Self-calibrating inertial measurement system and method

An in-use self-calibrating inertial measurement system configured to provide on-the-fly calibration of one or more sensors of the system to thereby to minimize errors associated therewith, the system comprising:

• at least one sensor cluster operably mounted to a vehicle that is a platform capable of moving, the at least one sensor cluster comprising a plurality of inertial sensors for:
• sampling, during movement of said at least one sensor cluster and said vehicle, at least one of acceleration and angular velocity of said at least one sensor cluster with respect to each axis in a plurality of axes of a reference frame of a coordinate system;
• and
• producing individual outputs associated with said at least one of acceleration and angular velocity, at least three of said inertial sensors sampling with respect to each same respective said axis;
• and
• a processing engine operably coupled to the at least one sensor cluster and configured to receive said individual outputs from the plurality of inertial sensors, said processing engine comprising a hardware processor coupled to non-transitory, computer-readable memory containing instructions executable by the processor to cause the processing engine to use said individual outputs acquired, during movement of said at least one sensor cluster and said vehicle, to dynamically self-calibrate, during movement of said inertial measurement system and said-vehicle, a parameter that includes at least a scale factor, wherein said dynamic self-calibration comprises:
• for each particular sensor type, combining said individual outputs of a particular sensor type, per said axis, to respectively yield a combined output;
• detecting a specific diverging individual output by at least one of inter-comparison between said individual outputs and its respective said combined output, according to a majority of non-diverging individual outputs;
• determining a re-calibration parameter for said specific diverging individual output according to said majority of non-diverging individual outputs, based on an assessment of a range of possible systematic errors potentially associated with causing the specific individual output of a particular sensor type to diverge from a respective combined output, said systematic errors being selected from the group consisting of bias error, gain error, non-linearity error, mutual alignment error, thermal gain error, and thermal bias error, said assessment for said systematic errors comprises:
• 1) determining whether an error of an inertial sensor associated with the specific diverging individual output is present by running one or more of a bias error model, scale factor error model, non-linearity error model, mutual alignment error model, time synchronization error model, and performing statistical analysis to identify statistically significant correlations of rapid changes in gain, bias, and/or non-orthogonality coinciding with temperature changes;
• and
• 2) determining an extent of any errors determined to be present comprising at least one of a quantity, magnitude, and value with respect to a given error model and/or statistical analysis;
• and
• calibrating said specific diverging individual output by applying said determined re-calibration parameter to said specific diverging individual output thereby updating, during operation and during movement of said at least one sensor cluster and said vehicle, said parameter with said re-calibration parameter of said specific individual output detected to diverge, wherein application of said re-calibration parameter reduces systematic errors identified as being associated with causing the specific individual output to diverge.