TY - JOUR
T1 - Robust Estimation of Insect Morphological Parameters for Entomological Radar Using Multifrequency Echo Intensity- Independent Estimators
AU - Wang, Rui
AU - Wang, Jiangtao
AU - Li, Weidong
AU - Li, Muyang
AU - Zhang, Fan
AU - Hu, Cheng
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2024
Y1 - 2024
N2 - Insect morphological parameters, including mass and length, are crucial for species identification. Entomological radar can estimate morphological parameters by establishing mappings from insect radar cross section (RCS) estimators to them. Current high-accuracy methods relying on absolute RCS estimators are sensitive to echo intensity. When applied to radars without angle measurement capability, these methods may underestimate morphological parameters. This underestimation arises from the inability of such radars to compensate for reduced echo intensity caused by insects deviating from the beam center. A method using single-frequency echo intensity-independent estimators (EIIEs) was attempted; however, it could only estimate the mass of insects below 200 mg with limited accuracy. This article explores the use of multifrequency EIIEs (MFEIIEs) to enhance the estimation of insect mass and length. Based on the multifrequency scattering dataset for 159 insects measured in an anechoic chamber, the insect multifrequency scattering matrix (SM) was studied. The study revealed that four EIIEs, including the amplitude ratio and phase difference of SM eigenvalues, and two relative RCS features related to the shape of the insect polarization pattern, were correlated with insect mass and length with varied correlations with frequency. Subsequently, morphological parameter estimation was achieved by establishing the mappings from MFEIIEs to mass and length using a random forest algorithm. The presented dataset demonstrated that this method was suitable for insects below 1000 mg. Finally, the method's effectiveness and robustness were demonstrated through field measurements on 160 insects, which yielded mean relative estimation errors of 21.82% for mass and 13.18% for length.
AB - Insect morphological parameters, including mass and length, are crucial for species identification. Entomological radar can estimate morphological parameters by establishing mappings from insect radar cross section (RCS) estimators to them. Current high-accuracy methods relying on absolute RCS estimators are sensitive to echo intensity. When applied to radars without angle measurement capability, these methods may underestimate morphological parameters. This underestimation arises from the inability of such radars to compensate for reduced echo intensity caused by insects deviating from the beam center. A method using single-frequency echo intensity-independent estimators (EIIEs) was attempted; however, it could only estimate the mass of insects below 200 mg with limited accuracy. This article explores the use of multifrequency EIIEs (MFEIIEs) to enhance the estimation of insect mass and length. Based on the multifrequency scattering dataset for 159 insects measured in an anechoic chamber, the insect multifrequency scattering matrix (SM) was studied. The study revealed that four EIIEs, including the amplitude ratio and phase difference of SM eigenvalues, and two relative RCS features related to the shape of the insect polarization pattern, were correlated with insect mass and length with varied correlations with frequency. Subsequently, morphological parameter estimation was achieved by establishing the mappings from MFEIIEs to mass and length using a random forest algorithm. The presented dataset demonstrated that this method was suitable for insects below 1000 mg. Finally, the method's effectiveness and robustness were demonstrated through field measurements on 160 insects, which yielded mean relative estimation errors of 21.82% for mass and 13.18% for length.
KW - Echo intensity-independent estimator (EIIE)
KW - entomological radar
KW - insect
KW - morphological parameter estimation
KW - radar cross section (RCS)
UR - http://www.scopus.com/inward/record.url?scp=85197527124&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2024.3420899
DO - 10.1109/TGRS.2024.3420899
M3 - Article
AN - SCOPUS:85197527124
SN - 0196-2892
VL - 62
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
M1 - 5109115
ER -