{"_buckets": {"deposit": "961fbe6b-53a1-40e6-bf54-55e2cc0c3138"}, "_deposit": {"id": "1775", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "1775"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/1775", "sets": ["user-uy"]}, "communities": ["ccm", "ccp", "kyauksetu", "ltc", "maas", "miit", "mlmu", "mmu", "mtlu", "mtu", "mub", "mude", "mufl", "pathein", "scu", "suoe", "tcu", "tgu", "tuh", "tum", "ucsm", "ucsmtla", "ucsmub", "ucspathein", "ucstaungoo", "ucsy", "udmm", "udmy", "uit", "um", "um1", "um2", "umkn", "umm", "uphy", "urj", "uvs", "uy", "yau", "ydbu", "ytu", "yude", "yueco", "yufl", "yuoe"], "control_number": "1775", "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Attitude Estimation System Using MEMS Inertial Sensors and Kalman Filter", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "This paper focuses on the attitude estimation problem\r for a moving object using two MEMS sensors: accelerometer and\r gyroscope. These two sensors have different noise characteristics\r and are combined using the Kalman filter so that accurate\r attitude estimation is obtained. The process noises of two MEMS\r sensors are selected as the nominal values of actual sensors. The\r gyroscope output is used for time update portion of the filter and\r the accelerometer output is utilized the measurement update\r portion of the filter. The performance of the attitude estimation\r system is demonstrated through numerical simulations."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "attitude estimation"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-05-05"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "7.Attitude Estimation System Using MEMS Inertial by Htoo Maung Maung.pdf", "filesize": [{"value": "2281 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 2281000.0, "url": {"url": "https://meral.edu.mm/record/1775/files/7.Attitude Estimation System Using MEMS Inertial by Htoo Maung Maung.pdf"}, "version_id": "d876066c-0012-4c13-a3f0-8fef90565193"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{}]}, "item_1583103147082": {"attribute_name": "Conference papaers", "attribute_value_mlt": [{}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_supervisor(s)": []}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Htoo Maung Maung"}, {"subitem_authors_fullname": "Zaw Min Naing"}, {"subitem_authors_fullname": "Hla Myo Tun"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2010"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://uyr.uy.edu.mm/handle/123456789/77"}, "item_title": "Attitude Estimation System Using MEMS Inertial Sensors and Kalman Filter", "item_type_id": "21", "owner": "1", "path": ["1582967549708"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000001775", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-03-05"}, "publish_date": "2020-03-05", "publish_status": "0", "recid": "1775", "relation": {}, "relation_version_is_last": true, "title": ["Attitude Estimation System Using MEMS Inertial Sensors and Kalman Filter"], "weko_shared_id": -1}