Online clutter estimation using a Gaussian kernel density estimator for multitarget tracking

In this study, the spatial distribution of false alarms is assumed to be a non‐homogeneous Poisson point (NHPP) process. Then, a new method is developed under the kernel density estimation (KDE) framework to estimate the spatial intensity of false alarms for the multitarget tracking problem. In the proposed method, the false alarm spatial intensity estimation problem is decomposed into two subproblems: (i) estimating the number of false alarms …