Evidence map›Paper›PMID 29690571›Full record

ArticleSensors (Basel, Switzerland)2018

Nonlinear Blind Compensation for Array Signal Processing Application.

Jialu Huang, Hong Ma, Jiang Jin, Hua Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. 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.

Jialu HuangSchool of Electronic Information and Communications, Huazhong University of Science & Technology, 1037 Luoyu Road, Wuhan 430074, China. huangjialu1987@126.com.ORCID 0000-0003-3071-8593
Hong MaSchool of Electronic Information and Communications, Huazhong University of Science & Technology, 1037 Luoyu Road, Wuhan 430074, China. mahong@hust.edu.cn.
Jiang JinSchool of Electronic Information and Communications, Huazhong University of Science & Technology, 1037 Luoyu Road, Wuhan 430074, China. jinjiang@hust.edu.cn.
Hua ZhangSchool of Electronic Information and Communications, Huazhong University of Science & Technology, 1037 Luoyu Road, Wuhan 430074, China. zhanghua@hust.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers.

Indexed as

array receiverarray signal processingnonlinear blind compensation algorithmspurious-free dynamic rangetwo-dimensional direction-of-arrival

Identifiers

PMID29690571
PMCPMC5949052

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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.