Kinematic constrained navigation is a subset of model-aided navigation systems that is attractive because of its independence from extra hardware equipment. In this study, the error-based Kalman Filter is used for the data fusion process through feedback strategy, and kinematic constraints are utilized to improve Inertial Navigation System-Doppler Velocity Log (INS-DVL) navigation performance. Here, the pseudo-measurement method is used for applying kinematic constraints. Real offline data obtained from field tests of an instrumented vessel in shallow water demonstrate that applying kinematic constraints improves navigation performance and robustness against initial condition uncertainty. Repeatability of results is also investigated for three different maneuvers.