Radio Frequency Spectrum Challenges for MPAR: Adaptive Interference Mitigation Techniques

Problem Statement: Government mandated shared spectrum presents challenges, such as intermittent Radio Frequency Interference (RFI), which have impacts on the national Multifunction Phased Array Radar (MPAR) initiative. This interference can affect radar target detection and identification, and weather data quality. Depending on the operating mode, the impacts of interference on generating an accurate meteorological product vary between minimal and severe.

Key Motivations: To reduce risk to the MPAR program, technologies need to be developed that will support RFI mitigation for phased arrays. RFI is an ever increasing problem to radar imaging systems, high resolution radar modes, cognitive radio systems, impulsive radars, passive radars, compressive radars, and the like – especially as these systems operate over wider bandwidths. For weather observations, radar products may have significant voids in coverage or other problems when biased data are passed to meteorological algorithms.

Proposed Solution: A quasi-MIMO, multichannel approach for interference mitigation is needed. The new approach will rely on: (1) novel ubiquitous modeling, (2) new signal processing architectures, (3) sample-by-sample processing, (4) recursive least squares and least mean squares algorithms, and (5) non-block adaptive architectures. Initial ideas will be tested on the SPY-1A Phased Array Radar at the National Weather Radar Testbed (NWRT) in Norman, OK to mitigate risks to the MPAR initiative.