JOINT DEINTERLEAVING/IDENTIFICATION OF RADAR PULSES USING MATRIX DIFFERENCES

A New Algorithm for the Deinterleaving of Radar Pulses

This paper presents a new algorithm for the deinterleaving of radar signals, based on the direction of arrival (DOA), carrier frequency (RF), and time of arrival (TOA). The algorithm is applied to classic (constant), jitter, staggered, and dwell switch pulse repetition interval (PRI) signals. This algorithm consists of two stages. In the first stage, a Kohonen neural network clusters the receiv...

Familiarity Discrimination of Radar Pulses

The ARTMAP-FD neural network performs both identification (placing test patterns in classes encountered during training) and familiarity discrimination (judging whether a test pattern belongs to any of the classes encountered during training). The performance of ARTMAP-FD is tested on radar pulse data obtained in the field, and compared to that of the nearest-neighbor-based NEN algorithm and to...

Radar clutter suppression and target discrimination using twin inverted pulses

The proposition that the use of twin inverted pulses could enhance radar is tested. This twin inverted pulse radar (TWIPR) is applied to five targets. A representative target of interest (a dipole with a diode across its feedpoint) is typical of covert circuitry one might wish to detect (e.g. in devices associated with covert communications, espionage or explosives), and then distinguish from o...

Joint Eigenvalue Decomposition Using Polar Matrix Factorization

In this paper we propose a new algorithm for the joint eigenvalue decomposition of a set of real non-defective matrices. Our approach resorts to a Jacobi-like procedure based on polar matrix decomposition. We introduce a new criterion in this context for the optimization of the hyperbolic matrices, giving birth to an original algorithm called JDTM. This algorithm is described in detail and a co...

Weather Radar image Based Forecasting using Joint Series Prediction