Lockheed Martin Corporation

Peter N Stiles

Robert J Szczerba

Ira S Glickstein

Marc Blais

Ronald Vienneau

Mark Allstadt

John Moody

Stephen J DeMarco

Adam L Jung

Joel J Tleon

Chris A Bodenhorn

Dale E DelNero

Peggy J Galkowski

A system and method for efficient intervisibility determination. The intervisibility determination method of the present invention provides a multiple threat processing capability within a specified area of terrain using a common database. Computation is simplified through the method of processing data posts in the terrain elevation database. By taking integer steps and incrementing distance, x or y, and a predicted elevation value at each step, a small number of operations may be performed. Recomputing a change in elevation value may be reduced. An umbra database provides an enhanced look-up capability for displaying and updating the intervisibility display information. The systems and methods of the present invention may be suitable for use on a vehicle and in mission management activities.

Intervisibility determination

A system collaboratively and autonomously plans and controls a team of vehicles having subsystems within an environment. The system includes a mission management component, a communication component, a payload controller component, and an automatic target recognition component. The mission management component plans and executes a mission plan of the team and plans and executes tasks of the vehicles. The communication component plans communication and networking for the team. The communication component manages quality of service for the team. The communication component directs communication subsystems for the team and for the vehicles. The payload controller component directs and executes sensor subsystems for the team and for the vehicles. The automatic target recognition component processes and fuses information from the sensor subsystems and from the vehicles for use by the mission management component.

System for intelligently controlling a team of vehicles

A hybrid of grid-based and graph-based search computations, together with provision of a sparse search technique effectively limited to high-probability candidate nodes provides accommodation of path constraints in an optimization search problem in substantially real-time with limited computational resources and memory. A grid of best cost (BC) values are computed from a grid of map cost (MC) values and used to evaluate nodes included in the search. Minimum segment/vector length, maximum turn angle, and maximum path length along a search path are used to limit the number of search vectors generated in the sparse search. A min-heap is preferably used as a comparison engine to compare cost values of a plurality of nodes to accumulate candidate nodes for expansion and determine which node at the terminus of a partial search path provides the greatest likelihood of being included in a near-optimal complete solution, allowing the search to effectively jump between branches to carry out further expansion of a node without retracing portions of the search path. Capacity of the comparison engine can be limited in the interest of expediting of processing and values may be excluded or discarded therefrom. Other constraints such as approach trajectory are accommodated by altering MC and BC values in a pattern or in accordance with a function of a parameter such as altitude or by testing of the search path previously traversed.

Real-time mission adaptable route planner

A dynamic optimal sensor employment system and method is used for searching an area. Each time the sensor in the search vehicle is activated, the dynamic optimal sensor employment system (&ldquo;the system&rdquo;) determines which areas were searched at that moment. It does this by using a terrain database, information about the sensor state when it scanned (azimuth, elevation, mode, etc.), and a line-of-sight algorithm. The system determines this instantaneous coverage not only for the primary search vehicle, designated &ldquo;ownership&rdquo;, but also for other teammates who report scan information to ownship via digital messages. The system maintains a dynamic history of all areas (e.g. 30 meter by 30 meter square &ldquo;cells&rdquo; of ground) that have been searched. Each cell has a counter that indicates how many time it has been scanned, and each time cells are scanned with ownship or team sensors the counter is incremented. Cells that are too steep or otherwise non-trafficable by a land vehicle, such as a lake or a river, are marked ahead of time to indicate there is no need to search them. The system then dynamically determines what sensor activations are required to search the areas that are known to be trafficable but have not yet been scanned by ownship or teammates. Specifically, it determines the time, location, direction, field-of-view, and altitude that best satisfy an optimization criteria, and then automatically activates the sensor to generate this coverage.

Dynamic optimal sensor employment for searching an area

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Owego, NY, United States of America

Peter N Stiles