Comprehensive analysis of polarimetric radar cross-section parameters for insect body width and length estimation

Li, Weidong; Hu, Cheng; Kong, Shaoyang; Zhang, Fan

doi:10.1007/s11432-020-3010-6

Cited by 16 publications

(7 citation statements)

References 25 publications

(39 reference statements)

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“…Weidong Li, Cheng Hu * , Senior Member, IEEE, Rui Wang, Muyang Li, Fan Zhang, Jiangtao Wang E of the radar properties of insects showed that use of these techniques can improve the accuracy of orientation measurements and mass estimates, enable body-length estimation, and discriminate between 'parallel' (PA) and 'perpendicular' (PE) insects (see below) [19][20][21] [22].…”

Section: Influence Of Non-horizontal Orientation On Measurement Of In...mentioning

confidence: 99%

Influence of Nonhorizontal Orientation on Measurement of Insect Biological Parameters With Entomological Radar

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Up till now, measurement of the biological parameters of insects traversing the beam of an entomological radar has been based on the assumption that the insects maintain a horizontal flight attitude. However, recent studies have revealed that some migrating insects fly with their bodies pitched upwards. This paper analyzes the influence of non-horizontal orientation (i.e. pitch and roll angles) on measurements of insect biological parameters with an entomological radar. The scattering matrices (SMs) of 15 insect specimens have been measured at different pitch and roll angles with a purpose-designed multi-aspect fully polarimetric laboratory rig. It is found that pitch angle has little influence on the discrimination of 'parallel" and "perpendicular" insects, but it affects the measurement accuracy of orientation and estimation of mass and body length. The roll angle has little influence on the insect class discrimination, and the measurement of orientation and body length, and slightly affects the accuracy of the mass estimation. The influence of a general combination of pitch and roll angles is approximate the linear superposition of the influence of pitch angle and roll angle.

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Section: Influence Of Non-horizontal Orientation On Measurement Of In...mentioning

confidence: 99%

Influence of Nonhorizontal Orientation on Measurement of Insect Biological Parameters With Entomological Radar

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…IoU = TP/(TP + FP + FN) (10) where TP (Ture Positive) and FN (False Negative) represent the number of positive pixels correctly classified and incorrectly classified respectively, and FP (False Positive) is the number of negative pixels classified incorrectly. For a segmentation task with a total of k + 1 classes (from L 0 to L k including background, in our task, k = 2), we assume that p ij is the number of pixels of class i inferred to belong to class j.…”

Section: Evaluation and Experimental Settingsmentioning

confidence: 99%

“…As an effective tool in studying animal migration patterns, they play an increasingly important role in protecting endangered species [9]. Insect radar can obtain the fine physical characteristics of flying animals [10] and is widely used in aerial biological monitoring. However, weather radar covers a wider area and can also effectively receive biological echoes in the scanning area, including birds [11], bats [12], and insects [13], so as to provide a reasonable explanation for a series of migration ecological problems [14].…”

Section: Introductionmentioning

confidence: 99%

Animal Migration Patterns Extraction Based on Atrous-Gated CNN Deep Learning Model

Wang

Cui

et al. 2021

Remote Sensing

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Weather radar data can capture large-scale bird migration information, helping solve a series of migratory ecological problems. However, extracting and identifying bird information from weather radar data remains one of the challenges of radar aeroecology. In recent years, deep learning was applied to the field of radar data processing and proved to be an effective strategy. This paper describes a deep learning method for extracting biological target echoes from weather radar images. This model uses a two-stream CNN (Atrous-Gated CNN) architecture to generate fine-scale predictions by combining the key modules such as squeeze-and-excitation (SE), and atrous spatial pyramid pooling (ASPP). The SE block can enhance the attention on the feature map, while ASPP block can expand the receptive field, helping the network understand the global shape information. The experiments show that in the typical historical data of China next generation weather radar (CINRAD), the precision of the network in identifying biological targets reaches up to 99.6%. Our network can cope with complex weather conditions, realizing long-term and automated monitoring of weather radar data to extract biological target information and provide feasible technical support for bird migration research.

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“…The fully polarized entomological radar simultaneously transmits two polarized and waveform orthogonal signals, and obtains the target scattering matrix (SM) through the received H and V polarization echoes [11,12]. The SM contains all the information of the target under the current radar perspective, which can be used to calculate the orientation, mass and body length of insects [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Polarization Measurement Errors on the Parameter and Characteristics Measurement of the Fully Polarized Entomological Radar

Li,

Yu,

Wang

et al. 2024

Remote Sensing

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Measuring the orientation, mass and body length of migratory insects through entomological radar is crucial for early warnings of migratory pests. The fully polarized entomological radar is an efficient device for observing migratory insects by calculating insect parameters through the scattering matrix obtained from the target. However, the measured target scattering matrix will be affected by system polarization measurement errors, leading to errors in insect parameter calculation, while the related analysis is currently relatively limited. Therefore, the scattering matrix measurement process is modeled, followed by an analysis of the effects of different errors on orientation, mass and body length estimation. The influence of polarization measurement errors on insect scattering characteristics is also analyzed. The results present that for fixed polarization measurement errors, the measurement errors of insect orientation, mass and body length will vary with insect orientation in specific patterns, and the distribution of measured insect parameters will be drastically distorted compared to the true parameter distribution. In addition, polarization measurement errors could seriously disrupt the reciprocity and bilateral symmetry of the measured insect scattering matrix. These analyses and conclusions provide a good basis for eliminating the effects of polarization measurement errors and improving the accuracy of insect parameter measurement.

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Comprehensive analysis of polarimetric radar cross-section parameters for insect body width and length estimation

Abstract: Insect flight speed estimation analysis based on a full-polarization radar SCIENCE CHINA Information Sciences 61, 109306 (2018); Estimation of the power flux supplied by an electric arc to Ag-SnO 2 electrodes based on cross-section observations of the melted zone

Cited by 16 publications

References 25 publications

Influence of Nonhorizontal Orientation on Measurement of Insect Biological Parameters With Entomological Radar

Influence of Nonhorizontal Orientation on Measurement of Insect Biological Parameters With Entomological Radar

Animal Migration Patterns Extraction Based on Atrous-Gated CNN Deep Learning Model

Analysis of the Influence of Polarization Measurement Errors on the Parameter and Characteristics Measurement of the Fully Polarized Entomological Radar

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