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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 1999"

共 764 条记录，以下是31-40 订阅

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Detection of small IR objects using wavelets, matched subspace detectors, and registration

Detection of small IR objects using wavelets, matched subspa...

引用

14th conference on signal and data processing of small targets

作者： Hewer, G Kuo, W Kenney, C Hanson, G Bobinchak, J USN Air Warfare Ctr China Lake CA 93555 USA

ISBN: (纸本)0819444782

Infrared sensors and advanced signal processing are used to detect small (or "point") targets in highly cluttered and noisy environments. In this paper, a wavelet detection algorithm and tracking of small targets in clutter will be discussed. A new registration algorithm based on optical flow estimates with matched subspace detectors against small maneuverable targets is also discussed. Both detectors incorporate adaptive constant false alarm rate (CFAR) detection statistics. Simulation of the detection and tracking algorithms using an unclassified database with a helicopter target and platform for the video cameras is summarized.

关键词： wavelets matched subspace detector registration

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Adaptive threshold based spatio-temporal filtering techniques for detection of small targets

Adaptive threshold based spatio-temporal filtering technique...

引用

conference on signal and data processing of small targets 2000

作者： Ronda, V New, WL Tan, MH Er, MH Nanyang Technol Univ CSP Singapore 639798 Singapore

ISBN: (纸本)0819436747

There are several methods reported in the literature for detecting dim targets against slowly moving clutter. However, each method has its own advantages and disadvantages. The challenge lies in reducing the 'false alarm rate' to an acceptable level. Choosing a threshold for achieving constant false alarm rate is always a tricky problem. Too less a threshold may ensure detection of target pixels. But this will result in with too many false targets, which limit the performance of the postprocessor to trace out target paths. Too high threshold results in fewer false alarms but the targets also may miss out, creating a problem in establishing track record of targets. These contradicting issues demand a via-media solution to improve the overall performance of detection process. This paper presents an adaptive threshold technique and a preliminary concept of CFAR for the detection of dim point-targets in the presence of the evolving clouds and heavy background clutter. The adaptive threshold is based on random and correlated noises of the incoming image sequence. The incoming frames of data are processed by adaptive threshold and accumulated recursively. The post-processor with built-in flexibility checks for validity of target paths. This paper presents an improvement over our paper presented at SPIE, Denver during July 1999. The algorithm has been tested with the available database and the results are very promising.

关键词： point-target random noise correlated noise false alarm rate

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Unified sensor management in unknown, dynamic clutter

Unified sensor management in unknown, dynamic clutter

引用

conference on signal and data processing of small targets 2010

作者： Mahler, Ronald El-Fallah, Adel Lockheed Martin MS2 (United States) Scientific Systems Co. Inc. (United States)

ISBN: (纸本)9780819481627

In recent years the first author has developed a unified, computationally tractable approach to multisensor-multitarget sensor management. This approach consists of closed-loop recursion of a PHD or CPHD filter with maximization of a "natural" sensor management objective function called PENT (posterior expected number of targets). In this paper we extend this approach so that it can be used in unknown, dynamic clutter backgrounds.

关键词： Sensors Target detection Process modeling Space sensors Current controlled current source data processing Electronic filtering Probability theory signal detection signal processing

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SUPER NONCOHERENT INTEGRATION - ANALYSIS OF PERFORMANCE

SUPER NONCOHERENT INTEGRATION - ANALYSIS OF PERFORMANCE

引用

conference on signal and data processing of small targets 1994

作者： DAUM, F RAYTHEON CO WAYLANDMA 01778

ISBN: (纸本)0819415391

This paper analyzes a new method to detect targets. The new method, called `super noncoherent integration' (SNCI), can improve overall detection performance by typically 5 dB to 10 dB relative to conventional noncoherent integration. A simple back-of-the-envelope formula is derived which quantifies the performance improvement of SNCI. Conventional noncoherent integration (CNCI) uses only amplitude measurements to distinguish targets from noise or clutter. In contrast, SNCI uses amplitude data in addition to: monopulse data, quadrature monopulse data, range and Doppler data over a sequence of N transmitted radar waveforms.

关键词： signal to noise ratio Doppler effect Radar Target detection Sensors Filtering (signal processing) Detection and tracking algorithms Error analysis Infrared sensors signal detection

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Simulation-based optimal filter for manoeuvring target tracking

Simulation-based optimal filter for manoeuvring target track...

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conference on signal and data processing of small targets 1999

作者： Doucet, A Gordon, NJ Univ Cambridge Signal Proc Grp Cambridge CB2 1PZ England

ISBN: (纸本)0819432954

Whilst single model filters are sufficient for tracking targets having fixed kinematic behaviour, manoeuvring targets require the use of multiple models. Jump Markov linear systems (JMLS), i.e. linear systems whose parameters evolve with time according to a finite state-space Markov chain, have been used in these situations with great success. However, it is well-known that performing optimal estimation for JMLS involves a prohibitive computational cost exponential in the number of observations. Many approximate methods have been proposed in the literature to circumvent this including the well-known GPB and IMM algorithms. These methods are computationally cheap but at the cost of being suboptimal. Efficient off-line methods have recently been proposed based on Markov chain Monte Carlo (MCMC) algorithms that out-perform recent methods based on the Expectation-Maximization algorithms. However, realistic tracking systems need on-line techniques. In this paper, we propose an original on-line Monte Carlo (MC) filtering algorithm to perform optimal state estimation of JMLS. The approach taken is loosely based on the bootstrap filter which, whilst being a powerful general algorithm in its original form, does not make the most of the structure of JMLS. The proposed algorithm exploits this structure and leads to a significant performance improvement.

关键词： particle filter Markov chain Monte Carlo switching state space model Bayesian methods target tracking

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Sidelobe reduction for efficient detection of multiple radar targets

Sidelobe reduction for efficient detection of multiple radar...

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conference on signal and data processing of small targets

作者： Deng, H Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

ISBN: (纸本)0819450774

With multiple radar targets the sidelobe of matched filtering outputs from the stronger targets become the interferences for the detection of weaker targets. An effective approach based on traditional CLEAN algorithm is proposed for sidelobe reduction for the matched filtering output of binary coding radar signals. A novel multilevel sidelobe reduction method is also developed for closely located multiple targets of nearly equally strong scatterings. The effectiveness of the sidelobe reduction algorithms is demonstrated through the numerous processing results.

关键词： radar target detection pulse compression CLEAN algorithms interference reduction

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Identity Variance for Multi-Object Estimation

Identity Variance for Multi-Object Estimation

引用

conference on signal and data processing of small targets

作者： Crouse, David F. Willett, Peter Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819487476

We define the notion of an "identity variance" for expressing the level of uncertainty between target identities in a PDF representing the states of multiple targets. This, coupled with an OSPA covariance introduced in past work, can form a basis for evaluating both the accuracy of the state estimates as well as the confidence in the identities of the states. A potential application of the identity variance is as a criterion for choosing between waveforms optimized for producing accurate position estimates versus good classification information on a multifunction radar.

关键词： Error analysis Radar Matrices Particles Computer engineering Current controlled current source data analysis data processing Particle filters signal processing

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Target detection by distributed sensors: distributed sensor concept-DISCO for small target detection

Target detection by distributed sensors: distributed sensor ...

引用

20th conference on signal and data processing of small targets

作者： Rafailov, Michael K. QinetiQ NA Reston VA 20191 USA

ISBN: (纸本)9780819471604

Distributed Sensor Concept - DISCO was proposed [I] for multiplication of individual sensor capabilities through non-coherent cooperative target engagement. The signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique [2] that was initially proposed as a way to improve the SNR [3], reduce data rate [4] and mitigate FPA noise for IR sensors [5]. In DISCO, the RAFIL technique is used in a segmented way, when constituencies of the technique are spatially and temporally separated between individual sensors. Each sensor provides to and receives data from other sensors in the network. In this paper efficiency of DISCO is discussed for acquisition, accurate handover and track correlation of small targets.

关键词： multiple sensor system distributed sensors distributed apertures accurate target detection frame integration data rate recursive processing double threshold

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Model-based estimation of small target parameters

Model-based estimation of small target parameters

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conference on signal and data processing of small targets

作者： Eitner, PG Lockheed Martin Management & Data Syst Philadelphia PA 19101 USA

ISBN: (纸本)0819428221

Resolution limitations have a significant impact on accuracy of small target parameters estimated from imagery. This paper describes a model-based method for small target parameter estimation. The method requires an a priori model of the target, and under many conditions will provide better results than deconvolution relying on pixel data alone. A description of the algorithm will be given, along with examples illustrating performance in a variety of situations, including a demonstration of the ability to handle some degree of saturation in the imaging process.

关键词： parameter estimation image restoration small targets model-based method

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Radar detection of multiple moving targets in clutter using time-frequency-radon transform

Radar detection of multiple moving targets in clutter using ...

引用

14th conference on signal and data processing of small targets

作者： Chen, VC USN Res Lab Div Radar Washington DC 20375 USA

ISBN: (纸本)0819444782

In this paper, we analyze features of radar returns from moving targets, introduce the basic concept of time-frequency-Radon transforms, describe the Radon transform for line feature detection, discuss their applications to detection of multiple moving targets in clutter, and demonstrate two examples of moving target detection using simulated radar data.

关键词： time-frequency transform Radon transform moving targets multiple targets

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