Maximum-likelihood source localization and unknown sensor location estimation for wideband signals in the near-field

By Joe C. Chen, Ralph E. Hudson, Kung Yao. IEEE Transactions on Signal Processing, 2002

551 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/2ce66b18cfc6a8e7fd46b03e1a93189f6460942b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Henk Wymeersch
2. Deborah Estrin
3. Karim Abed-Meraim
4. Emmanuèle Grosicki
5. Robert C. Williamson
6. Darren B. Ward
7. Eric A. Lehmann
8. Erik G. Larsson

In Signal Processing

1. Karim Abed-Meraim
2. Emmanuèle Grosicki
3. Robert C. Williamson
4. Darren B. Ward
5. Eric A. Lehmann
6. Deborah Estrin
7. Henk Wymeersch
8. Erik G. Larsson

Citations in the corpus

• Particle filtering algorithms for tracking an acoustic source in a reverberant environment (2003, methodology): “It is also stated in [15] that there is no significant performance degradation if the gain is chosen as unity or is modeled by the direct path attenuation only.”
• A weighted linear prediction method for near-field source localization (2002, methodology): “Recently, many localization methods for near-field sources have been already proposed, including the Maximum Likelihood method in [1], [2], [16], the covariance approximation method [13], the 2D-MUSIC method [24], the 3D-MUSIC method [3], the higher order ESPRIT-method [15], [19], the higher order…”
• Best linear unbiased estimator approach for time-of-arrival based localisation (2008, unknown): “156 & T”
• An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, unknown): “In the first stage, the coarse estimation of the positions of the MU and scatterers is derived [232], [248].”
• Entropy-based sensor selection heuristic for target localization (2004, methodology): “For many DOA estimation algorithms like the approximate maximum likelihood (AML) algorithm [4], DOA estimation usually becomes much more uncertain when the candidate sensor is either very near or very far from the target.”
• Direct Localization for Massive MIMO (2016, background): “Some direct localization techniques [21], [22] targeted to mul-a tipath scenarios exist in the literature, but they are not tailored to AOA information and massive arrays.”
• Sensor network-based countersniper system (2004, unknown): “[1].”