  This paper derives a general expression for the Cram\'er-Rao bound (CRB) of
wireless localization algorithms using range measurements subject to bias
corruption. Specifically, the a priori knowledge about which range measurements
are biased, and the probability density functions (PDF) of the biases are
assumed to be available. For each range measurement, the error due to
estimating the time-of-arrival of the detected signal is modeled as a Gaussian
distributed random variable with zero mean and known variance. In general, the
derived CRB expression can be evaluated numerically. An approximate CRB
expression is also derived when the bias PDF is very informative. Using these
CRB expressions, we study the impact of the bias distribution on the mean
square error (MSE) bound corresponding to the CRB. The analysis is corroborated
by numerical experiments.
