JOURNAL ARTICLE

Optimal joint azimuth-elevation and signal-array response estimation using parallel factor analysis

Abstract

We consider deterministic joint azimuth-elevation, signal, and array response estimation, and establish a direct link to parallel factor (PARAFAC) analysis, a tool with roots in linear algebra for multi-way arrays. This link affords a powerful identifiability result, plus the opportunity to tap on and extend the available expertise for fitting the PARAFAC model, to derive a deterministic (least squares) joint estimation algorithm, also applicable to multiple-parameter/multiple-invariance ESPRIT subspace fitting problems. These and other issues are demonstrated in pertinent simulation experiments.

Keywords:
Identifiability Azimuth Algorithm Joint (building) Subspace topology Elevation (ballistics) Computer science Signal subspace Least-squares function approximation SIGNAL (programming language) Signal processing Link (geometry) Estimation theory Linear algebra Mathematics Artificial intelligence Statistics Telecommunications Machine learning Engineering

Metrics

13
Cited By
1.43
FWCI (Field Weighted Citation Impact)
15
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Direction-of-Arrival Estimation Techniques
Physical Sciences →  Computer Science →  Signal Processing
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics

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