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Record W2139209052 · doi:10.1109/vetecf.2008.138

Practical Results of Hybrid AOA/TDOA Geo-Location Estimation in CDMA Wireless Networks

2008· article· en· W2139209052 on OpenAlexaff
Ali Broumandan, Tao Lin, John Nielsen, G. Lachapelle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultilaterationAngle of arrivalComputer scienceEstimatorChannel (broadcasting)Time of arrivalCode division multiple accessTelecommunications linkCramér–Rao boundWirelessFDOAReal-time computingElectronic engineeringAlgorithmEstimation theoryTelecommunicationsAcousticsEngineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

This paper describes a hybrid AOA/TODA mobile station (MS) location estimation method based on the CDMA wireless communications signals. The method utilized estimates the angle of arrival (AOA) and time difference of arrival (TDOA) of downlink pilot channel. In this paper, signal parameter estimations including AOA and TDOA, and position estimation challenges in real wireless communications systems are denoted. For position estimation, the mathematical model and its linearized model for a hybrid TDOA/AOA method based on the Taylor series expansion are derived. The performance analysis of the high-resolution MUSIC angle and double delta delay estimators using field measurements from a typical outdoor IS-95 CDMA radio propagation channel are demonstrated. In this paper, practical considerations on the implementation of a standalone positioning system are described. The performance of TDOA and hybrid AOA/TDOA positioning system when the receiver has access to minimum LOS signals are compared.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.786
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.246
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2008
Admission routes1
Has abstractyes

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