Performance Analysis of Angular Ambiguity Elimination for Multi-Subband STAP

The Multi-Subband Space-Time Adaptive Processing (STAP) is usually used in wideband multi-channel radar system to realize moving target detection and parameter estimation. This paper analyzes the performance of eliminating angular ambiguity for Multi-Subband STAP in sparse array. We set up the multi-subband STAP model firstly. And then the realization procedure of the method is exploited to derive the analytic form of multi-subband Improvement Factor (IF). This analytic form indicates that due to the different ambiguous notches’ positions of IF corresponding to the different central frequencies, these notches could be leveled up after correlated integration of multiple subbands, and thus the phenomenon of blind velocity could be alleviated. We also derive the analytic form of Signal-to-Interference-plus-Noise Ratio Loss (SINRLoss). This expression demonstrates that because the positions of peaks of different subbands’ SINRLoss vary with the central frequencies, the outputs of pseudo targets are weak than that of the true target after multiple subbands recombination, and thus the phenomenon of repeated detection could be suppressed. Thereby the method of Multi-Subband STAP can suppress the angular ambiguity caused by sparse array configure in a certain extent, which means the phenomena of blind velocity and repeated detection are released. The paper also analyzes the relationship between the method’s performance of eliminating angular ambiguity and the relative bandwidth of the radar system. The result shows that the larger the relative bandwidth of system is, the better the performance gets. As for a four-channel sparse array system with relative bandwidth larger than 46.3% in an ideal case, the effect of angular ambiguity can be eliminated totally via the Multi-Subband STAP method. The echo data of four-channel ultra-wide band Synthetic Aperture Radar (SAR) sparse array are simulated, and then an experiment of moving target detection and parameter estimation is carried on, which validates the performance of eliminating angular ambiguity of the method.