Multiple emitter location and signal parameter estimation
1986/03/01 by R. Schmidt, René Schmidt · 14,338 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Algorithm #Angle of arrival #Animal Vocal Communication and Behavior #Antenna (radio) #Artificial intelligence #Beamforming #Common emitter #Computer science #Covariance matrix #Direction of arrival #Direction-of-Arrival Estimation Techniques #Electronic engineering #Estimator #Mathematics #Principle of maximum entropy #Speech and Audio Processing #Statistics #Telecommunications
paper · doi:10.1109/tap.1986.1143830
published in IEEE Transactions on Antennas and Propagation 34(3), 276-280 (IEEE Antennas & Propagation Society)
openalex publication_date 1986/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
Abstract
Processing the signals received on an array of sensors for the location of the emitter is of great enough interest to have been treated under many special case assumptions. The general problem considers sensors with arbitrary locations and arbitrary directional characteristics (gain/phase/polarization) in a noise/interference environment of arbitrary covariance matrix. This report is concerned first with the multiple emitter aspect of this problem and second with the generality of solution. A description is given of the multiple signal classification (MUSIC) algorithm, which provides asymptotically unbiased estimates of 1) number of incident wavefronts present; 2) directions of arrival (DOA) (or emitter locations); 3) strengths and cross correlations among the incident waveforms; 4) noise/interference strength. Examples and comparisons with methods based on maximum likelihood (ML) and maximum entropy (ME), as well as conventional beamforming are included. An example of its use as a multiple frequency estimator operating on time series is included.
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- A Survey of Latest Wi-Fi Assisted Indoor Positioning on Different Principles. [europepmc]
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