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Neuro-fuzzy model for multi-channel underwater imaging

Neuro-fuzzy model for multi-channel underwater imaging

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sensor array and multichannel signal processing workshop

作者： V.M. Contarino P.A. Molchanov I.M. Petrosyuk Y.Y. Podobna O.V. Asmolova Research and Engineering Group Naval Air Systems Command MD USA National Technical University Kharkov Polytechnic Institute Kiev Ukraine

Multispectral imaging system usually consist 2-15 different color channels, hyperspectral system - 100-200 channels. The image processing in each channel includes the complicated calculations and the final results have quite a large error. As is well known that there are large number of input parameters and some their uncertainty in the case of airborne and underwater LIDAR systems modeling. The using of statistical and determined models give the result having quite a large error of optical information processing and the given calculations take a lot of time to compute. The fundamentally different mathematical algorithms - the neural networks and the fuzzy logic is offered to use. It is realized with specially developed algorithms for multi-channel image processing. The new neuro-fuzzy model of foam coverage for four color channels has been developed to determine the interval of the minimal reflections and to obtain the images of non-foam covered areas.

关键词： Hyperspectral imaging Image processing Optical computing Optical imaging Multispectral imaging Uncertainty Laser radar Modeling Information processing Neural networks

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MUSIC using Off-Origin Hessians of the Second Characteristic Function

MUSIC using Off-Origin Hessians of the Second Characteristic...

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sensor array and multichannel signal processing workshop

作者： A. Yeredor School of Electrical Engineering Tel-Aviv University Tel-Aviv Israel

In its classical form, the multiple signal classification (MUSIC) algorithm applies eigen-decomposition to the estimated correlation matrix of the noisy sensors' outputs in order to estimate the directions of arrival (DOAs) of several sources. When the noise is spatially white, consistent estimates of the DOAs are obtained. However, when the noise is spatially correlated (and / or has different variances at different sensors), the correlation-based MUSIC cannot produce consistent DOA estimates, unless the noise covariance is known in advance. To mitigate this drawback, the use of certain matrices of higher order statistics (HOS), mainly fourth-order cumulants, has been proposed, which can still lead to consistent DOA estimates when the noise is not spatially white, as long as it has a Gaussian distribution. However, estimates of the required HOS often introduce larger variances; Moreover, if the sources happen to have null cumulants of the chosen order, they remain unaccounted for in the algorithm. In this paper we propose a new target-matrix to substitute HOS as the input to MUSIC. Our target matrix is based on subtracting the observations' correlation matrix from Hessians of their second characteristic function, evaluated at several "processing points". These Hessians are related to the array steering-vectors (hence to the DOAs) in the same way as the correlation matrix, and can be easily estimated from the data. The subtraction of the correlation matrices eliminates (asymptotically) the effect of any additive independent Gaussian noise, hence maintaining consistency. We demonstrate the attainable improvement in comparative simulation

关键词： Multiple signal classification Direction of arrival estimation Matrices Gaussian noise Classification algorithms sensor phenomena and characterization White noise Covariance matrix Higher order statistics Gaussian distribution

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A Survey of Time Delay Estimation Performance Bounds

A Survey of Time Delay Estimation Performance Bounds

引用

sensor array and multichannel signal processing workshop

作者： B.M. Sadler R.J. Kozick Army Research Laboratory Adelphi MD USA Department of Electrical Engineering Bucknell University Lewisburg PA USA

In this paper we review performance bounds, as well as some current trends, in time delay estimation (TDE). Research over several decades reveals that a few key parameters determine TDE performance. The most basic are the signal-to-noise ratio (SNR), and the signal time-bandwidth (TB) product; larger values for each are desirable. The Cramer-Rao bound (CRB) reveals asymptotic maximum-likelihood estimation (MLE) behavior with respect to TB and SNR. At moderate to lower SNR, TDEs generally break down as ambiguities arise due to increased noise and the cross-correlation of the signal, causing the TDE to deviate (often quite sharply) away from the CRB. Because it is a local bound, the CRB does not indicate the threshold behavior, and Ziv-Zakai and other bounds have been developed to handle this. When TD is measured between multiple sensors, the coherence between them can fundamentally limit the result, an effect that occurs in acoustics due to the turbulent atmosphere. We discuss modifications to the classical bounds that accommodate the coherence loss, and reveal a threshold coherence phenomenon. When communications and other signals are utilized for TDE, they may have significant nuisance parameters, including carrier uncertainty, unknown symbols, as well as effects due to an unknown channel. Recent TDE performance limits reveal the effect of these parameters for various signal models, including the impact of diversity channels on TDE

关键词： Delay effects Delay estimation signal to noise ratio Maximum likelihood estimation Coherence Acoustic measurements Atmospheric measurements sensor phenomena and characterization Acoustic sensors Atmosphere

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Wide-band transducers and higher-order spectral characterization of low-level ultrasounds in wood

Wide-band transducers and higher-order spectral characteriza...

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sensor array and multichannel signal processing workshop

作者： J.J. Gonzaalez De la Rosa I. Lloret C.G. Puntonet J.M. Gorriz Research Group TIC-168 Computational Instrumentation and Industrial Electronics University of Cádiz Algeciras Spain University of Granada Granada Spain

Two high-sensitivity ultrasonic transducers have been used to perform the higher-order characterization of vibratory events, in order to get the tracks of low-level transients produced when wood fibres are broken. Although the power spectral density is a valid tool for a prior characterization, third and fourth-order spectra slices exhibit more distinctive shapes, because they content a few number of frequency components, which have been enhanced over the thermal noise, which comes from the sensor and the equipment, and the external sources of interference. The wide-band transducer exhibits better performance due to the expanded spectral pattern it outlines. Fourth-order slices can be used as a complement to third-order ones, when the resolution in the bi-spectrum is not as much satisfactory.

关键词： Ultra wideband technology Ultrasonic transducers Ultrasonic imaging Optical fiber devices Optical fiber sensors Shape Frequency Noise shaping sensor phenomena and characterization Thermal sensors

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Incorporating pulse-to-pulse motion effects into side-looking array radar models

Incorporating pulse-to-pulse motion effects into side-lookin...

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sensor array and multichannel signal processing workshop

作者： J.W. Green T.B. Hale M.A. Temple J.T. Buckreis Department of Electrical and Computer Engineering Air Force Institute of Technology OH USA

A technique is presented for incorporating pulse-to-pulse (inter-pulse) motion effects into side-looking array radar data models yielding a motion-sensitive space-time snapshot. Low flying, highly-maneuverable unmanned aerial vehicles (UAV) represent a potential worst case application scenario given their roll, yaw, and pitch rates are primarily limited by structural integrity. High degrees of maneuverability during the coherent processing interval (CPI) allow clutter and target returns to change significantly. The technique presented uses M coordinate transformations to describe platform attitude variations throughout the CPI. Ward's model then is extended to incorporate maneuver-induced changes in spatial frequency and Doppler. The new motion-sensitive space-time snapshot is used to characterize space time adaptive processing (STAP) performance without motion-compensation applied. Results clearly show motion-induced clutter-null broadening with measurable degradation of STAP algorithm minimal discernable velocity.

关键词： Frequency Geometry Unmanned aerial vehicles Vectors Interference Spaceborne radar Data models Clutter Propagation delay Linear algebra

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sensor Management with Uncertain Performance Characteristics

Sensor Management with Uncertain Performance Characteristics

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sensor array and multichannel signal processing workshop

作者： M.P. Kolba L.M. Collins Electrical and Computer Engineering Department Duke University Durham NC USA

Previous work has presented an information-theoretic sensor management framework for the detection of static targets. This framework is based on the expected discrimination gain maximization technique of Kastella. The sensor manager searches for N targets within a grid of cells using M sensors, which may be thought of as a reconfigurable sensor array. sensor probabilities of detection and false alarm are used in the mathematical structure of the sensor manager, and these probabilities have previously been assumed to be certain. Realistic problems, however, will inevitably involve uncertainty. This paper introduces uncertain sensor P d and P f values into the mathematical framework and allows for their incorporation into the sequential structure of the sensor manager. The performance of the presented sensor management technique is then compared to direct search, where the sensors sweep through the grid in a predefined sampling pattern. The sensor manager is found to be superior to direct search when the uncertainty present in the problem is properly modeled. When uncertainty is present but not modeled, the performance of the sensor manager is severely degraded. This result indicates that uncertainty modeling will be important and necessary for the successful application of the presented sensor manager to real-world problems. Additional simulations examine the robustness of the sensor manager to errors in the assumed densities for P d and P f , and the performance of the sensor manager is found to remain strong even when the assumed P d and P f densities differ from the true densities

关键词： sensor phenomena and characterization sensor arrays Uncertainty Multimodal sensors Engineering management Humans Landmine detection Gain measurement Sampling methods Degradation

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Extreme Beam Broadening using Phase Only Pattern Synthesis

Extreme Beam Broadening using Phase Only Pattern Synthesis

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sensor array and multichannel signal processing workshop

作者： G.C. Brown J.C. Kerce M.A. Mitchell Sensors and Electromagnetic Applications Laboratory Georgia Tech Research Institute Georgia Institute of Technology Atlanta GA USA

This paper describes methods for broadening the beam of a phased array antenna using phase-only element weights. This type of broadening can be valuable for improving the search occupancy and/or reducing the search frame time for large phased arrays, when transmit beam broadening is combined with multiple simultaneous receive beams. Phase-only broadening is required for typical solid-state (active phased) arrays because control of the transmit amplitude at each element is not practical. A notable result is that there is a relationship between the amount of beam broadening and the efficiency (directivity) of the resulting beam. In particular it is shown that broadening less than ~2.5:1 results in reduced beam efficiency for both linear and circular arrays, while a broadening of greater than ~2.5:1 results in improved beam efficiency, and that, therefore, certain broadening configurations will be preferable to the radar designer (e.g. 4:1 in one plane rather than 2:1 in two planes, due to a large difference in efficiency). The algorithms used to achieve the broadening patterns presented here are based on a combination of homotopy from known optimality with a stochastic gradient descent approach using a carefully constructed one parameter family of penalty functions

关键词： sensor arrays Apertures Laboratories Radar Robustness

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Blind Detection, Separation, and Location of Dense Co-Channel Emitters using Multiplatform Spatial-Coherence Restoral

Blind Detection, Separation, and Location of Dense Co-Channe...

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sensor array and multichannel signal processing workshop

作者： B.G. Agee B3 Advanced Communication Systems San Jose CA USA

The multiplatform spatial-coherence restoral (MP-SCORE) algorithm, introduced in 1988 to blindly separate spatially-coherent, temporally featureless signals based on their differing TDOA and FDOA at spatially separated antenna arrays, is extended to blind detection, separation, and location of dense co-channel emitters using wide-baseline collection networks. The original MP-SCORE algorithm is reviewed and related to the ML estimator of the location of a Gaussian-distributed source (or of the location and content of an unknown source) received in the presence of independent Gaussian-distributed interference with arbitrary spatial covariance at each array in the network. False-alarm and miss-rates for the corresponding MP-SCORE detector are also derived, and are shown to be a function of only the time-bandwidth product of the detector and the maximum source SENR attainable at each array in the network. Practical methods for detecting, separating, and locating multiple co-channel sources using MP-SCORE are then presented, and the end-to-end algorithm is demonstrated for a GPS C/A code jamming scenario in which two 8-sensor airborne receivers attempt to detect and locate 100 narrowband (2 MHz) noise-loaded emitters continuously transmitting over a wide (150times150 nmi) geographical region at the center of the GPS L1 frequency band. The simulated algorithm detects and geolocates 27 emitters to within 1/2 nmi over a single 26 ms snapshot, and detects and geolocates 38 emitters to within 445 feet over eleven 26 ms snapshots collected at 15 nmi intervals along the edge of the emission region

关键词： signal restoration Gaussian processes Detectors Global Positioning System Antenna arrays Maximum likelihood estimation Interference sensor arrays Jamming Narrowband

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Model for a Smart Network Monitoring a Wired sensor Matrix

Model for a Smart Network Monitoring a Wired Sensor Matrix

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sensor array and multichannel signal processing workshop

作者： L. Magagni D. Gennaretti M. Nicolini M. Sergio R. Guerrieri R. Canegallo ARCES University of Bologna Italy STMicroelectronics Italy

Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance; nevertheless, it poses additional challenges compared with standard applications. At Transducers2005 we presented a wired addressing architecture of distributed sensors for monitoring real-time in-situ pressure variations in underwater environment that faces the above-mentioned issues. This architecture consists in a double array of identical and interconnected smart nodes monitoring a matrix of passive sensors. In this paper, we present an analysis of the delay model related to the presented architecture and a calculation of the overall frame-rate of the system as a function of the geometrical topology of the arrays. The topology of the network, i.e. the length of each bus and the number of nodes, can be chosen according to the application, and directly affects the global capacitive load on the serial lines. Each serial line can be schematized with a distributed RC model for the flat cable plus a lumped capacitance for each smart node. Then, a 3 rd -order pi-segmented model of O'Brien-Savarino is calculated for a 16-block line with block length equal to 0.3 m. Thanks to that, the global time per iteration is calculated on each bus as well as the scanning time of the whole matrix and the frame rate for the system as a function of sensor distribution and of the aspect ratio of the matrix. This model can be employed to identify the optimal arrangement for the sensor matrix and smart node arrays

关键词： Monitoring Intelligent sensors sensor arrays Aircraft navigation Network topology Surveillance Delay Solid modeling Power cables Underwater cables

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DSP-Based Dual-Polarity Mass Spectrum Pattern Recognition for Bio-Detection

DSP-Based Dual-Polarity Mass Spectrum Pattern Recognition fo...

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sensor array and multichannel signal processing workshop

作者： V. Riot K. Coffee E. Gard D. Fergenson S. Ramani P. Steele Lawrence Livemore National Laboratory Livermore CA USA

The bio-aerosol mass spectrometry (BAMS) instrument analyzes single aerosol particles using a dual-polarity time-of-flight mass spectrometer recording simultaneously spectra of thirty to a hundred thousand points on each polarity. We describe here a real-time pattern recognition algorithm developed at Lawrence Livermore National Laboratory that has been implemented on a nine digital signal processor (DSP) system from Signatec Incorporated. The algorithm first pre-processes independently the raw time-of-flight data through an adaptive baseline removal routine. The next step consists of a polarity dependent calibration to a mass-to-charge representation, reducing the data to about five hundred to a thousand channels per polarity. The last step is the identification step using a pattern recognition algorithm based on a library of known particle signatures including threat agents and background particles. The identification step includes integrating the two polarities for a final identification determination using a score-based rule tree. This algorithm, operating on multiple channels per-polarity and multiple polarities, is well suited for parallel real-time processing. It has been implemented on the PMP8A from Signatec Incorporated, which is a computer based board that can interface directly to the two one-Giga-sample digitizers (PDA1000 from Signatec Incorporated) used to record the two polarities of time-of-flight data. By using optimized data separation, pipelining, and parallel processing across the nine DSPs it is possible to achieve a processing speed of up to a thousand particles per seconds, while maintaining the recognition rate observed on a non-real time implementation. This embedded system has allowed the BAMS technology to improve its throughput and therefore its sensitivity while maintaining a large dynamic range (number of channels and two polarities) thus maintaining the systems specificity for bio-detection

关键词： Pattern recognition signal processing algorithms Mass spectroscopy Magnesium compounds Digital signal processing Instruments Aerosols Real time systems Laboratories Digital signal processors

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