Abstract: A method and apparatus is taught for a signal processing breakthrough that significantly alleviates the “Curse of Dimensionality” (COD) in the characterization of nonlinear physical systems; namely, the reduction in the number of coefficients used to describe the higher order (i.e., nonlinear) kernels in the Volterra series expansion. The latter technique provides the means to evaluate simultaneously from a wide band excitation, all the inter-modulation products up to a specified order by greatly reducing the number of coefficients in the higher order kernel estimation to a manageable set that can be easily manipulated by current personal computers used to enhance a finite element (FE) model that generates a bio-inspired acoustic transducer model.

Abstract: The invention is a method for improved active sonar using a singular value decomposition filtering and a Volterra-Hermite Basis Expansion to model real active sonar measurements. The fitting model minimizes the sum of the squared errors between a measured channel response, z(t), and model response, y(t), which is a fitted Volterra Series solution. The model requires as input an excitation waveform, x(t), to which is fitted the model response, y(t). A contracted broadband cross-ambiguity function is used to correct the excitation waveform for Doppler and range effects. Once completed, the modeled response can be used to determine the linearity or non-linearity of the channel effects. Appropriate measures can be utilized to reduce these effects on the measured channel response.

Abstract: A fault detection system designed to evaluate the structural integrity of a material employs an array of sensors disposed over the material being evaluated. The sensors detect vibrations in the material and the sensor signals are fed to a data processor. The processor employs a method to analyze the linear and nonlinear characteristics of the sensor signals and then determines whether to proceed with a linear signal processing analysis or a nonlinear signal processing analysis of the sensor signals. Once the analysis is completed, the results are compared to baseline results to determine what if any divergence exists between the results and the baseline results. A significant divergence indicates a potential material failure. The fault detection system will indicate such a potential failure through a visual alarm on a graphical user interface.

Abstract: A fault detection system designed to evaluate the structural integrity of a material employs an array of sensors disposed over the material being evaluated. The sensors detect vibrations in the material and the sensor signals are fed to a data processor. The processor employs a method to analyze the linear and nonlinear characteristics of the sensor signals and then determines whether to proceed with a linear signal processing analysis or a nonlinear signal processing analysis of the sensor signals. Once the analysis is completed, the results are compared to baseline results to determine what if any divergence exists between the results and the baseline results. A significant divergence indicates a potential material failure. The fault detection system will indicate such a potential failure through a visual alarm on a graphical user interface.

Abstract: The invention is a method for improved active sonar using a singular value decomposition filtering and a Volterra-Hermite Basis Expansion to model real active sonar measurements. The fitting model minimizes the sum of the squared errors between a measured channel response, z(t), and model response, y(t), which is a fitted Volterra Series solution. The model requires as input an excitation waveform, x(t), to which is fitted the model response, y(t). A contracted broadband cross-ambiguity function is used to correct the excitation waveform for Doppler and range effects. Once completed, the modeled response can be used to determine the linearity or non-linearity of the channel effects. Appropriate measures can be utilized to reduce these effects on the measured channel response.

Abstract: A method and apparatus is provided for suppressing noise which includes receiving a plurality of signals from an array of sensors and transforming each of these signals to the frequency domain. The transformed signals are beamformed so that noise sources can be identified by bearing and frequency range. A planewave-fit noise-suppression routine is then used to remove identified noise sources from the transformed signals and to provide a noise-suppressed transformed signal having signals from said identified noise sources suppressed.

Abstract: A method is provided for identifying a disease of a patient. The method includes collecting data of at least one cardio-respiratory function of the patient over time, eliminating artifacts from the collected data to create a new data record, constructing a phase-space from the new data record, and constructing a hypercube covering the phase-space. The method further includes calculating threshold criteria for quantifying dispersion characteristics of an attractor of the phase-space and determining the patient's tendency towards the disease based on the threshold criteria.

Abstract: The present invention provides a method and apparatus for enhancing active sonar signal detection by estimating the channel/target response utilizing measured values of the excitation signals and received signals. A Wiener/Volterra series expansion for the excitation and received signals is used as a model, wherein a time invariant environment is assumed, thereby disregarding all random noise contributions. The Wiener/Volterra kernels are then determined in a nonlinear processor using a method of correlations which is designed to produce the kernels utilizing only measured white Gaussian excitation signals and received signals. The kernels can be used to give an optimum correlation between the excitation signals and the received signals.

Abstract: A method and apparatus for detecting, processing and tracking sonar signals o provide bearing, range and depth information that locates an object in three-dimensional underwater space. An inverse beamformer utilizes signals from a towed horizontal array of hydrophones to estimate a bearing to a possible object. A matched field processor receives measured covariance matrix data based upon signals from the hydrophones and signals from a propagation model. An eight nearest neighbor peak picker provides plane wave peaks in response to output beam levels from the matched processor. A five-dimensional M of N tracker identifies peaks within the specified limit of frequency, bearing change over time, range and depth to specify an object as a target and to display its relative range and depth with respect to the array of hydrophones.

Abstract: An apparatus and method for detecting, processing, and tracking sonar sigs is provided. Plane wave energy from the sonar signal source is measured at multiple points using an array of plane wave energy receptors. These measurements are processed using an inverse beamformer to generate output beam levels. These output beam levels are then processed using the spectrum normalizer to yield spatially and spectrally normalized output beam levels. The normalized beam levels are then processed using an eight nearest-neighbor peak-picker to provide plane wave peaks. Finally, the plane wave peaks are processed by a three-dimensioned M of N tracker to identify peaks within a specified limit of frequency and angle change over time. The identified peaks may be displaced or recorded for further analysis.