Adaptive Null-Forming for the Spy-1A at the National Weather Radar Testbed
RFI signals may be transient and can be difficult to mitigate. Their non-stationary behavior suggests that analog RF filtering is not a viable approach and that real-time digital filtering could be a better approach. A sample-by-sample method of RFI mitigation, the Interference Spike Detection Algorithm (ISDA), was explored in 2013-2014 to address the interference in the time domain. In contrast, the adaptive null-forming approach is a type of spatial filter, and our focus will be the real-time implementation of this kind of technique.
With a multichannel receiver, a linearly constrained minimum power beamformer can be designed for adaptive null-forming. This beamformer leverages the signal data, in particular the inverse of the covariance matrix of the receiving channels, to introduce nulls in the directions of interference. Calculating the inverse of the covariance matrix is typically a time-consuming task: first all data samples must be gathered to estimate the covariance matrix, then the mathematically complex inversion must be performed. Because we want our research to explore the area of real-time null forming, we propose to use the matrix inversion lemma to update the estimate of the inverse of the covariance matrix as radar data arrive, in realtime.