Suppose I have an object that I am tracking with moving sensors using a basic Kalman Filter (for example, think of a ship being tracked by satellites). In the simplest case where the sensors are stationary and the object moves in a straight line, the constant velocity (CV) motion model works well. However, when sensors also start to move in different linear trajectories, the CV motion model does not perform well resulting in filter divergence as the assumption of constant velocity is broken.
Is there a way to salvage the CV model by adjusting it or the incoming measurements so that the model does not diverge? If not, is there a more preferable motion model to use or a different method to deal with motion introduced by the sensor? I am considering the constant acceleration (CA) model, TURN model (constant turn rate), and the Integrated Ornstein-Uhlenbeck (IOU) motion model. The IOU model seems promising as it does account for varying velocity with parameters determining some behaviors of the distribution of velocity, but I am unsure if it would require adaptive filtering with changing the parameters based on the particular sensor.
I have not yet tried to use a nonlinear Kalman filter, like a Sigma Point Kalman Filter (UKF), to see how this would perform. If this is the appropriate solution, I am uncertain of a justification why this would even be a remedy for the issue. Naturally, I would like to extend my above example to the case where I have nonlinear motion for the object I am tracking, but I wanted to solve the linear target motion case first without moving to a nonlinear Kalman filter.
I am aware a Particle Filter may be a solution to this problem, but I would like to stick to a filter with complexity more comparable to a Kalman Filter.
Any input on how to apply a Kalman filter with moving target and moving sensors would be greatly appreciated. I am new to Kalman filtering, so any references where I could read about filtering with this particular issues would also be welcome!
EDIT: as requested, the sensor paths for majority of the sensors are known, and some others have sensor paths that are unknown.
The information I have about the object from each sensor is it’s position (Latitude, Longitude, Altitude). Some, but not all, sensors give me velocity (speed and course).