… filters some information about the unknown noise properties [1]–[4]. A limit of the stochastic
environment of Kalman filtering … output is considered as affected by additive noise, the input is …

… In this brief, we propose a new robust Kalman filter-based subspace tracking method in
impulsive noise to address the above limitations. We first adopt the Kalman filter, instead of the …

… of the problem and also with extremely high noise levels. Against this may be balanced a …
extended Kalman filter (EKF) method for frequency tracking in such high-noise environments. …

… [21] and [22] by extending Kalman filtering to the more general case of symmetrical noise
environments in order to include both Kalman and EIV filtering, as particular cases. This paper …

… noise environments have large positioning errors. Owing to the environmental noise, Kalman
filters (… RSSI will be interfered with by environmental noise, the Kalman filter (KF) is used to …

… The Kalman filter is the most common adaptive filter because of … and process noises are
Gaussian, the Kalman filter is the … noise environments the performance of the Kalman filter can …

… and the application of the Kalman filter in ANC may be easily … the Kalman filter fitted to
ANC is developed; both control filter … noise can be achieved in non-stationary environments, …

… experiments a tag was placed inside a ball traveling along a predefined trajectory in a noisy
environment (with many occluding objects), and the results did not show any loss of signal. …

… tries to do is obtain an "optimal" estimate of desired quantities from data provided by a noisy
environment, "optimal" meaning that it minimizes errors in some respect. There are many …

… Kalman Filter and Smoother (KFS) to tackle the problem of channel estimation in the presence
of impulsive noise … simultaneously the channel and impulsive noise by exploiting the joint …