Development of decentralized data fusion algorithm with optimized kalman filter.

Development of decentralized data fusion algorithm with optimized kalman filter.

Manfaat positif teknik penggabungan data telah mempengaruhi beberapa aplikasi kejuruteraan untuk melaksanakan teknologi tersebut. Walau bagaimanapun, terdapat beberapa cabaran yang masih perlu diatasi seperti pemilihan algoritma yang bersesuaian, kelewatan pemprosesan dan masalah jejalan memori....

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Main Author: Quadri, Sayed Abulhasan
Format: Thesis
Language:English
Published: 2016
Subjects:
T Technology
TK7800-8360 Electronics
Online Access:http://eprints.usm.my/41009/1/Development_of_decentralized_data_fusion_algorithm_with_optimized_kalman_filter_Sayed_Abulhasan_Quadri_E3_2016_MJMS.pdf
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spelling my-usm-ep.410092018-08-15T03:58:03Z Development of decentralized data fusion algorithm with optimized kalman filter. 2016-08 Quadri, Sayed Abulhasan T Technology TK7800-8360 Electronics Manfaat positif teknik penggabungan data telah mempengaruhi beberapa aplikasi kejuruteraan untuk melaksanakan teknologi tersebut. Walau bagaimanapun, terdapat beberapa cabaran yang masih perlu diatasi seperti pemilihan algoritma yang bersesuaian, kelewatan pemprosesan dan masalah jejalan memori. Tesis ini mencadangkan satu model penggabungan data yang akan memudahkan proses pemilihan algoritma selain mengoptimumkan jumlah pemilihan algoritma yang berpotensi. Model ini menggabungkan teknologi penggabungan data dengan domain kejuruteraan algoritma, dan dengan itu mengoptimumkan algoritma penggabungan data menggunakan teknik yang canggih seperti pengaturcaraan berfungsi untuk mengurangkan lengah pemprosesan dan penggunaan memori. Model ini direalisasikan dalam empat aplikasi penggabungan data seperti sistem unit pengukuran inersia (IMU), sistem OktoKopter, penggabungan data satelit dan penilaian struktur konkrit. Bagi keseluruhan aplikasi pelbagai penggabungan data algoritma seperti algoritma turas Kalman, algoritma faktor analisis (FA) dan pengusulan algoritma QR-FA telah dibandingkan dalam jangkaan kesalahan asas. Algoritma QR-FA yang dicadangkan telah dibangunkan dengan memperkenalkan beberapa langkah tambahan algoritma penguraian QR ke dalam algoritma piawai analisis faktor. Algoritma dengan paling kurang jangkaan kesalahan akan dipilih bagi proses pengoptimuman. Hasil keputusan bagi semua aplikasi mengesahkan bahawa pengoptimuman telah mengurangkan masa pelaksanaan dan penggunaan memori bagi penggabungan data algoritma. ________________________________________________________________________________________________________________________ The positive virtues of data fusion technique have influenced several engineering applications to implement the technology. However, a number of challenges remain to be addressed, such as selection of appropriate algorithm, processing delay and bottleneck-memory problem. This thesis proposes a data fusion model that facilitates selection of algorithm and recommends selected algorithm to be optimized. The model collaborates data fusion technology with algorithm engineering domain, accordingly data fusion algorithm is optimized using sophisticated technique such as functional programming to reduce the processing delay and memory usage. The model is realized in four data fusion applications such as inertial measurement unit (IMU) system, OktoKopter system, satellite data fusion and concrete structure evaluation. In all the applications, various data fusion algorithms such as Kalman filter algorithm, factor analysis (FA) algorithm and the proposed QR-FA algorithm are compared on basis of estimation error. The proposed QR-FA algorithm is developed by introducing additional step of QR decomposition in the standard factor analysis algorithm. The algorithm with the least estimation error is selected for optimization. The results in all the applications confirm that optimization has significantly reduced execution time and memory usage of selected data fusion algorithm. 2016-08 Thesis http://eprints.usm.my/41009/ http://eprints.usm.my/41009/1/Development_of_decentralized_data_fusion_algorithm_with_optimized_kalman_filter_Sayed_Abulhasan_Quadri_E3_2016_MJMS.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik Dan Elektronik
institution Universiti Sains Malaysia
collection USM Institutional Repository
language English
topic T Technology
TK7800-8360 Electronics
spellingShingle T Technology
TK7800-8360 Electronics
Quadri, Sayed Abulhasan
Development of decentralized data fusion algorithm with optimized kalman filter.
description Manfaat positif teknik penggabungan data telah mempengaruhi beberapa aplikasi kejuruteraan untuk melaksanakan teknologi tersebut. Walau bagaimanapun, terdapat beberapa cabaran yang masih perlu diatasi seperti pemilihan algoritma yang bersesuaian, kelewatan pemprosesan dan masalah jejalan memori. Tesis ini mencadangkan satu model penggabungan data yang akan memudahkan proses pemilihan algoritma selain mengoptimumkan jumlah pemilihan algoritma yang berpotensi. Model ini menggabungkan teknologi penggabungan data dengan domain kejuruteraan algoritma, dan dengan itu mengoptimumkan algoritma penggabungan data menggunakan teknik yang canggih seperti pengaturcaraan berfungsi untuk mengurangkan lengah pemprosesan dan penggunaan memori. Model ini direalisasikan dalam empat aplikasi penggabungan data seperti sistem unit pengukuran inersia (IMU), sistem OktoKopter, penggabungan data satelit dan penilaian struktur konkrit. Bagi keseluruhan aplikasi pelbagai penggabungan data algoritma seperti algoritma turas Kalman, algoritma faktor analisis (FA) dan pengusulan algoritma QR-FA telah dibandingkan dalam jangkaan kesalahan asas. Algoritma QR-FA yang dicadangkan telah dibangunkan dengan memperkenalkan beberapa langkah tambahan algoritma penguraian QR ke dalam algoritma piawai analisis faktor. Algoritma dengan paling kurang jangkaan kesalahan akan dipilih bagi proses pengoptimuman. Hasil keputusan bagi semua aplikasi mengesahkan bahawa pengoptimuman telah mengurangkan masa pelaksanaan dan penggunaan memori bagi penggabungan data algoritma. ________________________________________________________________________________________________________________________ The positive virtues of data fusion technique have influenced several engineering applications to implement the technology. However, a number of challenges remain to be addressed, such as selection of appropriate algorithm, processing delay and bottleneck-memory problem. This thesis proposes a data fusion model that facilitates selection of algorithm and recommends selected algorithm to be optimized. The model collaborates data fusion technology with algorithm engineering domain, accordingly data fusion algorithm is optimized using sophisticated technique such as functional programming to reduce the processing delay and memory usage. The model is realized in four data fusion applications such as inertial measurement unit (IMU) system, OktoKopter system, satellite data fusion and concrete structure evaluation. In all the applications, various data fusion algorithms such as Kalman filter algorithm, factor analysis (FA) algorithm and the proposed QR-FA algorithm are compared on basis of estimation error. The proposed QR-FA algorithm is developed by introducing additional step of QR decomposition in the standard factor analysis algorithm. The algorithm with the least estimation error is selected for optimization. The results in all the applications confirm that optimization has significantly reduced execution time and memory usage of selected data fusion algorithm.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Quadri, Sayed Abulhasan
author_facet Quadri, Sayed Abulhasan
author_sort Quadri, Sayed Abulhasan
title Development of decentralized data fusion algorithm with optimized kalman filter.
title_short Development of decentralized data fusion algorithm with optimized kalman filter.
title_full Development of decentralized data fusion algorithm with optimized kalman filter.
title_fullStr Development of decentralized data fusion algorithm with optimized kalman filter.
title_full_unstemmed Development of decentralized data fusion algorithm with optimized kalman filter.
title_sort development of decentralized data fusion algorithm with optimized kalman filter.
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Kejuruteraan Elektrik Dan Elektronik
publishDate 2016
url http://eprints.usm.my/41009/1/Development_of_decentralized_data_fusion_algorithm_with_optimized_kalman_filter_Sayed_Abulhasan_Quadri_E3_2016_MJMS.pdf
_version_ 1747820859376009216

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