  Discovering sequences with desired properties has long been an interesting
intellectual pursuit. In pulse compression radar (PCR), discovering phase codes
with low aperiodic autocorrelations is essential for a good estimation
performance. The design of phase code, however, is mathematically non-trivial
as the aperiodic autocorrelation properties of a sequence are intractable to
characterize. In this paper, we put forth a genetic algorithm (GA) approach to
discover new phase codes for PCR with the mismatched filter (MMF) receiver. The
developed GA, dubbed GASeq, discovers better phase codes than the state of the
art. At a code length of 59, the sequence discovered by GASeq achieves a
signal-to-clutter ratio (SCR) of 50.84, while the best-known sequence has an
SCR of 45.16. In addition, the efficiency and scalability of GASeq enable us to
search phase codes with a longer code length, which thwarts existing deep
learning-based approaches. At a code length of 100, the best phase code
discovered by GASeq exhibit an SCR of 63.23.
