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共 447 条记录，以下是381-390 订阅

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the Network Centric Warfare Paradigm: the primacy of estimation, tracking and data fusion algorithms for implementation of this vision

The Network Centric Warfare Paradigm: The primacy of estimat...

引用

14th conference on signal and data processing of small targets

作者： Gray, JE Smith-Carroll, AS McCabe, DH Murray, WJ Alouani, AT USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819444782

What underpins this vision as axiomatic is the mantra "Information is power". Besides the necessary requirement of information exchange networks with sufficient bandwidth and computational power to treat the data being passed around the network;, algorithms are required to make sense of the data. It is estimation algorithms that turn the straw (data) into gold (information). Both proper execution and improvements in estimation algorithms are the enabling technology that facilitates the formation and usage of data across the envisioned warfare networks. We focus on some of the requirements that are driving the formation of these networks from a surface navy perspective in terms of estimation. We also discuss how these requirements focus the design of potentially new algorithms. We also discuss some of the crucial issues that may drive future requirements and algorithms.

关键词： Military operations

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Mysterious computational complexity of particle filters

Mysterious computational complexity of particle filters

引用

14th conference on signal and data processing of small targets

作者： Daum, F Huang, J Raytheon Elect Syst Sudbury MA 01776 USA

ISBN: (纸本)0819444782

Particle filtering (PF) is a relatively new method to solve the nonlinear filtering problem, which is very general and easy to code. the main issue with PF is the large computational complexity. In particular, for typical low dimensional tracking problems, the PF requires 2 to 4 orders of magnitude more computer throughput than the EKF, to achieve the same accuracy. It has been asserted that the PF avoids the curse of dimensionality, but there is no formula or theorem that bounds or approximates the computational complexity of the PF as a function of dimension (d). In this paper, we will derive a simple back-of-the-envelope formula that explains why a carefully designed PF should mitigate the curse of dimensionality for typical tracking problems, but that it does not avoid the curse of dimensionality in general. this new theory is related to the fact that the volume of the d dimensional unit sphere is an amazingly small fraction of the d dimensional unit cube, for large d.

关键词： Error analysis Monte Carlo methods Nonlinear filtering Particles Particle filters Filtering (signal processing) Optical spheres Electronic filtering Probability theory Statistical analysis

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Unresolved target detection - Detailed case study of a particular technique assuming correct calibration

Unresolved target detection - Detailed case study of a parti...

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14th conference on signal and data processing of small targets

作者： McCabe, DH Smith-Carroll, AS Gray, JE USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819444782

A particular method of detecting unresolved targets using simulated monopulse radar data is examined in detail. the system is assumed to be correctly calibrated i.e. the decision boundary is calculated based on the true values governing the hypothesis that only a single target is present in the range cell. the system performance is analyzed under varying values for target ranges, angles between the beam pointing direction and the actual off-boresight angle of the targets, waveform power and number of pulses. It is shown that these parameters have a pronounced impact on the Boundary, Metric and Decision Surfaces. the False Alarm probability for a single target as a function of waveform power is considered, as also are the detection probabilities when two targets are present. the important issue of locating the decision point on the Boundary Surface is briefly discussed.

关键词： unresolved targets radar cross-section Neyman Pearson hypothesis testing detection probability

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Expected likelihood for tracking in clutter with particle filters

Expected likelihood for tracking in clutter with particle fi...

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14th conference on signal and data processing of small targets

作者： Marrs, A Maskell, S Bar-Shalom, Y QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)0819444782

the standard approach to tracking a single target in clutter, using the Kalman filter or extended Kalman filter, is to gate the measurements using the predicted measurement covariance and then to update the predicted state using probabilistic data association. When tracking with a particle filter, an analog to the predicted measurement covariance is not directly available and could only be constructed as an approximation to the current particle cloud. A common alternative is to use a form of soft gating, based upon a Student's-t likelihood, that is motivated by the concept of score functions in classical statistical hypothesis testing. In this paper, we combine the score function and probabilistic data association approaches to develop a new method for tracking in clutter using a particle filter. this is done by deriving an expected likelihood from known measurement and clutter statistics. the performance of this new approach is assessed on a series of bearings-only tracking scenarios with uncertain sensor location and non-Gaussian clutter.

关键词： tracking probabilistic data association particle filters

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An MDL approach for multiple low observable track initiation

An MDL approach for multiple low observable track initiation

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14th conference on signal and data processing of small targets

作者： Chen, H Kirubarajan, T Bar-Shalom, Y Pattipati, KR Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)0819444782

In this paper the track initiation problem is formulated as multiple composite hypothesis testing using maximum likelihood estimation with probabilistic data association (ML-PDA), an algorithm known to work under very low SNR conditions. this algorithm does not have to make a decision as to which measurement is target originated. the hypothesis testing is based on the minimum description length (MDL) criterion. We first review some well-known approaches for statistical model selection and the advantage of the MDL criterion. then we present an approximate penalty in accounting for the model complexity to simplify the calculation of MDL. Finally, we apply the. MDL approach for the detection and initiation of tracks of incoming tactical ballistic missiles in the exo-atmospheric phase using a surface based electronically scanned array (ESA) radar. the targets are characterized by low SNR, which leads to low detection probability and high false alarm rate. the target acquisition problem is formulated using a batch of radar scans to detect the presence of up to two targets. the ML-PDA estimator is used to initiate the tracks assuming the target trajectories follow a deterministic state propagation. the approximate MDL criterion is used to determine the number of valid tracks in a surveillance region. the detector and estimator are shown to be effective even at 4.4 dB average SNR in a resolution cell (at the end of the signal processing chain).

关键词： track initiation minimum description length maximum likelihood estimator probabilistic data association model selection

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On track and tracklet fusion filtering

On track and tracklet fusion filtering

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14th conference on signal and data processing of small targets

作者： Drummond, OE CyberRnD Inc Culvar City CA 90230 USA

ISBN: (纸本)0819444782

Track and tracklet fusion filtering is complicated because the estimation errors of tracks from two sources for the same target may be cross-correlated. this cross-correlation of these errors should be taken into account when designing the filter used to combine the track data. this paper addresses the various track and tracklet fusion methods and their impact on communications load and tracking characteristics. In track and tracklet fusion a sequence of measurements is processed at the sensor or platform level to form tracks;then sensor level track data (in the form of tracks or tracklets) for a target is distributed and fused with each other or with a global track. Track Fusion and Tracklet Fusion are also sometimes called Hierarchical Fusion, Federated Fusion, or Distributed Fusion. Track data can include features or other information useful for target classification. One characteristic of track and tracklet fusion that distinguishes one method from another is whether the local track data is combined or if global tracks are maintained and updated using the sensor track data. Another important issue is whether there is filter process noise to accommodate target maneuvers. Some filtering methods are designed for maneuvering targets and others are not. this paper enumerates the various track and tracklet fusion methods for processing data from distributed sensors and their impact on filter performance and communications load.

关键词： target tracking multiple sensor tracking track fusion multiple target tracking sensor data fusion Bayesian methods tracklet distributed tracking estimation and filtering

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On expectation maximization applied to GMTI convoy tracking

On expectation maximization applied to GMTI convoy tracking

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14th conference on signal and data processing of small targets

作者： Koch, W FGAN FKIE D 53343 Wachtberg Neuenahrer Strasse 20 Germany

ISBN: (纸本)0819444782

Collectively moving ground targets are typical of a military ground situation and have to be treated as separate aggregated entities. For a long-range ground surveillance application with airborne GMTI radar we in particular address the task of track maintenance for ground moving convoys consisting of a small number of individual vehicles. In the proposed approach the identity of the individual vehicles within the convoy is no longer stressed. their kinematical state vectors are rather treated as internal degrees of freedom characterizing the convoy. which is considered as a collective unit. In this context, the Expectation Maximization technique (EM), originally developed for incomplete data problems in statistical inference and first applied to tracking applications by STREIT et al. [1, 2], seems to be a promising approach. We suggest to embed the EM algorithm into a more traditional Bayesian tracking framework for dealing with false or unwanted sensor returns. the proposed distinction between 'external' and 'internal' data association conflicts (i.e. those among the convoy vehicles) should also enable the application of sequential track extraction techniques introduced by VAN KEUK [3] for aircraft formations, providing estimates of the number of the individual convoy vehicles involved. Even with sophisticated signal processing methods (STAP: Space-Time Adaptive processing). ground moving vehicles can well be masked by the sensor specific clutter notch (Doppler blinding). this physical phenomenon results in interfering fading effects, which can well last over a longer series of sensor updates and therefore will seriously affect the track quality unless properly handled. Moreover, for ground moving convoys the phenomenon of Doppler blindness often superposes the effects induced by the finite resolution capability of the sensor. In many practical cases a separate modeling of resolution phenomena for convoy targets can therefore be omitted, provided the GMTI detectio

关键词： Ground Moving targets (GMT) Expectation Maximization (EM) Bayesian/Probabilistic Multiple Hypothesis Tracking (PMHT, MHT, PDA) Minimum Detectable Velocity (MDV) Doppler blinding sensor resolution phenomena

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Adaptive sensor management in target tracking

Adaptive sensor management in target tracking

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14th conference on signal and data processing of small targets

作者： Sworder, DD Boyd, JE Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)0819444782

Model-based. path estimation algorithms are commonly derived from a linear kinematic equation and an expansive observation model. the premise that the measurement region is all-inclusive simplifies the performance analysis, but it does not describe the relevant characteristics of some sensors. Most sensors have an active region. If the region contains, the target. a noisy location measurement is made. Alternatively, no location measurement is returned. there is a clear tradeoff between measurement acuity and broad coverage. A sensor that adapts its active region to the most likely target location should achieve higher quality tracking and identification. However. effective utilization of this flexibility requires an accurate determination of the conditional distribution of the target-state. In this paper, the Gaussian Wavelet Estimator is used in an adaptive algorithm for sensor management. It is shown that the adaptive window provides performance that is superior to that achieved using a fixed window of comparable cover probability.

关键词： nonlinear filters target tracking data fusion

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Adaptive mean and variance filter for detection of dim point-like targets

Adaptive mean and variance filter for detection of dim point...

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14th conference on signal and data processing of small targets

作者： Lim, ET Shue, L Venkarteswarlu, R Nanyang Technol Univ Ctr Signal Proc Singapore 639798 Singapore

ISBN: (纸本)0819444782

the problem of detecting small target in IR imagery has attracted much research effort over the past few decades. As opposed to early detection algorithms which detect targets spatially in each image and then apply tracking algorithm, more recent approaches have used multiple frames to incorporate temporal as well as spatial information. they often referred to as "track before detect" algorithms. this approach has shown promising results particularly for detection of dim point-like targets. However, the computationally complexity has prohibited practical usage for such algorithms. this paper presents an adaptive, recursive and computation efficient detection method. this detection algorithm updates parameters and detects occurrence of targets as new frame arrived without storing previous frames, thus achieved recursiveness. Besides, the target temporal intensity change is modeled by two Gaussian distribution with different mean and variance. the derivation of this generalized model has taken account of the wide variation of target speed, therefore detects wider range of targets.

关键词： small target temporal filter triple temporal filter continuous wavelet transform

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Track-to-track association and bias removal

Track-to-track association and bias removal

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14th conference on signal and data processing of small targets

作者： Stone, LD Williams, ML Tran, TM Metron Inc Reston VA 20190 USA

ISBN: (纸本)0819444782

this paper develops methods for associating two sets of sensor tracks in the presence of missing tracks and translation bias. Key results include (1) Extension of the Maximum A Posteriori Probability method of matching tracks to use feature information as well as kinematic information;(2) translation bias removal techniques that are computationally tractable for large numbers of tracks, and effective in the presence of missing tracks. these methods were evaluated by Monte Carlo simulation. the experimental results indicate that the Maximum A Posteriori Probability method with its adaptive threshold achieves close to its best performance for matching tracks without an additional threshold adjustment.

关键词： Sensors Target detection Monte Carlo methods Computer programming Fourier transforms Computer simulations Detection and tracking algorithms signal to noise ratio Kinematics Copper

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