Lessons learned through the implementation of Space-Time Adaptive Processing algorithms for GPS reception in jammed environments

The use of Space-Time Adaptive Processing (STAP) algorithms to mitigate the detrimental effects of jamming upon GPS receivers has gained significant interest in the signal processing community. Sufficient spatial and temporal degrees of freedom allow these algorithms to position nulls in the space-time locations of jammers while concurrently allowing the reception of the GPS signal. Unfortunately, algorithm design assumptions tend to be optimistic and can prove to be unrealistic and inaccurate. Additionally, much of the analysis, development, and evaluation of these digital beamforming algorithms have been accomplished with computer-generated simulations that may not accurately address mismatches between the assumed signal model and the actual environment. In recognition of these shortcomings, MITRE has recently processed recorded data containing both the GPS signal and jamming that can be used to evaluate current and future generation antenna array electronics and signal processing algorithms. In this paper, practical issues encountered during the analysis of the recorded data are presented. These issues must be addressed to ensure the successful evaluation of STAP algorithms for GPS. Techniques are developed to accurately calculate jammer mitigation performance as well as the resulting satellite availability. A methodology for beampattern visualization is also described. We conclude that careful consideration of data collection methods and conditions is required to adequately assess adaptive algorithm performance.