Analytical expressions for space-time adaptive processing (STAP) performance

Space-time adaptive processing (STAP) is a family of algorithms frequently employed in surface moving target indication radar systems to enable detection of moving objects in the presence of fixed (i.e., nonmoving) clutter. In this paper, two new closed-form expressions that quantify the loss associated with the STAP notch centered on clutter are derived in terms of system parameters of interest. Although there are many excellent reports, books, and papers focused on STAP, a simple yet accurate approximation for the STAP notch has not previously appeared. It is also shown that a new, accurate approximation for the important STAP metric known as minimum detectable velocity may be derived from the STAP notch expression. Furthermore, accurate expressions are derived that predict when "aperture-limited" STAP performance may be obtained. This work provides the first analytical, unifying connection between these STAP metrics. As they are implemented in compact closed-form expressions, the new results are attractive for system design. The significant computational benefits associated with the new results can be very advantageous in trade studies or large simulations in which STAP performance estimates must be computed thousands of times. It is expected that this work will be of great use to both readers with a background in STAP and readers new to this field. For readers with STAP experience, this work provides a new understanding of the drivers of STAP performance and of the interconnections between STAP performance measures. For readers new to the STAP field, this work removes the mystery associated with STAP by providing intuition into how STAP works. With accurate, analytical expressions, system engineers can now implement accurate predictions of STAP performance without the necessity of constructing patch-based analysis tools that estimate STAP performance by computing the notch associated with hundreds to thousands of clutter patches.