2023 - Research.com Electronics and Electrical Engineering in United States Leader Award
2008 - IEEE Dennis J. Picard Medal for Radar Technologies and Applications “For contributions to techniques for radar target tracking in clutter.”
Yaakov Bar-Shalom mainly investigates Algorithm, Artificial intelligence, Tracking, Control theory and Sensor fusion. His work focuses on many connections between Algorithm and other disciplines, such as Detection theory, that overlap with his field of interest in Machine learning. The various areas that Yaakov Bar-Shalom examines in his Artificial intelligence study include Clutter, Computer vision and Pattern recognition.
His Tracking research also works with subjects such as
Yaakov Bar-Shalom mainly focuses on Algorithm, Control theory, Artificial intelligence, Tracking and Estimator. His Algorithm research incorporates elements of Radar, Upper and lower bounds, Covariance and Sensor fusion. His study on Control theory is mostly dedicated to connecting different topics, such as Estimation theory.
The Artificial intelligence study combines topics in areas such as Clutter, Computer vision and Pattern recognition. Yaakov Bar-Shalom is interested in Tracking system, which is a field of Tracking. His Estimator research includes elements of Likelihood function, Observability and Mathematical optimization.
His primary scientific interests are in Algorithm, Tracking, Control theory, Artificial intelligence and Cramér–Rao bound. The concepts of his Algorithm study are interwoven with issues in Covariance, Estimator, Mathematical optimization, Radar and Monte Carlo method. In general Tracking study, his work on Tracking system often relates to the realm of Field, thereby connecting several areas of interest.
His Observability and Kalman filter study in the realm of Control theory interacts with subjects such as Fuel gauge. The study incorporates disciplines such as Clutter, Computer vision and Pattern recognition in addition to Artificial intelligence. His research in Cramér–Rao bound intersects with topics in Point spread function, Least squares and Noise.
His main research concerns Control theory, Tracking, Artificial intelligence, Algorithm and Battery. He is interested in Kalman filter, which is a branch of Control theory. Yaakov Bar-Shalom has researched Tracking in several fields, including Estimator, Real-time computing, Filter and Noise.
Yaakov Bar-Shalom combines subjects such as Trajectory, Propagation delay and Sensor fusion with his study of Filter. His work deals with themes such as Clutter, Computer vision and Pattern recognition, which intersect with Artificial intelligence. His Algorithm research is multidisciplinary, incorporating perspectives in Mathematical optimization and Radar tracker.
Estimation with Applications to Tracking and Navigation: Theory, Algorithms, and Software
Yaakov Bar-Shalom;T. Kirubarajan;Xiao Rong Li.
Estimation with Applications to Tracking and Navigation
Yaakov Bar-Shalom;Thiagalingam Kirubarajan;X.-Rong Li.
Tracking and data association
Y Bar-Shalom;T. E Fortmann.
Mathematics in science and engineering (1988)
Estimation and Tracking: Principles, Techniques, and Software
Yaakov Bar-Shalom;Xiao-Rong Li.
The interacting multiple model algorithm for systems with Markovian switching coefficients
H.A.P. Blom;Y. Bar-Shalom.
IEEE Transactions on Automatic Control (1988)
Tracking and data association
Sonar tracking of multiple targets using joint probabilistic data association
T. Fortmann;Y. Bar-Shalom;M. Scheffe.
IEEE Journal of Oceanic Engineering (1983)
Interacting multiple model methods in target tracking: a survey
E. Mazor;A. Averbuch;Y. Bar-Shalom;J. Dayan.
IEEE Transactions on Aerospace and Electronic Systems (1998)
Tracking in a cluttered environment with probabilistic data association
Yaakov Bar-Shalom;Edison Tse.
Multitarget-multisensor tracking: Advanced applications
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