Optimization approach to adapt Kalman filters for the real-time application of accelerometer and gyroscope signals' filtering

Kownacki, Cezary

doi:10.1016/j.dsp.2010.09.001

Cited by 56 publications

(31 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For acceleration, which varies significantly with time, the noise reduction becomes much more challenging. Kownacki investigated such problems using the Kalman filter, though the model was built with the assumption of constant acceleration [13]. A conflict between the output signal noise level and filter response rate was discussed.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

et al. 2016

Sensors

View full text Add to dashboard Cite

Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy.

show abstract

Section: Introductionmentioning

confidence: 99%

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

et al. 2016

Sensors

View full text Add to dashboard Cite

show abstract

“…Lo cual hace necesario la implementación de filtros que permitan minimizar los efectos indeseados causados por las perturbaciones externas ajenas a las señales involucradas en el sistema. Una estrategia muy utilizada consiste en el filtro de Kalman, el cual actualmente se encuentra en un sinnúmero de aplicaciones tales como el modelamiento de espacio de estados [1], procesamiento de datos biomecánicos [2], estimación de sistemas de control de tráfico [3], control de posición en interferometría láser [4], filtrado de señales de acelerómetros y giroscopios [5] y control de bombas centrífugas de agua [6], entre otros. Si bien la aplicación de las estrategias descritas anteriormente suministra una estimación aceptable del sistema objeto de estudio, la implementación de los algoritmos demanda sistemas robustos de procesamiento, lo cual pone en riesgo la operación en tiempo real del estimador cuando se desea modelar sistemas dinámicos en plena operación.…”

Section: Introductionunclassified

Metodología para la Estimación de Parámetros en Tiempo Real mediante Filtros de Kalman y Mínimos Cuadrados

Bravo¹,

Arias²,

Salazar³

2013

Iteckne

View full text Add to dashboard Cite

“…The filter is used to minimize the mean of the squared error. The filter has expanded its application to position and orientation tracking, image processing filter and navigation system [11].…”

Section: Kalman Filtermentioning

confidence: 99%

A Study of State Estimation Algorithms in an OktoKopter

Quadri¹,

Sidek²,

Abdullah³

2014

IJUNESST

View full text Add to dashboard Cite

show abstract

Optimization approach to adapt Kalman filters for the real-time application of accelerometer and gyroscope signals' filtering

Cited by 56 publications

References 8 publications

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

Metodología para la Estimación de Parámetros en Tiempo Real mediante Filtros de Kalman y Mínimos Cuadrados

A Study of State Estimation Algorithms in an OktoKopter

Contact Info

Product

Resources

About