This　study　proposes　an　image-based　visual　servoing　(IBVS)　method　based　on　a　velocity　observer　for　an　unmanned　aerial　vehicle　(UAV)　for　tracking　a　dynamic　target　in　Global　Positioning　System　(GPS)-denied　environments.　The　proposed　method　derives　the　simplified　and　decoupled　image　dynamics　of　underactuated　UAVs　using　a　constructed　virtual　camera　and　then　considers　the　uncertainties　caused　by　the　unpredictable　rotations　and　velocities　of　the　dynamic　target.　A　novel　image　depth　model　that　extends　the　IBVS　method　to　track　a　rotating　target　with　arbitrary　orientations　is　proposed.　The　depth　model　ensures　image　feature　accuracy　and　image　trajectory　smoothness　in　rotating　target　tracking.　The　relative　velocities　of　the　UAV　and　the　dynamic　target　are　estimated　using　the　proposed　velocity　observer.　Thanks　to　the　velocity　observer,　translational　velocity　measurements　are　not　required,　and　the　control　chatter　caused　by　noise-containing　measurements　is　mitigated.　An　integral-based　filter　is　proposed　to　compensate　for　unpredictable　environmental　disturbances　in　order　to　improve　the　anti-disturbance　ability.　The　stability　of　the　velocity　observer　and　IBVS　controller　is　analyzed　using　the　Lyapunov　method.　Comparative　simulations　and　multistage　experiments　are　conducted　to　illustrate　the　tracking　stability,　anti-disturbance　ability,　and　tracking　robustness　of　the　proposed　method　with　a　dynamic　rotating　target.　©　2023