Abstract: A system for bearinqs-only contact state estimation in response to target bearing and ownship speed and course information provided for a plurality of observation legs at successive points in time, includes a plurality of neural networks and a data fusion circuit. Each of the neural networks generates range-normalized parameter estimate information for one of the observation legs in response to target bearing and ownship speed and course information for an associated one of the observation legs, provided thereto at each point in time and information generated for the previous point in time. The data fusion system receives the range-normalized parameter estimate information from the neural networks and generates the contact state estimate in response thereto.

Abstract: A method for the selection of hypotheses for modeling physical phenomena, includes detecting if selected features are present by analyzing actual sensed data and parameter values of an initial physical phenomena model; comparing feature estimating hypotheses to the actual data for determining a belief probability assignment value (bpa) for each of the hypotheses which indicates the likelihood that the selected features exist in the actual data and the likelihood that such selected features cannot accurately be determined as existing due to the presence of noise; selecting a set of the hypotheses most accurately modeling the physical phenomena based on the bpa of each selected hypotheses meeting a predetermined criteria; generating evidential support values and lack of evidential support values for subsets of the set having non-zero subset bpa's; ranking the subsets having non-zero subset bpa's in order of decreasing subset bpa; unioning subsets of the power set for forming unioned subsets and determ

Abstract: The present invention relates to a method and a system for providing an estimate of the state of a contact. The method includes the steps of sensing the state of the contact; generating signals representative of the state of the contact; and processing the signals using a random search procedure to arrive at an estimate of the state of the contact. The random search procedure may employ the simulated annealing-based algorithm methodology or the genetic-based algorithm methodologies. The system includes sensors for sensing the state of the contact and a pre-programmed computer for generating the desired contact state estimates.

Abstract: The present invention relates to a system and a method for signal classification. The system comprises a sensor array for receiving a series of input signals such as acoustic signals, pixel-based image signal (such as from infrared images detectors), light signals, temperature signals, etc., a wavelet transform module for transforming the input signals so that characteristics of the signals are represented in the form of wavelet transform coefficients and an array of hybrid neural networks for classifying the signals into multiple distinct categories and generating a classification output signal.

Abstract: A system and method for signal processing using wavelets are disclosed. The method includes the steps of generating a wavelet decomposition tree modeling the signal. The tree includes a plurality of levels of wavelet coefficients representative of the signal. The method further includes determining the actual number of wavelet coefficients available at each of the plurality of levels; measuring mean energy for each of the plurality of levels; and determining a desired number of wavelet coefficients for each of the plurality of levels based on the mean energy determined in the step of measuring. The mean energy in the step of measuring for each of the plurality of levels is indicative of the desired number of wavelet coefficients selected from each of the plurality of level. The method further includes the step of retaining the desired number of wavelet coefficients and forming a compressed representation of the signal.

Abstract: A chaotic signal processing system receives an input signal provided by a nsor in a chaotic environment and performs a processing operation in connection therewith to provide an output useful in identifying one of a plurality of chaotic processes in the chaotic environment. The chaotic signal processing system comprises an input section, a processing section and a control section. The input section is responsive to input data selection information for providing a digital data stream selectively representative of the input signal provided by the sensor or a synthetic input representative of a selected chaotic process. The processing section includes a plurality of processing modules each for receiving the digital data stream from the input means and for generating therefrom an output useful in identifying one of a plurality of chaotic processes. The processing section is responsive to processing selection information to select one of the plurality of processing modules to provide the output.

Abstract: A signal processing system provides and processes a digital signal, generd in response to an analog signal, which includes a noise component and possibly also an information component representing three mutually orthogonal items of measurement information representable as a sample point in a symbolic Cartesian three-dimensional spatial reference system. A noise likelihood determination sub-system receives the digital signal and generates a random noise assessment of whether or not the digital signal comprises solely random noise, and if not, generates an assessment of degree-of-randomness. The noise likelihood determination system controls the operation of an information processing sub-system for extracting the information component in response to the random noise assessment or a combination of the random noise assessment and the degree-of-randomness assessment.

Abstract: A signal processing system and computer-implemented method for processing a igital data sequence representing an input signal to generate a fractal dimension value. The system includes a correlation integral value generation module, correlation plot generation module, a segmentation module, correlation dimension generation module, and a control module. The correlation integral value generation module generates a series of correlation integral values for points w.sub.n (k) in "N"-dimensional space corresponding to vectors of said digital data sequence, and in particular generates inter-point distance values within each of a plurality of volume elements of said "N"-dimensional space. The correlation plot generation module generates a correlation integral plot comprising a plot of the correlation integral values as a function of said "N"-dimensional space volume elements. The segmentation module generates, from the plot, a series of correlation integral plot segments.

Abstract: The present invention comprises a method for filling in missing data intels in a quantized time-dependent data signal that is generated by, e.g., an underwater acoustic sensing device. In accordance with one embodiment of the invention, this quantized time-dependent data signal is analyzed to determine the number and location of any intervals of missing data, i.e., gaps in the time series data signal caused by noise in the sensing equipment or the local environment. The quantized time-dependent data signal is also modified by a low pass filter to remove any undesirable high frequency noise components within the signal. A plurality of mathematical models are then individually tested to derive an optimum regression curve for that model, relative to a selected portion of the signal data immediately preceding each previously identified data gap.

Abstract: A system for providing an iterative method of assessing accuracy of selected models of physical phenomena and for determining selection of alternate models in response to a data sequence in the presence of noise. Initially, a residual sequence is generated reflecting difference values between in response to said data sequence and an expected data sequence as would be represented by a selected model. Feature estimate values of a plurality of predetermined data features in the residual sequence are then generated. In response to the feature estimate values, a threshold value is generated for each feature at an estimated ratio of data to noise power.

Abstract: An adaptive statistical filter system for receiving a data stream comprising a series of data values from a sensor associated with successive points in time. Each data value includes a data component representative of the motion of a target and a noise component, with the noise components of data values associated with proximate points in time being correlated. The adaptive statistical filter system includes a prewhitener module, a plurality of statistical filters of different orders and a selection module. The prewhitener module receives the data stream from the sensor and generates a corrected data stream comprising a series of corrected data values each associated with a data value of the data stream, each including a data component and a noise component with the noise components of data values associated with proximate points in time being decorrelated. The plural statistical filters are coupled to receive the corrected data stream in parallel from the prewhitener.

Abstract: A system for compensating for noise induced in a sensor data stream from a sensor array towed by a towing device includes a towing device motion data input receives a towed motion data stream representative of towing motion of the towing device. A sensor array input for receiving the sensor data stream. An adaptive filter connected to the towing device motion data input and the sensor array input for receiving the towed motion data stream from the towing device motion data input and the sensor data stream from the sensor array input and for generating a corrected sensor data stream representing sensor array data with ship motion noise attenuated therefrom.

Abstract: A system for facilitating the tracking of a target vehicle in connection h successively-received acoustic sensor signal data items. A fast Fourier transform operation is performed in connection with each successive acoustic sensor signal data item to generate a phase and amplitude beam map reflecting spectral signal energy in the received acoustic sensor signal data item. If the beam map for a acoustic sensor signal data item indicates that the item represents a signal having a signal-to-noise ratio above a first predetermined threshold value, a beam map generated for a previous acoustic sensor signal data item is used to generate a bounded beam map, a determination is made as to whether the bounded beam map represents a signal having a second predetermined signal-to-noise ratio. In response to a positive determination for the latter signal-to-noise determination, both the beam maps are used to generate tracking information for the target vehicle.