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Santosh, Sandeep
- A Review on Multiple Emitter Location and Signal Parameter Estimation
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Authors
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1 Department of Electronics and Communication, NIT Kurukshetra, Haryana-136119, IN
1 Department of Electronics and Communication, NIT Kurukshetra, Haryana-136119, IN
Source
International Journal of Engineering Research, Vol 2, No 3 (2013), Pagination: 239-244Abstract
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.Full Text
- A Review on ESPRIT-Estimation of Signal Parameters Via Rotational Invariance Techniques
Abstract Views :163 |
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Authors
Affiliations
1 Department of Electronics and Communication, NIT Kurukshetra, Haryana-136119, IN
1 Department of Electronics and Communication, NIT Kurukshetra, Haryana-136119, IN
Source
International Journal of Engineering Research, Vol 2, No 3 (2013), Pagination: 245-254Abstract
High-resolution signal parameter estimation is a problem of significance in many signal processing applications. Such applications include direction-of-arrival (DOA) estimation, system identification, and time series analysis. A novel approach to the genera! Problem of signal parameter estimation is described. Although discussed in the context of direction-of-arrival estimation, FSPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise. It exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a rotational invariance structure. The technique, when applicable, mani-fests significant performance and computational advantages over previous algorithms such as MEM, Capon's MLM, and Ml SIC.Keywords
DOA, FSPRIT, MEM, MLM.Full Text