Zobrazeno 1 - 10
of 1 347
pro vyhledávání: '"radar network"'
Autor:
Ginaldi Ari Nugroho, Halimurrahman, Asif Awaludin, Ibnu Fathrio, Nurjanna Joko Trilaksono, Edy Maryadi, Tiin Sinatra, Findy Renggono, Didi Satiadi, Erwin Makmur, Agie Wandala Putra, Nani Cholianawati, Asri Indrawati, Tesalonika Angela Putri Madethen, Ratih Indri Hapsari
Publikováno v:
Geoenvironmental Disasters, Vol 11, Iss 1, Pp 1-19 (2024)
Abstract Background This study presents a 4-year (January 2019–April 2023) X-band radar network-based bow echo observation over Great Bandung Indonesia. This study provides insight into the temporal and spatial variability of bow echo distribution
Externí odkaz:
https://doaj.org/article/69a266ca1dee4a4294443fa58842f06d
A Track Initiation Method for FM-based Passive Radar Network Based on Multiple Elementary Hypotheses
Publikováno v:
Leida xuebao, Vol 13, Iss 3, Pp 601-612 (2024)
Passive radars based on FM radio signals have low detection probability, high false alarm rates and poor accuracy, presenting considerable challenges to target tracking in radar networks. Moreover, a high false alarm rate increases the computational
Externí odkaz:
https://doaj.org/article/6887bb53d8944bed8b710ab609530ea8
Autor:
Carlo Noviello, Salvatore Maresca, Gianluca Gennarelli, Antonio Malacarne, Filippo Scotti, Paolo Ghelfi, Francesco Soldovieri, Ilaria Catapano, Rosa Scapaticci
Publikováno v:
Remote Sensing, Vol 16, Iss 21, p 3940 (2024)
This paper deals with the imaging problem from data collected by means of a microwave photonics-based distributed radar network. The radar network is leveraged on a centralized architecture, which is composed of one central unit (CU) and two transmit
Externí odkaz:
https://doaj.org/article/0cf9ad5e8d5f4456803a7998e4c51a7c
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 45, Iss 6, Pp 42-46 (2023)
In this paper, the key technologies of multi-radar network and cooperative detection are studied in order to meet the urgent needs of radar network operations in the future strong countermeasure environment. Firstly, the operational capability requir
Externí odkaz:
https://doaj.org/article/da23ee47e54a4cfb863a7b7a929d50be
Publikováno v:
Remote Sensing, Vol 16, Iss 18, p 3490 (2024)
In this article, a mission planning and trajectory optimization scheme in unmanned aerial vehicle (UAV) swarm for track deception against radar networks is proposed. The core of this scheme is to formulate the track deception problem as a model with
Externí odkaz:
https://doaj.org/article/7bd9608081b7460a8e08ebe5b2e09219
Publikováno v:
Leida xuebao, Vol 12, Iss 3, Pp 616-628 (2023)
In this study, a real-time dwell scheduling algorithm based on pulse interleaving is proposed for a distributed radar network system. A time pointer vector is introduced to indicate the moment when the dwell task with the highest synthetic priority s
Externí odkaz:
https://doaj.org/article/efd55358d9364bb08f7a8058cebfabbf
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 4, Pp 2165-2175 (2023)
To achieve low probability of intercept (LPI) in radar networks for multiple target detection, it is necessary to find the optimal assignment of distributed radars to targets. The multi-radar to multi-target assignment (MRMTA) problem aims to find th
Externí odkaz:
https://doaj.org/article/c40a8a52be584c27b5e74a27807c6eee
Publikováno v:
Leida xuebao, Vol 11, Iss 5, Pp 778-793 (2022)
This paper investigates the joint optimization problem of transmit resources and trajectory planning for target tracking in airborne radar networks. First, the analytical expression for the Bayesian Cramér-Rao Lower Bound (BCRLB) with the variables
Externí odkaz:
https://doaj.org/article/5aa4e5dfbdb84b0b92c4281c236befda
Publikováno v:
Remote Sensing, Vol 16, Iss 1, p 198 (2024)
The performance of a high-frequency (HF) radar network situated within the Pearl River Estuary from 17 July to 13 August 2022 is described via a comparison with seven acoustic Doppler current profilers (ADCPs). The radar network consists of six OSMAR
Externí odkaz:
https://doaj.org/article/99c6104abb654b039bfa0fd78488f6e7
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