To　address　the　asynchronicity　issue　of　the　multiple　sensor　data　of　the　Jiangyin　Bridge　measured　during　a　ship-bridge　collision,　a　state-space　(SS)　model　was　proposed　to　identify　the　time　lag　between　the　asynchronous　accelerations　at　different　locations　of　the　bridge.　First,　one　of　the　accelerations　was　randomly　chosen　as　a　reference　signal,　and　the　time　axes　of　the　rest　of　them　(termed　as　time　shifted　signals)　were　individually　shifted　relatives　to　that　of　the　reference　signal　with　a　series　of　time　instant.　Then,　the　SS　model　with　two　output　variables,　i.e.,　one　reference　signal　and　one　time　shifted　signal,　was　formulated　in　correspondence　with　each　time　instant.　The　system　matrices　were　computed　by　a　data-driven　stochastic　subspace　identification　algorithm　and　the　model　order　was　estimated　by　the　Akaike＇s　information　theoretic　criterion　(AIC)　and　final　prediction　error　(FPE).　If　the　two　accelerations　for　model　fitting　are　asynchronous,　errors　may　be　introduced　into　the　formulated　SS　model　and　its　loss　function　is　expected　to　be　greater　than　the　counterpart　obtained　with　synchronous　accelerations.　Therefore,　the　actual　time　lag　between　them　can　be　identified　from　the　time　instant　that　corresponds　to　the　minimum　of　loss　function.　To　evaluate　the　reproducibility　of　the　SS　model　for　time　synchronization,　asynchronous　acceleration　data　measured　two　hours　ahead　of　the　ship-bridge　collision　were　analyzed　as　well.　In　addition,　the　synchronous　acceleration　data　measured　long　after　the　ship-bridge　collision　were　utilized　to　examine　its　anti-false-identification　capability.　The　results　show　that　the　SS　model　achieves　a　satisfactory　performance　in　the　identification　of　the　time　lag　for　both　asynchronous　and　synchronous　measurement　data.　©　2018,　Editorial　Office　of　Journal　of　Vibration　and　Shock.　All　right　reserved.