Probabilistic and Statistical Methods - Information Fusion in Signal and Image Processing - page 73

Figure 6.3. Detection images by Bayesian inference of the classes city, river and C 3

in the scene of Vignola by fusing 6 SPOT satellite images

- delays (radar, sonar, interferometers, etc.);
- Doppler shifts (differentials);
- intensity variations, image deformations, etc.

We note that these measurements are very diverse. One common trait, however,
is that they have a non-linear dependence on parameters defining the moving object's
trajectory. In many cases, we will call system's state the vector of parameters, instan-
taneous or not, defining the trajectory. These parameters can be the moving object's
position, its speed at each instant or at a reference time.