Therefore, the filter like the Maximum Correntropy Kalman Filter (MCKF) could not achieve the good performance under some complex non-Gaussian noise.

Kalman filters have long stood as a cornerstone in the field of target tracking and state estimation, providing an optimally recursive solution for estimating the state of dynamic systems in the ...

ECEA 5850 Kalman-Filter Boot Camp and State-Estimation Application ECEA 5851 Kalman Filter Deep Dive and Target-Tracking Application Learning Outcomes Execute the joint EKF and joint SPKF code ...

This course introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. It develops the background theoretical topics in state ...

Multi-target tracking algorithms and filters underpin a broad spectrum of modern sensing applications by providing robust methodologies to estimate the trajectories of multiple moving objects amid ...

EnSilica has launched a Kalman Filter acceleration IP core for use in situational awareness radar sensors for advanced driver assistance systems (ADAS), ...

The Kalman Filter acceleration IP core also provides a generic algorithm framework for fusing measurements from different sensors into a single target track. For a typical automotive radar system, ...