Accelerometers and gyroscopes are used in many smart weapon sensor suites. If dominant sensor error sources such as misposition. bias. cross axis sensitivity, and scale factor can be quickly and efficiently identified and loaded onto the sensor suites, quality feedback can be achieved at significant cost savings. The work reported here describes a relatively simple sensor calibration device suitable for a high volume production line environment. It consists of a freely vibrating table supported by a ball and socket joint in the middle and springs on the corners of the platform. Robotic devices are rigidly fastened to the vibrating table. Table orientation is measured with a six-camera. motion-capture system. Sensor suite and table orientation data are blended together in an extended Kalman filter to estimate accelerometer and gyroscope bias, cross axis sensitivity, and scale factor, along with accelerometer misposition. Experimental results indicate that a two-phase procedure including static and dynamic conditions was found to be most successful at identifying all calibration constants.