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检索条件"任意字段=Signal and Data Processing of Small Targets 1995 Conference"

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Particle Filter Tracking for the Banana Problem

Particle Filter Tracking for the Banana Problem

引用

25th SPIE conference on signal and data processing of small targets

作者： Romeo, Kevin Willett, Peter Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819497079

In this paper we present an approach for tracking with a high-bandwidth active sensor in very long range scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems;and most flavors of particle filter suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and the divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter is shown to avoid this diversity problem while producing consistent results. The regularization is accomplished using a modified version of the Epanechnikov kernel.

关键词： Particles Particle filters Detection and tracking algorithms Filtering (signal processing) Gaussian filters Digital filtering Error analysis Sensors Active sensors Statistical analysis

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On Covariance Structure in Noisy, Big data

On Covariance Structure in Noisy, Big Data

引用

25th SPIE conference on signal and data processing of small targets

作者： Paffenroth, Randy C. Nong, Ryan Du Toit, Philip C. Numerica Corp Loveland CO 80538 USA

ISBN: (纸本)9780819497079

Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large- scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.

关键词： Sensors Matrices Computer networks Algorithms Computer intrusion detection Optimization (mathematics) Principal component analysis Sensor fusion data fusion Veins

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A Minimalist Approach to Bias Estimation for Passive Sensor Measurements with targets of Opportunity

A Minimalist Approach to Bias Estimation for Passive Sensor ...

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25th SPIE conference on signal and data processing of small targets

作者： Belfadel, Djedjiga Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819497079

In order to carry out data fusion, registration error correction is crucial in multisensor systems. This requires estimation of the sensor measurement biases. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. This paper provides a solution for bias estimation for the minimum number of passive sensors (two), when only targets of opportunity are available. The sensor measurements are assumed time-coincident (synchronous) and perfectly associated. Since these sensors provide only line of sight (LOS) measurements, the formation of a single composite Cartesian measurement obtained from fusing the LOS measurements from different sensors is needed to avoid the need for nonlinear filtering. We evaluate the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

关键词： Bias estimation bias observability statistical efficiency CRLB composite measurements maximum likelihood

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Efficient Multiple Emitter Localization for Fully Decentralized Large-Scale/Low-Cost Multimodal Sensor Networks

Efficient Multiple Emitter Localization for Fully Decentrali...

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25th SPIE conference on signal and data processing of small targets

作者： Haney, Philip J. Fiore, Paul D. BAE Syst 6 New England Execut Pk Burlington MA 01803 USA MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)9780819497079

This paper presents a robust approach to the problem of localizing multiple emitters in cluttered environments using a network of low-cost sensors. A pseudo maximum likelihood (PML) function, whose peaks strongly indicate the number and locations of the true emitters, is generated from available sensor measurements. Localization is performed by first iteratively associating the individual sensor measurements to the PML peaks and then generating true maximum likelihood (ML) estimates of the emitter locations based on the associated measurements. These emitter location estimates are fed to an EKF-based, decentralized architecture for initiating, sustaining and sharing local track activity throughout the sensor network. The iterative PML approach is shown to be efficient with computational complexity that is linear in the number of measurements. Additionally, simulation results illustrate the ability of the proposed approach to generate accurate emitter location estimates in cluttered environments for generating and sustaining all track activity in a fully decentralized sensor network.

关键词： Emitter Localization Multimodal Sensor Networks Maximum Likelihood Decentralized data Fusion

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Lightweight SAR GMTI Radar Technology Development

Lightweight SAR GMTI Radar Technology Development

引用

conference on Radar Sensor Technology XVII

作者： Kirk, John C., Jr. Lin, Kai Gray, Andrew Hseih, Chung Darden, Scott Kwong, Winston Majumder, Uttam Scarborough, Steven Goleta Star LLC Torrance CA 90501 USA WPAFB RYAP AFRL Wright Patterson AFB OH USA

ISBN: (纸本)9780819495051

A small and lightweight dual-channel radar has been developed for SAR data collections. Using standard Displaced Phase Center Antenna (DPCA) radar digital signal processing, SAR GMTI images have been obtained. The prototype radar weighs 5-lbs and has demonstrated the extraction of ground moving targets (GMTs) embedded in high-resolution SAR imagery data. Heretofore this type of capability has been reserved for much larger systems such as the JSTARS. Previously, small lightweight SARs featured only a single channel and only displayed SAR imagery. Now, with the advent of this new capability, SAR GMTI performance is now possible for small UAV class radars.

关键词： Radar Synthetic aperture radar Doppler effect Antennas signal processing Target detection Radar signal processing Image processing Digital filtering Filtering (signal processing)

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Improving variance estimation ratio score calculation for slow moving point targets detection in infrared imagery sequences

Improving variance estimation ratio score calculation for sl...

引用

25th SPIE conference on signal and data processing of small targets

作者： Huber-Shalem, Revital Hadar, Ofer Rotman, Stanley R. Huber-Lerner, Merav Evstigneev, Stanislav Ben Gurion Univ Negev Dept Commun Syst Engn POB 653 IL-84105 Beer Sheva Israel Ben Gurion Univ Negev Dept Elect & Comp Engn POB 653 IL-84105 Beer Sheva Israel

ISBN: (纸本)9780819497079

Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. The target detection performance is measured via the variance estimation ratio score (VERS), which essentially calculates the pixel scores of the sequences, where a high score indicates a target is suspected to traverse the pixel. VERS uses two parameters - long and short term windows, which were predetermined individually for each movie, depending on the target velocity and on the clouds intensity and amount, as opposed to clear sky (noise), in the background. In this work, we examine the correlation between the sequences' spatial and temporal features and these two windows. In addition, we modify VERS calculation, to enhance target detection and decrease cloud-edge scores and false detection. We conclude this work by evaluating VERS as a detection measure, using its original version and its modified version. The test sequences are both original real IR sequences as well as their relative compressed sequences using our designated temporal DCT quantization method.

关键词： compression cosine filter discrete cosine transform (DCT) infrared (IR) imagery spatial characteristics temporal characteristics variance estimation ratio score

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Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

Detection of shallow buried objects using an autoregressive ...

引用

conference on Detection and Sensing of Mines, Explosive Objects, and Obscured targets XVIII

作者： Nabelek, Daniel P. Ho, K. C. Univ Missouri Dept Elect & Comp Engn Columbia MO 65211 USA

ISBN: (纸本)9780819495006

The detection of shallow buried low-metal content objects using ground penetrating radar (GPR) is a challenging task. This is because these targets are right underneath the ground and the ground bounce reflection interferes with their detections. They do not create distinctive hyperbolic signatures as required by most existing GPR detection algorithms due to their special geometric shapes and low metal content. This paper proposes the use of the Autoregressive (AR) modeling method for the detection of these targets. We fit an A-scan of the GPR data to an AR model. It is found that the fitting error will be small when such a target is present and large when it is absent. The ratio of the energy in an A-scan before and after AR model fitting is used as the confidence value for detection. We also apply AR model fitting over scans and utilize the fitting residual energies over several scans to form a feature vector for improving the detections. Using the data collected from a government test site, the proposed method can improve the detection of this kind of targets by 30% compared to the pre-screener, at a false alarm rate of 0.002/m(2).

关键词： Classification Ground Penetrating Radar signal processing

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Comparison of Measured and Simulated IR signals from a Scaled Model Ship

Comparison of Measured and Simulated IR Signals from a Scale...

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25th SPIE conference on signal and data processing of small targets

作者： Kim, Dong-Geon Han, Kuk-Il Choi, Jun-Hyuk Kim, Tae-Kuk Chung Ang Univ Dept Mech Engn Seoul 156756 South Korea

ISBN: (纸本)9780819497079

The goal of the present study is to develop a S/W that predicts infrared signals from objects synthetically by considering the internal and external factors, such as surface properties, internal heat sources, solar irradiations, atmospheric temperature, etc. As a part of developing a S/W, this paper contains some results of the measured and simulated IR signals for comparison and validation. The scaled model ship used in this study is made of 3mm-thick steel and 1.5m long. It has virtual internal heat sources that are made of a brass block with a heater. The experiments are performed under an indoor environment to exclude the external effects such as solar irradiance, wind effect, etc. The radiance from the ship is mainly due to the surface temperature because the effects of solar and wind are excluded. Also the IR signals are collected by the IR cameras which are operated at MWIR(3.7 similar to 5.1 mu m) and LWIR(7.5 similar to 9.1 mu m), respectively. At the same time, the atmospheric temperature and the relative humidity are measured to use for input conditions for calculation. The surface temperature and the IR signals within the two wavelengths are calculated by using the S/W developed in this study considering the 3D ship model, the internal heater temperature, and the atmospheric conditions. The temperature and IR signals from the scaled model ship obtained from measurements and from the S/W developed in this study are compared each other by showing fairly good agreements with each other.

关键词： Surface temperature IR signal Scaled model ship Heat source

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A robust motion compensation algorithm for ISAR imaging of sea-surface targets by Airborne Radar

A robust motion compensation algorithm for ISAR imaging of s...

引用

2013 IEEE International conference on signal processing, Computing and Control, ISPCC 2013

作者： Mohapatra, B.B. Jaisaval, Vinod K. Rajagopal, Suchith Electronics and Radar Development Establishment DRDO C.V. Raman Nagar Bangalore India

ISBN: (纸本)9781467361903

Motion compensation is the most critical part of Inverse Synthetic Aperture Radar (ISAR) processing in Airborne Radars. For an X-band Airborne Radar where resolution requirement is not sub-metric, Range-Doppler algorithm is the preferred choice to generate ISAR images due to small rotation angle requirement. In addition when both the radar platform and target are expected to move at nearly steady course and speed within the image formation interval, the use of highly sophisticated motion compensation algorithms is not desirable. This paper presents a robust and computationally efficient algorithm for translational motion compensation based on batch profile correlation. The algorithm is robust to background noise and target scintillation effects. It removes the problem of error accumulation inherent in peak-tracking method and avoids limitation of range-shift in integer steps. The effectiveness of the approach is verified by applying the algorithm to simulated ISAR data as well as actual ISAR data collected by an X-band airborne radar. The ISAR data simulation and processing are carried out using MATLAB. Different noise levels and target amplitude fluctuation are added to the simulated ISAR data to test the robustness of the algorithm. © 2013 IEEE.

关键词： Inverse synthetic aperture radar

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Fusion of multispectral and stereo information for unsupervised target detection in VHR airborne data

Fusion of multispectral and stereo information for unsupervi...

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conference on signal processing, Sensor Fusion, and Target Recognition XXII

作者： Borghys, Dirk C. Idrissa, Mahamadou Shimoni, Michal Friman, Ola Axelsson, Maria Lundberg, Mikael Perneel, Christiaan Royal Mil Acad Dept CISS Brussels Belgium Swedish Def Res Agy Linkoping Sweden Royal Mil Acad Dept Math Brussels Belgium

ISBN: (纸本)9780819495365

Very high resolution multispectral imaging reached a high level of reliability and accuracy for target detection and classification. However, in an urban scene, the complexity is raised, making the detection and the identification of small objects difficult. One way to overcome this difficulty is to combine spectral information with 3D data. A set of (very high resolution) airborne multispectral image sequences was acquired over the urban area of Zeebrugge, Belgium. The data consist of three bands in the visible (VIS) region, one band in the near infrared (NIR) range and two bands in the mid-wave infrared (MWIR) region. Images are obtained images at a frame rate of 1/2 frame per second for the VIS and NIR image and 2 frames per second for the MWIR bands. The sensors have a decimetric spatial resolution. The combination of frame rate with flight altitude and speed results in a large overlap between successive images. The current paper proposes a scheme to combine 3D information from along-track stereo, exploiting the overlap between images on one hand and spectral information on the other hand for unsupervised detection of targets. For the extraction of 3D information, the disparity map between different image pairs is determined automatically using an MRF-based method. For the unsupervised target detection, an anomaly detection algorithm is applied. Different methods for inserting the obtained 3D information into the target detection scheme are discussed.

关键词： target detection people detection vehicle detection aerial images stereo processing multispectral data

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