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Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

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Snapshot-deficient active target localization in beam-time domain using multi-frequency expectation-maximization

He Wang¹, Ting Zhang¹, Lei Cheng¹

¹College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China.

The Journal of the Acoustical Society of America

|March 1, 2023

Summary

This summary is machine-generated.

This study introduces a novel 2D expectation-maximization-based vertical-time-record (EMVTR) method for robust active target localization. EMVTR effectively addresses snapshot deficiency, improving accuracy in challenging scenarios.

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Area of Science:

Signal Processing
Array Signal Processing
Target Localization

Background:

2D active target localization faces challenges in snapshot-deficient scenarios due to high sidelobe levels.
Traditional adaptive methods degrade in performance without sufficient snapshots for covariance matrix estimation.

Purpose of the Study:

To develop a robust 2D active localization approach for snapshot-deficient scenarios.
To enhance localization accuracy by compensating for limited data snapshots.

Main Methods:

Proposed a 2D expectation-maximization-based vertical-time-record (EMVTR) approach.
Reconstructed the covariance matrix using estimated hyperparameters (signal powers, noise variance).
Utilized short-time Fourier transform to reduce echo temporal correlation for beam-time localization.

Main Results:

EMVTR demonstrated robustness and effectiveness in snapshot-deficient active localization.
The multi-frequency EMVTR improved localization of weak echoes.
Validated through simulations and tank experiments with single and multiple targets.

Conclusions:

The proposed EMVTR approach offers a robust solution for 2D active localization in snapshot-deficient conditions.
EMVTR successfully compensates for data limitations, enabling high-resolution target identification.