Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion

K. N. Nirmal; A. G. Sreejith; Joice Mathew; Mayuresh Sarpotdar; Ambily Suresh; Ajin Prakash; Margarita Safonova; Jayant Murthy

doi:10.1117/12.2234255

Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion

K. N. Nirmal^*, A. G. Sreejith, Joice Mathew, Mayuresh Sarpotdar, Ambily Suresh, Ajin Prakash, Margarita Safonova, Jayant Murthy

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

48 Citations (Scopus)

Abstract

We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

Original language	English
Title of host publication	Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II
Editors	Ramon Navarro, James H. Burge
Publisher	SPIE
ISBN (Electronic)	9781510602038
DOIs	https://doi.org/10.1117/12.2234255
Publication status	Published - 2016
Externally published	Yes
Event	Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II - Edinburgh, United Kingdom Duration: 26 Jun 2016 → 1 Jul 2016

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	9912
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II
Country/Territory	United Kingdom
City	Edinburgh
Period	26/06/16 → 1/07/16

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10.1117/12.2234255

Cite this

Nirmal, K. N., Sreejith, A. G., Mathew, J., Sarpotdar, M., Suresh, A., Prakash, A., Safonova, M., & Murthy, J. (2016). Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion. In R. Navarro, & J. H. Burge (Eds.), Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II Article 99126W (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9912). SPIE. https://doi.org/10.1117/12.2234255

Nirmal, K. N. ; Sreejith, A. G. ; Mathew, Joice et al. / Noise modeling and analysis of an IMU-based attitude sensor : Improvement of performance by filtering and sensor fusion. Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II. editor / Ramon Navarro ; James H. Burge. SPIE, 2016. (Proceedings of SPIE - The International Society for Optical Engineering).

@inproceedings{a60bb5f8d86941dab57e2aebe255f338,

title = "Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion",

abstract = "We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.",

keywords = "Attitude sensor, Balloon experiment, MEMS sensors, Pointing system",

author = "Nirmal, {K. N.} and Sreejith, {A. G.} and Joice Mathew and Mayuresh Sarpotdar and Ambily Suresh and Ajin Prakash and Margarita Safonova and Jayant Murthy",

note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II ; Conference date: 26-06-2016 Through 01-07-2016",

year = "2016",

doi = "10.1117/12.2234255",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Ramon Navarro and Burge, {James H.}",

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Nirmal, KN, Sreejith, AG, Mathew, J, Sarpotdar, M, Suresh, A, Prakash, A, Safonova, M & Murthy, J 2016, Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion. in R Navarro & JH Burge (eds), Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II., 99126W, Proceedings of SPIE - The International Society for Optical Engineering, vol. 9912, SPIE, Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II, Edinburgh, United Kingdom, 26/06/16. https://doi.org/10.1117/12.2234255

Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion. / Nirmal, K. N.; Sreejith, A. G.; Mathew, Joice et al.
Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II. ed. / Ramon Navarro; James H. Burge. SPIE, 2016. 99126W (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9912).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Noise modeling and analysis of an IMU-based attitude sensor

T2 - Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II

AU - Nirmal, K. N.

AU - Sreejith, A. G.

AU - Mathew, Joice

AU - Sarpotdar, Mayuresh

AU - Suresh, Ambily

AU - Prakash, Ajin

AU - Safonova, Margarita

AU - Murthy, Jayant

PY - 2016

Y1 - 2016

N2 - We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

AB - We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

KW - Attitude sensor

KW - Balloon experiment

KW - MEMS sensors

KW - Pointing system

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DO - 10.1117/12.2234255

M3 - Conference contribution

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II

A2 - Navarro, Ramon

A2 - Burge, James H.

PB - SPIE

Y2 - 26 June 2016 through 1 July 2016

ER -

Nirmal KN, Sreejith AG, Mathew J, Sarpotdar M, Suresh A, Prakash A et al. Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion. In Navarro R, Burge JH, editors, Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation II. SPIE. 2016. 99126W. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2234255

Noise modeling and analysis of an IMU-based attitude sensor: Improvement of performance by filtering and sensor fusion

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