Other

Rockwell International Corporation

Boeing North American, Inc.

Jeffrey P Woodard

Stanley A White

Karl Einar Nelson

Michael Alan Soderstrand

Phong Vu Dao

Phong Vu Nguyen Dao

Noise is removed from the digitized output of a sensor, subject to undesired resonance, even when the resonant frequency is unknown or drifts, with sufficiently low phase delay for the sensor to be used in closed-loop control. A very narrow notch filter which removes the resonance-induced noise is recursive (IIR) and therefore has a low phase delay. However, the apparatus which determines the center frequency of the notch filter is non-recursive, and therefore stable. It includes a tunable FIR filter which tracks the same resonance that we wish the IIR filter to remove. Tuning the FIR filter to minimize the output of the FIR filter therefore tunes the notch frequency to align with the resonant frequency. The tuning parameter which adaptively produces this result is suitably scaled and biased, and is applied to the IIR filter.

Adaptive removal of resonance-induced noise

Noise may be reduced or eliminated from a digital sawtooth signal representing the phase of a periodic signal. This may be done precisely, even when inexpensive fixed-point arithmetic is used. In one aspect of the invention, the input signal (noise plus true signal) 12 is filtered to produce, in succession: (a) mod one differentiated noise plus slope of true phase signal 28; (b) mod one differentiated noise plus slope of residual phase signal (true phase signal minus estimated slope of true phase signal) 36; (c) mod one differentiated noise 46; (d) estimated noise 62; and (e) smoothed phase signal 72. In a second aspect, a noisy phase signal 12 is extracted from a first arbitrary periodic signal and the above steps are used to generate a noise-reduced phase signal 72. The noise-reduced phase signal 72 is then used to generate a second arbitrary periodic signal of the same frequency.

Sawtooth phase filter

A vehicle navigation system uses a one-multiplier Gray-Markel filter. The sign parameter of each stage of the filter is selected by an algorithm which limits the maximum signal passing through the filter, thereby preventing overflow.

Vehicle navigation system with non-overflow digital filter

A SOUND RECOGNITION PROCESS comprises training a sound recognition system to a shape Hidden Markov Model (HMM) from a shape codebook of shape codewords, and to a separate gain HMM from a gain codebook of gain codewords. An unknown token is assigned to the sound category associated with the shape HMM and gain HMM with the greatest probability product. Shape and gain codewords replacements for incoming Linear Predictive Coded (LPC) vectors are selected by choosing the codeword with minimum distortion between the codeword and a combination of the vector and some of the preceding codewords, exponentially weighted by time.

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Irvine, CA, United States of America

Jeffrey P Woodard