I've come across the following resampling identity and was wondering if this is known since it seems rather natural. Take $X$ a two-sided Brownian motion conditioned to always stay below $1$. (So if you take $Y$ and $\tilde Y$ two independent Bessel(3) processes with initial condition $1$, one can set $X_t = 1-Y_t$ for $t \ge 0$ and $X_t = 1-\tilde Y_{-t}$ for $t \le 0$.) Let now $A = \{t\in\mathbb{R} : X_t \ge \sup_s X_s - 1\}$, pick a point $t^\ast$ uniformly at random in $A$ (according to normalised Lebesgue measure), and set $X^\ast_t = X_{t+t^\ast} - X_{t^\ast}$. The claim is that $X^\ast$ then has the same law as $X$.
Is this known and does it have a name? It's presumably known to someone like Pitman and there are various well known decomposition results about Bessel(3) processes and Brownian motion, but I wasn't able to find a reference for this one...
Edit: A similar identity is true if one gives $X$ a linear drift $-\gamma |t|$, but then $t^\ast$ has to be picked according to the (random) probability measure on $A$ with weight proportional to $e^{\gamma X_t}$.