University Corporation for Atmospheric Research

Lawrence B Cornman

Robert Kent Goodrich

Corinne Sue Morse

Richard A Weekley

Shelly D Dalton

Nathaniel Beagley

A processing system uses image processing technology to classify features in time series data. In atmospheric applications, the features can be used to detect outliers and/or failure modes in time series data from atmospheric measurement systems. The processing system is configured to: 1) process the time series data with a plurality of membership functions to generate a plurality of hypersurfaces, 2) process the hypersurfaces to generate a composite hypersurface, 3) process the composite hypersurface to identify clusters, and 4) process the clusters to classify the features.

Feature classification for time series data

A multi-stage processing system receives data from signals that indicate information related to scatterers, such as signals from a Doppler scanning system. The multi-stage processing system tracks allowed processing time for the data. The multi-stage processing system performs a first stage of processing for the data to generate first estimates of spectral moments for the signals. The multi-stage processing system performs additional stages of processing for the data as the allowed processing time permits and stops the additional stages of processing for the data when the allowed processing time expires. The additional stages of processing may comprise generating second estimates for at least some of the spectral moments. The additional stages of processing may use methods having increasing complexity and accuracy.

Multi-stage processing for efficient and accurate spectral moment estimation

The computation system of the present invention comprises an improved method of moment estimation for devices which measure spectra as a function of range or time. The preferred embodiment of this system is illustrated as part of an automated meteorological monitoring system for the accurate real time detection of meteorological phenomena, such as winds, wind shear and turbulence. This automated meteorological monitoring system uses a standard weather radar transmitter to scan a predetermined volume of space with a stream of radar pulses to determine the characteristics of meteorological phenomena that are extant in the predetermined volume. The computation system of the present invention utilizes novel signal processing algorithms in the improved method of moment estimation to excise the valid data from the returns echoes, which are corrupted by the presence of contaminating signals. Separating the valid data from the noise in this manner improves the responsiveness and accuracy of the system in which this method is implemented.

Method of moment estimation and feature extraction for devices which measure spectra as a function of range or time

The computation system of the present invention comprises an improved method of moment estimation for devices which measure spectra as a function of range or time. The preferred embodiment of this system is illustrated as part of an automated meteorological monitoring system for the accurate real time detection of meteorological phenomena, such as winds, wind shear and turbulence. This automated meteorological monitoring system uses a standard weather radar transmitter to scan a predetermined volume of space with a stream of radar pulses to determine the characteristics of meteorological phenomena that are extant in the predetermined volume. The computation system of the present invention utilizes novel signal processing algorithms in the improved method of moment estimation to excise the valid data from the return echoes, which are corrupted by the presence of contaminating signals. Separating the valid data from the noise in this manner improves the responsiveness and accuracy of the system in which this method is implemented.

Method of moment estimation and feature extraction for devices which

The apparatus of the present invention improved low-level wind shear alert system that provides an improved method of identifying the presence and locus of wind shear in a predefined area. This system enhances the operational effectiveness of the existing LLWAS system by mapping the two-dimensional wind velocity, measured at a number of locations, to a geographical indication of wind shear events. This system can also integrate data and processed information received from a plurality of sources, such as anemometers and Doppler radar systems, to produce low-level wind shear alerts of significantly improved accuracy over those of prior systems. In particular, the apparatus of the present invention makes use of the data and processed information produced by the existing Low-Level Wind Shear Alert System as well as that produced by the Terminal Doppler Weather Radar to precisely identify the locus and magnitude of low-level wind shear events within a predetermined area. This resultant geographical indication is displayed in color-graphic form to the air traffic control personnel and can also be transmitted via a telemetry link to aircraft in the vicinity of the airport for display therein.

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Longmont, CO, United States of America

Lawrence B Cornman