This　article　addresses　the　issue　of　the　adaptive　fractional-order　fault-tolerant　coordinated　tracking　control　(FO-FTCTC)　for　multiple　unmanned　aerial　vehicles　and　unmanned　ground　vehicles　with　fixed-time　prescribed　performance　subjected　to　actuator　and　sensor　faults　under　deception　attacks.　Deception　attacks　disrupt　the　sensor　network,　making　the　output　and　state　unavailable.　To　achieve　the　tracking　control　of　the　system,　the　coordinate　transformation　method　is　developed,　in　which　the　attack　gains　are　considered　and　the　compromised　states　are　utilized　to　design　a　control　scheme.　Then,　the　fixed-time　prescribed　performance　function　(PPF)　is　illustrated　to　transform　the　coordinated　tracking　errors　(CTEs)　into　another　error　variable　so　that　the　unconventional　errors　are　limited　to　the　prescribed　range.　Next,　the　sliding-mode　surface　is　built　by　utilizing　the　errors　and　fractional　calculus.　In　addition,　the　radial　basis　function　neural　network　is　utilized　to　deal　with　the　unknown　term.　Based　on　the　error,　the　adaptive　FO-FTCTC　scheme　by　utilizing　the　radial　basis　function　neural　network　(RBFNN),　fractional　calculus,　and　fixed-time　PPF　with　prescribed　performance　can　be　achieved,　which　can　strengthen　the　system　performance.　Based　on　the　Lyapunov　function　approach,　all　vehicles　can　coordinately　track　their　desired　references　and　CTEs　can　be　bounded　within　the　prescribed　boundary.　Finally,　simulation　studies　are　provided　to　verify　the　validity　of　the　developed　FO-FTCTC　scheme.