Evidence map›Paper›PMID 39338681›Full record

ArticleSensors (Basel, Switzerland)2024

High-Resolution and Robust One-Bit Direct-of-Arrival Estimation via Reweighted Atomic Norm Estimation.

Rui Li, Jianchao Yang, Zheng Dai, Xingyu Lu, Ke Tan, Weimin Su

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Rui LiSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.ORCID 0009-0008-0241-9127
Jianchao YangSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.
Zheng DaiSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.
Xingyu LuSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.
Ke TanSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.
Weimin SuSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology (NJUST), Nanjing 210094, China.

Funding

China Postdoctoral Science Foundation 2020M681604Jiangsu Province Postdoctoral Science Foundation 2020Z441National Natural Science Foundation of China 62001229National Natural Science Foundation of China 62101260National Natural Science Foundation of China 62101264Natural Science Foundation of Jiangsu Province BK20210334Natural Science Foundation of Jiangsu Province BK20230915
6 · The paper itself

Abstract

In recent years, one-bit quantization has attracted widespread attention in the field of direction-of-arrival (DOA) estimation as a low-cost and low-power solution. Many researchers have proposed various estimation algorithms for one-bit DOA estimation, among which atomic norm minimization algorithms exhibit particularly attractive performance as gridless estimation algorithms. However, current one-bit DOA algorithms with atomic norm minimization typically rely on approximating the trace function, which is not the optimal approximation and introduces errors, along with resolution limitations. To date, there have been few studies on how to enhance resolution under the framework of one-bit DOA estimation. This paper aims to improve the resolution constraints of one-bit DOA estimation. The log-det heuristic is applied to approximate and solve the atomic norm minimization problem. In particular, a reweighted binary atomic norm minimization with noise assumption constraints is proposed to achieve high-resolution and robust one-bit DOA estimation. Finally, the alternating direction method of multipliers algorithm is employed to solve the established optimization problem. Simulations are conducted to demonstrate that the proposed algorithm can effectively enhance the resolution.

Indexed as

atomic norm minimizationdirection-of-arrival estimationone-bit quantization

Identifiers

PMID39338681
PMCPMC11436199

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.