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

共 9213 条记录，以下是4841-4850 订阅

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On the accuracy of decay constant measurement by swept-cavity heterodyne cavity ringdown spectroscopy

On the accuracy of decay constant measurement by swept-cavit...

引用

conference on Next-Generation Spectroscopic Technologies IV

作者： Silva, K. K. M. B. Dilusha van der Walt, Aislinn Dell, John M. Faraone, Lorenzo Univ Western Australia Sch Elect Elect & Comp Engn Crawley WA 6009 Australia

ISBN: (纸本)9780819486066

Cavity ringdown spectroscopy (CRDS) measures the decay time, of a resonant optical cavity containing a measurand, as a function of optical frequency. The measurand is identified and quantified by the cavity decay time, which is modified by the measurand within. As coupling light into a high-finesse optical cavity is difficult, the throughput of the cavity is small. A recent variant, swept-cavity heterodyne CRDS, interferes backward escaping cavity light, with light reflected from the cavity input mirror, providing better signal sensitivity due to the heterodyne advantage. The measured interference signal is demodulated and log-amplified to produce a signal whose slope is representative of the cavity decay time. This paper, for the first time, examines the conditions required for high-fidelity measurements of the cavity decay time using swept-cavity heterodyne CRDS and log-amplification technique. We demonstrate that, due to the very large bandwidth and dynamic range of the log-amplifier, for realistic measurement conditions, the log-amplifier does not impose any significant restrictions on the measurement accuracy. We also demonstrate, however, the measurement accuracy is limited by two factors, the detector bandwidth, and segment of acquired data used to measure the slope.

关键词： Cavity ringdown spectroscopy CRDS swept cavity heterodyne signal processing

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Performance Analysis of Three-Dimentional Imaging Using Single-Pass Multi-Azimuth-Angle SAR data

Performance Analysis of Three-Dimentional Imaging Using Sing...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Hui Kuang Yu Zhu Zheng Lu Zhibin Wang Yufei Huang Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

In this paper, the performance of three-dimensional (3-D) image obtained by processing single-pass multi-azimuth-angle (SP-MAA) synthetic aperture radar (SAR) data is analyzed and the result shows that it is unsuitable for 3-D imaging using SP-MAA SAR data. Firstly, the imaging geometry and signal model of the SP-MAA SAR are built. Then, the 3-D imaging algorithm is used to process the SP-MAA SAR data, and the 3-D image is obtained. Thirdly, the performance of the 3-D image is analyzed, and there are many ghost targets caused by azimuth sidelobes of the true targets in the 3-D image, which means it is unsuitable to obtain 3-D image using the SP-MAA SAR data. Finally, the simulation results verify the analysis results.

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Evaluation of Knowledge-Aided STAP Using Experimental data

Evaluation of Knowledge-Aided STAP Using Experimental Data

引用

IEEE conference on Aerospace

作者： Jameson S. Bergin David R. Kirk Guy Chaney Steven McNeil Peter A. Zulch Information Systems Laboratories Inc. Vienna VA USA Air Force Research Laboratory Rome NY USA

Recent advances in knowledge-aided space-time adaptive processing (KA-STAP) have resulted in significant performance improvements for ground moving target indication (GMTI) radar systems. In particular, the use of prior knowledge including terrain, clutter discretes, and previously detected targets has been shown to be effective for mitigating the poor performance often encountered when operating in heterogeneous clutter environments. This paper provides an evaluation of KA-STAP techniques based on extensive processing of experimental data. Two major performance issues are addressed: high false alarm rates due to under-nulled clutter discretes and target cancellation due to corruption of the STAP training data by other targets in the scene. Each of these problems is demonstrated using experimental multi-channel X-band radar data. Methods for using prior knowledge to improve performance are presented and processing results using the experimental data are provided that show how KA-STAP can lead to significantly improved detection performance relative to conventional STAP processing.

关键词： Clutter Radar signal processing Radar detection signal processing algorithms Radar tracking Training data Biomedical signal processing Filters Interference constraints Laboratories

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Conflict-Free Vectorized In-order In-place Radix-r Belief Propagation Polar Code Decoder Algorithm 20

Conflict-Free Vectorized In-order In-place Radix-r Belief Pr...

引用

8th International conference on Communications and Broadband Networking (ICCBN) / 3rd International conference on Communication Engineering and Technology (ICCET)

作者： van den Brink, Arvid B. Bekooij, Marco J. G. Univ Twente Dept Comp Architecture Design & Test Embedded Sys Enschede Netherlands NXP Semicond Dept Embedded Software & Signal Proc Eindhoven Netherlands

ISBN: (纸本)9781450375047

A vectorized belief propagation polar code decoder is desirable because of the potentially high throughput and the ability of integration in processors that perform vectorized processing and access wide memory words. However, current state-of-the-art belief propagation polar code decoder algorithms do not perform vector processing and store intermediate results in non consecutive memory locations. Also the current state-of-the-art belief propagation polar code decoders require separate memories to store left and right bound intermediate results. In this paper we propose a vectorized in-order in-place belief propagation polar code decoder algorithm where all stages access vectorized data from memory. This results in a high throughput because vectors of elements can be fetched from and stored in memory in each clock cycle. Our algorithm also accommodates for per stage in-place computations which halves the required internal memory. Furthermore, the algorithm has a regular memory addresses access pattern. Conflict free vectorized memory access is achieved by making use of transpose operations on small groups of intermediate results. The use of the transpose operations also results in that both input and output results are placed on subsequent locations in memory.

关键词： Conflict-free Vectorized Belief Propagation Polar Code

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An optimal radar detector threshold adaptation for maneuvering targets in clutter

An optimal radar detector threshold adaptation for maneuveri...

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IEEE signal processing and Communications Applications (SIU)

作者： Murat Samil Aslan Afsar Saranli TUB-TAK UEKAE/ILTAREN Ankara Turkey Elektrik ve Elektronik Muhendislii Bolumu Orta Dogu Teknik Universitesi Turkey

In this paper, we consider the problem of radar detector threshold optimization for maneuvering targets in clutter. In the earlier works, the problem was studied in the context of the probabilistic data association filter (PDAF) for non-maneuvering targets. In this study, we have extended the ideas, which were applied to the PDAF, to the interacting multiple model PDAF (IMM-PDAF) for maneuvering targets. The proposed optimization problem and its solution show better results over the traditional approaches in terms of track loss percentage and RMS position error criteria.

关键词： Radar clutter Radar detection Detectors Riccati equations Radar tracking Target tracking Kalman filters Doppler radar

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Joint Trajectory and Beamforming Design for UAV-Enabled Integrated Sensing and Communication

Joint Trajectory and Beamforming Design for UAV-Enabled Inte...

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IEEE International conference on Communications (ICC)

作者： Lyu, Zhonghao Zhu, Guangxu Xu, Jie Chinese Univ Hong Kong Shenzhen SSE Shenzhen Peoples R China Chinese Univ Hong Kong Shenzhen FNii Shenzhen Peoples R China Shenzhen Res Inst Big Data Shenzhen Peoples R China

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

This paper studies the unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC), in which UAVs are dispatched as aerial dual-functional access points (APs) that can exploit the UAV maneuver control and strong line-of-sight (LoS) aerial-to-ground (A2G) links for efficient ISAC. Particularly, we consider a scenario with one UAV-AP equipped with a vertically placed uniform linear array (ULA), which sends combined information and sensing signals to communicate with multiple users and at the same time sense potential targets on the ground. Our objective is to jointly design the UAV trajectory and transmit beamforming to maximize the average weighted sum-rate throughput of communication users over the whole period, subject to the sensing beampattern gain requirements and transmit power constraints over different time slots, as well as practical flight constraints. While the above problem is challenging to solve, we propose an efficient algorithm by adopting the alternating optimization together with the successive convex approximation (SCA) and semidefinite relaxation (SDR). Numerical results are provided to validate the superiority of our proposed designs as compared to various benchmark schemes with heuristic trajectory designs.

关键词： Array signal processing conferences Radar Benchmark testing Autonomous aerial vehicles Throughput Sensors

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Abnormal Dynamic Detection of Space targets from ISAR Sequences with LSTM Regression

Abnormal Dynamic Detection of Space Targets from ISAR Sequen...

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International conference on Vision, Image and signal processing (ICVISP)

作者： Zi Wang Jia Duan Lei Zhang Nana Hu School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

In both military and civilian contexts, accurate detection of radar attitude deviations using ISAR is crucial but challenging due to the incomplete target edges and missing electromagnetic scattering components. Available dynamic detection of space targets transforms detection into binary classification, which faces an imbalanced dataset and an incomplete repre-sentation of all anomalous samples. In this paper, we propose an abnormal dynamic detection method with small amounts of anomalies. An LSTM architecture is first constructed for the geometrical feature flow regression for stabilized space targets. Then, a small number of anomalies and normal samples are used to calculate the value of the mean absolute error (MAE) threshold to distinguish anomalies from normal samples using a statistical histogram. In this way, abnormal dynamic detection can be accomplished by comparing MAE to the threshold. Experiments validate the effectiveness of the proposal with limited anomalies.

关键词： Training Radar detection Transforms Radar signal processing Radar scattering Robustness Proposals Long short term memory Testing

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Time-lenses placed in an array with overlapping between adjacent time-lenses 17

Time-lenses placed in an array with overlapping between adja...

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Symposium on Nanoscale Imaging, Sensing, and Actuation for Biomedical Applications, held at SPIE BiOS conference

作者： Klein, Avi Sibony, Inbar Meir, Sara Freedman, Ori Shahal, Shir Duadi, Hamootal Fridman, Moti Bar Ilan Univ Fac Engn IL-5290002 Ramat Gan Israel Bar Ilan Univ Inst Nanotechnol & Adv Mat IL-5290002 Ramat Gan Israel

ISBN: (纸本)9781510632714;9781510632721

Time-lenses in general proved to be useful for many applications and specifically when utilizing them for temporal imaging schemes where they can image ultrafast signals that cannot be detected by any electronic based device. Over the last few years, we demonstrated that when joining together several time-lenses into a single time-lens array, it is possible to gain more information on the input signal. Such as measuring temporal depth imaging, the state of polarization of the input signal as a function of time, and retrieving the phase dynamics. However, when designing an array of time-lenses, there is a trade-off between joining large number of small time-lenses, so each signal will interact with many time-lenses but each one has low resolution, and joining small number of large time-lenses, so each has better temporal resolution but on the expanse of interacting with smaller number of time-lenses in the array. We showed that one way to overcome this drawback is to overlap adjacent time-lenses. Thus it is possible to both have large number of time-lenses without compromising on the size of each time-lens and obtaining high temporal resolution. In this proceeding, we overlap two time-lenses and measure the spectrum of the idler. We compare the numerical simulations of the frequency domain of the idler to the measured spectrum of the idler.

关键词： temporal optics time-lens optical data processing four-wave mixing

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New data fusion and tracking approaches in multiple targets/distributed sensors network contexts

New data fusion and tracking approaches in multiple targets/...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： F. Martinerie Thomson Sintra Activités-Sous-Mariiies Arcueil France

The problem of target tracking from distributed sensors in a cluttered environment is addressed. The author and P. Forster have introduced a new and original approach in target tracking and target motion analysis. Two variants of this method have been developed, one using the Bayesian probabilities theory, and one using the theory of evidence. These variants and their specificities with regard to classic tracking methods are recalled, with some extensions to the previous work. Special attention is given to the comparison of these two variants, and to difficult cases such as multiple maneuvering targets or crossing targets.< >

关键词： Target tracking Intelligent networks Sensor fusion Sensor phenomena and characterization Time measurement Equations State-space methods Bayesian methods Doppler measurements Motion analysis

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Correlation generated targets for neural network based speech recognition

Correlation generated targets for neural network based speec...

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International conference on signal processing Proceedings (ICSP)

作者： Fei Li Yonghong Yan Nanjing Institute of Post and Telecommunications Nanjing China Center for Spoken Language Understanding Technology Oregon Graduate Institute of Science and Technology OR USA

This paper presents a novel technique for data sharing through neural network training target manipulation. It uses correlations between output values of a network to create a set of non-zero targets for each training pattern. Experimental results show that more than 20% error reduction is achieved on a speaker-independent continuous digit string recognition task.

关键词： Neural networks Speech recognition Hidden Markov models Training data Natural languages Context modeling Least squares approximation Telephony Robustness Acoustic measurements

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