  Land vehicle navigation based on inertial navigation system (INS) and
odometers is a classical autonomous navigation application and has been
extensively studied over the past several decades. In this work, we seriously
analyze the error characteristics of the odometer (OD) pulses and investigate
three types of odometer measurement models in the INS/OD integrated system.
Specifically, in the pulse velocity model, a preliminary Kalman filter is
designed to obtain accurate vehicle velocity from the accumulated pulses; the
pulse increment model is accordingly obtained by integrating the pulse
velocity; a new pulse accumulation model is proposed by augmenting the
travelled distance into the system state. The three types of measurements,
along with the nonhonolomic constraint (NHC), are implemented in the standard
extended Kalman filter. In view of the motion-related pulse error
characteristics, the multiple model adaptive estimation (MMAE) approach is
exploited to further enhance the performance. Simulations and long-distance
experiments are conducted to verify the feasibility and effectiveness of the
proposed methods. It is shown that the standard pulse velocity measurement
achieves the superior performance, whereas the accumulated pulse measurement is
most favorable with the MMAE enhancement.
