First steps toward the implementation of a cognitive radar to study plasma instabilities along the magnetic equator

Robert Sorbello, Julio Urbina, Zach Stephens

    Research output: Contribution to journalArticle

    1 Scopus citations

    Abstract

    Cognitive radar is envisioned to be the future of remote-sensing systems. The idea proposed by details that a cognitive radar will have the ability to learn about the sensing environment and, over time, optimize returns from targets of interest by altering the transmitted pulse waveform. This paper focuses on the first step of the cognitive process for ionospheric radar observations in the equatorial region. In this region, three plasma irregularities are observed very regularly via radar, namely, Spread F, 150 km echoes, and electrojet. During real-time observations, the first step of the cognitive process entails automatically recognizing the current plasma instability forming in the ionosphere. A preliminary test for the detection and classification of these events is performed off-line using radar observations from the Jicamarca Radio Observatory, located in Lima, Peru. The chosen classification process utilizes a supervised learning algorithm (Expectation-Maximization) to generate a probability distribution function (Gaussian Mixture Model) for each plasma instability based on certain measurable criterion. This paper outlines the training and classification process with the resulting cross validation performance subsequently reported. Results demonstrate the effectiveness of the chosen classifier because of the high cross validation and minimal misclassifications of the events. Key Points Cognitive radar is the future of radar systems The first step of the cognitive process is to classify returns Classification process results in desirable cross validations

    Original languageEnglish (US)
    Pages (from-to)229-237
    Number of pages9
    JournalRadio Science
    Volume50
    Issue number3
    DOIs
    Publication statusPublished - Mar 1 2015

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    All Science Journal Classification (ASJC) codes

    • Condensed Matter Physics
    • Earth and Planetary Sciences(all)
    • Electrical and Electronic Engineering

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