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Signal Processing Magazine, IEEE

Issue 1 • Date Jan. 2006

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Displaying Results 1 - 25 of 26
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  • Space-time adaptive processing: a knowledge-based perspective for airborne radar

    Page(s): 51 - 65
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1807 KB)  

    This article provides a brief review of radar space-time adaptive processing (STAP) from its inception to state-of-the art developments. The topic is treated from both intuitive and theoretical aspects. A key requirement of STAP is knowledge of the spectral characteristics underlying the interference scenario of interest. Additional issues of importance in STAP include the computational cost of the adaptive algorithm as well as the ability to maintain a constant false alarm rate (CFAR) over widely varying interference statistics. This article addresses these topics, developing the need for a knowledge-based (KB) perspective. The focus here is on signal processing for radar systems using multiple antenna elements that coherently process multiple pulses. An adaptive array of spatially distributed sensors, which processes multiple temporal snapshots, overcomes the directivity and resolution limitations of a single sensor. View full abstract»

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  • New Fellows and Constitution changes

    Page(s): 7 - 9
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  • Knowledge-based radar signal and data processing: a tutorial review

    Page(s): 18 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (602 KB)  

    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. View full abstract»

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  • Signal processing for optical communication

    Page(s): 88 - 96
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (585 KB)  

    Optical communication plays a significant and increasing role in our society. The public demand for higher network speed requires an optical backbone network with larger capacity. Accompanying high transmission-rate optical communications system are severe technical specifications for optical devices and systems. Many popular optical devices could be represented with a digital filter model as described in this article. Use of well-developed signal processing techniques and algorithms to design these optical devices is a wise use of existing technology. The wavelength division multiplexing (WDM) system, which is the dominating optical communication system, is introduced in this article. Three signal processing application examples for optical communications are presented: optical wavelength interleaver, an all-pass filter for chromatic dispersion compensation, and an electronic equalizer. As demonstrated in this article, signal processing could play an important role in the development of advanced optical communication systems. However, as demonstrated in the case of an electronic equalizer, some optical system characteristics may require special attention if signal processing techniques are to be applied successfully. Therefore, interdisciplinary cooperation between researchers in optics and signal processing will be crucial for optical communications to fully benefit from signal processing. View full abstract»

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  • Knowledge-based resource management for multifunction radar: a look at scheduling and task prioritization

    Page(s): 66 - 76
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (988 KB) |  | HTML iconHTML  

    In this article, we consider two related aspects of radar resource management, scheduling and task prioritization. Two different methods of scheduling are examined and compared and their differences and similarities highlighted. The comparison suggests that prioritization of tasks plays a dominant role in determining performance. A prioritization scheme based on fuzzy logic is subsequently contrasted and compared with a hard logic approach as a basis for task prioritization. The setting of priorities is shown to be critically dependent on prior expert knowledge. By assessing the priorities of targets and sectors of surveillance according to a set of rules it is attempted to imitate the human decision-making process such that the resource manager can distribute the radar resources in a more effective way. Results suggest that the fuzzy approach is a valid means of evaluating the relative importance of the radar tasks; the resulting priorities have been adapted by the fuzzy logic prioritization method, according to how the radar system perceived the surrounding environment. View full abstract»

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  • Advertisers index

    Page(s): 104
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  • Knowledge-aided adaptive radar at DARPA: an overview

    Page(s): 41 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1658 KB) |  | HTML iconHTML  

    For the past several years, the Defense Advanced Research Projects Agency (DARPA) has been pioneering the development of the first ever real-time knowledge-aided (KA) adaptive radar architecture. The impetus for this program is the ever increasingly complex missions and operational environments encountered by modern radars and the inability of traditional adaptation methods to address rapidly varying interference environments. The DARPA KA sensor signal processing and expert reasoning (KASSPER) program has as its goal the demonstration of a high performance embedded computing (HPEC) architecture capable of integrating high-fidelity environmental knowledge (i.e., priors) into the most computationally demanding subsystem of a modern radar: the adaptive space-time beamformer. This is no mean feat as environmental knowledge is a memory quantity that is inherently difficult (if not impossible) to access at the rates required to meet radar front-end throughput requirements. In this article, we will provide an overview of the KASSPER program highlighting both the benefits of KA adaptive radar, key algorithmic concepts, and the breakthrough look-ahead radar scheduling approach that is the keystone to the KASSPER HPEC architecture. View full abstract»

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  • An effective color scale for simultaneous color and gray-scale publications

    Page(s): 82 - 96
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1489 KB)  

    Pseudocolored images are used in many signal processing applications to represent signal properties as a function of two independent variables, such as time and frequency. This paper describes a color scale that can be used to unambiguously represent these images in printed gray-scale publications as well as full color electronic publications. The image resolution when viewed in color is enhanced in this article. This color scale also allows for correct interpretation by people with common types of color blindness, which accounts for approximately 10% of the male population and 1% of the female population. While it may be possible to obtain a better resolution with a color scale that is designed for a particular image on hand, the proposed color scale works well in many applications where the user does not have the time or resources to tailor the color scale to a specific image. The proposed color scale is also easy to implement and has an intuitive interpretation in that it cycles through a sequence of hues that roughly resembles the familiar rainbow. View full abstract»

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  • Cognitive radar: a way of the future

    Page(s): 30 - 40
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (596 KB)  

    This article discusses a new idea called cognitive radar. Three ingredients are basic to the constitution of cognitive radar: 1) intelligent signal processing, which builds on learning through interactions of the radar with the surrounding environment; 2) feedback from the receiver to the transmitter, which is a facilitator of intelligence; and 3) preservation of the information content of radar returns, which is realized by the Bayesian approach to target detection through tracking. All three of these ingredients feature in the echo-location system of a bat, which may be viewed as a physical realization (albeit in neurobiological terms) of cognitive radar. Radar is a remote-sensing system that is widely used for surveillance, tracking, and imaging applications, for both civilian and military needs. In this article, we focus on future possibilities of radar with particular emphasis on the issue of cognition. As an illustrative case study along the way, we consider the problem of radar surveillance applied to an ocean environment. View full abstract»

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  • IEEE Signal Processing Magazine - Jan. 2006

    Page(s): 0_1
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    Freely Available from IEEE
  • Table of contents - Vol 23 No 1

    Page(s): 1
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    Freely Available from IEEE
  • EDERS 2006

    Page(s): 5
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    Freely Available from IEEE
  • Academic leadership: building the base camp

    Page(s): 10 - 12
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    Freely Available from IEEE
  • ICUWB 2006 - Final Call for Papers

    Page(s): 91
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    Freely Available from IEEE
  • Embedded Systems Conference [2006]

    Page(s): 93
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    Freely Available from IEEE
  • IEEE Job site

    Page(s): 97
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  • New products

    Page(s): 98 - 100
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  • Fourth IEEE Workshop on Sensor Array and Multi-channel Processing (SAM-2006)

    Page(s): 101
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    Freely Available from IEEE
  • Dates ahead

    Page(s): 102
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  • 2006 IEEE Workshop on Machine Learning for Signal Processing - Call for Papers

    Page(s): 103
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    Freely Available from IEEE

Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/