Sensorlinearisation

Sensor linearisation refers to the process of removing or reducing the nonlinear relation between a sensor's raw output and the quantity being measured, so that the reported value is approximately proportional to the measurand over a specified range. Linearisation is typically achieved by applying a mapping to the sensor signal, either in hardware or in software, to approximate a linear response or to express the measurement in standard units.

Common approaches include polynomial or curve fitting to a known sensor characteristic, which yields a function that maps the raw output to the desired quantity; piecewise linearisation, which subdivides the measurement range and uses simple linear relations within each segment; and look-up tables with interpolation (linear or spline) to invert the nonlinear response. Calibration data are generated by exposing the sensor to known reference values and recording the outputs.

Digital correction is often implemented in microcontrollers, digital signal processors, or within the sensor module. The chosen method is integrated with the measurement chain, and linearised results are typically used to drive control loops, display units, or data logs. Linearisation can also be used to reduce the burden on downstream processing by delivering a near-linear signal.

Key considerations include the required accuracy, speed, temperature dependence, hysteresis, and long-term drift. Higher-order models can improve fit but may increase noise sensitivity or introduce instability if not carefully regularised. The method should preserve monotonicity and ensure stability across the operating range and temperature.

Applications span process control, metrology, instrumentation, automotive sensors, aerospace, and robotics, where linearised sensor outputs simplify control algorithms and improve measurement integrity.