Filtering of Volume Clutter in Pulse Surveillance Radar using Discrete Wavelet Transform

Moving weather systems will have a nonzero Doppler response at rate at which the rain droplets are approaching the radar system. The complete data the radar collects contain the returns of both the target and the clutter. The signal processing block in a radar system uses filtering operations to extract the target information while suppressing the clutter. Typically the filters are designed based on Doppler Frequency using a Fourier filter bank. Instead of the frequency domain, the wavelet analysis allows the time-scale domain in processing. The filter bank in this project utilizes Discrete Wavelet Transform (DWT), DWT coefficients represent the results of a multi-resolution analysis of the radar signal. The experiments indicate that the Fourier filter bank filter the volume clutter very well. However, a DWT filter bank has different time resolution for different frequency ranges. The experiments were performed in MATLAB environment as well as python and data is real radar rain clutter data from PSR, TERLS(low PRF). The objective of this paper is to develop a DWT based filtering system and to test it’s operation in one situation of volume clutter and then plotting PPI.