In urban mobile mapping activity, odometer data is used to complement global navigation satellite system (GNSS)/ inertial navigation system (INS) data in positioning & orientation systems (POSs). We analyze the two error sources in POS, misalignment and odometer scale factor error, and their propagation in ECEF. A cascaded extend Kalman filter (EKF) was designed to estimate errors without changing the GNSS/INS EKF, after which is the INS/Odometer (ODO) EKF. Navigation errors and misalignment, and scale factor error are modeled as system states in two EKFs, respectively. Given GNSS continuous observation and fixed ambiguity, the INS was effectively calibrated by GNSS/INS EKF and its position increment was used as the measurement of the INS/ODO EKF. Meanwhile, the calibrated odometer was used as an observation for INS when the GNSS experienced loss of lock. These tests indicate that the algorithm can calibrate misaligned angles of the POS and the scale factor of the odometer. Consequently, positioning accuracy was significantly improved when GNSS experienced loss of lock. Accuracy could be restricted in half a meter when two minutes GNSS gap happened in the process of mobile mapping with the use of a smoothing Kalman filter.