I'm using a bayesian framework to estimate the pose of a moving vehicle with a single camera. The state vector of the vehicle is $$ X = \begin{bmatrix} x\\ y\\ \theta\\ \end{bmatrix}$$ where $x$ and $y$ are the coordinates in the plan and $\theta$ is the heading angle. The state vector $X$ is constatntly updated in the prediction step.
In the correction step, an image retrieval algorithm compares the current image to a database of images by a measure based on pixel by pixel differences. Then, it returns the best match which is an image of index $j\in N$ together with its pose, the measurement $z$ $$ z= \begin{bmatrix} x_{m}\\ y_{m}\\ \theta_{m}\\ \end{bmatrix}$$.
Let's say my current image is actually the image of index $j=1000$ but the algorithm returns $j=1005$, how to evaluate the uncertainty? How to calculate the covariance matrix of this measurement?