Mitigation of Wind Turbine Clutter With Digital Phased Array Radar

Wind turbine clutter (WTC) contamination affects polarimetric meteorological observations and automatic high-impact weather detection algorithms in several ways, such as, misidentification of precipitation echoes, false mesocyclone detections, incorrect storm cell identification. With the dramatic growth wind power industry, this would only aggravate future. Since fully digital Phased Array Radar (PAR) is a promising candidate technology for next generation radars, evolutionary signal processing that make use their capabilities should be investigated to mitigate WTC contamination. This article investigates Space-Time Adaptive Processing (STAP) with ground-based PAR. First, flexible time-series simulator developed characterize signatures space-time domain. Then, STAP algorithm removes presented demonstrated on simulated data. Two radar back-end architectures are considered evaluate performance proposed algorithm. One sub-array outputs other one (i.e., element-level digital). Results indicate spectrum has characteristic structure domain, biases induced variables can more effectively mitigated using an