A novel application of adaptive filtering for initial alignment of Strapdown Inertial Navigation System

Malakar, Bidhan; Roy, B. K.

doi:10.1109/cscita.2014.6839257

Cited by 9 publications

(6 citation statements)

References 12 publications

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“…For an improvement in the accuracy of the present TCAS installed in IR, a BRLS‐based adaptive multisensor data fusion technique is proposed to estimate the position and velocity errors. Earlier works are also carried out for improving the alignment accuracy of the strapdown inertial navigation system and may be found in [61, 62].…”

Section: Proposed System For Localisation Of Railway Vehiclesmentioning

confidence: 99%

Adaptive multisensor data fusion technique for train localisation and detection of accidental train parting

Malakar¹,

Roy²

2018

IET Radar, Sonar & Navigation

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Section: Proposed System For Localisation Of Railway Vehiclesmentioning

confidence: 99%

Adaptive multisensor data fusion technique for train localisation and detection of accidental train parting

Malakar¹,

Roy²

2018

IET Radar, Sonar & Navigation

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“…Various (6k±1)th harmonics filtering methods have been proposed in [37]- [45]. Resonant filter, as one of the promising solutions, has been widely used in grid-connected inverter control.…”

Section: Introductionmentioning

confidence: 99%

“…Two feedback regulation mechanisms are involved in the BRLS adaptive filter, which improves the harmonic component detection accuracy. In [45], the BRLS adaptive filter is used for the initial alignment of an inertial navigation system, which improves the initial alignment accuracy and ensures a fast convergence rate of the strap down inertial navigation system. In [46], the BRLS adaptive filter has been applied in grid-connected inverter control due to its capability of detecting and suppressing the selected harmonic component.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Position Sensorless Control Using Bilinear Recursive Least Squares Adaptive Filter for Interior Permanent Magnet Synchronous Motor

Huang

Liu

et al. 2020

IEEE Trans. Power Electron.

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In the back electromotive force (EMF)-based sensorless control of interior permanent magnet synchronous motor (IPMSM), the inverter nonlinearity and flux linkage spatial harmonics will possibly give rise to (6k±1)th harmonics in the estimated back-EMF, especially the 5th and 7th harmonics. Those harmonics will consequently introduce (6k)th harmonic ripples to the estimated rotor position, especially the 6th harmonic component. In order to solve this problem, a bilinear recursive least squares (BRLS) adaptive filter is proposed and integrated into a sliding mode position observer to suppress the dominant harmonic components in the estimated back-EMF and as a result, the accuracy of the estimated rotor position can be greatly improved. A unique feature of the BRLS adaptive filter is its ability to track and suppress the specified harmonic components in different steady state and dynamic operational conditions. The proposed method can compensate harmonic ripples caused by the inverter nonlinearity and machine spatial harmonics at the same time; this method is also robust to machine parameter variation and the BRLS algorithm itself is machine parameter independent. The implementation of the proposed BRLS filter in the sensorless control of IPMSM is explained in details in this paper. The enhanced drive performances using the BRLS filter have been thoroughly validated in different steady state and dynamic operational conditions on a 1.5kW IPMSM sensorless drive. 1

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“…Точная выставка состоит в определении малых углов между опорной системой координат и системой координат объекта, которые вычисляются с использованием информации от различных датчиков. Использование при этом фильтра Калмана позволяет получить оценки погрешностей ориентации, ошибок северной и восточной составляющих скорости [10][11][12][13][14][15][16].…”

Section: Introductionunclassified

Initial Alignment of the Attitude and Heading Reference System

Avrutov¹,

Buhaiov²,

Meleshko³

2018

Nauk. Visti KPI

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Проблематика. При выставке бесплатформенных инерциальных навигационных систем основными проблемами являются точность и время выставки. В статье обсуждается вопрос точности выставки малогабаритной бескарданной курсовертикали, а именно точность режима гирокомпасирования. Цель исследования. Разработка математической модели погрешности режима гирокомпасирования. Методика реализации. Для разработки математической модели погрешности режима гирокомпасирования на основе выходных сигналов акселерометров и гироскопов получена матрица направляющих косинусов. С использованием элементов матрицы направляющих косинусов методом варьирования получена полная математическая модель погрешности гирокомпасирования, которая зависит от дрейфов гироскопов, погрешностей акселерометров и погрешности определения широты места. Результаты исследования. Главным результатом исследования является вывод полной формулы погрешности гирокомпасирования. Выводы. Наибольшее влияние на погрешность гирокомпасирования оказывает дрейф гироскопов. Поэтому для повышения точности выставки курсовертикали необходимо использовать более точные гироскопы. Ключевые слова: гироскоп; акселерометр; выставка в горизонте; курсовертикаль; инерционный измерительный модуль.

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A novel application of adaptive filtering for initial alignment of Strapdown Inertial Navigation System

Cited by 9 publications

References 12 publications

Adaptive multisensor data fusion technique for train localisation and detection of accidental train parting

Adaptive multisensor data fusion technique for train localisation and detection of accidental train parting

Enhanced Position Sensorless Control Using Bilinear Recursive Least Squares Adaptive Filter for Interior Permanent Magnet Synchronous Motor

Initial Alignment of the Attitude and Heading Reference System

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