System　identification　provides　an　effective　way　to　predict　the　ship　manoeuvrability.　In　this　paper　several　measures　are　proposed　to　diminish　the　parameter　drift　in　the　parametric　identification　of　ship　manoeuvring　models.　The　drift　of　linear　hydrodynamic　coefficients　can　be　accounted　for　from　the　point　of　view　of　dynamic　cancellation,　while　the　drift　of　nonlinear　hydrodynamic　coefficients　is　explained　from　the　point　of　view　of　regression　analysis.　To　diminish　the　parameter　drift,　reconstruction　of　the　samples　and　modification　of　the　mathematical　model　of　ship　manoeuvring　motion　are　carried　out.　Difference　method　and　the　method　of　additional　excitation　are　proposed　to　reconstruct　the　samples.　Using　correlation　analysis,　the　structure　of　a　manoeuvring　model　is　simplified.　Combined　with　the　measures　proposed,　support　vector　machines　based　identification　is　employed　to　determine　the　hydrodynamic　coefficients　in　a　modified　Abkowitz　model.　Experimental　data　from　the　free-running　model　tests　of　a　KVLCC2　ship　are　analyzed　and　the　hydrodynamic　coefficients　are　identified.　Based　on　the　regressive　model,　simulation　of　manoeuvres　is　conducted.　Comparison　between　the　simulation　results　and　the　experimental　results　demonstrates　the　validity　of　the　proposed　measures.　©　2017　Elsevier　Ltd