Methodology to Suppress Weather Echoes in Radar Signals: An Experimental Study

This paper investigates the use of the constrained Minimum Mean Square Error (cMMSE) method to calculate a clutter covariance matrix with a small number of signal samples, which enables radar detection methods to work in the presence of less-stationary and colored clutter noise. Improvements given by the cMMSE method were tested and evaluated on measured radar data in which the target signal was obscured by weather clutter “noise”. The weather covariances were used in three detection methods, namely the Matched Subspace Detector (MSD), the Adaptive Coherence Estimator (ACE), and the Clutter Subspace Estimation (CSE). Comparison of the detector outputs with ones based on covariances calculated by a conventional method showed that the cMMSE method produced significantly superior Doppler profiles. That is, the evaluation confirmed that, while the conventional method requires <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L \gg N$</tex> where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L$</tex> is the number of signal samples to compute covariance matrix and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$N$</tex> is the number of elements of the received signal vector (the number of rows or columns of covariance matrix), the cMMSE method works even with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L \ll N$</tex>.