Systems for data processing, anaylsis and representation

Allam, Mosaad; Plunkett, Gordon

Bibliographic data

Monograph

Persistent identifier:: 1067490280

Title:: Systems for data processing, anaylsis and representation

Sub title:: ISPRS Commission II Symposium : June 6 - 10, Ottawa, Canada

Scope:: 1 Online-Ressource (XX, 530 Seiten)

Year of publication:: 1994

Place of publication:: Ottawa

Publisher of the original:: The Surveys, Mapping and Remote Sensing, Natural Resources Canada

Identifier (digital):: 1067490280

Illustration:: Illustrationen

Signature of the source:: ZS 312(30,2)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Allam, Mosaad; Plunkett, Gordon

Corporations:: Symposium Systems for Data Processing, Analysis and Representation, 1994, Ottawa; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis; Kanada, Surveys, Mapping and Remote Sensing Sector

Adapter:: Symposium Systems for Data Processing, Analysis and Representation, 1994, Ottawa; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis; Kanada, Surveys, Mapping and Remote Sensing Sector

Founder of work:: Symposium Systems for Data Processing, Analysis and Representation, 1994, Ottawa; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis; Kanada, Surveys, Mapping and Remote Sensing Sector

Other corporate:: Symposium Systems for Data Processing, Analysis and Representation, 1994, Ottawa; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis; Kanada, Surveys, Mapping and Remote Sensing Sector

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: [Tuesday, June 7, 1994]

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: [Session C-1 WG II/1 - Real-Time Mapping Technologies - Applications]

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: GUIDING SHIPS ON WATERWAYS M. Sandler, U. Kabatek, R. Neul, E. D. Gilles

Document type:: Monograph

Structure type:: Chapter

algorithms. The matching algorithms themselves are part of the block comparison in figure 10. The dif- ference signals are weighted according to the actual situation and the accuracy of the measurements and are used as corrections on the model world. This is for example performed within the update steps of the Kalman filter discussed in section 6. Thus the model world is driven to converge towards the real world. The advantage of this model based processing scheme stems from the fact that the model world sim- ulated on the computer provides considerably more detailed information of the ship and its environment than the real world sensors themselves. As explained in the previous sections, a precise estimate of the own ship's position, a detailed reconstruction of the navi- gation environment and a dependable observation of the actual traffic situation can be obtained from the sensor processing level. Therefore all information required at the control level is provided. The most important task of this level is the trajectory genera- tion for the own ship determining the control inputs to engine and rudder. 8 PLANNING AN ACTUAL TRAJECTORY Trajectory generation is done in two steps: First, an optimal trajectory for upstream and downstream travel is computed off-line, assuming the absence of foreign ships. However, time invariant environmental constraints as well as ship dependent dynamics are taken into account. In addition to this, it is possible to compute a set of trajectories for different water levels. These trajectories are stored in the electronic chart as ideal guiding lines. For the case that the actual traffic situation results in interferences with other ships, a second step of on-line trajectory recomputation has to follow in the sequel. This second step uses the ideal guiding lines and the limits of navigable water as well as traffic rules stored in the chart. This a-priori information is combined with the results of the multiple-target track- ing algorithm. Here the navigator may also interact, telling the system how foreign ships are to be passed and how they should be encountered. This allows to incorporate information resulting from the commu- nication with navigators of other ships or from other external sources. All these sources of information are combined in the on-line computation. The algorithm employed starts from a coarse grid superimposed over the waterway. A risk function is assigned to every point in the grid. This function consists of a constant part derived from the chart information and a time-varying part repre- senting the results of the multiple-target tracking al- gorithm. A foreign ship is taken into account at a predicted place of encounter. The second step in the on-line calculations is a search algorithm resulting in possibly several trajectories through the grid and a 74 cumulative risk for each trajectory. Finally, one of these trajectories is selected as input for the control task. The control task is implemented as a linear state controller designed for variable command control [3]. This task generates the signals acting on the rudder and engine throttle. For large ships in narrow canals this controller is not sufficient. Current research fo- cuses on the development of new control concepts incorporating results from nonlinear and predictive control theory. References [1] Blackman, S. S.: Multiple-Target Tracking with Radar Applications. Artech House, Norwood, MA, 1986. [2] Gelb, A. (Hrsg.): Applied Optimal Estimation. The M.I.T. Press, Cambridge, Massachusetts, 1974. [3] Gilles, E. D., Neul, R., Plocher, T., und Kabatek, U.: Ein integriertes Navigationssystem für Bin- nenschiffe. Automatisierungstechnik 38 (1990), S. 202-209, 247—257. [4] Kabatek, U., Sandler, M., Neul, H., und Gilles, E. D.: Eine elektronische FluBkarte als Wissens- basis in einem integrierten Navigationssystem. Zeitschrift für Vermessungswesen 117 (1992), S. 35-45. [b] Neul, R.: Positionsbestimmung eines navigieren- den Schiffes durch kartengestützte Radarbildver- arbeitung, volume 323 of Fortschittsberichte VDI Reihe 8. VDI-Verlag, Düsseldorf, 1993. [6] Plocher, T.: Einsatz von Kalman-Filtern und Bayesschen Schátzverfahren zur Verfolgung be- wegter Objekte in Bildsequenzen, volume 320 of Fortschittsberichte VDI Reihe 8. VDI-Verlag, Düsseldorf, 1993. [7] Plocher, T. und Gilles, E. D.: Rekursive Objek- tverfolgung in Bildsequenzen. Automatisierung- stechnik 40 (1992), S. 14—20,59-63. [8] Reid, D.: An algorithm for tracking multiple tar- gets. IEEE Trans. Automat. Contr. 24(12) (1979), S. 843-854. Cet a serva navig emplo laser combi élect navir navir moind capte élect mesur d'un cible et év du ss traje métho La Xst navig circu

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