Distributed Beams: Concept of Operations for Polarimetric Rotating Phased Array Radar

Schvartzman, David; Torres, Sebastián; Yu, Tian-You

doi:10.1109/tgrs.2020.3047090

Cited by 20 publications

(11 citation statements)

References 31 publications

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“…From this figure, the SCA algorithm explores higher dimensional solution spaces through amplitudes in sine and cosine functions. When the amplitude is between [−2,−1] or [1,2], the algorithm is in the detection stage [28]. When the amplitude is between [−1,1], the algorithm is in the mining stage.…”

Section: Hsca With Dynamic Inertia Weight and Adaptive Strategiesmentioning

confidence: 99%

“…Especially, as the core part of the radar system, the normal working state of transceiver has a direct impact on system performance and data accuracy. Firstly, the radar system relies on the coordinated work of key components to detect targets and obtain data [2]. If any of the components malfunctions, it may lead to a decrease in radar performance, affecting the accuracy and * Author to whom any correspondence should be addressed.…”

Section: Introductionmentioning

confidence: 99%

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An optimized sparse deep belief network with momentum factor for fault diagnosis of radar transceivers

Shi,

Li,

Chen

2024

Meas. Sci. Technol.

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Transceiver is a crucial component of radar system that allows for the regulation of signal phase and amplitude as well as the amplification of both transmitted and received signals. Its operational efficiency has a significant impact on the whole dependability of the radar system. To ensure the safe and reliable operation of the radar system, an optimized sparse deep belief network with momentum factor is developed to diagnose potential faults of radar transceivers. Firstly, a momentum term is added into the parameter update to enhance the anti-oscillation ability of model parameters in training, while a sparse regular term is integrated into the deep belief network to prevent the model from overfitting. Secondly, to automatically configure the model hyper-parameters, a hybrid sine cosine algorithm with dynamic inertia weight and adaptive strategies is proposed. Thus, an effective diagnostic model named HSCA-MS-DBN is formed by combining sparse deep belief network with momentum factor and hybrid sine cosine algorithm. The efficiency of the proposed HSCA-MS-DBN model is confirmed using an actual-world radar transceiver dataset, and the findings from experiments reveal that this model surpasses multiple prominent intelligent models.

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Section: Hsca With Dynamic Inertia Weight and Adaptive Strategiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An optimized sparse deep belief network with momentum factor for fault diagnosis of radar transceivers

Shi,

Li,

Chen

2024

Meas. Sci. Technol.

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“…It realizes the sharing of data resources by controlling the server. Establish a virtual network on the Internet [17][18]. The system is mainly composed of client and server.…”

Section: Distributed Remote Processing Technologymentioning

confidence: 99%

Development of Distributed Remote Processing System Based on Net Remoting Technology

2022

DPS

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With the development of network technology, multimedia teaching has become an indispensable part of today's education, and remting is also a new type of remote processing server. The system is designed and implemented with java development framework and JS architecture. This topic mainly introduces the function modules such as management of simulation interactive single machine training center, database management and transaction logic engine based on net platform, and analyzes and explains them respectively. At the same time, the front-end page is designed and built in detail, including the scheme of web page layout and data access control and the application of related technologies. After that, this paper tests the operation and processing of the distributed remote processing system. The test results show that the IP address information is sent to the client through the serial port for interactive operation. At the same time, it can also receive the return command from the terminal device to support the normal 5-10S time control of the remote processing, and complete the analysis and test of the performance and function.

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“…Furthermore, digital PAR offers maximum flexibility in scanning strategies. It can perform different scanning patterns, including those transmitting "pencil" beams, spoiled beams, and/or multiple beams in different directions [3]. Digital beamforming (DBF) is a unique capability of PAR, which is accomplished by transmitting a spoiled beam and simultaneously receiving multiple narrow (i.e., pencil) beams within the transmit envelope.…”

Section: Introductionmentioning

confidence: 99%

Fast Adaptive Beamforming for Weather Observations with Convolutional Neural Networks

Kim,

Schvartzman,

et al. 2023

Remote Sensing

Self Cite

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Polarimetric phased array radar (PAR) can achieve high temporal resolutions for improved meteorological observations with digital beamforming (DBF). The Fourier method performs DBF deterministically, and produces antenna radiation patterns with fixed sidelobe levels and angular resolution by pre-computing the beamforming weights based on the geometry of receivers. In contrast, the Capon method performs DBF adaptively in response to the changing environment by computing the beamforming weights from the received signals at multiple channels. However, it becomes computationally expensive as the number of receivers grows. This paper presents computationally efficient adaptive beamforming with an application of convolutional neural networks, named ABCNN. ABCNN is trained with the phase and amplitude of complex-valued time-series IQ signals and the Capon beamforming weights as input and output. ABCNN is tested and evaluated using simulated time-series data from both point targets and weather scatterers for a planar of fully digital PAR architecture. The preliminary results show that ABCNN lowers computation time by a factor of three, compared to the Capon method, for a phased array antenna with 1024 elements, while mitigating the contamination from sidelobes by placing nulls at the location of the clutter. Furthermore, ABCNN produces antenna patterns similar to those from the Capon method, which shows that it has successfully learned the data.

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Distributed Beams: Concept of Operations for Polarimetric Rotating Phased Array Radar

Cited by 20 publications

References 31 publications

An optimized sparse deep belief network with momentum factor for fault diagnosis of radar transceivers

An optimized sparse deep belief network with momentum factor for fault diagnosis of radar transceivers

Development of Distributed Remote Processing System Based on Net Remoting Technology

Fast Adaptive Beamforming for Weather Observations with Convolutional Neural Networks

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