A parametric approach to radar processing of reentry vehicle signatures

Summary form only given, as follows. We investigate the development of parametric techniques to extract dynamical information about a reentry vehicle (RV) from noisy radar cross-section (RCS) measurement data. We develop a simplified signal processing model of the entire measurement process based on the underlying physics and radar system operations. Signal processing techniques are developed to extract the desired RV dynamical parameters. This suite of techniques includes: trajectory motion compensation, environmental transfer function estimation and its inverse, instantaneous spectrogram estimation using parametric autoregressive moving average (ARMA) models and recursive-in-time algorithms, demodulation, and event detection schemes based on the prediction errors and instantaneous ARMA coefficients. The overall processing is applied to both synthesized and raw flight data demonstrating its effectiveness.