Clutter removal for measuring low-frequency narrow-band antenna using spectral estimation

Abstract

The measurement accuracy of low-frequency narrow-band antenna is heavily influenced by its environment, which is also difficult to remove the clutter with a time gating. This paper proposes a method to improve the measurement accuracy of low-frequency narrow-band antenna using signal processing technique. The method is to predict the unknown value out of received original signal with an auto-regressive model (AR model) based on modern spectral estimation theory, and the parameters in AR model are calculated by maximum entropy spectral estimation algorithm. Thus, a wideband signal compared with the original band is obtained, and then the time-domain resolution is enhanced. The time gating is more exactly to separate the antenna radiation signal from multipath signals. The simulation and experimental results show that about 50% extended data for each ends of original band can be obtained after spectral extrapolation, and the time-domain resolution after extrapolation is twice than the original narrow-band signal, and the influence of measurement environment can be eliminated effectively. The method can be used to improve accuracy in actual antenna measurement.