Abstract: A method, apparatus, and computer program product for joint kinematic and feature tracking are presented. Kinematic measurements and feature/class measurements regarding an object are received from a sensor. A probabilistic argumentation operation is performed on the feature/class measurements using information from a knowledge base and a track file ect to generate feature track likelihood scores regarding likely tracks for the object. Kinematic track likelihood scores are generated based on the kinematic measurements and the track file. Joint track likelihood scores are generated based on the feature track likelihood scores and the kinematic track likelihood scores. Joint track likelihood scores are used to generate a multi-frame track measurement association to determine a most likely track for the object. The track file is continually updated with the most likely track for the object, so that the most likely trajectory of the object is obtained.

Abstract: An apparatus and method provides application specific multidimensional information to an application running on a user computing device from a plurality of member documents electronically extracted from a library of electronically searchable documents. An information extractor is adapted to extract occurrences of prospective representations of dimensions of application specific multidimensional information and occurrences of non-application specific multidimensional information from the member documents. Also, an encoder is adapted to encode the occurrences of prospective dimensions of application specific and non-application specific multidimensional information contained in member documents. A member document identifier determines document formatting and decides whether to proceed with further processing. An information verification unit optionally verifies the extraction of application specific multidimensional information from the member documents.

Abstract: A method, apparatus, and computer program product for joint kinematic and feature tracking are presented. Kinematic measurements and feature/class measurements regarding an object are received from a sensor. A probabilistic argumentation operation is performed on the feature/class measurements using information from a knowledge base and a track file ect to generate feature track likelihood scores regarding likely tracks for the object. Kinematic track likelihood scores are generated based on the kinematic measurements and the track file. Joint track likelihood scores are generated based on the feature track likelihood scores and the kinematic track likelihood scores. Joint track likelihood scores are used to generate a multi-frame track measurement association to determine a most likely track for the object. The track file is continually updated with the most likely track for the object, so that the most likely trajectory of the object is obtained.

Abstract: A method and apparatus for accurate estimation of forward path geometry of a vehicle based on a two-clothoid road model are presented. Road data provided by a camera or a radar system is collected 200 and a full measurement transfer function of the two-clothoid model is computed 202. The near-range and the far-range clothoid coefficients are estimated simultaneously 204; and the forward path of the vehicle is estimated using the data provided by the two-clothoid model 206.

Abstract: The present invention provides a method and apparatus for estimation of vehicle forward path geometry utilizing an adaptive Kalman filter bank and a two-clothoid road model. The invention provides that each of a plurality of Kalman filters, utilizing the latest available measurement vector Yk at time k, estimates the state vector Xk and error covariance matrix Pk. The outputs of filter 504a, 504b, and 504c denoted as as Xkj and Pkj, are provided to a plurality of weighting elements, which calculate weight factors, Wkj 506a, 506b, and 506c for each filter. The weight factor of each filter is the probability that the upcoming road geometry matches the road model hypothesized in the filter. After being assigned a weighted value, the weighted value road models are fused in a fusion element 508, and a weighted output road geometry model is provided.

Abstract: An apparatus and method are disclosed for electronically extracting application specific multidimensional information from a library of electronically searchable documents, wherein at least one dimension of the information is a category, which may comprise an automatic document miner in communication with the contents of the library and adapted to electronically extract relevant documents from the library; an E-Space filter creator adapted to create from the extracted relevant documents a category specific representation of the extracted relevant documents comprising the E-Space filter; a document selector adapted to utilize the E-Space filter to separate the extracted relevant documents into member documents and non-member documents and to discard the non-member documents; and an application specific multidimensional information extractor adapted to extract occurrences of application specific multidimensional information from the member documents.

Abstract: Apparatus and method for providing application specific multi-dimensional information to an application running on a user computing device, wherein at least one dimension of the information is a category, from a plurality of member documents electronically extracted from a library of electronically searchable documents, may comprise an application specific multidimensional information extractor to extract occurrences of prospective representations of dimensions of application specific multidimensional information and to extract occurrences of non-application specific multidimensional information; and, an encoder adapted to encode the occurrences of prospective dimensions of application specific multidimensional information and non-application specific multidimensional information contained in member documents according to a dimension specific coded representation of each dimension of application specific multidimensional information and a non-application specific coded representation of each non-application s

Abstract: The disclosed invention provides a method and apparatus for accurate estimation of forward path geometry of a vehicle based on a two-clothoid road model. Road data provided by a camera or a radar system is collected 200 and a full measurement transfer function of the two-clothoid model is computed 202. The near-range and the far-range clothoid coefficients are estimated simultaneously 204; and the forward path of the vehicle is estimated using the data provided by the two-clothoid model 206.

Abstract: A system and method for automatic weapon allocation and scheduling of the present invention. The inventive method includes the steps of providing data with respect to threats, weapons, weapon allocation options; weapon allocation rules; and temporally dependent constraints with respect thereto; evaluating the data; and temporally allocating the weapons to the threats automatically in accordance with the evaluation. The invention computes the optimal pairing and the best time to deploy each weapon system against threat(s) it is paired with in arriving at the pairing. This results in an optimal assignment where weapon resource constraints are not exceeded and therefore guarantee availability of sufficient resources for engagement of every threat that is paired with a weapon system.

Abstract: A system and method for automatic weapon allocation and scheduling of the present invention. The inventive method includes the steps of providing data with respect to threats, weapons, weapon allocation options; weapon allocation rules; and temporally dependent constraints with respect thereto; evaluating the data; and temporally allocating the weapons to the threats automatically in accordance with the evaluation. The invention computes the optimal pairing and the best time to deploy each weapon system against threat(s) it is paired with in arriving at the pairing. This results in an optimal assignment where weapon resource constraints are not exceeded and therefore guarantee availability of sufficient resources for engagement of every threat that is paired with a weapon system.