الفهرس 
Cover EnglishOnly 14 pages are availabe for public view
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Abstract
Development of a laser scanning and processing system which is both robust and capable of maintaining obstacle avoidance logic for sea unmanned surface vehicles. So web design of data fusion architectures and propose an architecture that combines most of the advantages of previously published architectures, so we Design and implementation of a multisensory data fusion algorithm for laser, radar, lidar, laser range finder and sonar sensors also we use the normal navigation sensors as encompassing commercial global positioning system (GPS) and gyro in a common container and the application of multisensor data fusion theory to integrate the GPS and gyro signals. To build a robust obstacle avoidance system. The data resources are the GPS, the gyro, the automatic identification system (AIS) contacts, the received automated radar plotting aid (ARPA) contacts, and the digital nautical charts (DNC) which is built for this purpose. And analysis and testing of the proposed system against simulation data collected from realistic scenarios. Unmanned surface vessels (USVs) are expected to perform key commercial, naval, and scientific tasks in the sea space. Such vessels can either be remotely controlled by a human operator or perform their tasks autonomously. In autonomous mode, a USV depends on reliable and high-quality position and velocity measurements in order to control its own motion satisfactorily. These measurements can be obtained by high-cost integrated navigation systems that employ a suite of different sensor systems to achieve the required degree of quality. However, such navigation systems are typically too expensive for use with small USVs. Consequently, a need arises to develop low-cost systems that meet the performance requirements of typical USV applications. This thesis introduces the development of a low-cost integrated navigation system.