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conference on signal and data processing of small targets 1994

作者： BARTOLAC, TJ ANDERT, EP SPARTA SYST INC EL SEGUNDOCA 90245

ISBN: (纸本)0819415391

In this paper we extend the capabilities of the Wave Process in three major areas. This is a continuation of work that was reported earlier. The Wave Process can now adapt its behavior to detect a point target moving with an arbitrary velocity while still rejecting stationary background and clutter. It can also adapt to different target velocities simultaneously occurring at different locations on the focal plane. This is achieved through neuromorphic methods, without recourse to clocks, programmability, or other aspects of the digital processing paradigm. We also present a single planar circuit that performs the functions of the positive, negative, and wave-sum planes, with a more efficient analog VLSI implementation for on- focal plane integration. Finally, we develop a more through understanding of the Wave Process performance through numerical simulations of the ideal modeling equations and SPICE simulations of the ideal hardware representations for stationary sources and moving targets.

关键词： Analog electronics Very large scale integration Sensors Target detection Resistance signal detection Resistors signal processing Device simulation Transistors

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LIKELIHOOD INTERPOLATION FOR PEAK DETECTION

LIKELIHOOD INTERPOLATION FOR PEAK DETECTION

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conference on signal and data processing of small targets 1994

作者： LINDGREN, R WESTON, D ARETE ASSOCIATES SHERMAN OAKSCA 91413

ISBN: (纸本)0819415391

In this paper we present a likelihood technique for determining candidate target detections to pass to a tracker over successive temporal intervals. In a representative situation sensor data are available from each interval as matched-filter output sampled at discrete position-velocity state hypotheses. A likelihood ratio for an arbitrary target hypothesis from the continuous state domain can be constructed from the sampled filter output, and we seek local maxima in this likelihood-ratio field as the candidate detections. We obtain a readily implemented algorithm which closely follows this optimal prescription by limiting the sample points in the likelihood construction to the immediate vicinity of a discrete local maximum in the filter output.

关键词： signal to noise ratio Electronic filtering Detection and tracking algorithms Target detection Interference (communication) signal detection Reconstruction algorithms Sensors Radon signal attenuation

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PERFORMANCE EVALUATION OF MULTIPLE HYPOTHESIS FILTER FOR TRACK INITIATION

PERFORMANCE EVALUATION OF MULTIPLE HYPOTHESIS FILTER FOR TRA...

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conference on signal and data processing of small targets 1994

作者： CASSASSOLLES, E TOMASINI, B SYSTELIA TECHNOL F-83320 CARQUEIRANNEFRANCE

ISBN: (纸本)0819415391

This paper deals with global track initiation problem and our purpose is to apply a quite efficient method called the Multiple Hypothesis Filter to solve it for Radar applications. This original measurement-oriented approach has been implemented in an object-oriented way and applied to simulated and realdata. This paper presents some results of MHF perfonnance evaluation which are based on determination of VfIOUS track initiation criteria (initiation time, initiation lapse. false track rate, ...)

关键词： Target detection data processing Monte Carlo methods Detection and tracking algorithms Computer simulations data modeling Radar Time metrology Environmental sensing Palladium

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ELEMENT QUALITY ANALYSIS - ESTIMATING THE ACCURACY OF EPHEMERIS PREDICTION FROM ORBITAL ELEMENTS

ELEMENT QUALITY ANALYSIS - ESTIMATING THE ACCURACY OF EPHEME...

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conference on signal and data processing of small targets 1994

作者： SIEGEL, A MITRE CORP COLORADO SPRINGSCO 80906

ISBN: (纸本)0819415391

Element Quality Analysis (EQA) is the evaluation of the accuracy with which an orbital element set describes the orbit of a satellite. This paper proposes practical methods for evaluating element quality and describes the benefits of improved EQA. The paper first discusses the need for and applications of EQA. Past and current operational methods for EQA are then considered. The main portion of the paper describes alternative methods for EQA.

关键词： Satellites Chemical elements Error analysis Sensors Statistical analysis Differential equations Surface plasmons Filtering (signal processing) Motion models Stochastic processes

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Detection and Localization of Multiple Unresolved Extended targets via Monopulse Radar signal processing

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2009年第2期45卷 455-472页

作者： Zhang, Xin Willett, Peter Bar-Shalom, Yaakov United Technol Res Ctr E Hartford CT 06108 USA Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

When the size of targets is comparable to the range resolution of monopulse radars, these targets should be considered as extended rather than point targets. If several closely-spaced targets fall within the same radar beam and between adjacent matched filter samples in range, the full monopulse information from all of these samples can and should be used to resolve these targets, i.e., estimate the number of targets and their respective angles-of-arrival and ranges. To detect and localize multiple unresolved extended targets, we establish a model for monopulse radar returns from extended objects, and present a maximum likelihood estimator (MLE) to localize the targets. Rissanen's minimum description length (MDL) criterion will be used to decide the number of existing extended objects. We also derive the upper limit on the number of targets and their scattering centers that can be resolved, and we provide necessary conditions for these targets to be uniquely identified. We compare the new extended target monopulse processing scheme with previously developed point-target monopulse techniques in the simulations.

关键词： RADAR ELECTRONIC pulse techniques ELECTRONIC systems signal processing -- Digital techniques MACHINE theory

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FUSION OF RADAR AND IMAGING SENSOR data FOR TARGET TRACKING

FUSION OF RADAR AND IMAGING SENSOR DATA FOR TARGET TRACKING

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conference on signal and data processing of small targets 1994

作者： ROMINE, JB KAMEN, EW SASTRY, CR GEORGIA INST TECHNOL SCH ELECT & COMP ENGNATLANTAGA 30332

ISBN: (纸本)0819415391

This paper deals with the fusing of data from radar and imaging sensors at the dynamic level by generating a common state and observation model that relates the measurements to the common state vector. A key point which is taken into account in the paper is the fact that a radar provides center-of-reflection measurements that may not correspond very well to the true target center, and as the target aspect changes, the center-of-reflection may vary about the true target center. For small targets at long range, this effect may be negligible, but for semi- extended or extended objects, the mismatch must be considered. In the approach developed in the paper, the radar center-of-reflection measurements are modeled in terms of random perturbations of unknown constant off-sets from the true target center in spherical coordinates. Estimate of these off-sets are used in an extended Kalman filter approach to target tracking using radar and imaging sensor data. The performance of the resulting tracking filter is evaluated via computer simulations.

关键词： Radar Optical sensors Sensors Filtering (signal processing) Radar sensor technology Spherical lenses data modeling Electronic filtering data fusion Computer simulations

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PERFORMANCE EVALUATION OF A MULTISENSOR data FUSION IMPLEMENTATION - A PROGRESS REPORT

PERFORMANCE EVALUATION OF A MULTISENSOR DATA FUSION IMPLEMEN...

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conference on signal and data processing of small targets 1994

作者： BOILY, E PARAMAX SYST CANADA INC MONTREAL H4P 1K6PQCANADA

ISBN: (纸本)0819415391

A sensor-level hard fusion system is currently being developed for the Canadian Patrol Frigate (CPF) within the simulation environment provided by the Combat System Test and Support Facility at Paramax. A number of operational criteria have been selected to evaluate and to compare the performance of the CPF's Command and Control System versus the data fusion system. The criteria operate on tracking and on identification in terms of time efficiency and precision. Since the implementation is done on a simulation environment, the target's ground truth is available (off-line in the current implementation). Some criteria are computed and displayed in real-time and the criteria needing access to ground truth are evaluated off-line. A subset of the performance evaluation criteria are presented and discussed. Implementation considerations are also presented.

关键词： data fusion databases Sensors Filtering (signal processing) data modeling Electronic filtering Environmental sensing Statistical analysis Telecommunications Software development

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ADAPTIVE SPATIAL SPECTRAL DETECTION OF SUBPIXEL targets WITH UNKNOWN SPECTRAL CHARACTERISTICS

ADAPTIVE SPATIAL SPECTRAL DETECTION OF SUBPIXEL TARGETS WITH...

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conference on signal and data processing of small targets 1994

作者： FERRARA, CF WJ SCHAFER ASSOCIATES INC ROMENY 13440

ISBN: (纸本)0819415391

This paper extends the maximum likelihood concept as applied to the adaptive detection of sub-pixel targets with unknown spectral signatures. The clutter is modeled stochastically with a spatial-spectral covariance matrix. The target model is primarily stochastic and partially deterministic. Within any given spectral band the spatial target signature is deterministic. For the sub-pixel target application, a system point spread function (PSF) is used. The PSF is allowed to vary spectrally, due to the dependency of a sensor's diffractive PSF on the spectral wavelength. The spectral target signature is completely stochastic and must be determined at each pixel using maximum likelihood estimation techniques. Based on these assumptions, an optimal maximum likelihood processor is derived. Encouraging performance results are presented from real IR data. Detection probabilities are shown in many cases to improve significantly when compared to spatial-only detection processes.

关键词： Detection and tracking algorithms Target detection data modeling Image processing databases Digital filtering Point spread functions Optical filters Statistical modeling Algorithm development

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FUSEDAT - A SOFTWARE PACKAGE FOR FUSION AND data ASSOCIATION AND TRACKING WITH MULTIPLE SENSORS

FUSEDAT - A SOFTWARE PACKAGE FOR FUSION AND DATA ASSOCIATION...

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conference on signal and data processing of small targets 1994

作者： CHANG, KC BARSHALOM, Y GEORGE MASON UNIV DEPT SYST ENGNFAIRFAXVA 22030

ISBN: (纸本)0819415391

Multisensor tracking and data fusion deals with combining data from various sources to arrive at an accurate assessment of the situation. Difficulties in performing multisensor tracking and fusion include not only ambiguous data, but also disparate data sources. In this paper, a software package called FUSEDAT which deals with tracking and data association with multiple sensors is described. FUSEDAT is implemented in the MATLAB environment and is portable to different platforms that support MATLAB. This software package provides a simple yet flexible environment for multitarget multisensor tracking and fusion. It is intended for rapid system prototyping and performance evaluation.

关键词： Sensors data fusion Detection and tracking algorithms MATLAB Personal digital assistants signal to noise ratio Error analysis Filtering (signal processing) Prototyping Target detection

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RADAR TARGET DISCRIMINATION USING WAVELET TRANSFORMS

RADAR TARGET DISCRIMINATION USING WAVELET TRANSFORMS

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conference on signal and data processing of small targets 1994

作者： VARAD, R MITRE CORP BEDFORDMA 01730

ISBN: (纸本)0819415391

In this paper, we describe a new approach to radar target discrimination. Specifically, we will apply it to the problem of exo-atmospheric object discrimination from UHF radar returns. The method uses wavelet transforms, pattern recognition techniques such as feature spaces, vectors and neural net classifiers. Feature vectors for each object are constructed from the wavelet transforms of the input data samples. The feature vectors are based on energies at each scale of the wavelet transforms and therefore effectively circumvent the problem of noncoherence due to target and ionospheric effects. This is a very important consideration when coherent signal processing is not feasible. The feature vectors are input to an unsupervised learning neural network for classification of the objects. In unsupervised learning, the network output is not forced towards a desired response for each input pattern but allowed to learn proximity to past input patterns. Limited results from simulated radar cross-section (RCS) data indicate that most objects can be correctly classified. The results also show that the overall scheme is quite immune to fair amounts of gaussian as well as uniformly distributed noise. Further efforts are under way to test the methodology against real object data as well as more extensive simulations.

关键词： Wavelets Neural networks Radar Wavelet transforms signal to noise ratio signal processing Neurons Image classification Doppler effect Machine learning

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