Implementing the optimum spatial-temporal (angle-Doppler) processor involves two crucial issues: the selection of processing configurations, and the development of adaptive algorithms which can efficiently approach the performance potential of the selected configuration. Among the three available configurations, the joint-domain, the cascade space-time, and the cascade time-space, this work shows that, in contrast to a popular belief, the detection performance potentials of both cascade configurations can fall far below that of the joint-domain optimum. In addition, this work presents a new adaptive algorithm, called the Joint-Domain Localized Generalized Likelihood Ratio detection (JDL-GLR), which is data efficient i.e., with fast convergence to the joint-domain optimum, as well as computationally efficient, together with such desirable features as the embedded constant false-alarm rate (CFAR) and robustness in non-Gaussian interference.
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