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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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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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New method for detection of dim point-targets in infrared images

New method for detection of dim point-targets in infrared im...

引用

conference on signal and data processing of small targets 1999

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

ISBN: (纸本)0819432954

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. 'False alarm rate' defined in case of a significant size of the target in a frame may not be applicable to point-targets. This paper presents a new method for the detection of dim point-targets in the presence of the evolving clouds and heavy background clutter. 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 too many false targets, which limit the performance of the post-processor to trace out target paths. Too high a threshold result in fewer false alarms but the targets may also be missing out. Based on off-line studies, it has been found that a 'desirable condition' is required to limit the number of accumulated pixels not to exceed 8% of the total image size for post-processing. This paper presents a method based on random and correlated noises which in turn selects an auto threshold that leads to the 'desirable condition' for the postprocessor. An effort has been made to derive an empirical formula based on random and correlated noises to obtain an auto threshold value that achieves the desirable condition. Then the incoming frames of data are then processed by a constant threshold and accumulated as total number of pixels. At the same time the track record of pixels along with frame numbers are recorded. The post-processor to filter out the false alarms uses this information. One advantage of this method is that there is no need to store all the frames to obtain the desired information. The algorithm has been tested with the available database and the results are very promising. It is assumed that most of the targets occupy a couple of pixels. Head-on moving and manoeuvring targets are not

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

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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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Detection of small targets and their Characterization Based on their Formation using an Image Feature Network-Based Object Recognition Algorithm

Detection of Small Targets and their Characterization Based ...

引用

conference on signal and data processing of small targets

作者： Straub, Jeremy Univ N Dakota Dept Comp Sci Grand Forks ND 58202 USA

ISBN: (纸本)9781628410297

small target detection and classification is problematic. For targets that operate as part of a cluster, classification can be performed based on the characteristics of the cluster's operations, instead of trying to identify an individual cluster-member directly. This paper presents an algorithm for object identification based on comparing networks of point-to-point distances between features identified by an image feature detection algorithm. It discusses the alterations required to make the algorithm suitable for performing cluster-formation based characterization of small targets from point or near-point source data. An analysis of the algorithm's performance is presented and it efficacy for this application assessed.

关键词： small target detection and classification point targets classification decision cluster object identification cluster-formation based characterization of small targets

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IMMPDAF solution for the tracking and radar management benchmark with merged measurements and multipath

IMMPDAF solution for the tracking and radar management bench...

引用

conference on signal and data processing of small targets

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

ISBN: (纸本)0819450774

Radar signal processing is a key part in tracking closely spaced targets and targets in the presence of sea-surface-induced multipath. These issues are the salient features of the benchmark problem for tracking unresolved targets combined with radar management, for which this paper presents the only complete solution to date. In this paper a modified version of a recently developed "superresolution" maximum likelihood (ML) angle estimator for closely spaced targets as well as targets in the presence of multipath are presented. Efficient radar resource allocation algorithms for two closely spaced targets and targets flying close to the sea surface are also presented. Finally, the IMMPDAF (interacting multiple model estimator with probabilistic data association filter modules) is used to track these targets. It is found that a two-model IMMPDAF performs better than the three model version used in the previous benchmark. Also, the IMMPDAF with a coordinated turn model works better than the one using a Wiener process acceleration model. The signal processing and tracking algorithms presented here, operating in a feedback manner, form a comprehensive solution to the most realistic tracking and radar management problem to date.

关键词： Radar signal processing Performance modeling Detection and tracking algorithms Target detection signal to noise ratio Super resolution Sensors data modeling Radar signal processing

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Unified sensor management in unknown, dynamic clutter

Unified sensor management in unknown, dynamic clutter

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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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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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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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Sidelobe reduction for efficient detection of multiple radar targets

Sidelobe reduction for efficient detection of multiple radar...

引用

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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Model-based estimation of small target parameters

Model-based estimation of small target parameters

引用

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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