In this paper a nonlinearity compensation algorithm based on the extended Kalman filter is proposed to improve the measurement accuracy of a heterodyne laser interferometer. The heterodyne laser interferometer is used for ultra-precision measurements such as those used in semiconductor manufacturing. However the periodical nonlinearity property caused by frequency-mixing restricts the accuracy of the nanometric measurements. In order to minimize the effect of the nonlinearity, the measurement process of the laser interferometer is modeled as a state equation and the extended Kalman filtering approach is applied to the process. The effectiveness of our proposed algorithm is demonstrated by comparing the results of the algorithm with experimental results for the laser system.

The heterodyne laser interferometer acts as an ultra-precise measurement apparatus in semiconductor manufacture. However the periodical nonlinearity property caused from frequency cross-talk is an obstacle to improve the high measurement accuracy in nanometer scale. In order to minimize the nonlinearity error of the heterodyne interferometer, we propose a frequency cross-talk compensation algorithm using an artificial intelligence method. The feedforward neural network trained by back-propagation compensates the nonlinearity error and regulates to minimize the difference with the reference signal. With some experimental results, the improved accuracy is proved through comparison with the position value from a capacitive displacement sensor.

This paper presents a power amplifier (PA) designed as a part of a transceiver front-end fabricated in 130-nm SiGe BiCMOS. The PA shares its output antenna port with a low noise amplifier using a low-loss transmission/reception switch. The output matching network of the PA is designed to provide high output power, low AM-AM distortion, and uniform performance over frequencies in the range of 24.25-29.5GHz. Measurements of the front-end in TX mode demonstrate peak S21 of 30.3dB at 26.7GHz, S21 3-dB bandwidth of 9.8GHz from 22.2to 32.0GHz, and saturated output power (Psat) above 20dBm with power-added efficiency (PAE) above 22% from 24 to 30GHz. For a 64-QAM 400MHz bandwidth orthogonal frequency division multiplexing (OFDM) signal, -25dBc error vector magnitude (EVM) is measured at an average output power of 12.3dBm and average PAE of 8.8%. The PA achieves a competitive ITRS FoM of 92.9.