  A reliable self-contained navigation system is essential for autonomous
vehicles. Based on our previous study on Wheel-INS \cite{niu2019}, a
wheel-mounted inertial measurement unit (Wheel-IMU)-based dead reckoning (DR)
system, in this paper, we propose a multiple IMUs-based DR solution for the
wheeled robots. The IMUs are mounted at different places of the wheeled
vehicles to acquire various dynamic information. In particular, at least one
IMU has to be mounted at the wheel to measure the wheel velocity and take
advantages of the rotation modulation. The system is implemented through a
distributed extended Kalman filter structure where each subsystem
(corresponding to each IMU) retains and updates its own states separately. The
relative position constraints between the multiple IMUs are exploited to
further limit the error drift and improve the system robustness. Particularly,
we present the DR systems using dual Wheel-IMUs, one Wheel-IMU plus one vehicle
body-mounted IMU (Body-IMU), and dual Wheel-IMUs plus one Body-IMU as examples
for analysis and comparison. Field tests illustrate that the proposed multi-IMU
DR system outperforms the single Wheel-INS in terms of both positioning and
heading accuracy. By comparing with the centralized filter, the proposed
distributed filter shows unimportant accuracy degradation while holds
significant computation efficiency. Moreover, among the three multi-IMU
configurations, the one Body-IMU plus one Wheel-IMU design obtains the minimum
drift rate. The position drift rates of the three configurations are 0.82\%
(dual Wheel-IMUs), 0.69\% (one Body-IMU plus one Wheel-IMU), and 0.73\% (dual
Wheel-IMUs plus one Body-IMU), respectively.
