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18th conference on signal and data processing of small targets

作者： Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Storrs CT USA

ISBN: (纸本)0819462926

A number of methods exist to track a target's uncertain motion through space using inherently inaccurate sensor measurements. A powerful method of adaptive estimation is the interacting multiple model (IMM) estimator. In order to carry out state estimation from the noisy measurements of a sensor, however, the filter should have knowledge of the statistical characteristics of the noise associated with that sensor. the statistical characteristics (accuracies) of real sensors, however, are not always available, in particular for legacy sensors. this paper presents a method of determining the measurement noise variances of a sensor by using multiple IMM estimators while tracking targets whose motion is not known - targets of opportunity. Combining techniques outlined in [1] and [3], the likelihood functions are obtained for a number of IMM estimators, each with different assumptions on the measurement noise variances. then a search is carried out to bracket the variances of the sensor measurement noises. the end result consists of estimates of the measurement noise variances of the sensor in question.

关键词： tracking noise estimation

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RECONSTRUCTION OF NON-LAMBERTIAN SURFACES BY FUSION OF SHAPE FROM SHADING AND ACTIVE RANGE SCANNING

RECONSTRUCTION OF NON-LAMBERTIAN SURFACES BY FUSION OF SHAPE...

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18th IEEE International conference on Image processing (ICIP)

作者： Herbort, Steffen Grumpe, Arne Woehler, Christian Dortmund Univ Technol Image Anal Grp D-44227 Dortmund Germany

ISBN: (纸本)9781457713033

In this paper, we present an algorithm for the fusion of surface normals estimated based on Shape from Shading with absolute depth data under exploitation of the mutual advantages, regarding non-Lambertian surfaces with non-uniform albedos. While photometric 3D reconstruction methods yield dense surface detail information which is reliable on small scales, active range scanning provides absolute depth data which are typically noisy on small scales but reliable on large scales. the proposed algorithm applies an iterative refinement to the reconstructed surface in order to suppress errors that result from measurement uncertainties in the surface normals and the absolute depth data by simultaneous minimization of a global error functional. the obtained surface is the best fit to the observed image intensities and depth data. We apply our framework to small-scale real-world objects and to regions of the lunar surface.

关键词： 3D surface reconstruction Shape from Shading range scanning data fusion

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Joint detection and tracking of unresolved targets with a joint-bin processing monopulse radar - art. no. 62360T

Joint detection and tracking of unresolved targets with a jo...

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18th conference on signal and data processing of small targets

作者： Nandakumaran, N. Sinha, A. Kirubarajan, T. McMaster Univ ETFLab Dept Elect & Comp Engn Hamilton ON Canada

ISBN: (纸本)0819462926

Detection and estimation of multiple unresolved targets with a monopulse radar is limited by the availability of information in monopulse signals. the maximum possible number of targets that can be extracted from the monopulse signals of a single bin is two. Recently two approaches have been proposed in the literature to overcome this limitation. the first is joint-bin processing that exploits target spill-over among adjacent cells by modeling the target returns in the adjacent cells. In addition to making use of the additional information available in target spill-over, it handles a more practical problem where the usual assumption of ideal sampling is relaxed. the second approach is to make use of tracking information in detection through joint detection and tracking with the help of Monte Carlo integration of a particle filter. It was shown that the extraction of even more targets is possible with tracking information. In this paper, a new approach is proposed to combine make the best of these two approaches - a new joint detection and tracking algorithm with multibin processing. the proposed method increases the detection ability as well as tracking accuracy. Simulation studies are carried out. with amplitude comparison monopulse radar for an unresolved target scenario. the relative performances of various methods are also provided.

关键词： U nresolved targets closely-spaced targets monopulse radar multitarget tracking particle filters joint-bin processing

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Comparison of two MDA algorithms for a problem in missile defense

Comparison of two MDA algorithms for a problem in missile de...

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18th conference on signal and data processing of small targets

作者： Areta, J. Bar-Shalom, Y. Levedahl, M. Univ Connecticut Storrs CT USA

ISBN: (纸本)0819462926

In this paper we compare the performance of two Multidimensional Assignment Algorithms (MDA), the Lagrangean Relaxation based S-D algorithm and the Sequential m-best 2-D algorithm, applied to a realistic problem in missile defense surveillance. the benchmark problem consists of a set of sources that provide "event" (track) estimates of multiple launches, via a number of communication networks to a Fusion Center (FC) which has to perform data association prior to fusion. the network model used "loses" the information tag that distinguishes reports from the same source transmitted through different networks, i.e., the track identity (ID) assigned by the source is not passed on. Only a track ID assigned by the network, and the source ID accompany the track. thus detection and elimination of track duplications at the FC is needed. the proposed hierarchical approach to the problem requires the solution of several MDA problems before calculating the fused estimate, so accuracy of the solution of each is crucial. Examples with several launches, sources and networks are presented to compare the performance of the two assignment algorithms.

关键词： multidimensional assignment data association benchmark

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TRANSMISSION OF CORRELATED INFORMATION SOURCES WIth NETWORK CODING

TRANSMISSION OF CORRELATED INFORMATION SOURCES WITH NETWORK ...

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18th European signal processing conference (EUSIPCO)

作者： Park, Hyunggon thomos, Nikolaos Frossard, Pascal Ewha Womans Univ Multimedia Commun & Networking Lab Seoul South Korea Ecole Polytech Fed Lausanne Signal Proc Lab LTS4 CH-1015 Lausanne Switzerland

this paper addresses the problem of the distributed delivery of correlated data sources with help of network coding. Network coding provides an alternative to routing algorithms and offers improved system performance, robustness and throughput, with no need of deploying sophisticated routing strategies. However, the performance is directly driven by the number of innovative data packets that reach the receiver. If the number of received innovative data packets is significantly small, the decoder cannot perfectly recover the transmitted information. However, we show that the correlation between the data sources can be used at decoder for effective approximate decoding. We analytically investigate the impact of the network coding algorithm, and in particular, of the size of finite fields on the decoding performance. then, we determine an optimal field size that minimizes the expected decoding error, which represents a trade-off between quantization of the source data and probability of decoding error. the network coding with approximate decoding algorithm is implemented in illustrative multimedia streaming and sensor network applications. In both cases, the experimental results confirm the field size analysis and illustrate the effectiveness of approximate decoding of correlated data.

关键词： Network coding

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Detection and Localization of Multiple Unresolved Extended targets via Monopulse Radar signal processing

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2009年第2期45卷 455-472页

作者： Zhang, Xin Willett, Peter Bar-Shalom, Yaakov United Technol Res Ctr E Hartford CT 06108 USA Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

When the size of targets is comparable to the range resolution of monopulse radars, these targets should be considered as extended rather than point targets. If several closely-spaced targets fall within the same radar beam and between adjacent matched filter samples in range, the full monopulse information from all of these samples can and should be used to resolve these targets, i.e., estimate the number of targets and their respective angles-of-arrival and ranges. To detect and localize multiple unresolved extended targets, we establish a model for monopulse radar returns from extended objects, and present a maximum likelihood estimator (MLE) to localize the targets. Rissanen's minimum description length (MDL) criterion will be used to decide the number of existing extended objects. We also derive the upper limit on the number of targets and their scattering centers that can be resolved, and we provide necessary conditions for these targets to be uniquely identified. We compare the new extended target monopulse processing scheme with previously developed point-target monopulse techniques in the simulations.

关键词： RADAR ELECTRONIC pulse techniques ELECTRONIC systems signal processing -- Digital techniques MACHINE theory

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MULTICHANNEL COMPRESSED SENSING VIA SOURCE SEPARATION FOR HYPERSPECTRAL IMAGES

MULTICHANNEL COMPRESSED SENSING VIA SOURCE SEPARATION FOR HY...

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18th European signal processing conference (EUSIPCO)

作者： Golbabaee, Mohammad Arberet, Simon Vandergheynst, Pierre Ecole Polytech Fed Lausanne Signal Proc Inst CH-1015 Lausanne Switzerland

this paper describes a novel framework for compressive sampling of multichannel signals that are highly correlated across the channels. In this work, we assume few number of independent sources are generating the multichannel observations based on a linear mixture model. Moreover, sources are assumed to have sparse/compressible representations in some orthonormal basis. the main contribution of this paper lies in rephrasing the compressed sampling of multichannel data as the compressive source separation problem by knowing the mixture parameters. A number of simulations measure the performance of our recovery algorithm. Comparing to the classical CS scheme -which recovers data of all channels separately-ours indicates a significant reduction in both, the number of measurements to be sent and the complexity of the decoding algorithm (i.e., scaling by the number of sources rather than the number of channels). We demonstrate an application of our scheme in acquisition of the Hyperspectral images. Our algorithm proposes an accurate, low cost and fast recovery from small number of the transmitted measurements that are taken by a low resolution camera.

关键词： Compressed sensing Hyperspectral images Mixture model Source separation Sparsity l(1)-minimization

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FAST DETECTION OF small INFRARED OBJECTS IN MARITIME SCENES USING LOCAL MINIMUM PATTERNS

FAST DETECTION OF SMALL INFRARED OBJECTS IN MARITIME SCENES ...

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18th IEEE International conference on Image processing (ICIP)

作者： Qi, Baojun Wu, Tao Dai, Bin He, Hangen Natl Univ Def Technol Inst Automat Coll Mechatron Engn & Automat Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781457713033

this paper describes a novel approach for fast detecting small maritime objects in infrared (IR) images. It is based on the local minimum patterns (LMP), which are theoretically the approximations of some stationary wavelet transforms (SWT). Using LMP to estimate the background with a single image, we obtain an object-aware saliency map by background subtraction. Regions of potential objects are then segmented by an adaptive threshold based on the histogram of the saliency map. We finally propose a fast clustering algorithm for localizing objects from segmented regions. Extensive experiments on challenging data sets show a competitive performance.

关键词： Infrared surveillance wavelet background subtraction object detection

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Extended dwell Doppler characteristics of birds and micro-UAS at L-Band 18

Extended dwell Doppler characteristics of birds and micro-UA...

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18th International Radar Symposium (IRS)

作者： Jahangir, Mohammed Baker, Chris J. Aveillant Ltd 300 Sci Pk Cambridge England

ISBN: (纸本)9783736993433

Unmanned Aerial Systems (UAS), commonly referred to as drones, are rapidly proliferating bringing about new challenges for security and safety. the reason being their small size and ability to fly low in a highly irregular manner makes them particularly difficult to detect with conventional wide-area surveillance sensors such as a scanning radar. Here, we use staring radar that employs a 2-D antenna array and appropriate signal processing to create a multibeam, 3-D, wide-area, continuously staring surveillance sensor capable of achieving high detection sensitivity, whilst providing fine Doppler resolution with update rates of fractions of a second. Whilst staring radar is able to detect miniature UAS against a background of complex clutter, the necessary high detection sensitivity means that many other small moving targets are detected, birds being a principle example. Good Doppler discrimination is central to the ability to distinguish between genuine drones and other confuser targets such as birds that are reported by the radar sensor. Results from field trials are presented illustrating the signal characteristics of rotary wing micro-drones and birds. Analysis of the detailed data features leads to refinements enabling better discrimination between low observable micro-drones and birds.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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Nonlinear estimation techniques for impact point prediction of ballistic targets - art. no. 62360C

Nonlinear estimation techniques for impact point prediction ...

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18th conference on signal and data processing of small targets

作者： Hardiman, David F. Kerce, J. Clayton Brown, George C. USA Redstone Arsenal AL 35898 USA

ISBN: (纸本)0819462926

this paper considers three nonlinear estimation algorithms for impact point prediction (IPP) of ballistic targets. the paper assumes measurements are available from a 3D surveillance radar or phased array radar over some portion of the ballistic trajectory. the ballistic target (BT) is tracked using an extended Kalman filter (EKF), an unscented Kalman filter (UKF), and a particle filter (PF). With the track estimate as an initial condition, the equations of motion for the BT are integrated to obtain a prediction of the impact point. this paper compares the performance of the EKF, UKF, and a particular choice of PF for impact point prediction. the traditional Extended Kalman Filter equations are based on a first-order Taylor, series approximation of the nonlinear transformations (expanded about the latest state estimate). Both the Unscented Kalman Filter and the Particle Filter allow nonlinear systems to be modeled without prior linearizion. the primary focus of the analysis presented in this paper is comparing the performance and accuracy of the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF), and the chosen Particle Filter implementation for impact point prediction. the three filtering techniques are compared to the theoretical Cramer-Rao lower bounds (CRLB) of estimation error.

关键词： estimation non-linear dynamic system Cramer-Rao lower bound (CRLB) Kalman filter

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