MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array

A micro-inertial measurement unit (MIMU) is usually used to sense the angular rate and acceleration of the flight carrier. In this study, multiple MEMS gyroscopes were used to form a spatial non-orthogonal array to construct a redundant MIMU system, and an optimal Kalman filter (KF) algorithm was es...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Liang Xue [verfasserIn] Bo Yang [verfasserIn] Xinguo Wang [verfasserIn] Guangbin Cai [verfasserIn] Bin Shan [verfasserIn] Honglong Chang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	MEMS sensor redundant MIMU non-orthogonal array noise correlation Kalman filter performance improvement

Übergeordnetes Werk:	In: Micromachines - MDPI AG, 2010, 14(2023), 4, p 759
Übergeordnetes Werk:	volume:14 ; year:2023 ; number:4, p 759

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/mi14040759

Katalog-ID:	DOAJ089809114

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520			\|a A micro-inertial measurement unit (MIMU) is usually used to sense the angular rate and acceleration of the flight carrier. In this study, multiple MEMS gyroscopes were used to form a spatial non-orthogonal array to construct a redundant MIMU system, and an optimal Kalman filter (KF) algorithm was established by a steady-state KF gain to combine array signals to improve the MIMU’s accuracy. The noise correlation was used to optimize the geometric layout of the non-orthogonal array and reveal the mechanisms of influence of correlation and geometric layout on MIMU’s performance improvement. Additionally, two different conical configuration structures of a non-orthogonal array for 4,5,6,8-gyro were designed and analyzed. Finally, a redundant 4-MIMU system was designed to verify the proposed structure and KF algorithm. The results demonstrate that the input signal rate can be accurately estimated and that the gyro’s error can also be effectively reduced through fusion of non-orthogonal array. The results for the 4-MIMU system illustrate that the gyro’s ARW and RRW noise can be decreased by factors of about 3.5 and 2.5, respectively. In particular, the estimated errors (1σ) on the axes of <i<X<sub<b</sub<</i<, <i<Y<sub<b</sub<</i< and <i<Z<sub<b</sub<</i< were 4.9, 4.6 and 2.9 times lower than that of the single gyroscope.
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callnumber-first	T - Technology
author	Liang Xue
spellingShingle	Liang Xue misc TJ1-1570 misc MEMS sensor misc redundant MIMU misc non-orthogonal array misc noise correlation misc Kalman filter misc performance improvement misc Mechanical engineering and machinery MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array
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topic_title	TJ1-1570 MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array MEMS sensor redundant MIMU non-orthogonal array noise correlation Kalman filter performance improvement
topic	misc TJ1-1570 misc MEMS sensor misc redundant MIMU misc non-orthogonal array misc noise correlation misc Kalman filter misc performance improvement misc Mechanical engineering and machinery
topic_unstemmed	misc TJ1-1570 misc MEMS sensor misc redundant MIMU misc non-orthogonal array misc noise correlation misc Kalman filter misc performance improvement misc Mechanical engineering and machinery
topic_browse	misc TJ1-1570 misc MEMS sensor misc redundant MIMU misc non-orthogonal array misc noise correlation misc Kalman filter misc performance improvement misc Mechanical engineering and machinery
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title	MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array
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title_full	MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array
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author_browse	Liang Xue Bo Yang Xinguo Wang Guangbin Cai Bin Shan Honglong Chang
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title_sort	mimu optimal redundant structure and signal fusion algorithm based on a non-orthogonal mems inertial sensor array
callnumber	TJ1-1570
title_auth	MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array
abstract	A micro-inertial measurement unit (MIMU) is usually used to sense the angular rate and acceleration of the flight carrier. In this study, multiple MEMS gyroscopes were used to form a spatial non-orthogonal array to construct a redundant MIMU system, and an optimal Kalman filter (KF) algorithm was established by a steady-state KF gain to combine array signals to improve the MIMU’s accuracy. The noise correlation was used to optimize the geometric layout of the non-orthogonal array and reveal the mechanisms of influence of correlation and geometric layout on MIMU’s performance improvement. Additionally, two different conical configuration structures of a non-orthogonal array for 4,5,6,8-gyro were designed and analyzed. Finally, a redundant 4-MIMU system was designed to verify the proposed structure and KF algorithm. The results demonstrate that the input signal rate can be accurately estimated and that the gyro’s error can also be effectively reduced through fusion of non-orthogonal array. The results for the 4-MIMU system illustrate that the gyro’s ARW and RRW noise can be decreased by factors of about 3.5 and 2.5, respectively. In particular, the estimated errors (1σ) on the axes of <i<X<sub<b</sub<</i<, <i<Y<sub<b</sub<</i< and <i<Z<sub<b</sub<</i< were 4.9, 4.6 and 2.9 times lower than that of the single gyroscope.
abstractGer	A micro-inertial measurement unit (MIMU) is usually used to sense the angular rate and acceleration of the flight carrier. In this study, multiple MEMS gyroscopes were used to form a spatial non-orthogonal array to construct a redundant MIMU system, and an optimal Kalman filter (KF) algorithm was established by a steady-state KF gain to combine array signals to improve the MIMU’s accuracy. The noise correlation was used to optimize the geometric layout of the non-orthogonal array and reveal the mechanisms of influence of correlation and geometric layout on MIMU’s performance improvement. Additionally, two different conical configuration structures of a non-orthogonal array for 4,5,6,8-gyro were designed and analyzed. Finally, a redundant 4-MIMU system was designed to verify the proposed structure and KF algorithm. The results demonstrate that the input signal rate can be accurately estimated and that the gyro’s error can also be effectively reduced through fusion of non-orthogonal array. The results for the 4-MIMU system illustrate that the gyro’s ARW and RRW noise can be decreased by factors of about 3.5 and 2.5, respectively. In particular, the estimated errors (1σ) on the axes of <i<X<sub<b</sub<</i<, <i<Y<sub<b</sub<</i< and <i<Z<sub<b</sub<</i< were 4.9, 4.6 and 2.9 times lower than that of the single gyroscope.
abstract_unstemmed	A micro-inertial measurement unit (MIMU) is usually used to sense the angular rate and acceleration of the flight carrier. In this study, multiple MEMS gyroscopes were used to form a spatial non-orthogonal array to construct a redundant MIMU system, and an optimal Kalman filter (KF) algorithm was established by a steady-state KF gain to combine array signals to improve the MIMU’s accuracy. The noise correlation was used to optimize the geometric layout of the non-orthogonal array and reveal the mechanisms of influence of correlation and geometric layout on MIMU’s performance improvement. Additionally, two different conical configuration structures of a non-orthogonal array for 4,5,6,8-gyro were designed and analyzed. Finally, a redundant 4-MIMU system was designed to verify the proposed structure and KF algorithm. The results demonstrate that the input signal rate can be accurately estimated and that the gyro’s error can also be effectively reduced through fusion of non-orthogonal array. The results for the 4-MIMU system illustrate that the gyro’s ARW and RRW noise can be decreased by factors of about 3.5 and 2.5, respectively. In particular, the estimated errors (1σ) on the axes of <i<X<sub<b</sub<</i<, <i<Y<sub<b</sub<</i< and <i<Z<sub<b</sub<</i< were 4.9, 4.6 and 2.9 times lower than that of the single gyroscope.
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container_issue	4, p 759
title_short	MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array
url	https://doi.org/10.3390/mi14040759 https://doaj.org/article/be1736af8cca4cfebf2b894e65acb738 https://www.mdpi.com/2072-666X/14/4/759 https://doaj.org/toc/2072-666X
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author2	Bo Yang Xinguo Wang Guangbin Cai Bin Shan Honglong Chang
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up_date	2024-07-04T00:44:34.643Z
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MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array

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