Under coloured noise, known modifications of the Kalman filter (KF) exist only for discrete‐
time state‐space models produced by the forward Euler (FE) method, which fits with …

This article introduces two new algorithms to accurately estimate the process noise
covariance of a discrete-time Kalman filter online for robust orbit determination in the …

This work develops algorithms for the estimation of sparse interpretable data-driven models.
Linear combination of linear and nonlinear basis functions is considered for candidate …

Most of the existing studies mainly consider the process and measurement noise as
Gaussian white noises, while a large number of systems are influenced by colored noises in …

The increasing availability of sensing techniques provides a great opportunity for engineers
to design state estimation methods, which are optimal for the system under observation and …

This letter develops the Kalman and unbiased finite impulse response filtering algorithms for
linear discrete-time state-space models with Gauss-Markov colored process noise (CPN) …

A-PL systems have been proposed as a means of augmenting GNSS in difficult areas where
GNSS-only navigation cannot be guaranteed, due to signal blockages, signal jamming, etc …

Obtaining reliable wind information is critical for efficiently managing air traffic and airport
operations. Wind forecasting has been considered one of the most challenging tasks in the …

Consensus filtering is an effective method for distributed state estimation of distributed
sensor networks and the assumption of white measurement noise is widely used. However …

With the advent of unmanned aerial vehicles (UAVs), a major area of interest in the research
field of UAVs has been vision-aided inertial navigation systems (V-INS). In the front-end of V …