Adaptive Detection and Estimation Using a Conformal Array Antenna

Abstract

Conformal arrays possess certain desirable characteristics for deployment on unmanned aerial vehicles and other payload-limited platforms: aerodynamic design, minimal payload weight, increased field of view, and ease of integration with diverse sensor functions. However, the conformal arrays nonplanar geometry causes high adaptive losses in conventional space-time adaptive processing (STAP) algorithms. In this thesis, we develop a conformal array signal model and apply it to evaluate the performance of conventional STAP algorithms on simulated ground clutter data. We find that array-induced clutter nonstationarity leads to high adaptive losses, which greatly burden detection performance. To improve adaptive performance, we investigate the application of existing equivalent-linear-array transformations and develop novel deterministic and adaptive angle-Doppler compensation techniques, which align nonstationary clutter returns. Through the application of these techniques, we are able to nearly fully mitigate the nonstationary behavior yielding performance similar to that of a conventional planar array. Finally, we investigate the impact of array errors on the performance of conformal arrays, and propose several array calibration techniques as ameliorating solutions.