國立虎尾科技大學 |

Fuzzy Inference System to Detect GPS Health in the Urban Environment.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Fuzzy Inference System to Detect GPS Health in the Urban Environment./
作者:	Wessels, Austin M.
面頁冊數:	1 online resource (108 pages)
附註:	Source: Masters Abstracts International, Volume: 85-03.
Contained By:	Masters Abstracts International85-03.
標題:	Aerospace engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9798380198714

Fuzzy Inference System to Detect GPS Health in the Urban Environment.
Wessels, Austin M.

Fuzzy Inference System to Detect GPS Health in the Urban Environment. - 1 online resource (108 pages)

Source: Masters Abstracts International, Volume: 85-03.

Thesis (M.S.)--University of Cincinnati, 2023.

Includes bibliographical references

One major challenge to the widespread adoption and progress of autonomous vehicles relies on answering the simple question - where am I? Vehicles operating in an urban canyon, such as a city, must be able to trust their sensors, especially for localization in the dense urban environment. The use of LiDAR and high definition maps requires effort in advance to develop the high definition map. Also, the high definition map may not be able to account for the seasonal changes in the environment like changing foliage or accumulated snow. Other localization methods require additional fixed infrastructure such as base stations in the case of Real-Time Kinematic solutions. GPS is one common sensor used for localization that suffers from noise and inaccuracies in the urban canyon, due to increased horizontal dilution of precision, multipathing, and non-line-of-sight signals. This research serves to identify when the sensor is unreliable and how much error is in the measurement. This is accomplished using a fuzzy inference system and metadata about the GPS measurement and the measurement itself. The use of two GPS sensors allows for the measured relative position of the sensors to be compared to the known relative position of the sensors for one input. Then, the reported horizontal position error for each sensor are the other inputs. The membership functions and rulebase were generated using heuristic knowledge of the GPS sensors' measurements in the urban canyon. Testing this system required the operation of an uncrewed ground vehicle in an urban canyon and a motion capture camera system to measure ground truth. After this was tested successfully, the fuzzy inference system was applied to estimate the position of the uncrewed vehicle in an urban canyon. The position was estimated using a fuzzy adaptive Kalman filter, as the fuzzy inference system estimated the measurement noise covariance matrix.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380198714Subjects--Topical Terms:

686400
Aerospace engineering.
Subjects--Index Terms:

Fuzzy inference systemIndex Terms--Genre/Form:

554714
Electronic books.

Fuzzy Inference System to Detect GPS Health in the Urban Environment.
LDR:03276ntm a22003977 4500 001 1145190
005 20240617111405.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798380198714
035 $a (MiAaPQ)AAI30725311
035 $a (MiAaPQ)OhioLINKucin1692272131599053
035 $a AAI30725311
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Wessels, Austin M. $3 1470425
245 1 0 $a Fuzzy Inference System to Detect GPS Health in the Urban Environment.
264 0 $c 2023
300 $a 1 online resource (108 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 85-03.
500 $a Advisor: Cohen, Kelly.
502 $a Thesis (M.S.)--University of Cincinnati, 2023.
504 $a Includes bibliographical references
520 $a One major challenge to the widespread adoption and progress of autonomous vehicles relies on answering the simple question - where am I? Vehicles operating in an urban canyon, such as a city, must be able to trust their sensors, especially for localization in the dense urban environment. The use of LiDAR and high definition maps requires effort in advance to develop the high definition map. Also, the high definition map may not be able to account for the seasonal changes in the environment like changing foliage or accumulated snow. Other localization methods require additional fixed infrastructure such as base stations in the case of Real-Time Kinematic solutions. GPS is one common sensor used for localization that suffers from noise and inaccuracies in the urban canyon, due to increased horizontal dilution of precision, multipathing, and non-line-of-sight signals. This research serves to identify when the sensor is unreliable and how much error is in the measurement. This is accomplished using a fuzzy inference system and metadata about the GPS measurement and the measurement itself. The use of two GPS sensors allows for the measured relative position of the sensors to be compared to the known relative position of the sensors for one input. Then, the reported horizontal position error for each sensor are the other inputs. The membership functions and rulebase were generated using heuristic knowledge of the GPS sensors' measurements in the urban canyon. Testing this system required the operation of an uncrewed ground vehicle in an urban canyon and a motion capture camera system to measure ground truth. After this was tested successfully, the fuzzy inference system was applied to estimate the position of the uncrewed vehicle in an urban canyon. The position was estimated using a fuzzy adaptive Kalman filter, as the fuzzy inference system estimated the measurement noise covariance matrix.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Aerospace engineering. $3 686400
650 4 $a Computer science. $3 573171
650 4 $a Mechanical engineering. $3 557493
653 $a Fuzzy inference system
653 $a Motion capture
653 $a Urban canyon
653 $a Localization
655 7 $a Electronic books. $2 local $3 554714
690 $a 0538
690 $a 0984
690 $a 0548
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Cincinnati. $b Engineering and Applied Science: Aerospace Engineering. $3 1470399
773 0 $t Masters Abstracts International $g 85-03.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30725311 $z click for full text (PQDT)