Principles of Modern Radar - Volume 2 1891121537

10.9 Summary 49310.7.3 Computational BurdenSTAP remains a computationally demanding signal processing technique. Adaptive weightcalculation involves either implicitly or explicitly solving for the covariance matrix inverse,a cubic operation in the processor’s DoFs. The RD-STAP methods described inSection 10.6 greatly alleviate the computational demands of joint domain STAP andprovide a pathway to real-time implementation. Nevertheless, the computational aspectsof STAP limit weight updates and the implementation of certain techniques devised tomitigate heterogeneous or nonstationary clutter. This generally means that trade-offs inalgorithm design become necessary to support real-time capabilities. Examples of typicaltrades include training over several large training blocks to minimize the numberof adaptive weight updates, minimizing post-detection logic requiring recalculations ofrange-Doppler maps, and attempts to separately mitigate clutter and radio frequency interferenceto minimize the number of spatial DoFs.10.8 FURTHER READINGSTAP has been one of the most researched topics in radar technology over the past 15 to20 years. For this reason, numerous extant conference and journal papers are easily foundby interested readers.This chapter introduces the reader to important STAP fundamentals for clutter suppression.While the interested reader should consider consulting all the provided references,[4,5] are recommended as starting points. These full-length references give in-depth detailon STAP specifics.Moreover, [8] has proven popular and should be worthy of quick review. Also, [3,15]are classic papers that should be read early in one’s study of STAP.10.9 SUMMARYAerospace radar systems must detect targets competing with strong clutter and jammingsignals. For this reason, the radar system designer incorporates a mechanism to suppresssuch interference. A familiarity with the application of space-time degrees of freedom—shown herein to greatly enhance detection in interference-limited environments—is thusessential. This chapter discussed the important role of space-time adaptive processing inmoving target indication radar.The chapter began with descriptions of spatial and temporal sampling, along withbeamforming and Doppler processing. Both beamforming and Doppler processing methodswere shown to implement matched filtering, a procedure leading to maximal signalto-noiseratio. Joint space-time signals and characterization approaches based on thetwo-dimensional power spectral density, eigenspectrum, and minimum variance distortionlessresponse spectrum were then discussed.Leveraging these discussions, the chapter then introduced the space-time propertiesof ground clutter returns as the composite of the space-time responses of many clutterpatches summed over all azimuth at the range of interest. This discussion described theclutter ridge resulting from a deterministic angle-Doppler coupling, thereafter providinga numerical example showing the region of the angle-Doppler spectrum occupied by theclutter response.