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189 - Uncorrelated Tracks, Differing Phenomenologies and “More Data Is More Better”

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Manage episode 439359124 series 1755960
Indhold leveret af Kratos. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kratos eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

On the Constellations Podcast, we’ll discuss data, data visualization, and processing data for better understanding. In this episode, Paul Graziani, CEO of COMSPOC, talks about Space Situational Awareness (SSA) and the value of data fusion in enhancing SSA. Paul describes the various data sources for SSA, such as optical data from telescopes, RF data from sensors, and radar data from ground-based or transmitter sources. He also explains how these sources differ. David discusses observing data and determining its integrity using a Kalman filter. He highlights the vast number of live and dead objects in space, as well as suspiciously maneuvering spacecraft. Mr. Graziani emphasizes data fusion as a key solution to this problem. He describes the ecosystem of companies, governments, labs, and academics that collectively serve the mission of SSA more effectively.

  continue reading

131 episoder

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Manage episode 439359124 series 1755960
Indhold leveret af Kratos. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kratos eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

On the Constellations Podcast, we’ll discuss data, data visualization, and processing data for better understanding. In this episode, Paul Graziani, CEO of COMSPOC, talks about Space Situational Awareness (SSA) and the value of data fusion in enhancing SSA. Paul describes the various data sources for SSA, such as optical data from telescopes, RF data from sensors, and radar data from ground-based or transmitter sources. He also explains how these sources differ. David discusses observing data and determining its integrity using a Kalman filter. He highlights the vast number of live and dead objects in space, as well as suspiciously maneuvering spacecraft. Mr. Graziani emphasizes data fusion as a key solution to this problem. He describes the ecosystem of companies, governments, labs, and academics that collectively serve the mission of SSA more effectively.

  continue reading

131 episoder

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