Hellas: obstacle warning system for helicopters

Schulz, Karl R.; Scherbarth, Stefan; Fabry, Uwe

doi:10.1117/12.476398

Cited by 18 publications

(8 citation statements)

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“…1, Fig. 2) based on a 1.5 µm erbium fiber system, is derived from the EADS HELLAS 3 family [9]. It is a two-dimensional scanning device for measuring the three-dimensional geometry of objects.…”

Section: Lasermentioning

confidence: 99%

Generation of efficient 2D templates from 3D multisensor data for correlation-based target tracking

Witte¹,

Armbruster²,

Jäger³

et al. 2008

Signal Processing, Sensor Fusion, and Target Recognition XVII

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The general demand for the prevention of collateral damages in military operations requires methods of robust automatic identification of target objects like vehicles especially during target approach. This requires the development of sophisticated techniques for automatic and semi-automatic interpretation of sensor data. In particular the automatic pre-analysis of reconnaissance data is important for the human observer as well as for autonomous systems. In the phase of target approach fully automatic methods are needed for the recognition of predefined objects. For this purpose appropriate sensors are used like imaging IR sensors suitable for day/night operation and laser radar supplying 3D information of the scenario. Classical methods for target recognition based on comparison with synthetic IR object models imply certain shortcomings, e.g. unknown weather conditions and the engine status of vehicles. We propose a concept of generating efficient 2D templates for IR target signatures based on the evaluation of a precise 3D model of the target generated from real multisensor data. This model is created from near-term laser range and IR data gathered by reconnaissance in advance to gain realistic and up-to-date target signatures. It consists of the visible part of the object surface textured with measured infrared values. This enables recognition from slightly differing viewing angles. Our test bed is realized by a helicopter equipped with a multisensor suite (laser radar, imaging IR, GPS, and IMU). Results are demonstrated by the analysis of a complex scenario with different vehicles

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Section: Lasermentioning

confidence: 99%

Generation of efficient 2D templates from 3D multisensor data for correlation-based target tracking

Witte¹,

Armbruster²,

Jäger³

et al. 2008

Signal Processing, Sensor Fusion, and Target Recognition XVII

View full text Add to dashboard Cite

show abstract

“…1, Fig. 2) based on a 1.5 µm erbium fiber system, is derived from the EADS HELLAS 2 family [8]. It is a two-dimensional scanning device for measuring the three-dimensional geometry of objects.…”

Section: Lasermentioning

confidence: 99%

A novel segmentation method for object tracking and recognition

et al. 2007

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The increasing demand for the protection of persons and facilities requires the application of sophisticated technologies for surveillance and object tracking. For this purpose appropriate sensors are used like imaging IR sensors suitable for day/night operation and laser radar supplying 3D information of the scenario. In this context there is a requirement of automatic and semi-automatic methods supporting the human observer in his decision-making process. A prevalent task is automatic tracking of striking objects like vehicles or individual persons in an image sequence during a time slice. Classical methods are based on template matching implying certain shortcomings concerning homogeneous background or passing objects occluding the target object. The authors propose a new concept for generating templates for IR target signatures based on the interpretation of laser range data in order to optimize the tracking process. The testbed is realized by a helicopter equipped with a multisensor suite (laser radar, imaging IR, GPS, IMU). Results are demonstrated by the analysis of an exemplary data set. A vehicle situated in a complex scenario is acquired by a forward moving sensor platform and is tracked robustly by the proposed method

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“…The 3D points are calculated with respect to sensor pose and measured time-of-flight of the laser pulses. The laser scanner itself is an 1.5 µm erbium fiber system, derived from the EADS HELLAS family [7], which covers a field-of-view of 14.4 degrees in horizontal and vertical direction with a resolution of 128x128 pixels and a scan rate of about 4 Hz. The infrared images are taken with an AIM 8-10 µm FPA sensor (640x480 pixels) and a slightly wider field-of-view which overlaps that of the laser.…”

Section: Introductionmentioning

confidence: 99%

Imaging sensor fusion and enhanced vision for helicopter landing operations

2006

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An automatic target recognition system has been assembled and tested at the Research Institute for Optronics and Pattern Recognition in Germany over the last years. Its multisensorial design comprises off-the-shelf components: an FPA infrared camera, a scanning laser radar und an inertial measurement unit. In the paper we describe several possibilities for the use of this multisensor equipment during helicopter missions. We discuss suitable data processing methods, for instance the automatic time synchronization of different imaging sensors, the pixel-based data fusion and the incorporation of collateral information. The results are visualized in an appropriate way to present them on a cockpit display. We also show how our system can act as a landing aid for pilots within brownout conditions (dust clouds caused by the landing helicopter).

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Hellas: obstacle warning system for helicopters

Cited by 18 publications

References 0 publications

Generation of efficient 2D templates from 3D multisensor data for correlation-based target tracking

Generation of efficient 2D templates from 3D multisensor data for correlation-based target tracking

A novel segmentation method for object tracking and recognition

Imaging sensor fusion and enhanced vision for helicopter landing operations

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