Optimized detection of spatially extended fixed objects in clutter

Range-spread Doppler-spread signals in interference are readily discernable via the application of classical algorithms and architectures presented by Van Trees [1], and more recently by Kay [2] and others. However, when these returns emanate from stationary objects, the Generalized Inner Product (GIP) offers a unique tool for detection and discrimination processing. This paper offers insight into how the GIP may be applied to optimize the detection of spatially extended fixed objects in clutter.