Knowledge Base Applications to Adaptive Space-Time Processing, Volume 1: Summary

Salama, Y.; Senn, Roy

doi:10.21236/ada388939

Cited by 3 publications

(3 citation statements)

References 1 publication

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“…However, many on-going and promising research and development investigations increase our confidence that maturing technologies will foster success. Examples which will augment Distributed and Layered sensing and advances in UAVs include the development of knowledge based space time adaptive processing (KBSTAP), [5] [6] a dynamic software architecture for the filtering, detection, and tracking stages of radar processing, using the "non-homogeneity detector"; United States Geological Service (USGS) "map" data [7]; archival radar data; as well as off board sensor data to select the most appropriate space time adaptive processing (STAP) training data for improvements in filtering, detection, track, identification and handoff; as well as waveform selection and flight planning. As a result of recent and current research efforts, well-grounded and validated signal processing algorithms [8] [9] abound.…”

Section: Motivationmentioning

confidence: 99%

Distributed and Layered Sensing

Wicks

Moore

2007

2007 International Waveform Diversity and Design Conference

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One can easily envision future military operations and emerging civilian requirements (e.g. intelligent unmanned vehicles for urban warfare, intelligent manufacturing plants) that will be both complex and stressing and will demand innovative sensors and sensor configurations. The goal of our research into Distributed and Layered Sensing is to develop a cost effective and extendable approach for providing surveillance for a variety of applications in dynamically changing military and civilian environments. Within Distributed and Layered sensing, we foresee a new sensor archetype. In this paradigm, sensors and algorithms will be autonomously altered depending on the environment. Radars will use the same returns to perform detection and discrimination, to adjust the platform flight path and change mission priorities. The sensors will dynamically and automatically change waveform parameters to accomplish these goals. Disparate sensors will communicate and share data and instructions in real-time. Intelligent sensor systems will operate within and between sensor platforms such that the integration of multiple sensor data provides information needed to achieve dynamic goals and avoid electromagnetic fratricide. Intelligent sensor platforms working in partnership will increase information flow, minimize ambiguities, and dynamically change multiple sensors' operations based upon a changing environment. Concomitant with the current emphasis on more flexible defense structures, Distributed and Layered sensing will allow the appropriate incremental application of remote sensing assets by matching resources to the situation at hand.In this paper, we discuss the electromagnetic compatibility (EMC) issues that must be addressed and understood as part of the development of a futuristic intelligence, surveillance and reconnaissance concept utilizing Distributed and Layered sensing waveform diverse systems. These systems involve the innovative integration of cutting edge technologies such as: knowledge-based signal processing, robotics, wireless networking, waveform diversity, the semantic web, advanced computer architectures and supporting software languages. This concept is projected as an autonomous constellation of air, space, and ground vehicles that would offer a robust paradigm to build toward future deployments. The goal is to develop waveform-time-space adaptive processing algorithms for distributed apertures that could reduce EMC issues.

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Section: Motivationmentioning

confidence: 99%

Distributed and Layered Sensing

Wicks

Moore

2007

2007 International Waveform Diversity and Design Conference

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“…Because a discrete in a test cell is absent from the associated secondary data cells, STAP will not suppress the corresponding interference, and the discrete, especially if strong, could mask smaller RCS targets that are not well separated in angle or Doppler from that of the discrete. The conventional approach for suppressing the discrete is to first preprocess the primary and secondary data by deterministically combining elements (or PRIs) to form beam or subarray patterns in space (or time) with nulls in the direction of the discrete (or at the Doppler of the discrete) [22]. STAP is then applied with space-time data vectors formed from the preprocessed data.…”

Section: Discrete Scatterer Signal Injection (Dssi)mentioning

confidence: 99%

Space-Time Adaptive Processing (STAP) for Low Sample Support Applications

Schuman¹,

Li²

2004

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Section: Figure 1 Futuristic Scenariomentioning

confidence: 99%

Radar the next generation - sensors as robots

Wicks

2003 Proceedings of the International Conference on Radar (IEEE Cat. No.03EX695)

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Abstract-One can easily envision future military operations and emerging civilian requirements (e.g. intelligent unmanned vehicles for urban warfare, intelligent manufacturing plants) that will be both complex and stressing and will demand innovative sensors and sensor configurations. The goal of our research into Sensors as Robots is to develop a cost effective and extendable approach for providing surveillance for a variety of applications in dynamically changing military and civilian environments. Within Sensors as Robots, we foresee a new sensor archetype. In this paradigm, sensors and algorithms will be autonomously altered depending on the environment. Radars will use the same returns to perform detection and discrimination, to adjust the platform flight path and change mission priorities. The sensors will dynamically and automatically change waveform parameters to accomplish these goals. Disparate sensors will communicate and share data and instructions in real-time. Intelligent sensor systems will operate within and between sensor platforms such that the integration of multiple sensor data provides information needed to achieve dynamic goals and avoid electromagnetic fratricide. Intelligent sensor platforms working in partnership will increase information flow, minimize ambiguities, and dynamically change multiple sensors' operations based upon a changing environment. Concomitant with the current emphasis on more flexible defense structures, Sensors as Robots will allow the appropriate incremental application of remote sensing assets by matching resources to the situation at hand.In this paper, we discuss the development of a futuristic intelligence, surveillance and reconnaissance concept utilizing the innovative integration of cutting edge technologies such as: knowledge-based signal processing, robotics, wireless networking, waveform diversity, the Semantic Web, advanced computer architectures and supporting software languages. This concept is projected as an autonomous constellation of air, space, and ground vehicles that would offer a robust paradigm to build toward future deployments.

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Knowledge Base Applications to Adaptive Space-Time Processing, Volume 1: Summary

Cited by 3 publications

References 1 publication

Distributed and Layered Sensing

Distributed and Layered Sensing

Space-Time Adaptive Processing (STAP) for Low Sample Support Applications

Radar the next generation - sensors as robots

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