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检索条件"任意字段=18th Conference on Signal and Data Processing of Small Targets"

共 390 条记录，以下是91-100 订阅

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Tracking manoeuvring targets using a scale mixture of normals

Tracking manoeuvring targets using a scale mixture of normal...

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16th conference on signal and data processing of small targets

作者： Maskell, S Gordon, N Everett, N Robinson, M QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)081945351X

the assumption of Gaussian noise in the system and measurement model has been standard practice for target tracking algorithm development for many years. For problems involving manoeuvring targets this is known to be an over-simplification and a potentially poor approximation. In this paper the use of heavy-tailed distributions is suggested as a means of efficiently modelling the behaviour of manoeuvring targets with a single dynamic model. We exploit the fact that all heavy-tailed distributions can be written as scale mixture of Normals to propose a Rao-Blackwellised particle filter (SMNPF) where particles sample the history of the continuous scale parameter and a Kalman filter is used to conduct the associated filtering for each particle. Schemes are proposed for making the proposal of new particles efficient. Performance of a heavy-tailed system model implemented via the SMNPF filter is compared against an IMM for a sample trajectory taken from a benchmark problem.

关键词： tracking filtering manoeuvring target non-Gaussian heavy-tailed distribution particle filter

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small object hyperspectral detection from a low-flying UAV

Small object hyperspectral detection from a low-flying UAV

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20th conference on signal and data processing of small targets

作者： Murray-Krezan, J. Neumann, J. G. Leathers, R. A. USN Res Lab Washington DC 20375 USA

ISBN: (纸本)9780819471604

small object detection with a low false alarm rate remains a challenge for automated hyperspectral detection algorithms when the background environment is cluttered. In order to approach this problem we are developing a compact hyperspectral sensor that can be fielded from a small unmanned airborne platform. this platform is capable of flying low and slow, facilitating the collection of hyperspectral imagery that has a small ground-sample distance (GSD) and small atmospheric distortion. Using high-resolution hyperspectral imagery we simulate various ranges between the sensor and the objects of interest. this numerical study aids in analysis of the effects of stand-off distance on detection versus false alarm rates when using standard hyperspectral detection algorithms. Preliminary experimental evidence supports our simulation results.

关键词： hyperspectral HSI GSD small object detection

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18th International conference on Artificial Intelligence and Natural Language processing and International conference on Artificial Intelligence and Internet of things, iSAI-NLP 2023

18th International Conference on Artificial Intelligence and...

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18th International Joint Symposium on Artificial Intelligence and Natural Language processing, iSAI-NLP 2023 and 4th International conference on Artificial Intelligence and Internet of things, AIoT 2023

ISBN: (纸本)9798350371215

the proceedings contain 43 papers. the topics discussed include: solar-powered IoT charging system for ESP32 in organic rice field;STAT intelligence: data management and monitoring platform for BCG economy model;comment usefulness classification on YouTube using artificial neural networks;vehicle telematics system design for real-time applications using mobile networks;using knowledge graphs to enhance keyword search efficiency of the online encyclopedia and taxonomy system of the office of the royal society;decode brain signal into thai word using EEG and L-SVM;cloud stateless server failover prediction using machine learning on proactive system metrics;generative AI for self-healing systems;machine learning to examine the foraging periods of bees;spoof detection using voice contribution on LFCC features and ResNet-34;and Simple2In1: a simple method for fusing two sequences from different captioning systems into one sequence for a small-scale thai dataset.

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Maximum likelihood angle extractor in the presence of sea-surface multipath

Maximum likelihood angle extractor in the presence of sea-su...

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14th conference on signal and data processing of small targets

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

ISBN: (纸本)0819444782

In the presence of sea-surface multipath monopulse radar signals from a low elevation target have three alternative paths in addition to the direct (radar-to-target) path due to reflections from the sea surface. the specular reflection causes significant signal fading. the diffuse reflection causes an approximately constant bias to the in-phase component of the monopulse ratio, which is the standard extractor of the direction of arrival (DOA) in the monopulse processing. the diffuse reflection also causes higher standard deviation to the in-phase component of the monopulse ratio. In this paper we propose a maximum likelihood (ML) angle extraction technique for low elevation targets of known average signal strength having a Rayleigh fluctuation. the results show that this method reduces the error of the estimated angle compared to the conventional monopulse ratio estimator. Subsequently, the ML angle extractor is modified for the unknown average signal strength case. this modified angle extractor has only a small performance degradation compared with the known average signal strength case, but it performs much better than the monopulse ratio based estimator. this angle extractor reduces the root mean square error (RMSE) by more than 50% in the signal processing stage when used in a low flying target (sea skimmer) tracking scenario.

关键词： Radar Reflection signal to noise ratio Specular reflections Error analysis signal processing Detection and tracking algorithms Silicon Analytical research Computer engineering

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Discriminating small extended targets at sea from clutter and other classes of boats in infrared and visual light imagery

Discriminating small extended targets at sea from clutter an...

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20th conference on signal and data processing of small targets

作者： van den Broek, Sebastiaan P. Bouma, Henri Degache, Marianne A. C. TNO Def Secur & Safety NL-2509 JG The Hague Netherlands

ISBN: (纸本)9780819471604

Operating in a coastal environment, with a multitude of boats of different sizes, detection of small extended targets is only one problem. A further difficulty is in discriminating detections of possible threats from alarms due to sea and coastal clutter, and from boats that are neutral for a specific operational task. Adding target features to detections allows filtering out clutter before tracking. Features can also be used to add labels resulting from a classification step. Both will help tracking by facilitating association. Labeling and information from features can be an aid to an operator, or can reduce the number of false alarms for more automatic systems. In this paper we present work on clutter reduction and classification of small extended targets from infrared and visual light imagery. Several methods for discriminating between classes of objects were examined, with an emphasis on less complex techniques, such as rules and decision trees. Similar techniques can be used to discriminate between targets and clutter, and between different classes of boats. Different features are examined that possibly allow discrimination between several classes. data recordings are used, in infrared and visual light, with a range of targets including rhibs, cabin boats and jet-skis.

关键词： classification clutter reduction target recognition small targets boats jet-ski

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Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets

Detection of unusual trajectories using multi-objective evol...

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25th SPIE conference on signal and data processing of small targets

作者： Smolinski, Tomasz G. Newell, Trevor McDaniel, Samantha Pokrajac, David Delaware State Univ Dept Comp & Informat Sci Dover DE 19901 USA

ISBN: (纸本)9780819497079

Detection of unusual trajectories of moving objects (e.g., people, automobiles, etc.) is an important problem in many civilian and military surveillance applications. In this work, we propose a multi-objective evolutionary algorithms and rough sets-based approach that breaks down 2-dimensional trajectories into a set of additive components, which then can be used to build a classifier capable of recognizing typical, but yet unseen trajectories, and identifying those that seem suspicious.

关键词： Detection of Unusual Trajectories data Mining Evolutionary Algorithms Rough Sets

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New lamps for old: A shell game for generalized likelihood ratio use in radar? Or this isn't you father's GLR!

New lamps for old: A shell game for generalized likelihood r...

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13th conference on signal and data processing of small targets

作者： Kerr, th TeK Associates Lexington MA USA

ISBN: (纸本)0819441872

We alert the reader here to a discrepancy between what has recently been referred to as the Generalised Likelihood Ratio (GLR) approach to radar target detection and what has historically been used as the GLR approach to this same problem in detection theory. Despite these identified discrepancies, the recent version is tractable arid has desirable properties and consequently exhibits behavior that is very encouraging. After making the necessary clarifications, we summarize the status of the new pseudo-GLR and contrast it to what was available from the older (evidently antiquated) literature on GLR formulation, which, however, did serve as an historical precedent.

关键词： detection theory from first principles statistical basis of generalized likelihood ratio hypotheses tests mixed hypotheses GLR radar target detection and tracking nonlinear filtering growing banks-of-kalman filters (not IMM) central limit theorem (CLT) update

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Simulation assessment of RCS-aided multiple target tracking

Simulation assessment of RCS-aided multiple target tracking

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19th conference on signal and data processing of small targets

作者： Dunham, Darin T. Ehrman, Lisa. M. Blair, W. Dale Frost, Susan A. Vectraxx Inc Glen Allen VA 23059 USA Georgia Inst Technol Sensors & Electromagnet Applicat Lab Georgia Tech Res Inst Atlanta GA 30332 USA Vectraxx Inc Ft Collins CO 80521 USA

ISBN: (纸本)9780819468475

Closely-spaced (but resolved) targets pose a significant challenge for single-frame unique measurement-to-track data association algorithms. this is due to the similarity of the Mahalanobis distances between the closely-spaced measurements and tracks. Contrary to conventional wisdom, adding target feature information (e.g target amplitude) does not necessarily improve the probability of correctly assigning measurements to tracks. In this paper, the theoretical limitations of using radar cross section (RCS) data to aid in measurement-to-track association are reviewed. the results of a hi,h-fidelity simulation assessment of the benefits of RCS-aided measurement-to-track association (using the signal-to-Noise Ratio) are given and other possibilities for RCS-aided tracking are discussed. Namely, we show the analytical results of our investigation into using RCS information to determine the presence of merged measurements.

关键词： signal to noise ratio Target detection Sensors Switches Kinematics Radar Mahalanobis distance signal processing Time metrology Detection and tracking algorithms

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A dynamic approach to efficiently clustering and predicting groups for moving targets

A dynamic approach to efficiently clustering and predicting ...

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16th conference on signal and data processing of small targets

作者： Ma, DY Zhang, AD SUNY Buffalo Dept Comp Sci & Engn Buffalo NY 14260 USA

ISBN: (纸本)081945351X

Effective and efficient approaches to monitor and manage maneuvering objects are of great importance in various applications, such as wide battlefields, traffics, and wireless communications. Modern airborne radar sensors can provide wide-area surveillance coverage of ground activities. the huge volume of radar data renders it impractical and inefficient to examine all the activities of individual moving object. Clustering moving objects and predicting motion tendencies of large groups are becoming a crucial issue for optimizing resource distribution and formulating sound decisions. However, most traditional clustering techniques are static-object-oriented and not effective at clustering maneuvering objects. In addition, the radar data intermittence and noise data, which are caused by extraneous objects and stationary clutter background, are major difficulties in clustering and predicting groups. In this paper, we present a dynamic-object-oriented clustering approach to detecting and predicting large group activities over time. We propose a "core member" concept to support dynamic-object-oriented clustering and to mitigate the effects of data intermittence and noise data. In general, some special targets always tend to remain in a constant group and stay near the center of that group. To a large extent, the movement of these targets represents the activity of the entire group. To exploit this characteristic, we consider these special targets to be core members of their own cluster. the movements of the core members can help us detect clusters and predict their future movements. the performance and results of the application of our approach to CASTFOREM data sets are also presented.

关键词： Radar Detection and tracking algorithms Filtering (signal processing) Target detection Electronic filtering Sensors data modeling Surveillance Wireless communications signal detection

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MHT tracking for crossing sonar targets

MHT tracking for crossing sonar targets

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19th conference on signal and data processing of small targets

作者： Willett, Peter Luginbuhl, Tod Giannopoulos, Evangelos Univ Connecticut Dept ECE Storrs CT 06269 USA Naval Undersea Warfare Ctr Newport RI 02841 USA

ISBN: (纸本)9780819468475

Sometimes radar targets cross and become unresolved;this is a concern, but with a reasonable track depth and an appropriate merged-measurement model the concern is considerably mitigated. Sonar targets, however, can become merged (in the same beam) for considerably longer, particularly with bearing-only measurements. In such cases the crossing times can be 100 scans long, and no reasonable depth exists for an multi-frame tracker that can "see" both ends of the merged period. Further, there is a demonstrable tendency for estimated targets to repel each other as they are being tracked. In this paper we explore the hypothesis-oriented multi-hypothesis tracker (HO-MHT), an MHT approach that uses the new "rollout" optimization insight and the to give an appropriate and cost-effective means to rank hypotheses, and also the PMHT tracker that operates on batches of scans with linear computational complexity in most quantities. We show results in terms of estimation error (RMSE), consistency (NEES) and computational effort in both linear and beam-space tracking scenarios.

关键词： tracking MHT PMHT unresolved targets sonar

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