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Conference on signal and data processing of small targets

作者： Brown, GC Blair, WD Ogle, TL GTRI SEAL AMDD Atlanta GA 30332 USA

ISBN: (纸本)0819450774

A key assumption in monopulse based angle-of-arrival (AOA) estimators is that at most one return from a single object is present in each range cell, or equivalently in each sample of the matched filter output. These algorithms break down if the data consists of merged measurements-multiple target returns contained in the same range cell. The proposed technique makes use of data from a three channel monopulse radar to estimate the AOA of two targets from merged measurements. Specifically, the technique capitalizes on the structure of squint beams in conjunction with multiple range samples to resolve the multiple targets. The paper focuses on the development of the new algorithm along with results from computer simulations that demonstrate its viability. To illustrate the utility of this technique to target tracking problems, comparative Monte Carlo results of performance of a tracker with the new technique and conventional monopulse AOA estimates are provided.

关键词： merged measurements monopulse angle of arrival radar signal processing

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Knowledge-based radar signal and data processing - A tutorial overview

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IEEE signal processing MAGAZINE 2006年第1期23卷 18-29页

作者： Capraro, GT Farina, A Griffiths, H Wicks, MC L.C. Smith College of Engineering and Computer Science Syracuse University Royal Academy of Engineering U.S. Air Force

Radar systems are an important component in military operations. In response to increasingly severe threats from military targets with reduced radar cross sections (RCSs), slow-moving and low-flying aircraft hidden in foliage, and in environments with large numbers of targets, knowledge-based (KB) signal and data processing techniques offer the promise of significantly improved performance of all radar systems. Radars under KB control can be deployed to utilize valuable resources such as airspace or runways more effectively and to aid human operators in carrying out their missions. As battlefield scenarios become more complex with increasing numbers of sensors and weapon systems, the challenge will be to use already available information effectively to enhance radar performance, including positioning, waveform selection, and modes of operation. KB processing fills this need and helps meet the challenge.

关键词： Radar signal processing signal processing data processing Radar detection Radar cross section Military aircraft Radar antennas Doppler radar Airborne radar Radar applications

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Recognition of moving ground targets by measuring and processing seismic signal

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MEASUREMENT 2005年第2期37卷 189-199页

作者： Lan, JH Nahavandi, S Lan, T Yin, YX Univ Sci & Technol Beijing Informat Engn Sch Dept Measurement & Control Technol Beijing 100083 Peoples R China Deakin Univ Sch Engn & Technol Geelong Vic 3217 Australia Oregon Hlth Sci Univ OGI Sch Sci & Engn Dept Biomed Engn Beaverton OR 97006 USA

Because vehicles moving over ground generate a succession of impacts, the soil disturbances propagate away from the source as seismic waves. Thus, in the battlefield environment, we can detect moving ground vehicles by means of measuring seismic signals using a seismic velocity transducer, and automatically classify and recognize them by advance signal processing method. Because seismic sensor is easy to be developed by emerging micro-electro-mechanical system (MEMS) technology, seismic detection that will be low cost, low power, small volume and light weight is a promising method for moving ground targets. Such a detection method can be used in many different fields, such as battlefield surveillance. traffic monitoring, law enforcement and so on. The paper researches seismic signals of typical vehicle targets in order to extract features of seismic signal and to recognize targets. As a data fusion method, the technique of artificial neural networks (ANN) is applied to recognize seismic signals for vehicle targets. An improved BP algorithm and ANN data fusion architecture have been presented to improve learning speed and avoid local minimum points in error curve. The algorithm had been used for classification and recognition of seismic signals of vehicle targets in the outdoor environment. It can be proven that moving ground vehicles can be detected by measuring seismic signal, feature extraction of target seismic signal is correct and ANN data fusion is effective to solve the recognition and classification problem for moving ground targets. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： target recognition seismic signal data fusion

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Tracking targets using matched field observations

Tracking targets using matched field observations

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Conference on signal and data processing of small targets

作者： Willett, PK Bishop, J Giannopoulos, E Univ Connecticut ECE Dept U 1157 Storrs CT 06269 USA

ISBN: (纸本)0819450774

The target tracking literature has traditionally been most interested in the "hit" model for the observations process, and the community has developed many techniques for data association. On the other hand, matched field processing (MFP) research has focused on signal processing with the main emphasis on target detection and localization. Treatments of combined tracking/MFP systems are not common. but most concentrate on signal processing, with the idea that a "track" is really a sequence or track-segment of detections that make sense from dynamics considerations. Thus, here we explore the MFP tracking problem, with the key that we attempt to use traditional target-tracking algorithms. In particular. we use an IMMPDAF-AI (interacting multiple-model probabilistic data association filter with amplitude information). It is shown that the use of such an advanced tracking algorithm - plus a number of MFP-specific refinements - produces tracking performance that is far superior to that obtained for a more traditional tracking (a strongest-neighbor Kalman filter), with the added advantage of a significantly reduced numerical load as measured in terms of the number of MFP replicas to be computed.

关键词： Target tracking matched field processing passive sonar interacting multiple models probabilistic data association filter

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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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Time-space transform:A novel signal processing approach for an acoustic vector-sensor

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Science China(Information Sciences) 2013年第4期56卷 135-145页

作者： LIANG GuoLong MA Wei WANG YiLin Key Laboratory of Underwater Acoustic Technology Harbin Engineering University

A new signal processing method using a single vector hydrophone is proposed for solving the problem of azimuth angle estimation for multiple targets based on a small aperture underwater *** method extends the aperture from a single vector hydrophone into a half wavelength distance uniform linear array by decomposing the time-domain sample data from different channels of the *** extended array has a narrower space beam pattern than a single vector *** azimuths of spatial multiple targets are estimated by using the appended array snapshots under the condition of broadband or narrow band *** new method is robust because there is no need to correct the array *** analysis and computer simulations show that,the new algorithm has the ability to distinguish two incoherent targets with either narrow band or broadband signals in an isotropic noise *** algorithm provides a non-biased estimate with a high signal-to-noise ratio.

关键词： time space transform beam forming DOA MUSIC single vector hydrophone

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Comparison of methods for tracking separating targets with a monopulse radar

Comparison of methods for tracking separating targets with a...

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Conference on signal and data processing of small targets

作者： Willett, PK Blair, WD Ogle, TL Register, AH Brown, GC Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819450774

In many tracking applications. and particularly those in ballistic missile defense, one concern involves the continuous tracking of an object that separates into two objects. Reliable tracking without track breaks demands early recognition of such a split, preferably well in advance of the two objects becoming resolvable by the radar. In previous work, signal processing techniques for detecting the presence of unresolved objects and angle-of-arrival estimation for unresolved targets have been developed for monopulse radars. In this paper, these techniques are reviewed and extended. Techniques for detecting the presence of unresolved objects are treated for the case of idealized resolution, in which all of the energy for a target is returned in a single range resolution sample or cell. The approaches work solely on monopulse angle statistics and rely on idealized range resolution. The requirement for idealized range resolution is relaxed by using joint statistics with adjacent matched filter returns. The AOA estimation and detection of the presence of unresolved objects for non-ideal resolution are then addressed. The performances are demonstrated using a high fidelity software simulation tool for target tracking.

关键词： radar target tracking radar signal processing resolution

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Improvement of small target detection based on tensorial filtering

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REMOTE SENSING LETTERS 2015年第10期6卷 765-774页

作者： Bourennane, S. Fossati, C. Aix Marseille Univ Ecole Cent Marseille Inst Fresnel CNRS Marseille France

Target detection is a key issue in processing hyperspectral images (HSIs). However, current spectral-identification-based algorithms are sensitive to noise during acquisition of the data. In most cases, the denoising algorithms cannot preserve small targets. In this paper, to overcome this problem, we propose a new algorithm which reduces noise to improve the target detection efficiency of HSI with small targets. First, a three-dimensional wavelet packet transform (3D-WPT) is used to decompose the HSI into several coefficient sets and models each coefficient set as a tensor. Then we exploit a powerful multilinear algebra model named parallel factor analysis (PARAFAC) to filter each tensor. The experiments conducted in both simulated and real-world hyperspectral images demonstrated the performance of the proposed method.

关键词： HYPERSPECTRAL imaging systems FILTERING theory (signal processing) COMPUTER algorithms signal denoising data acquisition systems FACTOR analysis TENSOR algebra

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24 GHz FMCW MIMO Radar for Marine Target Localization: A Feasibility Study

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IEEE ACCESS 2022年 10卷 68240-68256页

作者： Gennarelli, Gianluca Noviello, Carlo Ludeno, Giovanni Esposito, Giuseppe Soldovieri, Francesco Catapano, Ilaria Natl Res Council Italy Inst Electromagnet Sensing Environm I-80124 Naples Italy

Radar detection and tracking of targets in the marine environment are common tasks performed to ensure the safe navigation of ships or monitor traffic in harbor areas. More recently, radar technology has been proposed to support the collision avoidance system of autonomous surface vehicles, which are characterized by severe constraints in terms of payload and space. The paper investigates the performance of a small and lightweight 24 GHz Frequency Modulated Continuous Wave (FMCW) Multiple-Input Multiple-Output (MIMO) radar, originally developed for automotive applications, to localize marine targets at short range. A complete signal processing strategy is presented combining MIMO radar imaging, detection, and tracking algorithms. The validation of the proposed signal processing chain is firstly performed thanks to numerical tests based on synthetic data. After, results of experimental trials carried out in the marine environment are reported. These results demonstrate that the considered radar together with the adopted signal processing strategy allows the localization of static targets and the tracking of moving targets with satisfactory performance, thus encouraging its use in marine environments.

关键词： Radar Radar tracking Target tracking Radar detection Radar antennas MIMO radar signal processing Detection FMCW marine environment MIMO radar signal processing tracking

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Applying ordered statistics filters for point target detection in hyperspectral data

Applying ordered statistics filters for point target detecti...

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signal and data processing of small targets 2003

作者： Raviv, O. Rotman, S.R. Ben-Gurion University of the Negev Dept. of Electrical Engineering

In this paper, we apply higher ordered statistics filters to hyperspectral data to enable the detection of anomalous targets whose signatures are known. Each frame has subtracted from it an estimate based on an ordered statistics filter;the resulting frames are then combined optimally based on the covariance data of the cube and the spectral signature of the target. We show that the effect of the ordered statistic filter is to eliminate false alarms at edge points.

关键词： Image processing

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