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Exact and Large Sample Maximum Likelihood Techniques for Parameter Estimation and Detection in Array Processing

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Radar Array Processing

Part of the book series: Springer Series in Information Sciences ((SSINF,volume 25))

Abstract

Sensor array signal processing deals with the problem of extracting information from a collection of measurements obtained from sensors distributed in space. The number of signals present is assumed to be finite, and each signal is parameterized by a finite number of parameters. Based on measurements of the array output, the objective is to estimate the signals and their parameters. This research area has attracted considerable interest for several years. A vast number of algorithms has appeared in the literature for estimating unknown signal parameters from the measured output of a sensor array.

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Authors
  1. B. Ottersten
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  2. M. Viberg
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  3. P. Stoica
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  4. A. Nehorai
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Editor information

Editors and Affiliations

  1. Communications Research Laboratory, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada

    Simon Haykin  & John Litva  & 

  2. Royal Signals and Radar Establishment, St. Andrew’s Road, Malvern, Worcs., WR14 3PS, UK

    Terence J. Shepherd

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Ottersten, B., Viberg, M., Stoica, P., Nehorai, A. (1993). Exact and Large Sample Maximum Likelihood Techniques for Parameter Estimation and Detection in Array Processing. In: Haykin, S., Litva, J., Shepherd, T.J. (eds) Radar Array Processing. Springer Series in Information Sciences, vol 25. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77347-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-77347-1_4

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