Grumman Aerospace Corporation

William M Vojir

Cecelia Jankowski

Chelsea R Jones

Christopher Florentino

Joel R Davidson

Jason Asser

An adaptive weak signal identification system having a simple implementation which is capable of rapidly tracking weak signals with time varying frequencies in the presence of a strong interference signal. The system includes a first Fast Fourier Transform circuit for performing a Fast Fourier Transform on a discrete block of data points of an input data signal. A filter coefficient generator is coupled to the output of the Fast Fourier Transform circuit, and identifies the frequency of the strong interference signal, and then based thereon generates filter coefficients for a notch filter. A notch filter receives the generated filter coefficients, and further has the input data signal as an input, on which it performs a notch filtering operation to dramatically reduce the intensity of the interference signal. A second Fast Fourier Transform circuit then performs a Fast Fourier Transform on the output passed by the notch filter, and the output of the Fast Fourier Transform circuit is analyzed to identify the frequency of the weak signal of interest.

Adaptive weak signal identification system

A hardware implementation of a rank order filter includes inputs for inputting a window parameter or window size signal and a target rank signal, thereby permitting programming of the rank order filter to perform rank order filtering within any specified window and relative to any desired target rank.

Programmable rank order filter

Signal processing techniques are disclosed for applications such as finite impulse response filtering. After initial processing in residue number system (RNS) channels, the signals are converted from residue form to a true external representation of the filter output. The conversion employs a chinese remainder theorem decoder and shift accumulator controlled to utilize adaptive modulo reduction. As a consequence, each modulus function value is reduced during computation when it exceeds the modulus and not at the end of the function evaluation. This reduces hardware requirements by minimizing the arithmetic word length. In implementing the technique, each function value is tested to see if it is within a modulus range and the corresponding modulus value is subtracted if it is not. This is done as many times as is necessary to bring each function value within the range. By utilizing this technique, speed and computational accuracy are improved in filter processes thereby producing improved performance in radar, seismic, acoustic and other applications which depend on such filter characteristics.

Residue number system shift accumulator decoder

A digital circuit is disclosed for computing the magnitude of a complex number employing piece-wise linear approximations to achieve precision without the need for iteration. An illustrative implementing circuit employs a first stage for converting the in-phase and quadrature signals to their absolute values. The resultant signals are applied to a selection circuit which selects the maximum and minimum values. The resultant signals are combined with coefficients selected as a function of the operating interval and the resultant products added to yield a signal related to the magnitude of the input complex number.

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Seaford, NY, United States of America

William M Vojir