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A combined algorithm for the loosely fused ultra wide band (UWB) and inertial navigation system (INS)-based meas-urements is designed under the indoor human navigation condi-tions with missing data. The scheme proposed fuses the INS- and UWB-derived positions via a data fusion filter. Since the UWB signal is prone to drift in indoor environments and its outage highly affects the integrated scheme reliability, we also consider the missing data problem in UWB measurements. To overcome this problem, the loosely-coupled INS/UWB-integrated scheme is augmented with a prediction option based on the predictive un-biased finite impulse response (UFIR) fusion filter. We show ex-perimentally that, the standard UFIR fusion filter has higher ro-bustness than the Kalman filter. It is also shown that the predict-ive UFIR fusion filter is able to produce an acceptable navigation accuracy under temporary missing UWB-data.