TWS tracking techniques based on adaptive Gaussian mixture model in phased array radar

In this paper, an on-line real-time tracking algorithm for radar image sequences is proposed. First, a GMM (Gaussian mixture model) is used to approximate values of a particular pixel of the radar image sequences, parameters of the GMM are updated each time. Then, we use a simple heuristic to hypothesize which Gaussian of the mixture is most likely to be part of the adaptive background model. After the background model is established, pixel values that don\´t match the pixel "background" Gaussians are grouped using connected components. Features of the targets such as center position, size, radial and angular velocities are also computed in the mean time. Finally, the connected components are tracked across frames using a Kalman filter-based tracker. The experimental result shows that the algorithm is robust in clutter and easy to implement on-line.