Evidence map›Paper›PMID 35459002›Full record

ArticleSensors (Basel, Switzerland)2022

RSS/TDoA-Based Source Localization in Microwave UWB Sensors Networks Using Two Anchor Nodes.

Sergei Ivanov, Vladimir Kuptsov, Vladimir Badenko, Alexander Fedotov

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Sergei IvanovInstitute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 Saint Petersburg, Russia.ORCID 0000-0002-2882-0380
Vladimir KuptsovInstitute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 Saint Petersburg, Russia.ORCID 0000-0001-8594-9423
Vladimir BadenkoInstitute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 Saint Petersburg, Russia.ORCID 0000-0002-3054-1786
Alexander FedotovInstitute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 Saint Petersburg, Russia.ORCID 0000-0002-7511-8076

Funding

RFBR 19-29-06034
6 · The paper itself

Abstract

The manuscript presents an algorithm for the optimal estimation of the amplitude and propagation delay time of an ultra-wideband radio signal, in systems for the passive location of fixed targets based on the hybrid RSS/TDoA method in two-dimensional space with two base stations. The optimal estimate is based on the Bayesian strategy of maximum a posteriori probability density, taking into account a priori data on the statistical properties of the Line of Sight radio channel during Gaussian monocycle propagation. The Bayesian Cramer-Rao lower bound (BCRLB) of the delay time and the amplitude estimates for a time-discrete signal are calculated, and the resulting parameter estimate is compared with BCRLB. An algorithm has been developed for optimal estimation of distances from the radiation source to base stations, based on the results of the measurements of the amplitude and the propagation delay time of the UWB radio signal. The calculation of the statistical characteristics of the obtained estimate is carried out, and the functional dependence of the characteristics on various parameters is analyzed.

Indexed as

localizationmaximum likelihood (ML) estimatorreceived signal strength (RSS)time difference of arrival (TDOA)UWB Networks

Identifiers

PMID35459002
PMCPMC9031247

What OpenQuestion holds

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Registered trials

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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.