An attractor conforms coherent structures that are not always visible in raw dataseries. Finding these requires data processing to, for example, define high-order gradients spanning in different dimensions enabled by the own nature of the dynamical process.

You may see the method in the paper written by B Krauskopf and H M Osinga

Localization means discovering a region in the phase space, where the attractor is located. Usually, such a region lies in the basin of attraction. So, any point from the region tends to the attractor that allows to numerically compute it. Since for hidden attractors, their basins of attraction do not intersect with unstable manifolds of equilibria, one should develop an intuition for discovering such attractors. There are many developed approaches.

I recommend the following two surveys.