Figure 3.

An example of the PMFs defined by (10)–(15). Given an observation of $v\in \{\dot{d},\dot{p}\}$ or d, the functions model the probability that the observation was generated from the state pertaining to each function. (a) shows examples of velocity-based component PMFs (10)–(12) with parameter σ_v = 1. (b) shows examples of diameter-based component PMFs (13)–(15) with parameters σ_d = 1, μ_d = 8, and min_d = 0.