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
Autor*in: |
Liang Xue [verfasserIn] Bo Yang [verfasserIn] Xinguo Wang [verfasserIn] Guangbin Cai [verfasserIn] Bin Shan [verfasserIn] Honglong Chang [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2023 |
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Übergeordnetes Werk: |
In: Micromachines - MDPI AG, 2010, 14(2023), 4, p 759 |
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Übergeordnetes Werk: |
volume:14 ; year:2023 ; number:4, p 759 |
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DOI / URN: |
10.3390/mi14040759 |
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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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10.3390/mi14040759 doi (DE-627)DOAJ089809114 (DE-599)DOAJbe1736af8cca4cfebf2b894e65acb738 DE-627 ger DE-627 rakwb eng TJ1-1570 Liang Xue verfasserin aut MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MEMS sensor redundant MIMU non-orthogonal array noise correlation Kalman filter performance improvement Mechanical engineering and machinery Bo Yang verfasserin aut Xinguo Wang verfasserin aut Guangbin Cai verfasserin aut Bin Shan verfasserin aut Honglong Chang verfasserin aut In Micromachines MDPI AG, 2010 14(2023), 4, p 759 (DE-627)665016069 (DE-600)2620864-7 2072666X nnns volume:14 year:2023 number:4, p 759 https://doi.org/10.3390/mi14040759 kostenfrei https://doaj.org/article/be1736af8cca4cfebf2b894e65acb738 kostenfrei https://www.mdpi.com/2072-666X/14/4/759 kostenfrei https://doaj.org/toc/2072-666X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 4, p 759 |
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10.3390/mi14040759 doi (DE-627)DOAJ089809114 (DE-599)DOAJbe1736af8cca4cfebf2b894e65acb738 DE-627 ger DE-627 rakwb eng TJ1-1570 Liang Xue verfasserin aut MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MEMS sensor redundant MIMU non-orthogonal array noise correlation Kalman filter performance improvement Mechanical engineering and machinery Bo Yang verfasserin aut Xinguo Wang verfasserin aut Guangbin Cai verfasserin aut Bin Shan verfasserin aut Honglong Chang verfasserin aut In Micromachines MDPI AG, 2010 14(2023), 4, p 759 (DE-627)665016069 (DE-600)2620864-7 2072666X nnns volume:14 year:2023 number:4, p 759 https://doi.org/10.3390/mi14040759 kostenfrei https://doaj.org/article/be1736af8cca4cfebf2b894e65acb738 kostenfrei https://www.mdpi.com/2072-666X/14/4/759 kostenfrei https://doaj.org/toc/2072-666X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 4, p 759 |
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10.3390/mi14040759 doi (DE-627)DOAJ089809114 (DE-599)DOAJbe1736af8cca4cfebf2b894e65acb738 DE-627 ger DE-627 rakwb eng TJ1-1570 Liang Xue verfasserin aut MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MEMS sensor redundant MIMU non-orthogonal array noise correlation Kalman filter performance improvement Mechanical engineering and machinery Bo Yang verfasserin aut Xinguo Wang verfasserin aut Guangbin Cai verfasserin aut Bin Shan verfasserin aut Honglong Chang verfasserin aut In Micromachines MDPI AG, 2010 14(2023), 4, p 759 (DE-627)665016069 (DE-600)2620864-7 2072666X nnns volume:14 year:2023 number:4, p 759 https://doi.org/10.3390/mi14040759 kostenfrei https://doaj.org/article/be1736af8cca4cfebf2b894e65acb738 kostenfrei https://www.mdpi.com/2072-666X/14/4/759 kostenfrei https://doaj.org/toc/2072-666X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 4, p 759 |
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10.3390/mi14040759 doi (DE-627)DOAJ089809114 (DE-599)DOAJbe1736af8cca4cfebf2b894e65acb738 DE-627 ger DE-627 rakwb eng TJ1-1570 Liang Xue verfasserin aut MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MEMS sensor redundant MIMU non-orthogonal array noise correlation Kalman filter performance improvement Mechanical engineering and machinery Bo Yang verfasserin aut Xinguo Wang verfasserin aut Guangbin Cai verfasserin aut Bin Shan verfasserin aut Honglong Chang verfasserin aut In Micromachines MDPI AG, 2010 14(2023), 4, p 759 (DE-627)665016069 (DE-600)2620864-7 2072666X nnns volume:14 year:2023 number:4, p 759 https://doi.org/10.3390/mi14040759 kostenfrei https://doaj.org/article/be1736af8cca4cfebf2b894e65acb738 kostenfrei https://www.mdpi.com/2072-666X/14/4/759 kostenfrei https://doaj.org/toc/2072-666X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 4, p 759 |
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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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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 |
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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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