Real-time passive source localization: a practical linear-correction least-squares approach

By Yiteng Huang, Jacob Benesty, G. Elko, Russell M. Mersereati. IEEE Transactions on Speech and Audio Processing, 2001

500 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/f110bca08551a1049922b084232db89a52d4534e

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In Electrical and Electronic Engineering

In Signal Processing

Citations in the corpus

A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality (2006, methodology): “An improvement to the SI estimator is the LCLS method [ 15 ], which solves the LS cost function in (22) subject to the constraint of (u x − x1)2 +(u y − y1)2 = u R21 ,o r equivalently,”
Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks (2018, methodology): “Some popular parametric methods are based on time-difference-of-arrival (TDOA) [44], the steered-response-power (SRP) [45], multiple signal classi-ﬁcation (MUSIC) [46], and the estimation of signal parameters via rotational invariance technique (ESPRIT) [47].”
Least squares algorithms for time-of-arrival-based mobile location (2004, methodology): “[15] have also demonstrated that the constrained algorithms, namely, the QLCS and LCLS methods, possess negligible biases.”
Optimality analysis of sensor-target localization geometries (2010, background): “However, many localization algorithms are actually designed with unbiasedness in mind and with a goal of achieving the Cramer-Rao lower bound [18].”
Bias Reduction for an Explicit Solution of Source Localization Using TDOA (2012, unknown): “It is often used to assess the mean-square error performance of nonlinear estimator as well when the bias resulted from nonlinearity is small compared to variance.”
Multi-Speaker DOA Estimation Using Deep Convolutional Networks Trained With Noise Signals (2018, methodology): “based approaches such as multiple signal classiﬁcation (MUSIC) [1], [2], ii) time difference of arrival (TDOA) based approaches that use the family of generalized cross correlation (GCC) methods [3], [4], iii) generalizations of the cross-correlation methods such as steered response power with phase”