Jan Wendel | Karlsruhe Institute of Technology (KIT) (original) (raw)

Papers by Jan Wendel

Research paper thumbnail of Tightly coupled GPS/INS integration for missile applications

Aerospace Science and Technology, 2004

An approach to enhance the performance of tightly coupled GPS/INS systems is described. First, th... more An approach to enhance the performance of tightly coupled GPS/INS systems is described. First, the advantages of tightly coupled systems compared to loosely coupled systems are clarified. Then, it is shown in hardware-in-the-loop tests and in a test drive that processing time differenced carrier phase measurements instead of delta-range measurements results in an increased velocity and attitude accuracy for the tightly coupled system, which is of great importance in the beginning of a time interval with purely inertial navigation, e.g. when GPS is lost due to jamming. A measurement equation is derived allowing to process the time differenced carrier phase measurements in the navigation Kalman filter. Finally, the proposed method is applied to missile navigation systems, where significant vibrations enter the inertial sensor data.  2004 Elsevier SAS. All rights reserved.

Research paper thumbnail of An integrated GPS/MEMS-IMU navigation system for an autonomous helicopter

Aerospace Science and Technology, 2006

During the last years, there is an increasing demand for cheap and easy to operate platforms for ... more During the last years, there is an increasing demand for cheap and easy to operate platforms for surveillance and reconnaissance purposes. Therefore, the development of micro aerial vehicles is receiving an increasing attention. However, VTOL-MAVs often show an inherent instability that makes at least an automatic stabilization necessary, because otherwise the operator would not be able to keep these vehicles airborne. This requires the availability of navigation information, especially the vehicle's attitude has to be known. This paper addresses the development of an integrated navigation system based on MEMS inertial sensors and GPS for a VTOL-MAV. Special attention is paid to the handling of GPS outages. While usually periods without GPS aiding can be bridged using the unaided strapdown solution, the poor quality of the MEMS inertial sensors prohibits this approach here. Therefore, during GPS outages the accelerometer data is interpreted as approximate measurements of the local gravity vector. Additionally, the usage of a magnetometer providing measurements of the Earth's magnetic field is motivated and discussed. Finally, flight test results illustrate the performance of the resulting system, proving that the achieved attitude accuracy is sufficient for the automatic control of the MAV. This holds in situations with permanent GPS loss and dynamic maneuvering, too.

Research paper thumbnail of Post-processing GNSS/INS Measurements Using a Tightly Coupled Fixed-Interval Smoother Performing Carrier Phase Ambiguity Resolution

This paper describes a high accurate tightly cou- pled, differentially corrected GNSS/INS system ... more This paper describes a high accurate tightly cou- pled, differentially corrected GNSS/INS system for survey appli- cations in post-processing mode. A Kalman filter is described, that calculates the navigation solution as well as the the GNSS carrier phase integer ambiguities. The LAMBDA method is used to resolve the integer ambiguities. To achieve an optimum solution based on all measurement data

Research paper thumbnail of Development of a GPS/INS/MAG navigation system and waypoint navigator for a VTOL UAV

Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions... more Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path the range of possible applications is widened significantly. This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory. This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and interferences from surrounding electronic devices as well as ferrite metals. The described integration concept with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS outages which is mandatory for the flight control of the UAV. In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the UAV to operate in a semi-autonomous mode position hold as well an complete autonomous waypoint mode. In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are shown.

Research paper thumbnail of Detection and tracking of objects in an image sequence captured by a VTOL-UAV

This paper focusses on the automated detection and tracking of moving objects in a camera sequenc... more This paper focusses on the automated detection and tracking of moving objects in a camera sequence, that is provided by a small, electrically powered four-rotor helicopter in a hover-and-stare scenario. Two different algorithms for identifying independently moving areas are investigated and compared. The first approach bases on the previous compensation of the camera movement by estimation of homographies. Moving regions are extracted by robust background subtraction. The second approach bases on a dense optical flow field and needs no stabilization: Single points are identified that move not consistently with the background plane. These points are merged into objects by a cluster analysis algorithm. Furthermore, a strategy for tracking these objects over time is described including a Kalman filter. Due to several reasons, not every extracted area corresponds to an independently moving object and a heuristic rule set is used to sort artifacts out. Experimental results on in-flight images are presented and the performances of the developed algorithms are compared. Finally, first steps towards a geographic location of the tracked objects are described.

Research paper thumbnail of Using natural features for vision based navigation of an indoor-VTOL MAV

Aerospace Science and Technology, 2009

The use of natural features for vision based navigation of an indoor Vertical-Take-Off-and-Landin... more The use of natural features for vision based navigation of an indoor Vertical-Take-Off-and-Landing (VTOL) Micro Aerial Vehicle (MAV) named Air-Quad is presented. Air-Quad is a small four-rotor helicopter developed at the ITE. Such a helicopter needs reliable attitude information. The measurements of the used MEMS gyroscopes and accelerometers are corrupted by strong noise. To be useful, the MEMS sensors have to be part of an integrated navigation system with aiding through complementary sensors like GPS or the computer vision module presented here. In the computer vision module, feature points are detected and tracked through the image sequence. The relative rotation and translation of the camera are estimated using the two-dimensional motion of the feature points. The three-dimensional points in the scene are modeled with the image coordinates of their first sighting and their inverse depths. Only these inverse depths are estimated for the feature points. An efficient sparse bundle adjustment algorithm is used to improve the estimation of the scene structure and the navigation solution. It is shown that the use of the computer vision module greatly improves the navigation solution compared to a solution based only on MEMS sensors.

Research paper thumbnail of Tightly coupled GPS/INS integration for missile applications

Aerospace Science and Technology, 2004

An approach to enhance the performance of tightly coupled GPS/INS systems is described. First, th... more An approach to enhance the performance of tightly coupled GPS/INS systems is described. First, the advantages of tightly coupled systems compared to loosely coupled systems are clarified. Then, it is shown in hardware-in-the-loop tests and in a test drive that processing time differenced carrier phase measurements instead of delta-range measurements results in an increased velocity and attitude accuracy for the tightly coupled system, which is of great importance in the beginning of a time interval with purely inertial navigation, e.g. when GPS is lost due to jamming. A measurement equation is derived allowing to process the time differenced carrier phase measurements in the navigation Kalman filter. Finally, the proposed method is applied to missile navigation systems, where significant vibrations enter the inertial sensor data.  2004 Elsevier SAS. All rights reserved.

Research paper thumbnail of An integrated GPS/MEMS-IMU navigation system for an autonomous helicopter

Aerospace Science and Technology, 2006

During the last years, there is an increasing demand for cheap and easy to operate platforms for ... more During the last years, there is an increasing demand for cheap and easy to operate platforms for surveillance and reconnaissance purposes. Therefore, the development of micro aerial vehicles is receiving an increasing attention. However, VTOL-MAVs often show an inherent instability that makes at least an automatic stabilization necessary, because otherwise the operator would not be able to keep these vehicles airborne. This requires the availability of navigation information, especially the vehicle's attitude has to be known. This paper addresses the development of an integrated navigation system based on MEMS inertial sensors and GPS for a VTOL-MAV. Special attention is paid to the handling of GPS outages. While usually periods without GPS aiding can be bridged using the unaided strapdown solution, the poor quality of the MEMS inertial sensors prohibits this approach here. Therefore, during GPS outages the accelerometer data is interpreted as approximate measurements of the local gravity vector. Additionally, the usage of a magnetometer providing measurements of the Earth's magnetic field is motivated and discussed. Finally, flight test results illustrate the performance of the resulting system, proving that the achieved attitude accuracy is sufficient for the automatic control of the MAV. This holds in situations with permanent GPS loss and dynamic maneuvering, too.

Research paper thumbnail of Post-processing GNSS/INS Measurements Using a Tightly Coupled Fixed-Interval Smoother Performing Carrier Phase Ambiguity Resolution

This paper describes a high accurate tightly cou- pled, differentially corrected GNSS/INS system ... more This paper describes a high accurate tightly cou- pled, differentially corrected GNSS/INS system for survey appli- cations in post-processing mode. A Kalman filter is described, that calculates the navigation solution as well as the the GNSS carrier phase integer ambiguities. The LAMBDA method is used to resolve the integer ambiguities. To achieve an optimum solution based on all measurement data

Research paper thumbnail of Development of a GPS/INS/MAG navigation system and waypoint navigator for a VTOL UAV

Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions... more Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path the range of possible applications is widened significantly. This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory. This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and interferences from surrounding electronic devices as well as ferrite metals. The described integration concept with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS outages which is mandatory for the flight control of the UAV. In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the UAV to operate in a semi-autonomous mode position hold as well an complete autonomous waypoint mode. In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are shown.

Research paper thumbnail of Detection and tracking of objects in an image sequence captured by a VTOL-UAV

This paper focusses on the automated detection and tracking of moving objects in a camera sequenc... more This paper focusses on the automated detection and tracking of moving objects in a camera sequence, that is provided by a small, electrically powered four-rotor helicopter in a hover-and-stare scenario. Two different algorithms for identifying independently moving areas are investigated and compared. The first approach bases on the previous compensation of the camera movement by estimation of homographies. Moving regions are extracted by robust background subtraction. The second approach bases on a dense optical flow field and needs no stabilization: Single points are identified that move not consistently with the background plane. These points are merged into objects by a cluster analysis algorithm. Furthermore, a strategy for tracking these objects over time is described including a Kalman filter. Due to several reasons, not every extracted area corresponds to an independently moving object and a heuristic rule set is used to sort artifacts out. Experimental results on in-flight images are presented and the performances of the developed algorithms are compared. Finally, first steps towards a geographic location of the tracked objects are described.

Research paper thumbnail of Using natural features for vision based navigation of an indoor-VTOL MAV

Aerospace Science and Technology, 2009

The use of natural features for vision based navigation of an indoor Vertical-Take-Off-and-Landin... more The use of natural features for vision based navigation of an indoor Vertical-Take-Off-and-Landing (VTOL) Micro Aerial Vehicle (MAV) named Air-Quad is presented. Air-Quad is a small four-rotor helicopter developed at the ITE. Such a helicopter needs reliable attitude information. The measurements of the used MEMS gyroscopes and accelerometers are corrupted by strong noise. To be useful, the MEMS sensors have to be part of an integrated navigation system with aiding through complementary sensors like GPS or the computer vision module presented here. In the computer vision module, feature points are detected and tracked through the image sequence. The relative rotation and translation of the camera are estimated using the two-dimensional motion of the feature points. The three-dimensional points in the scene are modeled with the image coordinates of their first sighting and their inverse depths. Only these inverse depths are estimated for the feature points. An efficient sparse bundle adjustment algorithm is used to improve the estimation of the scene structure and the navigation solution. It is shown that the use of the computer vision module greatly improves the navigation solution compared to a solution based only on MEMS sensors.