Готові списки джерел за темами / Surveillance signal processing

Добірка наукової літератури з теми "Surveillance signal processing"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 29 січня 2023

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Статті в журналах з теми "Surveillance signal processing"

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Ksendzuk, A. V., A. A. Kanatchikov, and P. A. Gerasimov. "SPACE SURVEILLANCE SYSTEM’S SAR SIGNAL DETECTION RESULTS." Issues of radio electronics, no. 3 (March 20, 2018): 63–68. http://dx.doi.org/10.21778/2218-5453-2018-3-63-68.

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Special aspects of space objects radiotechnical surveillance system used for filling the space tracking and surveillance system (STSS) satellite catalogue described and analyzed. Special emphasis placed on spaceborne synthetic aperture radar signals detection. Parameters of the SAR signals estimated with the proposed radiotechnical surveillance system described. Two processing methods for unknown and partially known signals proposed and analyzed. Signal detection with incompletely known parameters performs with cumulative second-order statistic. Signal detection with unknown parameters performs for periodic signal in assumption that observation interval exceed pulse repetition frequency. Proposed methods implemented in hardware demonstrator of radiotechnical surveillance system. This demonstrator works in real-time on Field Programmable Gate Array or save data on storage device for post-processing. L-band Palsar2 signal detection results presented and analyzed. Further work for hardware and software optimization described.
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K. Abdul-Hussein, Mohammad, Oleksii Strelnytskyi, Ivan Obod, Iryna Svyd, and Haider Th Salim Alrikabi. "Evaluation of the Interference’s Impact of Cooperative Surveillance Systems Signals Processing for Healthcare." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 03 (March 8, 2022): 43–59. http://dx.doi.org/10.3991/ijoe.v18i03.28015.

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Patient signals produced from a physical device, such as electrocardiography (ECG), which records the electrical activity of the heart, are vulnerable to keep noise due to various physical constraints of acquisition devices. It is critical for the detection and diagnosis of a variety of diseases. An ECG signal should be displayed as clean and clear as feasible due to its relevance in assisting physicians and doctors in making appropriate judgments. ECG is vulnerable to many types of noise because it is an electrical signal. To improve the quality of assistance for consumers Info a surveillance system by cooperative surveillance systems, high-quality data processing by the observed surveillance systems is required, which predetermines the requirement for high noise immunity of the latter. At the same time, the basics of building cooperative surveillance systems as a network of two-channel asynchronous information communication systems which include numeral of transmitting and receiving process using diverse frequency limits for reception and transmission, failure-prone open single-channel queuing systems, and request signals do not allow to provide the required the noise resistance of the systems under consideration. This paper first gives a characterization of request and interference signal flows in cooperative surveillance systems and briefly examines the features of request signals and their effect on the immunity of cooperative surveillance systems. Then, it calculates the noise resistance of the demand signals of the cooperative surveillance systems for the probabilities of errors: signal skipping; First- and second-degree false alarms in the case of unrelated events, unintended and intra-system impulse interferences in the request channel
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3

Ferguson, Brian. "Signal processing for acoustic surveillance of the land environment." Journal of the Acoustical Society of America 109, no. 5 (May 2001): 2298. http://dx.doi.org/10.1121/1.4744059.

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4

Dimitropoulos, K., N. Grammalidis, H. Gao, C. Stockhammer, and A. Kurz. "Magnetic signal processing & analysis for airfield traffic surveillance." IEEE Aerospace and Electronic Systems Magazine 23, no. 1 (January 2008): 21–27. http://dx.doi.org/10.1109/aes-m.2008.4444485.

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5

Yani, Kalfika, Fiky Y. Suratman, and Koredianto Usman. "Design and Implementation Pulse Compression for S-Band Surveillance Radar." Journal of Measurements, Electronics, Communications, and Systems 7, no. 1 (December 30, 2020): 20. http://dx.doi.org/10.25124/jmecs.v7i1.2631.

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Анотація:
The radar air surveillance system consists of 4 main parts, there are antenna, RF front-end, radar signal processing, and radar data processing. Radar signal processing starts from the baseband to IF section. The radar waveform consists of two types of signal, there are continuous wave (CW) radar, and pulse compression radar [1]. Range resolution for a given radar can be significantly improved by using very short pulses. Pulse compression allows us to achieve the average transmitted power of a relatively long pulse, while obtaining the range resolution corresponding to a short pulse. Pulse compression have compression gain. With the same power, pulse compression radar can transmit signal further than CW radar. In the modern radar, waveform is implemented in digital platform. With digital platform, the radar waveform can optimize without develop the new hardware platform. Field Programmable Gate Array (FPGA) is the best platform to implemented radar signal processing, because FPGA have ability to work in high speed data rate and parallel processing. In this research, we design radar signal processing from baseband to IF using Xilinx ML-605 Virtex-6 platform which combined with FMC-150 high speed ADC/DAC.
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Westphal, R. "Sensors, Medical Image and Signal Processing." Yearbook of Medical Informatics 16, no. 01 (August 2007): 70–71. http://dx.doi.org/10.1055/s-0038-1638528.

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Анотація:
SummaryTo summarize current excellent research in the field of sensor, signal and imaging informatics.Synopsis of the articles selected for the IMIA Yearbook 2007.The selection process for this yearbook section “Sensor, signal and imaging informatics” results in five excellent articles, representing research in four different nations. Papers from the fields of brain machine interfaces, sound surveillance in telemonitoring, soft tissue modeling, and body sensors have been selected.The selection for this yearbook section can only reflect a small portion of the worldwide copious work in the field of sensors, signal and image processing with applications in medical informatics. However, the selected papers demonstrate, how advances in this field may positively affect future patient care.
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Худов, Г. В., Сальман Рашід Оваід, В. М. Ліщенко, and В. О. Тютюнник. "Methods of signal processing in a multiradar system of the same type of two-coordinated surveillance radars." Системи обробки інформації, no. 3(162), (September 30, 2020): 65–72. http://dx.doi.org/10.30748/soi.2020.162.07.

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Анотація:
The subject of research in the paper is the problem of developing methods of signal processing in a multiradar system of the same type of two-coordinate surveillance radars with mechanical rotation. The aim of the paper is to improve the quality of detection of air objects by combining the same type of two-coordinate radars in a multi-radar system. It is proposed to combine the existing surveillance radar stations into a spatially spaced coherent multi-radar system. The synthesis of optimal detectors of coherent and incoherent signals is carried out. The characteristics of detection of air objects in a multi-radar system with compatible signal receiving have been evaluated. The obtained results: the addition of the second radar, regardless of the degree of signal coherence, showed the greatest efficiency in the gain in terms of signal / noise, the optimal number of radars in the multi-radar system is not more than four. The expected signal / noise threshold gain in a system of four radars can be up to eighteen decibels for a system with coherent signals and up to eleven decibels for a system with incoherent signals. The using of more than four radars is impractical.
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Ksendzuk, A. V., and A. A. Kanatchikov. "SPACEBORNE SAR SIGNAL DETECTION AND PARAMETER ESTIMATION IN SPACE TRACKING AND SURVEILLANCE SYSTEM MODELING." Issues of radio electronics, no. 3 (March 20, 2019): 31–35. http://dx.doi.org/10.21778/2218-5453-2019-3-31-35.

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The development of information support of the space tracking and surveillance system is a highly topical task, the solution of which will help to increase the effectiveness of monitoring space objects. Development and practical application of the software for Spaceborne synthetic aperture radar (SAR) signal detection and parameter estimation described and analyzed. Architecture of the software is described, processing results in the simulation mode (comparison of different processing methods) and real SAR satellite signals processing mode analyzed. In simulation mode detection and parameter estimation methods compared statistically as averaged estimation error as a function of the signal‑to‑noise ratio. Estimator statistical characteristics – bias, variation, error histogram – derived and analyzed.
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Fadeev, E. V. "RECIEVED SIGNAL PROCESSING ALGORITHMS IN AVIATION-BASED RADIOELECTRONIC SURVEILLANCE SYSTEMS." Bulletin of Russian academy of natural sciences 21, no. 4 (2021): 11–19. http://dx.doi.org/10.52531/1682-1696-2021-21-4-11-19.

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10

Yan, He, Daiyin Zhu, Robert Wang, and Xinhua Mao. "Practical signal processing algorithm for wide‐area surveillance‐GMTI mode." IET Radar, Sonar & Navigation 9, no. 8 (October 2015): 991–98. http://dx.doi.org/10.1049/iet-rsn.2014.0452.

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Дисертації з теми "Surveillance signal processing"

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Adams, Andrew J. "Multispectral persistent surveillance /." Online version of thesis, 2008. http://hdl.handle.net/1850/7070.

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2

Górski, Tomasz. "Space-time adaptive signal processing for sea surveillance on-shore stationary radars." Télécom Bretagne, 2008. http://www.theses.fr/2008TELB0075.

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Анотація:
Il existe plusieurs limitations dans les systèmes radar de surveillance maritime. En particulier, un problème important est le fort retour électromagnétique de la surface de mer (notamment pour les mers formées). La définition de nouvelles techniques de traitement de ces données radar est un domaine en pleine expansion. Dans cette thèse, nous proposons l'utilisation de traitement adaptatif dans les domaines temps-fréquence (STAP en anglais) pour la détection d'objets sur la surface de mer. Cependant, cette méthodologie est confrontée à plusieurs difficultés : Non stationnarité (dans le temps et l'espace) du fouillis de mer, Non gaussianité de ce fouillis, fouillis avec un spectre Doppler étendu. Le propos de ce travail a été d'étudier des solutions à ces divers problèmes. En particulier, une modification des techniques de STAP (traitement et décision) pour la prise en compte des problèmes mentionnés ci-dessus est détaillée dans cette thèse. Ces modifications ont été testées sur des données simulées, mais aussi sur des données réelles obtenues grâce au radar à onde de surface WERA.
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3

Wortham, Cody. "Space-Time Processing for Ground Surveillance Radar." Thesis, Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14468.

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Анотація:
As the size of an adaptive antenna array grows, the system is able to resist interference signals of increasing bandwidth. This is a result of the transmit pattern gain increasing, which raises the target's return power, and a greater number of degrees of freedom. However, once the interference signal decorrelates completely from one channel to the next, increasing array size will cease to improve detection capability. The use of tapped delay-line processing to improve correlation between channels has been studied for smaller arrays with single element antennas, but previous analyses have not considereded larger systems that are partitioned into subarrays. This thesis quantifies the effect that subarrays have on performance, as measured by the interference bandwidth that can be handled, and explains how tapped delay-line processing can maintain the ability to detect targets in an environment with high bandwidth interference. The analysis begins by deriving equations to estimate the half-power bandwidth of an array with no taps. Then we find that a single delay with optimal spacing is sufficient to completely restore performance if the interference angle is known exactly. However, in practice, the tap spacing will never be optimal because this angle will not be known exactly, so further consideration is given to this non-ideal case and possible solutions for arbitrary interference scenarios are presented. Simulations indicate that systems with multiple taps have more tolerance to increasing interference bandwidth and unknown directions of arrival. Finally, the tradeoffs between ideal and practical configurations are explained and suggestions are given for the design of real-world systems.
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4

Hallermeyer, Alexandre. "Traitement du Signal d’un LIDAR Doppler scannant dédié à la surveillance aéroportuaire." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLC007/document.

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Un algorithme permettant d’estimer précisément les paramètres des tourbillons de sillage (positions et circulations) en utilisant les données spectrales fournies par un LIDAR a été développé. Il s’articule en 3 grandes étapes : La première permet de détecter la présence de tourbillon et d’en faire une localisation grossière grâce à la méthode des enveloppes de vitesses. La seconde étape a pour but d’affiner l’estimation des positions des tourbillons en utilisant une optimisation du critère des moindres carrés. Cette étape permet également de faire une première estimation de la circulation des tourbillons. La troisième et dernière étape se concentre sur l’estimation des circulations des tourbillons en maximisant le critère de vraisemblance. Les estimations sont de plus en plus fines et se concentrent au fur et à mesure sur les paramètres les plus critiques. La mise au point de cet algorithme a nécessité d’utiliser plusieurs modèles (LIDAR, tourbillons de sillage, atmosphère) et de formuler un certain nombre d’hypothèses et approximations simplificatrices afin d’atteindre un coût calculatoire raisonnable. L’algorithme proposé a ensuite fait l’objet d’une évaluation de performances, l’intérêt étant porté sur la robustesse par rapport aux différents bruits altérant la mesure, en particulier celui lié à la turbulence atmosphérique et par rapport aux erreurs de modèle. Cette évaluation a été menée à la fois sur des données simulées à l’aide de modèles paramétriques simplifiés, et sur des données de simulations aux grandes échelles.Les paramètres instrumentaux du LIDAR constituent de potentiels degrés de liberté pour améliorer les performances de l’estimateur, en particulier pour les grandeurs les plus critiques, c’est-à-dire les valeurs de circulation. Le calcul des performances de l’estimateur nécessitant un coût de calcul non négligeable, il se prête mal à des fins d’optimisation. C’est pourquoi une étude de l’influence des paramètres du LIDAR sur la Borne de Cramér-Rao (BCR) a été menée. Cette étude a permis de mieux comprendre l’influence des paramètres instrumentaux et d’aboutir à une configuration optimale pour la BCR
An algorithm was developed to estimate precisely wake vortices parameters (positions and circulations) using spectral data provided by a LIDAR. It is articulated in 3 main stages: The first one allows to detect the presence of vortices and to make a rough localization thanks to the method of the velocity envelopes. The second step is to refine the estimation of vortex positions using an optimization of the least squares criterion. This step also permits to make an first estimation of the vortices circulation. The third and final step focuses on estimating vortex circulations by maximizing the likelihood criterion. Estimates are becoming finer and more focused on the most critical parameters. The development of this algorithm required the use of several models (LIDAR, wake vortices, atmosphere) and to formulate a number of simplifying assumptions in order to reach a reasonable computational cost. The proposed algorithm was then subjected to a performance evaluation, the interest being focused on the robustness with respect to the different noises altering the measurement, particularly the one related to the atmospheric turbulence, and with respect to the model errors. This evaluation was carried out both on simulated data using simplified parametric models, and on Large Eddy Simulations.The instrumental parameters of LIDAR are potential degrees of freedom to improve the performance of the estimator, in particular for the most critical quantities, that is to say the circulation values. The calculation of the performance of the estimator requiring a significant computational cost, it lends itself poorly for optimization purposes. This is why a study of the influence of the LIDAR parameters on the Cramér-Rao Bound (CRB) was carried out. This study allowed to understand the influence of the instrumental parameters and to reach an optimal configuration for the CRB
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Comstedt, Erik. "Effect of additional compression features on h.264 surveillance video." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-30901.

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Анотація:
In video surveillance business, a recurring topic of discussion is quality versus data usage. A higher quality allows for more details to be captured at the cost of a higher bit rate, and for cameras monitoring events 24 hours a day, limiting data usage can quickly become a factor to consider. The purpose of this thesis has been to apply additional compression features to a h.264 video steam, and evaluate their effects on the videos overall quality. Using a surveillance camera, recordings of video streams were obtained. These recordings had constant GOP and frame rates. By breaking down one of these videos to an image sequence, it was possible to encode the image sequence into video streams with variable GOP/FPS using the software Ffmpeg. Additionally a user test was performed on these video streams, following the DSCQS standard from the ITU-R recom- mendation. The participants had to subjectively determine the quality of video streams. The results from the these tests showed that the participants did not no- tice any considerable difference in quality between the normal videos and the videos with variable GOP/FPS. Based of these results, the thesis has shown that that additional compression features can be applied to h.264 surveillance streams, without having a substantial effect on the video streams overall quality.
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6

Sekak, Fatima. "Microwave radar techniques and dedicated signal processing for Vital Signs measurement." Thesis, Université de Lille (2018-2021), 2021. https://pepite-depot.univ-lille.fr/LIBRE/EDENGSYS/2021/2021LILUN033.pdf.

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Анотація:
Dans le contexte de la sécurisation des systèmes de transport, la surveillance à courte distance de l’activité des personnes, en particulier du conducteur dans un véhicule, constitue un enjeu majeur dans l’amélioration du système d’aide à la conduite. L’application visée dans ce travail concerne principalement le domaine du ferroviaire.Les fréquences respiratoire et cardiaque du conducteur sont des indicateurs clés pour l’évaluation de l’état physiologique. Les méthodes de mesure conventionnelles de ces signes vitaux reposent sur des capteurs opérant en contact direct avec la peau. Par conséquent, le caractère intrusif de ces solutions ne s’avère pas adapté au domaine du transport, en particulier du fait de la gêne induite. Dans le cadre de ces travaux, une solution radar hyperfréquence opérant à faible puissance est proposée pour la mesure en continue des signaux d’activités respiratoire et cardiaque. En particulier, les signaux physiologiques (battements du cœur, mouvement mécanique de la cage thoracique) sont des indicateurs de l’activité humaine qui peuvent être détectés à distance (jusqu’à une dizaine de mètres) au moyen d’ondes électromagnétiques hyperfréquences rayonnées.Bien que la littérature montre un engouement grandissant pour le développement de techniques radars dédiés à la surveillance des personnes, il n’existe pas, à ce jour, de dispositif commercial robuste, sensible et précis. Une analyse fine des paramètres électriques et géométriques de la technique radar est proposée dans ce travail afin d’identifier les sources d’incertitudes, de définir les paramètres optimaux, de valider expérimentalement la solution proposée. Un traitement de signal original, basé sur l’approche cyclostationnaire, est mis en œuvre afin d’extraire les paramètres d’intérêt dans des environnements de mesure de référence ou perturbés. Les solutions matérielles proposées associées à un traitement de signal optimal permettent d’entrevoir des architectures de radar adaptées aux contingences hors laboratoire
In the context of securing transportation systems, short-range monitoring of people's activity, in particular the driver's activity in a vehicle, is a major issue in the improvement of the driver assistance system. The application targeted in this work concerns mainly the railway domain.Respiratory and heart rates of the driver are key indicators for the evaluation of the physiological state. Conventional methods of measuring these vital signs rely on sensors operating in direct contact with the skin. Therefore, the intrusive character of these solutions is not suited for the transportation domain, especially because of the induced discomfort. In this work, a microwave radar solution operating at low power is proposed for the continuous measurement of respiratory and cardiac activity signals. In particular, physiological signals (heartbeat, mechanical movement of the rib cage) are indicators of human activity that can be detected at a distance (up to ten meters) using radiated microwave electromagnetic waves.Although the literature shows a growing interest in the development of radar techniques dedicated to the surveillance of people, there is no robust, sensitive and accurate commercial device available to date. A detailed analysis of the electrical and geometrical parameters of the radar technique is proposed in this work in order to identify the sources of uncertainties, to define the optimal parameters, to validate experimentally the proposed solution. An original signal processing, based on the cyclostationary approach, is implemented in order to extract the parameters of interest in reference or disturbed measurement environments. The proposed hardware solutions associated with an optimal signal processing allow to foresee radar architectures adapted to non-laboratory contingencies
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7

Nyström, Axel. "Evaluation of Multiple Object Tracking in Surveillance Video." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

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Анотація:
Multiple object tracking is the process of assigning unique and consistent identities to objects throughout a video sequence. A popular approach to multiple object tracking, and object tracking in general, is to use a method called tracking-by-detection. Tracking-by-detection is a two-stage procedure: an object detection algorithm first detects objects in a frame, these objects are then associated with already tracked objects by a tracking algorithm. One of the main concerns of this thesis is to investigate how different object detection algorithms perform on surveillance video supplied by National Forensic Centre. The thesis then goes on to explore how the stand-alone alone performance of the object detection algorithm correlates with overall performance of a tracking-by-detection system. Finally, the thesis investigates how the use of visual descriptors in the tracking stage of a tracking-by-detection system effects performance.  Results presented in this thesis suggest that the capacity of the object detection algorithm is highly indicative of the overall performance of the tracking-by-detection system. Further, this thesis also shows how the use of visual descriptors in the tracking stage can reduce the number of identity switches and thereby increase performance of the whole system.
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Firla, Marcin. "Automatic signal processing for wind turbine condition monitoring. Time-frequency cropping, kinematic association, and all-sideband demodulation." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT006/document.

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Анотація:
Cette thèse propose trois méthodes de traitement du signal orientées vers la surveillance d’état et le diagnostic. Les techniques proposées sont surtout adaptées pour la surveillance d’état, effectuée à la base de vibrations, des machines tournantes qui fonctionnent dans des conditions d’opération non-stationnaires comme par exemple les éoliennes mais elles ne sont pas limitées à un tel usage. Toutes les méthodes proposées sont des algorithmes automatiques et gérés par les données.La première technique proposée permet de sélectionner la partie la plus stationnaire d’un signal en cadrant la représentation temps-fréquence d’un signal.La deuxième méthode est un algorithme pour l’association des dispositions spectrales, des séries harmoniques et des séries à bandes latérales avec des fréquences caractéristiques provennant du cinématique d'un système analysé. Cette méthode propose une approche unique dédiée à l’élément roulant du roulement qui permet de surmonter les difficultés causées par le phénomène de glissement.La troisième technique est un algorithme de démodulation de bande latérale entière. Elle fonctionne à la base d’un filtre multiple et propose des indicateurs de santé pour faciliter une évaluation d'état du système sous l’analyse.Dans cette thèse, les méthodes proposées sont validées sur les signaux simulés et réels. Les résultats présentés montrent une bonne performance de toutes les méthodes
This thesis proposes a three signal-processing methods oriented towards the condition monitoring and diagnosis. In particular the proposed techniques are suited for vibration-based condition monitoring of rotating machinery which works under highly non-stationary operational condition as wind turbines, but it is not limited to such a usage. All the proposed methods are automatic and data-driven algorithms.The first proposed technique enables a selection of the most stationary part of signal by cropping time-frequency representation of the signal.The second method is an algorithm for association of spectral patterns, harmonics and sidebands series, with characteristic frequencies arising from kinematic of a system under inspection. This method features in a unique approach dedicated for rolling-element bearing which enables to overcome difficulties caused by a slippage phenomenon.The third technique is an all-sideband demodulation algorithm. It features in a multi-rate filter and proposes health indicators to facilitate an evaluation of the condition of the investigated system.In this thesis the proposed methods are validated on both, simulated and real-world signals. The presented results show good performance of all the methods
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9

Song, Bi. "Scene analysis, control and communication in distributed camera networks." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3359910.

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Анотація:
Thesis (Ph. D.)--University of California, Riverside, 2009.
Includes abstract. Title from first page of PDF file (viewed January 27, 2010). Includes bibliographical references (p. 99-105). Issued in print and online. Available via ProQuest Digital Dissertations.
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10

Kazemisaber, Mohammadreza. "Clutter Removal in Single Radar Sensor Reflection Data via Digital Signal Processing." Thesis, Linnéuniversitetet, Institutionen för fysik och elektroteknik (IFE), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99874.

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Анотація:
Due to recent improvements, robots are more applicable in factories and various production lines where smoke, fog, dust, and steam are inevitable. Despite their advantages, robots introduce new safety requirements when combined with humans. Radars can play a crucial role in this context by providing safe zones where robots are operating in the absence of humans. The goal of this Master’s thesis is to investigate different clutter suppression methods for single radar sensor reflection data via digital signal processing. This was done in collaboration with ABB Jokab AB, Sweden. The calculations and implementation of the digital signal processing algorithms are made with Octave. A critical problem is false detection that could possibly cause irreparable damage. Therefore, a safety system with an extremely low false alarm rate is desired to reduce costs and damages. In this project, we have studied four different digital low pass filters: moving average, multiple-pass moving average, Butterworth, and window-based filters. The results are compared, and it is ascertained that all the results are logically compatible, broadly comparable, and usable in this context.
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Книги з теми "Surveillance signal processing"

1

Hippenstiel, Ralph Dieter. Detection theory: Applications and digital signal processing. Boca Raton, Fla: CRC Press, 2002.

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2

Klein, Lawrence A. Millimeter-wave and infrared multisensor design and signal processing. Boston: Artech House, 1997.

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3

A, Velastin Sergio, Remagnino Paolo 1963-, and Institution of Electrical Engineers, eds. Intelligent distributed video surveillance systems. London: Institution of Electrical Engineers, 2006.

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4

Foresti, Gian Luca. Multisensor Surveillance Systems: The Fusion Perspective. Boston, MA: Springer US, 2003.

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5

Calif.) Signal and Data Processing of Small Targets (Conference) (2013 San Diego. Signal and Data Processing of Small Targets 2013: 28-29 August 2013, San Diego, California, United States. Edited by Drummond Oliver E, Teichgraeber Richard D, and SPIE (Society). Bellingham, Washington, USA: SPIE, 2013.

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6

IEEE National Radar Conference (1997 Syracuse, N.Y.). Proceedings of the 1997 IEEE National Radar Conference: May 13-15, 1997, Syracuse, New York. New York, N.Y: IEEE Aerospace and Electronic Systems Society, 1997.

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7

IEEE, Radar Conference (1999 Waltham Mass ). The record of the 1999 IEEE Radar Conference: [RADARCON '99] : Radar into the next Millennium : held at the Westin Hotel, Waltham, Massachusetts, April 20-22, 1999. New York, N.Y: IEEE Aerospace and Electronic Systems Society, 1999.

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8

IEEE International Conference on Advanced Video and Signal Based Surveillance (2005 Como, Italy). Advanced video and signal based surveillance: Proceedings of AVSS 2005 : Como, Italy, 15-16 September 2005. Piscataway, NJ: IEEE, 2005.

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Poland) IEEE International Conference on Advanced Video and Signal Based Surveillance (10th 2013 Krakow. 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2013): Krakow, Poland, 27-30 August 2013. Piscataway, NJ: IEEE, 2013.

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10

IEEE International Conference on Advanced Video and Signal Based Surveillance (8th 2011 Klagenfurt, Austria). 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance: (AVSS 2001), Klagenfurt, Austria, 30 August-2 September 2011. Piscataway, NJ: IEEE, 2011.

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Частини книг з теми "Surveillance signal processing"

1

Swami, Kedar, Bhardwaz Bhuma, Semanto Mondal, and L. Anjaneyulu. "Audio Surveillance System." In Machine Intelligence and Signal Processing, 351–60. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1366-4_28.

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Chen, Wei-Gang. "Moving Shadow Detection in Video Surveillance Based on Multi-feature Analysis." In Multimedia and Signal Processing, 224–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_29.

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Sevaldsen, Erik. "Underwater Surveillance — Concepts, Equipment and Results." In Acoustic Signal Processing for Ocean Exploration, 459–64. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1604-6_42.

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Bondalapati, Anjanadevi, and D. H. Manjaiah. "Intelligent Video Surveillance Systems Using Deep Learning Methods." In Machine Learning in Signal Processing, 213–42. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003107026-9.

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5

Martínez, Fabio, Antoine Manzanera, and Eduardo Romero. "A Motion Descriptor Based on Statistics of Optical Flow Orientations for Action Classification in Video-Surveillance." In Multimedia and Signal Processing, 267–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_34.

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6

Arunnehru, J., and M. Kalaiselvi Geetha. "Automatic Human Emotion Recognition in Surveillance Video." In Intelligent Techniques in Signal Processing for Multimedia Security, 321–42. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44790-2_15.

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7

Ashwini and T. Kusuma. "Analysis of Global Motion Compensation and Polar Vector Median for Object Tracking Using ST-MRF in Video Surveillance." In Machine Intelligence and Signal Processing, 453–64. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1366-4_36.

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8

Sivarathinabala, M., S. Abirami, and R. Baskaran. "A Study on Security and Surveillance System Using Gait Recognition." In Intelligent Techniques in Signal Processing for Multimedia Security, 227–52. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44790-2_11.

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9

Ndungutse, Jean Bosco, Rui Xu, Gilbert Shyirambere, Fatana Jafari, and Shi-Jian Liu. "Deep Learning-Based Helmet Wearing Detection for Safety Surveillance." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 91–100. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1053-1_9.

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10

Gokula Vishnu Kirti, D., C. R. Balaji, and A. Joshuva. "A Smart Delimit Scrutinization Droid for Defence Border Surveillance Through LIDAR." In Advances in Automation, Signal Processing, Instrumentation, and Control, 795–800. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8221-9_74.

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Тези доповідей конференцій з теми "Surveillance signal processing"

1

Tsuhan Chen. "A journey from signal processing to surveillance." In 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007. IEEE, 2007. http://dx.doi.org/10.1109/avss.2007.4425272.

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2

Liu, Hanyu, Chong Tang, Shaoen Wu, and Honggang Wang. "Real-time video surveillance for large scenes." In Signal Processing (WCSP 2011). IEEE, 2011. http://dx.doi.org/10.1109/wcsp.2011.6096963.

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3

Misiurewicz, Jacek, Lukasz Maslikowuki, Artur Gromek, and Anna Kurowska. "MIMO Techniques for Space Surveillance Radar." In 2019 Signal Processing Symposium (SPSympo). IEEE, 2019. http://dx.doi.org/10.1109/sps.2019.8882084.

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4

Lv, Shao-Zhong, Xiao-Ping Wang, and Li-Jie Zhang. "Fast and robust video foreground segmentation for indoor surveillance." In Signal Processing (WCSP 2009). IEEE, 2009. http://dx.doi.org/10.1109/wcsp.2009.5371622.

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5

Dos Santos Fagundes, R., D. Lejeune, A. Mansour, F. Le Roy, and R. Lababidi. "Wideband high dynamic range surveillance." In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362411.

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6

Vergara, L., P. Bernabeu, and J. Igual. "Wide area fire surveillance by infrared digital signal processing." In Proceedings of the Third International Conference on Information Fusion. IEEE, 2000. http://dx.doi.org/10.1109/ific.2000.859859.

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7

Goriushkina, A. E., I. V. Svyd, G. E. Zavolodko, and G. V. Maistrenko. "Comparative analysis of signal processing methods secondary surveillance radar." In 2018 International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo). IEEE, 2018. http://dx.doi.org/10.1109/ukrmico43733.2018.9047593.

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8

Turley, Mike D. E. "Signal processing techniques for maritime surveillance with skywave radar." In 2008 International Conference on Radar (Radar 2008). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4653925.

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9

Klock, Clemens, Volker Winkler, and Michael Edrich. "LTE-signal processing for passive radar air traffic surveillance." In 2017 18th International Radar Symposium (IRS). IEEE, 2017. http://dx.doi.org/10.23919/irs.2017.8008105.

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10

Petroviu, V., and B. Bondzulic. "Objective assessment of surveillance video quality." In Sensor Signal Processing for Defence (SSPD 2012). Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/ic.2012.0105.

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Звіти організацій з теми "Surveillance signal processing"

1

Rhody, Harvey, David Sher, and James Modestino. Intelligent Signal Processing Techniques for Multi-Sensor Surveillance Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1989. http://dx.doi.org/10.21236/ada218890.

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2

Varshney, Pramod K. Multimodal Signal Processing for Personnel Detection and Activity Classification for Indoor Surveillance. Fort Belvoir, VA: Defense Technical Information Center, November 2013. http://dx.doi.org/10.21236/ada606602.

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