Abstract: The present invention relates to a radar emitter recognition system and method for classifying incoming emitters into their functional roles as disclosed by their electronic signatures and the context within which the radar transmissions are received. An electronic support system provides incoming data, including unknown attribute information, to a neural network which has been synthesized or trained to calculate a network solution indicative of an emitter's classification within a range of attributes. Similarly the electronic support system provides incoming data, including unknown context data, to a fuzzy logic system that has been provided with possibility distributions to classify the emitter as originating from one of several strategic contexts. The resultant categorizations from the neural network and the fuzzy logic system are combined in a classifier to yield an improved recognition of the emitter under observation.

Abstract: An apparatus for combining signals from a plurality of radar installations is described. A methodology for combining signals from a pluraltiy of radar installations/sensors has been developed. This methodology provides enhanced target detection performance by properly fusing together the commensurate range-Doppler filter bins of each sensor. In this methodology, the processing of each of the individual radars in the Doppler frequency domain is provided such that a common velocity domain is obtained from each of the radars. Using a zero fill discrete Fourier transform, the velocity domain obtained from each radar is further normalized to have a common bin size. Additionally, for the higher frequency radars, the normalized velocity bins are unfolded so that each radar signal produces the same number of velocity bins in its respective velocity domain.

Abstract: A method and apparatus for detecting innovations in a scene in an image of the type having a large array of pixels. The method comprises the step of generating a multitude of parallel signals representing the amount of light incident on a group of adjacent pixels (masks) and these signals may be considered as forming a n by one vector, Z, where n equals the number of pixels in the masks. L such groups of adjacent pixels or elementary masks are used to geometrically cover the entire image in parallel. The method further comprises the step of replicating the generating step a multitude of times to generate a multitude of Z vectors by taking multiple frames of observations of the image (scene). These Z vectors may be represented in the form A.sub.k, where k equals 1,2,3, . . . , m, where m equals the number of replicates. Each of the Z.sub.k vectors are related to a vector .beta..sub.k of three parameters by a measurement equation in a linear model framework, i.e. Z.sub.k =D.beta..sub.k +e.sub.k, where e.sub.