Detail publikace

Improving TDOA Radar Performance in Jammed Areas through Neural Network-Based Signal Processing

GÖTTHANS, J. GÖTTHANS, T. NOVÁK, D.

Originální název

Improving TDOA Radar Performance in Jammed Areas through Neural Network-Based Signal Processing

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

TDOA; radar; autoencoder; neural network; deep neural network; jamming; correlation method

Autoři

GÖTTHANS, J.; GÖTTHANS, T.; NOVÁK, D.

Vydáno

23. 3. 2023

Nakladatel

MDPI

Místo

BASEL

ISSN

1424-8220

Periodikum

SENSORS

Ročník

23

Číslo

6

Stát

Švýcarská konfederace

Strany od

1

Strany do

21

Strany počet

21

URL

https://www.mdpi.com/1424-8220/23/6/2889

BibTex

@article{BUT184348,
  author="Jakub {Götthans} and Tomáš {Götthans} and David {Novák}",
  title="Improving TDOA Radar Performance in Jammed Areas through Neural Network-Based Signal Processing",
  journal="SENSORS",
  year="2023",
  volume="23",
  number="6",
  pages="1--21",
  doi="10.3390/s23062889",
  issn="1424-8220",
  url="https://www.mdpi.com/1424-8220/23/6/2889"
}