This　paper　proposes　a　novel　zero　velocity　update　(ZUPT)　method　for　a　foot-mounted　pedestrian　navigation　system　(PNS).　First,　the　error　model　of　the　PNS　is　developed　and　a　Kalman　filter　is　built　based　on　the　error　model.　Second,　a　novel　zero　velocity　detection　algorithm　based　on　the　variations　in　speed　over　a　gait　cycle　is　proposed.　A　finite　state　machine　including　three　states　is　employed　to　model　a　gait　cycle.　The　state　transition　conditions　are　determined　based　on　speed　using　a　sliding　window.　Third,　the　ZUPT　software　flow　is　illustrated　and　described.　Finally,　the　performances　of　the　proposed　method　and　other　methods　are　examined　and　compared　experimentally.　The　experimental　results　show　that　the　mean　relative　accuracy　of　the　proposed　method　is　0.89%　under　various　motion　modes.