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processor. Such drivers are specific
for the module and include the
communication protocol as well.
Choices need to be made for the
hardware layer (e.g. I2C, SPI, UART)
and the communication protocol.
The communication protocols used
by some modules are flexible in
terms of output configuration and/
or integration level. For example, the
communication protocol of Fairchild’s
FMT1000 series is implemented for
low-level binary communication, for
C/C++ interfaces and as DLL/.so for
Windows/Linux. Ready-to-run sample
code is available for ARM
®
mbed™.
Test and Calibration
System integrators face several
challenges when mounting MEMS on
a board. For instance, the soldering
process may influence the factory
(statistical) calibration. A module,
in which the inertial sensors are
mounted, doesn’t have these
detrimental effects.
The calibration parameters in discrete
inertial sensors are statistical values.
This means that the variability is
significant. Accelerometer biases of
specifications is often required. Next
is the need for knowledge of MEMS,
sensors and sensor fusion, which is
also time-consuming.
Another challenge in the quickly
changing landscape of MEMS sensors
is that keeping track of changes and
EOL/PCN-notices by vendors also
consumes valuable time.
Dedicated MCU
Retrieving data from the MEMS
sensors is the first step. The next step
is to find an MCU to process this data.
This requires making estimations to
determine the required RAM and
program memory, necessitating
advanced knowledge of the sensor
fusion algorithm, OS, drivers and
signal processing. The type of
processor selected has a significant
impact on system architecture, and
without experience in designing an
IMU and associated signal processing
and sensor fusion, this can be a long
and complex process.
Signal Processing
Signal processing is the next step
in converting the MEMS signals
to a sensible output. For motion
tracking, the user is often interested
in low-bandwidth signals. Yet, a high
bandwidth is required to compensate
for vibrations and coning/sculling
errors. A signal processing pipeline
needs to be optimized for the
anticipated motion. Also, since every
MEMS sensor is different, the signal
processing pipeline should be tailored
to the specific MEMS sensor to make
the best use of its capabilities. An
incorrectly designed signal processing
pipeline will negatively affect the
performance of the module’s output.
OS drivers and communication
To communicate with the module,
there needs to be drivers for
the host, typically an application