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Accurate Localization and Tracking w...
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Pauls, Eric Joseph.
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Accurate Localization and Tracking with Passive RFID Technology.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Accurate Localization and Tracking with Passive RFID Technology./
作者:
Pauls, Eric Joseph.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:
50 p.
附註:
Source: Masters Abstracts International, Volume: 56-02.
Contained By:
Masters Abstracts International56-02(E).
標題:
Electrical engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10168983
ISBN:
9781369232066
Accurate Localization and Tracking with Passive RFID Technology.
Pauls, Eric Joseph.
Accurate Localization and Tracking with Passive RFID Technology.
- Ann Arbor : ProQuest Dissertations & Theses, 2016 - 50 p.
Source: Masters Abstracts International, Volume: 56-02.
Thesis (M.S.E.E.)--Villanova University, 2016.
This thesis explores the use of radio frequency identification (RFID) technology to solve the problem of localizing a mobile asset. RFID presents an opportunity for localization that is precise, easy to implement, and free of many of the problems that affect other positioning techniques such as optical imaging and radar. The method employed in this work uses the received signal strength indication (RSSI) from an RFID tag to localize an RFID reader mounted on a mobile unit. By reading unique tag ID's and their respective RSSI values, localization of the mobile unit is performed by comparing the tag measurements to a pre-generated table of expected RSSI values based on the physical properties of the RFID transmission. The expected RSSI values populating the dictionary table are derived from a series of experiments that study the changes in RSSI of a tag with respect to distance and orientation. These experiments validate the theoretical power equations for RFID transmissions and provide the data necessary for a finely tuned model of RSSI as a function of distance and tag orientation. A maximum likelihood (ML) search is then employed to find the best estimate of reader position. With an accurate localization method established, this thesis presents further improvements to the localization performance by employing and verifying a compensation method for known reflecting surfaces in the environment presented in previous work, and Kalman filter tracking for improved accuracy when the reader is moving. In concise summary, this thesis: 1) Gives a brief explanation of RFID technology, 2) Discusses previous contributions to the study of RFID-based localization, 3) Presents an experimental study on the effects of tag range and orientation on RSSI and gives a model for calculating RSSI as a function of tag position, 4) Presents an experimental validation of the ML search method for RSSI-based RFID localization with tag antenna pattern compensation, which is further improved with environmental reflection compensation and Kalman tracking; and 5) Compares the performance of the proposed localization method with other state of the art methods to show that ML search RFID localization offers superior localization accuracy.
ISBN: 9781369232066Subjects--Topical Terms:
649834
Electrical engineering.
Accurate Localization and Tracking with Passive RFID Technology.
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This thesis explores the use of radio frequency identification (RFID) technology to solve the problem of localizing a mobile asset. RFID presents an opportunity for localization that is precise, easy to implement, and free of many of the problems that affect other positioning techniques such as optical imaging and radar. The method employed in this work uses the received signal strength indication (RSSI) from an RFID tag to localize an RFID reader mounted on a mobile unit. By reading unique tag ID's and their respective RSSI values, localization of the mobile unit is performed by comparing the tag measurements to a pre-generated table of expected RSSI values based on the physical properties of the RFID transmission. The expected RSSI values populating the dictionary table are derived from a series of experiments that study the changes in RSSI of a tag with respect to distance and orientation. These experiments validate the theoretical power equations for RFID transmissions and provide the data necessary for a finely tuned model of RSSI as a function of distance and tag orientation. A maximum likelihood (ML) search is then employed to find the best estimate of reader position. With an accurate localization method established, this thesis presents further improvements to the localization performance by employing and verifying a compensation method for known reflecting surfaces in the environment presented in previous work, and Kalman filter tracking for improved accuracy when the reader is moving. In concise summary, this thesis: 1) Gives a brief explanation of RFID technology, 2) Discusses previous contributions to the study of RFID-based localization, 3) Presents an experimental study on the effects of tag range and orientation on RSSI and gives a model for calculating RSSI as a function of tag position, 4) Presents an experimental validation of the ML search method for RSSI-based RFID localization with tag antenna pattern compensation, which is further improved with environmental reflection compensation and Kalman tracking; and 5) Compares the performance of the proposed localization method with other state of the art methods to show that ML search RFID localization offers superior localization accuracy.
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