1. Integrated Smart Sensor Calibration Abstract Including at the sensor or sensor interface chip a programmable calibration facility, the calibration can easily be automated and executed for a batch of sensors at a time, thus minimizing time and costs A calibration method and options for integration in the smart sensor concept, in hardware as well as software An advantage, a step-by-step approach, not need a large matrix of calibration data

2. Introduction Integrated Smart Sensors (4 integrated functions) Analog sensor readout and signal conditioning A/D conversion, to provide a digital output signal A bus interface, to simplify communication to microcontrollers, PC’s and other devices Calibration of the sensor tranfer curve, preferably a digitally programmable calibration Calibration of Smart Sensors An analog calibration circuit, a limited accuracy bu large bandwidth and high processing speed A digital calibration facility implementatioin, high accuracy but limited processing speed To reduce costs, it is important to minimize the number of reference measurements, the communication and the computation power for each sensor to be calibrated.

3. 1-D Polynomial Calibration Method Calibration Principle Most methods rely on collecting a complete set of measrement data to calculate a correction formula or lookup table. As for this proposed method, each calibration measurement can be used directly to calculate one programmable coefficient in a correcion function, which can then immediately be used to correct the sensor output. The next calibration makes use of this corrected sensor signal. Each succeeding correction is applied in such a way that the previous calibrations remain undisturebed. Translating, rotating, and bending, more calibrations can be done in the same manner to further linearize the sensor transfer function. Simulation showes, for 3 or more calibration steps a good lineariztion is obtained, when the first calibration point is at one end of the sensor operation range, the second point at the other end of the range, and further points halfway between two previously selected points. Eq. 1-4, more mathematical details.

4. Implementation: analog signal processor for polynomial sensor calibration Fig.4, the signal flow diagram of a four-step polynomial correction. The diagram can become a repetitive chain as the dash-boxed part can be repeated to increase the order of the polynomial correction, which can be implemented in a software routine(microcontroller) or in hardware(either analog or digital). Fig.5, the block diagram of the analog signal processor Low-cost bipolar process All signals represented by differential currents Addtion/substraction done by connecting current signals, multiplication implemented in Gilbert Multiplier Current duplicator blocks (IV/VI convertor) Multiplying DAC (current-mode, 8bit, cascode dividers) Bandwidth in the order of 100KHz to 1MHz

5. Conlusion The proposed method doesn’t have the disadvantage of collecting a matrix of data first and then inverting it or use an iterative method to obtain the polynomial correction factors. Instead, it uses each calibration measurement to obtain one specific correction factor, at the first to correct the offset, at the second to correct gain, at the third to correct 2nd-order non-linearity, etc. Each calibration results in an additional correction term which is constructed in such a way that all previous calibrations remain undisturbed. This approach also applies for a 2-D calibration for sensors that suffer from cross-sensitivity to another parameter. The error correction is a repetitive procedure, which can be implemented in software as a small subroutine, or in hardware as a cascade, pipeline or a loop of the same building blocks.