Adaptive FFT-based signal processing on FMCW weather radar

Weather radar is usually used to monitor the precipitation events in atmosphere by estimating reflectivity from received power signals on receiver. Since received signals are contaminated by noise, such techniques are developed to calculate reflectivity accurately. Signal processing on Doppler domain is one of Fast Fourier Transform (FFT)-based method that is usually used to calculate reflectivity. Another FFT-based method that can be used to estimate reflectivity is using spectrum estimation to substitute FFT, so that the processing can be done in time domain. However, spectrum estimation requires more concern on signal modelling and filter coefficients estimation. This research compares and analyzes the performance of FFT-based spectrum estimation with Doppler domain processing. The spectrum estimation methods are based on autoregressive (AR) parametric estimation and adaptive filtering that has been well known in another application. Raw voltages on receiver are processed to estimate reflectivity. Simulation done for FMCW radar with center frequency 9.475 GHz (X-band) and typically bandwidth of 5 MHz. The simulation results show that time domain signal processing using adaptive filter gives more satisfying result com pared to parametric estimation.