Add to ORKGSensor data fusion algorithms based on H-Infinity filters are investigated for two sensor situation. Their performance is evaluated when there is data loss in either of the13; sensors. Results of validation are presented for two local filters tracking a moving object
The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to...
"This dissertation takes a filtering oriented point of view and systematically addresses modeling, f...
Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous...
Sensor data fusion algorithms based on H-Infinity filters are investigated for two sensor situation....
A sensor data fusion algorithm based on H-infinity filters is investigated for a two-sensor situatio...
This study is related to the use of adaptive H-infinity filter for multi sensor data fusion ( ...
In this paper factorization filtering, fusion filtering strategy and related algorithms are presente...
Abstract. In this paper factorization filtering, fusion filtering strategy and related algorithms ar...
In this paper Kalman filter and Gain fusion based multi-sensor data13; fusion algorithms are investi...
The application of information-based filtering algorithms for sensor fusion is studied. Both linear ...
Multi-sensor tracking potentially has many advantages over single sensor tracking. This report evalu...
Sensor fusion is a method of integrating signals from multiple sources. It allows extracting informa...
Sensor data fusion is essential for environmental perception within smart traffic applications. By u...
This paper evaluates the performances of H-infinity filter in differential time of arrival (TDoA) lo...
Several non-linear state estimation methods such as extended Kalman filter, cubature Kalman filter, ...
The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to...
"This dissertation takes a filtering oriented point of view and systematically addresses modeling, f...
Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous...
Sensor data fusion algorithms based on H-Infinity filters are investigated for two sensor situation....
A sensor data fusion algorithm based on H-infinity filters is investigated for a two-sensor situatio...
This study is related to the use of adaptive H-infinity filter for multi sensor data fusion ( ...
In this paper factorization filtering, fusion filtering strategy and related algorithms are presente...
Abstract. In this paper factorization filtering, fusion filtering strategy and related algorithms ar...
In this paper Kalman filter and Gain fusion based multi-sensor data13; fusion algorithms are investi...
The application of information-based filtering algorithms for sensor fusion is studied. Both linear ...
Multi-sensor tracking potentially has many advantages over single sensor tracking. This report evalu...
Sensor fusion is a method of integrating signals from multiple sources. It allows extracting informa...
Sensor data fusion is essential for environmental perception within smart traffic applications. By u...
This paper evaluates the performances of H-infinity filter in differential time of arrival (TDoA) lo...
Several non-linear state estimation methods such as extended Kalman filter, cubature Kalman filter, ...
The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to...
"This dissertation takes a filtering oriented point of view and systematically addresses modeling, f...
Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous...