Development of frontal impact airbag sensor algorithms/calibrations requires crash signals, which can be obtained from vehicle crash testing and/or CAE simulations. This paper presents the development of finite element sensor models to generate CAE simulated crash pulses/signals at the sensing location during frontal impacts. These signals will be evaluated for potential used in the airbag sensor algorithm/calibration. The study includes (1) use of the concept of frequency analysis to determine a cut-off frequency for extracting representative signals at the sensor locations for various carlines during frontal crashes, (2) assessment of current CAE capability in the frequency domain to see whether FEA models can predict sensor pulses up to this cut-off frequency, (3) identification of areas for potential further improvements in FEA methods, (4) development of signal processing to remove high frequency noise from CAE simulated pulses, and (5) development of a single quality sensor model. These methodologies are applicable to both car and truck programs. In addition, a single car crash/sensor model will be used to demonstrate generation of simulated sensor signals for calibration in a single-point sensing system. Simulated CAE singles include pulses from various frontal impact modes (fixed barrier at 90o and pole impact) for a spectrum impact velocities ranging from 8 mph to 35 mph. Comparisons between the simulated and test sensor signals will be presented.