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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2000"

共 865 条记录，以下是281-290 订阅

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ANGLE ONLY TRACKING WITH PARTICLE FLOW FILTERS

ANGLE ONLY TRACKING WITH PARTICLE FLOW FILTERS

引用

conference on signal and data processing of small targets

作者： Daum, Fred Huang, Jim Raytheon Co Waltham MA 02451 USA

ISBN: (纸本)9780819487476

We show the results of numerical experiments for tracking ballistic missiles using only angle measurements. We compare the performance of an extended Kalman filter with a new nonlinear filter using particle flow to compute Bayes' rule. For certain difficult geometries, the particle flow filter is an order of magnitude more accurate than the EKF. Angle only tracking is of interest in several different sensors;for example, passive optics and radars in which range and Doppler data are spoiled by jamming.

关键词： Particles Particle filters Nonlinear filtering Spherical lenses Electronic filtering Error analysis Missiles Filtering (signal processing) Palladium Sensors

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Improved Multiframe Association for Tracking Maneuvering targets

Improved Multiframe Association for Tracking Maneuvering Tar...

引用

conference on signal and data processing of small targets

作者： Habtemariam, Biruk K. Tharmarasa, R. Nandakumaran, N. McDonald, M. Kirubarajan, T. McMaster Univ ECE Dept Hamilton ON Canada Curtin Univ Technol Perth WA Australia Def Res & Dev Canada Ottawa ON Canada

ISBN: (纸本)9780819487476

data association is the crucial part of any multitarget tracking algorithm in a scenario with multiple closely spaced targets, low probability of detection and high false alarm rate. Multiframe assignment, which solves the data association problem as a constrained optimization, is one of the widely accepted methods to handle the measurement origin uncertainty. If the targets do not maneuver, then multiframe assignment with one or two frames will be enough to find the correct data association. However, more frames must be considered in the data association for maneuvering targets. Also, a target maneuver might be hard to detect when maneuvering index, which is the function of sampling time, is small. In this paper, we propose an improved multiframe data association with better cost calculation using backward multiple model recursion, which increases the maneuvering index. The effectiveness of the proposed algorithm is demonstrated with simulated data.

关键词： multiframe data association interacting multiple model maneuvering targets smoothing out-of-sequence measurements

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Dynamic Sector processing using 2D Assignment for Rotating Radars

Dynamic Sector Processing using 2D Assignment for Rotating R...

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conference on signal and data processing of small targets

作者： Habtemariam, Biruk K. Tharmarasa, R. Pelletier, M. Kirubarajan, T. McMaster Univ ECE Dept Hamilton ON Canada FLIR Raders Laval PQ Canada

ISBN: (纸本)9780819487476

Electronically scanned array radars as well as mechanically steered rotating antennas return measurements with different time stamps during the same scan while sweeping form one region to another. data association algorithms process the measurements at the end of the scan in order to satisfy the common one measurement per track assumption. data processing at the end of a full scan resulted in delayed target state update. This issue becomes more apparent while tracking fast moving targets with low scan rate sensors. In this paper, we present new dynamic sector processing algorithm using 2D assignment for continuously scanning radars. A complete scan can be divided into sectors, which could be as small as a single detection, depending on the scanning rate and sparsity of targets. data association followed by filtering and target state update is done dynamically while sweeping from one end to another. Along with the benefit of immediate track updates, continuous tracking results in challenges such as multiple targets spanning multiple sectors and targets crossing consecutive sectors. Also, associations performed in the current sector may require changes in association done in previous sectors. Such difficulties are resolved by the proposed 2D assignment algorithm that implements an incremental Hungarian assignment technique. The algorithm offers flexibility with respect to assignment variables for fusing of measurements received in consecutive sectors. Furthermore the proposed technique can be extended to multiframe assignment for jointly processing data from multiple scanning radars. Experimental results based on rotating radars are presented.

关键词： target tracking rotating radar dynamic data association 2D assignment Hungarian assignment

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Noise-induced outpulsing technique for energy efficiency improvement of laser radar systems

Noise-induced outpulsing technique for energy efficiency imp...

引用

conference on signal and data processing of small targets

作者： Serikova, Maria G. Lebedko, Evgeny G. St Petersburg State Univ Informat Technol Mech & St Petersburg 197101 Russia

ISBN: (纸本)9780819487476

There are stringent false alarm probability demands on laser radar systems systems, although their operation is often accompanied by a complex target environment, when the signal-to-noise ratio is low. New signal processing technique for laser radar systems is suggested. The technique provides detection of a backscattered signal from a target during an interval between a receiver noise bursts A pulse shoot is matched with a trailing edge of a noise burst, and the signal presence decision is made according to leading edge of the next burst. There is a contradiction between the impulse frequency and false alarm probability demands, that is why double-threshold processing is offered. The lower level induces outpulsing while the higher one determines target detection performance. Since duration of such sophisticated time intervals is random, statistic analysis was made via numerical model. The technique is aimed at providing low false alarm probability and energy efficiency of the system at the same time.

关键词： laser radar system signal detection low signal-to-noise ratio processing levels-crossing interval distribution energy efficiency

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Evaluation of automated algorithms for small target detection and non-natural terrain characterization using remote multi-band imagery

Evaluation of automated algorithms for small target detectio...

引用

conference on signal and data processing of small targets

作者： Hallenborg, Eric Buck, David L. Daly, Erin Space & Naval Warfare Syst Ctr San Diego CA 92152 USA

ISBN: (纸本)9780819487476

Experimental remote sensing data from the 8 to 12 mu m wavelength NASA Thermal Infrared Multispectral Scanner (TIMS) have been a valuable resource for multispectral algorithm proof-of-concept, a prime example being a Constant False Alarm Rate (CFAR) spectral small target detector founded on maximum likelihood theory;CFAR tests on low signal-to-clutter ratio rural Australian TIMS imagery yielded a detection rate of 5 out of 7 (71%) for small extended targets, e. g. buildings similar to 10 meters in extent, at a 10(-6) false alarm rate. Separately, techniques such as Independent Component Analysis (ICA) have since shown good promise for small target detection as well as terrain feature extraction. In this study, we first provide higher-confidence CFAR performance estimates by incorporating a larger set of imagery including ASTER satellite multi-band imagery and ground truth. Secondly, alongside CFAR we perform ICA, which effectively separates many non-natural features from the highly cluttered natural terrain background;in particular, our TIMS results show that a surprisingly small subset of ICA components contain the majority of non-natural "signal" such as paved roads amid the clutter of soil, rock, and vegetation.

关键词： multispectral imagery small target CFAR detection algorithm

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NUMERICAL EXPERIMENTS FOR COULOMB'S LAW PARTICLE FLOW FOR NONLINEAR FILTERS

NUMERICAL EXPERIMENTS FOR COULOMB'S LAW PARTICLE FLOW FOR NO...

引用

conference on signal and data processing of small targets

作者： Daum, Fred Huang, Jim Noushin, Arjang Raytheon Co Waltham MA 02451 USA

ISBN: (纸本)9780819487476

We show numerical results for a new nonlinear filtering algorithm that is analogous to Coulomb's law. We have invented a new theory of exact particle flow for nonlinear filters. The flow of particles corresponding to Bayes' rule is computed from the gradient of the solution of Poisson's equation, and it is analogous to Coulomb's law. Our theory is a radical departure from other particle filters in several ways: (1) we compute Bayes' rule using a flow of particles rather than as a pointwise multiplication;(2) we never resample particles;(3) we do not use a proposal density;(4) we do not use importance sampling or any other MCMC algorithm;and (5) our filter is roughly 6 to 8 orders of magnitude faster than standard particle filters for the same accuracy.

关键词： Particles Nonlinear filtering Particle filters Algorithm development signal processing signal to noise ratio Algorithms Interference (communication) Electronic filtering Filtering (signal processing)

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Comparison of data Reduction Techniques Based on SVM Classifier and SVR Performance

Comparison of Data Reduction Techniques Based on SVM Classif...

引用

conference on signal and data processing of small targets

作者： Zhao, Dave Georgescu, Ramona Willett, Peter Univ Connecticut ECE Dept Storrs CT 06269 USA

ISBN: (纸本)9780819487476

In this work, we applied several data compression techniques to simulated data and the Turbofan engine degradation simulation data set from NASA, with the goal of comparing their performance when coupled with the Support Vector Machine (SVM) classifier and the SVM regression (SVR) predictor. We consistently attained correct rates in the neighborhood of 90% for simulated data set, with the Principal Component Analysis (PCA), Sparse Reconstruction by Separable Approximation (SpaRSA) and Partial Least Squares (PLS) having a slight edge over the other data reduction methods for data classification. We achieved 22% error rate with SRM for the Turbofan data set 1 and 40% error rate with PCA for Turbofan data set 2. Throughout the tests we have performed, PCA proved to be the best data reduction method.

关键词： data reduction PCA PLS SRM OMP SpaRSA Classification Regression SVM SVR

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Tracking Group targets Using Hypergraph Matching in data Association

Tracking Group Targets Using Hypergraph Matching in Data Ass...

引用

conference on signal and data processing of small targets

作者： Wu, Shunguang Xiao, Jiangjiang SRI Int Sarnoff Princeton NJ 08540 USA

ISBN: (纸本)9780819487476

Group moving targets are number of targets independently moving in a physical space but keeping their relative order or pattern invariant. The up to date state-of-the-art multi-target tracking (MTT) data association methods (GNN,JPDA,MHT) are easily fail on group targets tracking problems, since the tracker-to-observation ambiguity cannot be resolved if only using the individual track to observation information. A hypergraph G is represented by G = {V, E}, where V is a set of elements called nodes or vertices, E is a set of non-empty subsets containing d-tuple of vertices called hyperedges. It can be used as a new mathematic tool to represent a group of moving targets if we let each target be a vertex and a d-target subset be an hyperedge. Under this representation, this paper reformulates the traditional MTT data association problem as an hypergraph matching one between the hypergraphs formed from tracks and observations, and shows that the traditional approach (only uses the vertex-to-vertex information) which is a special case under the proposed framework. In addition to the vertex-to-vertex information, since the hyperedge-to-hyperegde information is also used in building the assignment matrix, the hypergraph matching based algorithms give better performance than that from the traditional methods in group target tracking problems. We demonstrate the declaration from simulations as well as video based geotracking examples.

关键词： Group targets tracking data association hypergraph matching

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Application of a joint tracking and identification method to dismount targets

Application of a joint tracking and identification method to...

引用

conference on signal and data processing of small targets

作者： Blackman, Sam Krikorian, Kapriel Rosen, Robert Durand, Catherine Schwoegler, Stefan Raytheon Co Waltham MA 02451 USA

ISBN: (纸本)9780819487476

This paper presents a method for tracking dismounts/humans in a potentially dense clutter background. The proposed approach uses Multiple Hypothesis Tracking (MHT) for data association and Interacting Multiple Model (IMM) filtering. The problem is made difficult by the presence of random and persistent clutter, such as produced by moving tree branches. There may also be moving targets (such as vehicles and animals) that are not of interest to the user of the tracking system, but that must be tracked in order to separate these targets from the targets of interest. Thus, a joint tracking and identification method has been developed to utilize the features that are associated with dismount targets. This method uses a Dempster-Shafer (D-S) approach to combine feature data to determine the target type (dismount versus other). Feature matching is also included in the computation of the track score used for MHT data association. The paper begins by giving an overview of the features that have been proposed in the literature for distinguishing humans from other types of targets. These features include radar cross section, target dynamics, and spectral and gait characteristics. For example, the number of secondary peaks around the main peak corresponding to the mean Doppler shift is one feature that is sent to the tracker. A large number of secondary peaks will be an indication that the observation is from an animal, rather than a vehicle. Also, if spectral analysis of the variation in Doppler shift due to torso motion yields a distinct periodic pattern with a peak at about 2 Hz, this can be used to identify the target as a human and, along with the target speed, may even be used as a target signature. The manner in which these features are estimated during signal processing and how this data is included in the track score is described. A test program conducted to produce data for analysis and development is described. Typical results derived from real data, collected during

关键词： target tracking identification dismount MHT multiple hypothesis Dempster-Shafer IMM spectral

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Interacting Multiple Model estimators for tracking thousands of interacting, small targets in a complex plasma

Interacting Multiple Model estimators for tracking thousands...

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conference on signal processing, Sensor Fusion, and Target Recognition XX

作者： Oxtoby, Neil P. Ralph, Jason F. Durniak, Celine Samsonov, Dmitry Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England

ISBN: (纸本)9780819486240

Tracking a large number of small targets is a challenging task. This work considers tracking approximately 3000 micron-sized particles in a complex plasma. Inter-particle screened-Coulomb interactions increase the complexity of the tracking problem, which is further complicated by highly nonlinear dynamics - a shock wave. Subsets of the particles are tracked concurrently by Interacting Multiple Model estimators, with the results combined off-line. State estimation is performed by an extended Kalman filter. Estimator performance is quantified on synthetic data, with discussion focussing on aspects of the Interacting Multiple Model.

关键词： tracking extended kalman filter interacting multiple model complex plasma dusty plasma

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