Assessment of multichannel airborne radar measurements for analysis and design of space-time processing architectures and algorithms

System design studies and detailed radar simulations have identified the utility of space-time adaptive processing (STAP) to accomplish target detection in cases where the target Doppler is immersed in sidelobe clutter and jamming. A recent US Air Force investment in STAP has produced a database of multichannel airborne data, through Rome Laboratory's Multichannel Airborne Radar Measurement (MCARM) program, to further develop STAP architectures and algorithms suited to operational environments. An aspect of actual data not typically incorporated into simulation scenarios is the nonhomogeneous features of real-world clutter and interference scenarios. In this paper we investigate the impact of nonhomogeneous data on the performance of STAP. Furthermore, we propose a preliminary scheme to detect and excise nonhomogeneous secondary data in the sample covariance estimation, thereby dramatically improving STAP performance as shown through a specific example using monostatic MCARM data.