In this chapter, the authors present different strategies for target detection in through the-wall radar imaging (TWRI). The approaches can be classified into centralized and decentralized, as well as static and adaptive, approaches which are applicable to single- and multi-viewing operations. The authors provide a problem formulation and derive the centralized detection scheme using the Neyman–Pearson test when observing the scene of interest from an arbitrary number of vantage points. They examine the statistics of typical TWRI images and find appropriate probability density functions for modeling noise and target returns. This includes also a study of the effect of the wall, represented by its thickness and dielectric constant. The authors also provide a robust iterative detection scheme for targets behind walls under unknown image statistics. They also present a decentralized detection approach, which can be used instead of the centralized detector to reduce data transmission and complexity. The authors represent validation of all proposed detectors with experimental data.