  The upcoming PANDA experiment at FAIR will be among a new generation of
particle physics experiments to employ a novel event filtering system realised
purely in software, i.e. a software trigger. To educate its triggering
decisions, online reconstruction algorithms need to offer outstanding
performance in terms of efficiency and track quality. We present a method to
reconstruct longitudinal track parameters in PANDA's Straw Tube Tracker, which
is general enough to be easily added to other track finding algorithms that
focus on transversal reconstruction. For the pattern recognition part of this
method, three approaches are employed and compared: A combinatorial path
finding approach, a Hough transformation, and a recursive annealing fit. In a
systematic comparison, the recursive annealing fit was found to outperform the
other approaches in every category of quality parameters and reaches a
reconstruction efficacy of 95% and higher.
