Improving TDOA Radar Performance in Jammed Areas through Neural Network-Based Signal Processing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F24%3A00558950" target="_blank" >RIV/60162694:G43__/24:00558950 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26220/23:PU148791
Result on the web
<a href="http://www.mdpi.com/journal/sensors" target="_blank" >http://www.mdpi.com/journal/sensors</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/s23062889" target="_blank" >10.3390/s23062889</a>
Alternative languages
Result language
angličtina
Original language name
Improving TDOA Radar Performance in Jammed Areas through Neural Network-Based Signal Processing
Original language description
This paper presents a method for estimating the position of a target under jammed conditions using the Time Difference of Arrival (TDOA) method. The algorithm utilizes a deep neural network to overcome the challenges posed by the jammed conditions. The simulations and results indicate that the presented method is more accurate and efficient than the traditional TDOA methods.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
SENSORS
ISSN
1424-8220
e-ISSN
1424-8220
Volume of the periodical
23
Issue of the periodical within the volume
6
Country of publishing house
CH - SWITZERLAND
Number of pages
21
Pages from-to
2889
UT code for WoS article
000958228900001
EID of the result in the Scopus database
2-s2.0-85151203855