Quantifying Differential Phase Distortion in Dual Sourced Sensor Fusion Pipelines
Dual sourced sensor phase distortion corrupts fusion pipelines through unmodeled group delay mismatches, requiring dynamic transfer function verification.
Bias Drift
Zero Offset
Measurement against a zero-input baseline reveals low-frequency statistical instability that shifts sensor baseline output independent of physical input stimulus. Inertial sensor evaluation defines bias drift as the temporal migration of mean output offset under constant environmental conditions. Micro-electro-mechanical gyroscopes and accelerometers suffer from internal strain changes that alter sensor output baselines over extended operating hours.
Systematic zero-point shifts degrade dead-reckoning positioning accuracy unless corrected by filtering algorithms.
Thermal Hysteresis
Internal material stresses and electronic component heating cause baseline offsets to follow non-repeatable paths during temperature ramp cycles. This thermal lag creates offset uncertainty that standard static temperature compensation curves cannot eliminate.
Allan Variance
Characterization of low-frequency offset instability employs two-cluster variance processing across growing integration time windows to isolate flicker noise from random walk components. Logarithmic plots of cluster variance identify minimum error regions where bias stability reaches its optimal value before flicker noise dominates long-term output drift. System engineers select optimal calibration update rates by identifying the minimum point on the generated variance curve.
Calibration Interval
Operational drift limits dictate the maximum elapsed time allowed between sensor zeroing routines in continuous monitoring applications. Field recalibration resets the baseline calculation to suppress accumulated positioning error before system accuracy bounds are exceeded.