서는 안정적인 RSSI 수치가 필요하다. 그러나 실제 수집된 RSSI 수치는 불규칙적이고, 이상치가 많은 형태를 취한다. 이에 수집된 RSSI 수치를 바로 적용하게 된다면, 이상치가 많이 발생하는 RSSI 특성상 위치 측정의 정확성이 많이 떨어지게 된다. 본 논문에서는 이를 해결하기 위하여 수집된 RSSI 수치에 칼만 필터링과 이동평균을 동시에 적용하였다. 이를 통해 더 안정적이고 더 믿을 수 있는 RSSI 수치를 얻을 수 있었다. 이 방법을 통해서 더 정확한 측정이 가능하였다.

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Lode Location Management Using RSSI Regression Analysis in Wireless Sensor Network (RSSI의 회귀 분석을 이용한 무선센서노드의 위치관리)

  • Yang, Hyun-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.9
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    • pp.1935-1940
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    • 2009
  • One of the key technical challenges of wireless sensor network (WSN) is location management of sensor nodes. Typical node location management methods use GPS, ultrasonic sensors or RSSI. In this paper we propose a new location management method which adopts regression analysis of RSSI measurement to improve the accuracy of sensor node position estimation. We also evaluated the performance of proposed method by comparing the experimental results with existing scheme. According to the results, our proposed method, LM-RAR, shows better accuracy than existing location management scheme using RSSI and Friis' equation.

Implement of Zigbee Indooer location aware system by RSSI between anchors (고정 노드 간의 RSSI 값을 이용한 Zigbee 실내 위치 인식 시스템 구현)

  • Lee, Jin-Wook;Ryu, Jae-Jong;Lee, Wu-Sung;Han, Doug-Koo;Choi, Hyun-Chul
    • Proceedings of the KIEE Conference
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    • pp.43-44
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    • 2008
  • 본 논문에서는 Weighted Cenrtoid Localization(WCL) 알고리즘을 적용하여, 고정 노드 (Anchors) 사이의 측정된 수신 신호 강도(RSSI)로 Zigbee 실내 위치 인식 시스템을 구현하였다. 센서 노드의 위치는 RSSI에 의해 선택된 가상 고정 노드에 WCL을 적용하여 결정한다. WCL에서 부여하는 가중치는 고정 노드와 RSSI 센서 노드 위치의 거리에 대한 함수이며, 고정 노드 간의 측정된 RSSI 값으로 구한다. 고정 노드 간의 RSSI로 가상 고정 노드를 이용한 WCL은 기존의 방식에서 사용되는 고정 노드의 수를 줄이고, 측정 대상의 위치 정확도를 측정된 RSSI 값만으로 추정한 위치보다 7.8% 향상되는 것을 확인 하였다.

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High Accuracy Indoor Location Sensing Solution based on EMA filter with Adaptive Signal Model in NLOS indoor environment (NLOS 실내 환경 하에서 측위 정확도 개선을 위한 EMA 필터 적용 적응적 신호 모델 기반 위치 센싱 솔루션)

  • Ha, Kyunguk;Cha, Myeonghun;Kim, Dongwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.7
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    • pp.852-860
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    • 2019
  • In this paper, we proposed a new trilateration technique based on exponential moving average (EMA) filter with adaptive signal model which enhances accuracy of positioning system even if the RSSI changes randomly due to movement of obstacles or blind node in indoor environment. In the proposed scheme, three fixed transmitters sent out the signal to blind node. The transmitter decides the location of the blind node based on RSSI and it estimates the cause of RSSI fluctuation which is interference of obstacle or movement of blind node. When the path between blind node and transmitter has become NLOS path because of obstacles, the transmitter ignores the measured RSSI in NLOS path and replace estimated RSSI in LOS environment. In the other case, the transmitter updated the new RSSI to represent of movement of blind node. The proposed scheme has been verified on a ZigBee testbed and we proved the improved positioning accuracy compared to the existing indoor position system.

Usage of RSSI in WAVE Handover (WAVE 핸드오버상에서 수신 신호 세기의 이용)

  • Cho, Woong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1449-1454
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    • 2012
  • Received signal strength indicator (RSSI) represents the strength of the received signal at the front end of analog-to-digital convertor (ADC) input. RSSI value can be used for deciding the status of channel at the receiver. In this paper, the usage of RSSI in handover is studied using the practical measurement data. We first measure RSSI in 5.9GHz frequency band which is commonly used in wireless access in vehicular environments (WAVE) system. i.e., vehicular communications. Then, to implement a fast handover, the usability of RSSI data is analyzed based on the measured data. We also apply handover in practical highway environments.

Design And Implementation of RSSI Based Location Recognition System Using Neural Networks (신경회로망을 이용한 RSSI 기반 위치인식 시스템 설계 및 구현)

  • Jung, Kyung Kwon;Cho, Hyung Kook;Eom, Ki Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.742-745
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    • 2009
  • This paper proposed indoor location recognition method based on RSSI (received signal strength indication) using the LVQ (Learning Vector Quantization) network. The LVQ inputs are the RSSI values measured by the fixed reference nodes and the output are the spatial sections. In order to verify the effectiveness of the proposed method, we performed experiments, and then compared to the conventional triangularity measurement method.

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Adaptive Parameter Estimation Method for Wireless Localization Using RSSI Measurements

  • Cho, Hyun-Hun;Lee, Rak-Hee;Park, Joon-Goo
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.883-887
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    • 2011
  • Location-based service (LBS) is becoming an important part of the information technology (IT) business. Localization is a core technology for LBS because LBS is based on the position of each device or user. In case of outdoor, GPS - which is used to determine the position of a moving user - is the dominant technology. As satellite signal cannot reach indoor, GPS cannot be used in indoor environment. Therefore, research and study about indoor localization technology, which has the same accuracy as an outdoor GPS, is needed for "seamless LBS". For indoor localization, we consider the IEEE802.11 WLAN environment. Generally, received signal strength indicator (RSSI) is used to obtain a specific position of the user under the WLAN environment. RSSI has a characteristic that is decreased over distance. To use RSSI at indoor localization, a mathematical model of RSSI, which reflects its characteristic, is used. However, this RSSI of the mathematical model is different from a real RSSI, which, in reality, has a sensitive parameter that is much affected by the propagation environment. This difference causes the occurrence of localization error. Thus, it is necessary to set a proper RSSI model in order to obtain an accurate localization result. We propose a method in which the parameters of the propagation environment are determined using only RSSI measurements obtained during localization.

RSSI-based Location Determination via Segmentation-based Linear Spline Interpolation Method (분할기반의 선형 호 보간법에 의한 RSSI기반의 위치 인식)

  • Lau, Erin-Ee-Lin;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.473-476
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    • 2007
  • Location determination of mobile user via RSSI approach has received ample attention from researchers lately. However, it remains a challenging issue due to the complexities of RSSI signal propagation characteristics, which are easily exacerbated by the mobility of user. Hence, a segmentation-based linear spline interpolation method is proposed to cater for the dynamic fluctuation pattern of radio signal in complex environment. This optimization algorithm is proposed in addition to the current radiolocation's (CC2431, Chipcon, Norway) algorithm, which runs on IEEE802.15.4 standard. The enhancement algorithm involves four phases. First phase consists of calibration model in which RSSI values at different static locations are collected and processed to obtain the mean and standard deviation value for the predefined distance. RSSI smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the user is moving. Distances are computed using the segmentation formula obtain in the first phase. In situation where RSSI value falls in more than one segment, the ambiguity of distance is solved by probability approach. The distance probability distribution function(pdf) for each distances are computed and distance with the highest pdf at a particular RSSI is the estimated distance. Finally, with the distances obtained from each reference node, an iterative trilateration algorithm is used for position estimation. Experiment results obtained position the proposed algorithm as a viable alternative for location tracking.

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