On the Accuracy of the SINS Calibration Algorithm Based on the Fourier Transform. Comparison with the Cramer Rao Bound
EDN: IAOXHN
Abstract
Calibration of a strapdown inertial navigation system (SINS) on a simple turntable is considered. SINS calibration is carried out in the autonomous mode, relying only on the SINS sensors. One of the well-known algorithms for calibration in this scenario is the algorithm based on the extended Kalman filter proposed by N.A. Parusnikov. The algorithm is accurate enough, so that under certain assumptions, it is close to optimal. Some difficulties in its application are due to linearization of the problem, which requires the knowledge of initial approximation of the parameters to be calibrated. As an alternative, an algorithm based on the Fourier transform and subsequent transition to data spectrum analysis is proposed, after which the calibration algorithm becomes purely algebraic and does not involve any convergence problems. The accuracy of the proposed algorithm, as well as its nonoptimality are discussed through the comparison with the theoretical Cramer–Rao bound.
About the Authors
Yu. V. BolotinRussian Federation
Moscow
V. A. Savin
Russian Federation
Moscow
References
1. Емельянцев Г.И., Блажнов Б.А., Драницына Е.В., Степанов А.П. О калибровке измерительного модуля прецизионной БИНС и построении связанного с ним ортогонального трехгранника // Гироскопия и навигация. 2016. Т. 1 (92). С. 36–48. DOI 10.17285/0869-7035.2016.24.1.036-048.
2. Болотин Ю.В., Голиков В.П., Ларионов С.В., Требухов А.В. Алгоритмы калибровки платформенной инерциальной навигационной системы // Гироскопия и навигация. 2008. № 3 (62). С. 3–27.
3. Вавилова Н.Б., Сазонов И.Ю. Калибровка бескарданной инерциальной навигационной системы в сборе на грубых стендах с одной степенью свободы // Вестник Московского университета. Сер. 1: Математика. Механика. 2012. Т. 1. № 4. С. 64–66.
4. Козлов А.В., Сазонов И.Ю., Вавилова Н.Б., Парусников Н.А. Калибровка инерциальных навигационных систем на грубых стендах с учетом разнесения чувствительных масс ньютонометров // XX Санкт-Петербургская международная конференция по интегрированным навигационным системам. 2013. С. 104–107.
5. Браславский Д.А., Поликовский Е.Ф., Якубович A.M. Способ калибровки трехосного блока акселерометра. Заявка на авторское свидетельство № 2422425/23 с приоритетом от 24.11.1976.
6. Bolotin, Yu.V., Derevyankin, A.V., Matasov, A.I., Iteration Scheme for Accelerometer Unit Calibration by a Guaranteed Approach // Mechanics of Solids, 2008, vol. 43, no. 3, pp. 354–365.
7. Tedaldi, D., Pretto, A., Menegatti, E., A robust and easy to implement method for IMU calibration without external equipment // Proceedings – IEEE International Conference on Robotics and Automation, 2014, pp. 3042–3049, https://doi.org/10.1109/ICRA.2014.6907297/
8. Bolotin, Y., Savin, V., Turntable IMU calibration algorithm based on the Fourier transform technique // MDPI Sensors, 2023, 23(2):1045, https://doi.org/10.3390/s23021045/
9. Зорич В.А. Математический анализ. М.: Физматлит, 1984. 544 с.
10. x-io Technologies: https://x-io.co.uk/x-IMU/
11. Bar-Shalom, Y., Li, X., Kirubarajan, T., Estimation with applications to tracking and navigation. N.Y.: Wiley, Interscience, 2001.
Review
For citations:
Bolotin Yu.V., Savin V.A. On the Accuracy of the SINS Calibration Algorithm Based on the Fourier Transform. Comparison with the Cramer Rao Bound. Giroskopiya i Navigatsiya. 2025;33(4):64-77. (In Russ.) EDN: IAOXHN
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