Reduce noise of sensor by combining two
Assuming that the sensors share the same characteristics, have the same timing (acceleration signals are aligned), the model with $y_1= x + n_1$ and $y_2= x + n_2$, $n_1$ and $n_2$ being uncorrelated noises of the same power, averaging them is a way to reduce the noise. The theory that asymptotically, averaging $N$ sensors reduce the variance by a factor of $N$, hence the noise amplitude by $\sqrt{N}$. For small $N=2$, and with quantization, one should not expect too much (since the asymptotic formula is not valid), but this can be tried, you may have nice surprise. If noise powers are different, this method can be improved to take this into account.

Further, this problem can be addressed as a form of source separation, for which many methods have been developed (independent component analysis, Non-negative matrix factorization, low-rank decomposition to name a few). The choice will depend on how much more information you have, and your algorithmic constraints.