Kalman Filter in Interest Rate Models

A couple questions regarding the use of Kalman filtering in estimating parameters of short rate models:

1) In Duan & Simonato (1995), which seems to be one of the earliest applications of the Kalman filter to short rate models, they state on page 5,

"To deal with the estimation problem, it is reasonable to assume that the yields for different maturities are observed with errors of unknown magnitudes"

Note yields are the output of the observation equation. Mathematically, they mean the yield $R$ at time $t$ for a $T$-bond may be written as $$R_t(r_t, T) = -\frac{1}{T-t} \ln P_t(r_t,T) + \epsilon_t, \qquad (1)$$ where $r_t$ is the short rate value (the output of the state equation) at time $t$ and $\epsilon_t$ is the "error of unknown magnitude." Why is there an error term? The relationship (1) without the $\epsilon_t$ is simply the definition of the yield. Are we supposed to assume the "error" represents things like illiquidity or quotes with finite decimals?

2) With the exception of the Vasicek model, most short rate models are non-Gaussian. In filtering parlance, the conditional distribution of the current state given the past states is non-Gaussian. How is Kalman filter justified in this case, given it assumes both the state and the observation equations are Gaussian?