Instrumentation on a research aircraft includes sensors that measure accelerations, rates, and positions associated with the translational motion of the c.g. and the rotational motion about the c.g., as well as the magnitude and orientation of the air-relative velocity. Kinematic relationships among these quantities can be used to check that the measurements are mutually consistent. An analysis of this type is called a data compatibility analysis or a data consistency check.

If all the measurements were perfect, the data compatibility analysis would show that the kinematic relationships are perfectly satisfied by the sensor measurements. In practice, each sensor measurement has both systematic and random errors. The kinematic relationships are used as a tool to quantify these instrumentation errors and correct the measured data from the sensors for systematic errors. This is an important task, which results in a kinematically consistent data set with improved accuracy. A consistent and accurate data set is a prerequisite for the model structure determination and parameter estimation stages of the system identification process.

Measurements of control surface deflections, power settings, and pilot inputs are notably absent from the foregoing discussion. These measurements cannot be checked against others, because there are no kinematic relationships between these measurements and others in the data set. Consequently, the discussion that follows only applies for measurements associated with the rigid-body motion of the aircraft, which can be checked for compatibility with other measurements.