Adaptive detection of distributed target in the presence of signal mismatch in compound Gaussian clutter

Wang, Zeyu; Li, Gang; Li, Ming

doi:10.1016/j.dsp.2020.102755

Digital Signal Processing

2020

DOI: 10.1016/j.dsp.2020.102755

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Adaptive detection of distributed target in the presence of signal mismatch in compound Gaussian clutter

Zeyu Wang

Gang Li

Ming Li

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Cited by 8 publications

(1 citation statement)

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“…This section selects two-level WSN. Since PVAs are designed for a permanent operation in complex and harsh environments, it is crucial to ensure the reliability of sensor nodes' communication[18][19][20][21]. (II) Data monitoring center display.…”

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confidence: 99%

Application of Wireless Sensor Network Technology Using Intelligent Algorithm in Mismatch Detection of Photovoltaic Power Generation

Xie

Chen

2022

Wireless Communications and Mobile Computing

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The paper was aimed at ensuring the stable operation of the photovoltaic power generation system (PVPGS) and improving the accuracy of automatic mismatch detection. Consequently, this paper presents a PVPGS-oriented mismatch detection system based on wireless sensing technology (WSN). Firstly, the photovoltaic array (PVA) is constructed using a microcontroller, power management chip, nRF24L01, temperature sensor, voltage, and current sensor. Then, a fault detection and localization (FDL) scheme based on the Hampel algorithm is optimized, and Matlab/Simulink implements the PVA simulation model. Finally, several typical mismatch faults are simulated to verify the feasibility of the proposed FDL scheme using the measured voltage and current data. The empirical findings corroborate that the proposed FDL scheme can automatically and regularly collect photovoltaic (PV) electrical characteristic data and quickly and accurately identify and position a mismatch. In the case of a PVA open-circuit fault, the output current loss of the PVA is equal to the sum of the current of the open-circuit fault string in the array during normal operation. When the PVA is short-circuited, the PVA output voltage loss equals the sum of the output voltages of the faulty components in the most serious fault string under normal operation. Overall, the classification accuracy of the proposed FDL scheme is 97.556%. Lastly, the experiment reveals that the classification accuracy of the proposed FDL scheme is 100% for array aging, shadow, and the open circuit. Therefore, the research proposal has a good application prospect.

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Application of Wireless Sensor Network Technology Using Intelligent Algorithm in Mismatch Detection of Photovoltaic Power Generation

Xie

Chen

2022

Wireless Communications and Mobile Computing

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Detection of range-spread targets based on order statistics

Chen

Hou

Chang

et al. 2023

Digital Signal Processing

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Adaptive detectors for mismatched subspace target in clutter with lognormal texture

Guo,

Liu,

Huang

et al. 2024

Digital Signal Processing

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Adaptive detection of distributed target in the presence of signal mismatch in compound Gaussian clutter

Cited by 8 publications

References 43 publications

Application of Wireless Sensor Network Technology Using Intelligent Algorithm in Mismatch Detection of Photovoltaic Power Generation

Application of Wireless Sensor Network Technology Using Intelligent Algorithm in Mismatch Detection of Photovoltaic Power Generation

Detection of range-spread targets based on order statistics

Adaptive detectors for mismatched subspace target in clutter with lognormal texture

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