A Method for Rainfall Detection and Rainfall Intensity Level Retrieval from X-Band Marine Radar Images

Lu, Zhizhong; Sun, Lei; Zhou, Yongcan

doi:10.3390/app11041565

Cited by 17 publications

(8 citation statements)

References 27 publications

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“…Moreover, the model is less time-consuming and has promising application prospects. In addition, the existence of rainfall changes the roughness of the sea surface as well as increases the attenuation of electromagnetic waves, which seriously interferes with the precise detection of targets [ 38 , 39 ]. Therefore, in future work, we will utilize more modality data to design the detection network model that adapted to complex sea environments such as rainfall and typhoons.…”

Section: Discussionmentioning

confidence: 99%

A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes

Duan

Wang

Zhang

et al. 2022

Sensors

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Due to the interaction between floating weak targets and sea clutter in complex marine environments, it is necessary to distinguish targets and sea clutter from different dimensions by designing universal deep learning models. Therefore, in this paper, we introduce the concept of multimodal data fusion from the field of artificial intelligence (AI) to the marine target detection task. Using deep learning methods, a target detection network model based on the multimodal data fusion of radar echoes is proposed. In the paper, according to the characteristics of different modalities data, the temporal LeNet (T-LeNet) network module and time-frequency feature extraction network module are constructed to extract the time domain features, frequency domain features, and time-frequency features from radar sea surface echo signals. To avoid the impact of redundant features between different modalities data on detection performance, a Self-Attention mechanism is introduced to fuse and optimize the features of different dimensions. The experimental results based on the publicly available IPIX radar and CSIR datasets show that the multimodal data fusion of radar echoes can effectively improve the detection performance of marine floating weak targets. The proposed model has a target detection probability of 0.97 when the false alarm probability is 10−3 under the lower signal-to-clutter ratio (SCR) sea state. Compared with the feature-based detector and the detection model based on single-modality data, the new model proposed by us has stronger detection performance and universality under various marine detection environments. Moreover, the transfer learning method is used to train the new model in this paper, which effectively reduces the model training time. This provides the possibility of applying deep learning methods to real-time target detection at sea.

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Section: Discussionmentioning

confidence: 99%

A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes

Duan

Wang

Zhang

et al. 2022

Sensors

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“…Chai et al [204] described a self-siphoning gauge with capacitive measurement of rainfall that was designed for use in the marine environment. Lu et al [205] present a method for interpreting rainfall intensity at sea from ship-borne X-band radar. The use of acoustic methods for recording rain at sea has become an established method and has already been described.…”

Section: Miscellaneous Approaches To Rainfall Recordingmentioning

confidence: 99%

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Dunkerley

2023

Water

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Many design principles for rain gauges that have the capacity to record rainfall intensity have been proposed or developed. These are here grouped into 15 categories, and the abilities and limitations of each are discussed. No standard or optimum method has emerged, despite more than 80 years of effort in the last two centuries, together with prior work from the 17th C onwards. Indeed, new methods continue to be explored for both point-based and area-wide collections of intensity data. Examples include the use of signal attenuation by rain along the tower-to-tower links of cellular phone networks, monitoring the speed of vehicle windscreen wipers, and exploiting the sound or vision from security and traffic-monitoring cameras. Many of these approaches have the potential to provide vastly more observation sites than conventional meteorological stations equipped with rain gauges. Some of these contemporary approaches seek to harness the potential of crowdsourced or citizen-science data. It is hoped that the present overview of methods will provide a guide for those wishing to collect or analyses rainfall intensity data for application in areas such as soil erosion processes, ecohydrology, agrochemical washoff, or urban flash flooding. Because rainfall intensity is one of the key aspects of the hydrologic cycle likely to respond as climate change and variability proceed, the choice of appropriate data collection methods has additional contemporary importance for the monitoring of regional and global precipitation changes.

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“…To reduce the influence of rainfall noise, the zero-pixel percentage (ZPP) method can be used to detect rainfall in radar images, but the detection accuracy is limited, and the selection of the threshold needs to be further studied. Based on the ZPP method, the ratio of zero intensity to echo (RZE) method for rainfall detection was proposed in [11]. The detection threshold is determined by statistical analysis of a large amount of radar data.…”

Section: The Present Issuementioning

confidence: 99%

Advances in Vibroacoustics and Aeroacustics of Marine, Aerospace and Automotive Systems

2022

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This Special Issue highlights the latest enhancements in vibroacoustics and aeroacustics of marine, aerospace, and automotive systems. Topics covered in this Special Issue deal with computational, instrumentation, and data analysis of acoustics and vibrations of aircrafts, satellites, spacecrafts, automotives, trains, ships, etc., ranging from aerodynamically generated noise to engine noise, vibration transmission, sound absorption, acoustic treatments, modelling procedures and vibroacoustic properties of materials. The focus of this Special Issue is related to industrial aspects as dedicated numerical studies, experimental testing campaigns, and optimization problems. Procedures and algorithms useful to reach the abovementioned objectives in the most efficient way are illustrated in the collected papers.

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A Method for Rainfall Detection and Rainfall Intensity Level Retrieval from X-Band Marine Radar Images

Cited by 17 publications

References 27 publications

A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes

A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Advances in Vibroacoustics and Aeroacustics of Marine, Aerospace and Automotive Systems

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