An Autonomous Interference Detection and Filtering Approach Applied to Wind Profilers

An autonomous interference detection and filtering algorithm has been developed for removing the interference bands generated in the Doppler spectra of mesosphere-stratosphere-troposphere (MST) radar signals. The technique, implemented with the MST radar at Gadanki (13.5° N, 79° E), is based on identifying interferencelike band signals using a statistical signal variance approach for fixing the amplitude threshold, through which detecting the interference frequency and designing an adaptable notch filter to filter the undesired frequency bands are done. Signals received from the MST radar are sometimes contaminated with interference signals received from other objects or generated within the system through arcing of high-power devices. Multiple interference bands with different characteristics are observed in the power spectra, which contaminate the wind information and other atmospheric signals. The autonomous interference detection and filtering algorithm is applied to various cases, and it is found that the interference signals could effectively be removed, leaving behind the original signals. By this approach, the effective number of signal samples obtained is increased, which helps one to improve the temporal resolution.