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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2010"

共 976 条记录，以下是751-760 订阅

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Vehicle tracking using a network of small acoustic arrays

Vehicle tracking using a network of small acoustic arrays

引用

IEEE conference on Aerospace

作者： V. Calloway R. Hodges S. Harman A. Hume D. Beale QinetiQ Limited Malvern Worcestershire UK

Major advances in base technologies of computer processors and low cost communications have paved the way for a resurgence of interest in unattended ground sensors. Networks of sensors offer the potential of low cost persistent surveillance capability in any area that the sensor network can be placed. Key to this is the choice of sensor on each node. If the system is to be randomly deployed then nonline of sight sensor become a necessity. Acoustic sensors potentially offer the greatest level of capability and will be considered here. As a passive sensor, only time of arrival or bearing information can be obtained from an acoustic array, thus the tracking of targets must be done in this domain. This work explores the critical step between array processing and implementation of the tracking algorithm. Specifically, unlike previous implementations of such a system, the bearings from each frequency interval of interest are not averaged but are used as data points within a Kalman filter. Thus data is not averaged and then filtered but all data is put into the tracking filter.

关键词： Vehicles Acoustic arrays Acoustic sensors Sensor arrays Costs Target tracking Surveillance Sensor systems Array signal processing Frequency

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Developing a CFAR filter for detecting point targets using a dynamic programming algorithm

Developing a CFAR filter for detecting point targets using a...

引用

conference on signal and data processing of small targets

作者： Madar, H Avishai, T Succary, R Rotman, SR Ben Gurion Univ Negev Dept Elect & Comp Engn IL-84105 Beer Sheva Israel

ISBN: (纸本)0819450774

A method to detect and track point targets in infrared imagery is briefly described. The final output of the algorithm is a single image containing scores related to the probability of a target being located at any particular pixel. This image will be analyzed to deterrrtine the presence and location of suspected targets, based on CFAR requirements.

关键词： Target detection Detection and tracking algorithms Algorithm development Filtering (signal processing) Image processing signal to noise ratio Computer programming Image filtering Image analysis signal processing

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IMMPDAF solution for the tracking and radar management benchmark with merged measurements and multipath

IMMPDAF solution for the tracking and radar management bench...

引用

conference on signal and data processing of small targets

作者： Sinha, A Kirubarajan, T Bar-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06268 USA

ISBN: (纸本)0819450774

Radar signal processing is a key part in tracking closely spaced targets and targets in the presence of sea-surface-induced multipath. These issues are the salient features of the benchmark problem for tracking unresolved targets combined with radar management, for which this paper presents the only complete solution to date. In this paper a modified version of a recently developed "superresolution" maximum likelihood (ML) angle estimator for closely spaced targets as well as targets in the presence of multipath are presented. Efficient radar resource allocation algorithms for two closely spaced targets and targets flying close to the sea surface are also presented. Finally, the IMMPDAF (interacting multiple model estimator with probabilistic data association filter modules) is used to track these targets. It is found that a two-model IMMPDAF performs better than the three model version used in the previous benchmark. Also, the IMMPDAF with a coordinated turn model works better than the one using a Wiener process acceleration model. The signal processing and tracking algorithms presented here, operating in a feedback manner, form a comprehensive solution to the most realistic tracking and radar management problem to date.

关键词： Radar signal processing Performance modeling Detection and tracking algorithms Target detection signal to noise ratio Super resolution Sensors data modeling Radar signal processing

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Sidelobe reduction for efficient detection of multiple radar targets

Sidelobe reduction for efficient detection of multiple radar...

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conference on signal and data processing of small targets

作者： Deng, H Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

ISBN: (纸本)0819450774

With multiple radar targets the sidelobe of matched filtering outputs from the stronger targets become the interferences for the detection of weaker targets. An effective approach based on traditional CLEAN algorithm is proposed for sidelobe reduction for the matched filtering output of binary coding radar signals. A novel multilevel sidelobe reduction method is also developed for closely located multiple targets of nearly equally strong scatterings. The effectiveness of the sidelobe reduction algorithms is demonstrated through the numerous processing results.

关键词： radar target detection pulse compression CLEAN algorithms interference reduction

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Two-dimensional assignment with merged measurements using Lagrangian relaxation

Two-dimensional assignment with merged measurements using La...

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conference on signal and data processing of small targets

作者： Briers, M Maskell, S Philpott, M QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)0819450774

Closely spaced targets can result in merged measurements, which complicate data association. Such merged measurements violate any assumption that each measurement relates to a single target. As a result, it is not possible to use the auction algorithm in its simplest form (or other two-dimensional assignment algorithms) to solve the two-dimensional target-to-measurement assignment problem. We propose an approach that uses the auction algorithm together with Lagrangian relaxation to incorporate the additional constraints resulting-from the presence of merged measurements. We conclude with some simulated results displaying the concepts introduced, and discuss the application of this research within a particle filter context.

关键词： signal processing

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AOA estimation with merged measurements from squint beam monopulse data in conjunction with multiple range samples

AOA estimation with merged measurements from squint beam mon...

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conference on signal and data processing of small targets

作者： Brown, GC Blair, WD Ogle, TL GTRI SEAL AMDD Atlanta GA 30332 USA

ISBN: (纸本)0819450774

A key assumption in monopulse based angle-of-arrival (AOA) estimators is that at most one return from a single object is present in each range cell, or equivalently in each sample of the matched filter output. These algorithms break down if the data consists of merged measurements-multiple target returns contained in the same range cell. The proposed technique makes use of data from a three channel monopulse radar to estimate the AOA of two targets from merged measurements. Specifically, the technique capitalizes on the structure of squint beams in conjunction with multiple range samples to resolve the multiple targets. The paper focuses on the development of the new algorithm along with results from computer simulations that demonstrate its viability. To illustrate the utility of this technique to target tracking problems, comparative Monte Carlo results of performance of a tracker with the new technique and conventional monopulse AOA estimates are provided.

关键词： merged measurements monopulse angle of arrival radar signal processing

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Tracking targets using matched field observations

Tracking targets using matched field observations

引用

conference on signal and data processing of small targets

作者： Willett, PK Bishop, J Giannopoulos, E Univ Connecticut ECE Dept U 1157 Storrs CT 06269 USA

ISBN: (纸本)0819450774

The target tracking literature has traditionally been most interested in the "hit" model for the observations process, and the community has developed many techniques for data association. On the other hand, matched field processing (MFP) research has focused on signal processing with the main emphasis on target detection and localization. Treatments of combined tracking/MFP systems are not common. but most concentrate on signal processing, with the idea that a "track" is really a sequence or track-segment of detections that make sense from dynamics considerations. Thus, here we explore the MFP tracking problem, with the key that we attempt to use traditional target-tracking algorithms. In particular. we use an IMMPDAF-AI (interacting multiple-model probabilistic data association filter with amplitude information). It is shown that the use of such an advanced tracking algorithm - plus a number of MFP-specific refinements - produces tracking performance that is far superior to that obtained for a more traditional tracking (a strongest-neighbor Kalman filter), with the added advantage of a significantly reduced numerical load as measured in terms of the number of MFP replicas to be computed.

关键词： Target tracking matched field processing passive sonar interacting multiple models probabilistic data association filter

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Comparison of methods for tracking separating targets with a monopulse radar

Comparison of methods for tracking separating targets with a...

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conference on signal and data processing of small targets

作者： Willett, PK Blair, WD Ogle, TL Register, AH Brown, GC Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819450774

In many tracking applications. and particularly those in ballistic missile defense, one concern involves the continuous tracking of an object that separates into two objects. Reliable tracking without track breaks demands early recognition of such a split, preferably well in advance of the two objects becoming resolvable by the radar. In previous work, signal processing techniques for detecting the presence of unresolved objects and angle-of-arrival estimation for unresolved targets have been developed for monopulse radars. In this paper, these techniques are reviewed and extended. Techniques for detecting the presence of unresolved objects are treated for the case of idealized resolution, in which all of the energy for a target is returned in a single range resolution sample or cell. The approaches work solely on monopulse angle statistics and rely on idealized range resolution. The requirement for idealized range resolution is relaxed by using joint statistics with adjacent matched filter returns. The AOA estimation and detection of the presence of unresolved objects for non-ideal resolution are then addressed. The performances are demonstrated using a high fidelity software simulation tool for target tracking.

关键词： radar target tracking radar signal processing resolution

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Tracking with classification-aided multiframe data association

Tracking with classification-aided multiframe data associati...

引用

conference on signal and data processing of small targets

作者： Bar-Shalom, Y Kirubarajan, T Gokberk, C Univ Connecticut ECE Dept Storrs CT 06269 USA

ISBN: (纸本)0819450774

In most conventional tracking systems. only the tar-et kinematic information is used in measurement-to-track association. Target class information, which is typically used in postprocessing, can also be used to improve data association to give better tracking accuracy. In addition. the use of tar-et class information in data association can improve discrimination by yielding purer tracks and preserve their continuity. In this paper. we present the integrated use of target classification information and target kinematic information for target tracking. In our approach, target class information is integrated into the data association process using the two-dimensional (one track list and one measurement list) as well as multiframe (one track list and multiple measurement lists) assignments. The latter is an optimization based MHT. A generic model of the classifier output is considered and its use in association likelihoods is discussed. The multiframe association likelihood is developed to include the classification results based on the confusion matrix that specifies the accuracy of the target classifier. The objective is to improve association results using class information when the kinematic likelihoods are similar for different targets, i.e., there is ambiguity in using kinematic information alone. Performance comparison with and without the use of class information in data association is presented on a ground target tracking problem where targets are moving in an open field and their tracks can merge, branch and cross. Simulation results quantify the benefits of classification aided data association for improved target tracking, especially in the presence of association uncertainty in kinematic measurements. Also the benefit of S-D (multiframe) association vs. 2-D association is investigated for different quality classifiers. The main contribution is the development of the methodology to incorporate exactly the classification information into multidimensional (mu

关键词： multitarget-tracking feature-aided tracking classification-aided tracking ground target tracking multiframe association assignment algorithms

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Fractal properties of background noise and target signal enhancement using CSEM data

Fractal properties of background noise and target signal enh...

引用

conference on Detection and Remediation Technologies for Mines and Minelike targets VIII

作者： Benavides, A Everett, M Pierce, C Nguyen, C Texas A&M Univ Dept Geol & Geophys College Stn TX 77843 USA

ISBN: (纸本)0819449490

Controlled-source electromagnetic (CSEM) spatial profiles and 2-D conductivity maps were obtained on the Brazos Valley, TX floodplain to study the fractal statistics of geological signals and effects of man-made conductive targets using Geonics EM34, EM31 and EM63. Using target-free areas, a consistent power-law power spectrum (\A(k)\ similar to k(boolean AND-)beta) for the profiles was found with P values typical of fractional Brownian motion (fBm). This means that the spatial variation of conductivity does not correspond to Gaussian statistics, where there are spatial correlations at different scales. The presence of targets tends to flatten the power-law power spectrum (PS) at small wavenumbers. Detection and localization of targets can be achieved using short-time Fourier transform (STFT). The presence of targets is enhanced because the signal energy is spread to higher wavenumbers (small scale numbers) in the positions occupied by the targets. In the case of poor spatial sampling or small amount of data, the information available from the power spectrum is not enough to separate spatial correlations from target signatures. Advantages are gained by using the spatial correlations of the fBm in order to reject the background response, and to enhance the signals from highly conductive targets. This approach was tested for the EM31 using a pre-processing step that combines apparent conductivity readings from two perpendicular transmitter-receiver orientations at each station. The response obtained using time-domain CSEM is influence to a lesser degree by geological noise and the target response can be processed to recover target features. The homotopy method is proposed to solve the inverse problem using a set of possible target models and a dynamic library of responses used to optimize the starting model.

关键词： fractal noise spectral analysis background noise target signal enhancement controlled source electromagnetic homotopy

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