Research Article  Open Access
ChiungShen Ku, PaoChi Chang, YangLang Chang, "Experimental Study of Polarized Radar Scattering from the Tree Canopy at the KaBand", International Journal of Antennas and Propagation, vol. 2019, Article ID 4610713, 10 pages, 2019. https://doi.org/10.1155/2019/4610713
Experimental Study of Polarized Radar Scattering from the Tree Canopy at the KaBand
Abstract
In this study, experimental measurements were carried out to estimate the polarized backscattering coefficient at the Kaband through deciduous and coniferous trees. By utilizing a groundbased scatterometer, the returned signal was obtained in three polarized states at an incident angle ranging from 30 to 80 degrees. The scattering coefficients were estimated from the radar equation for the distributed target under narrow beam approximation. Radiometric calibration was conducted using a metal sphere, and a set of corner reflectors was used as the calibration target to ensure measurement accuracy. Both frequency and angular response of backscattering coefficients with three polarizations were analyzed for the cases of deciduous (banyan) and coniferous (pine) trees. The results indicated that the dynamic range for HV polarization is higher than that of HH and VV polarizations for both banyan and pine trees. Comparatively, the dynamic range for the pine tree is larger than that of the banyan tree.
1. Introduction
Microwave propagation, attenuation, and scattering in vegetation are important in the fields of communication [1, 2] and remote sensing [3–7]. Vegetation occupies onethird of the land surface on earth, which plays a key role in the global circulation of carbon and nitrogen and considerably affects the energy and water balance of the biosphere. In electromagnetics, vegetation may be considered as a blockage to obstruct the line of sight between a transmitter and a receiver. In this case, propagating radio waves are forced to go through different paths to the receiver, which leads to signal degradation. The vegetation canopy represents a dynamic and complicated object of investigation in radio wave propagation due to the dimensions of leaves, branches, and trunks being comparable to the wavelengths of radio frequencies.
In the last three decades, extensive research by theoretical modeling and numerical simulations on vegetation such as agricultural plants, grasslands, and forests from the VHF to Kubands has been reported [3–12]. For example, by solving for the singlescattering solution of the radiative transfer equation, physical and dielectric properties of the canopy have been characterized [11]. The numerical Maxwell model of 3D (NMM3D) [12] comprises randomly distributed dielectric cylinders to simulate the electromagnetic behavior of a vegetation canopy. Additionally, different types of measurement systems provide reliable data from the local to global scale. Ulaby et al. [13] applied a groundbased scatterometer at 1.6 GHz with a 40degree incident angle to acquire tree attenuation data. PiSAR [14] is an airborne radar system that provides 4look, 2 m resolution, and polarimetric data at the L band, which demonstrates the capability to display the backscattering coefficient as a function of canopy biomass.
It is clear that the study of scattering and propagation of the vegetation canopy at the Kaband is still limited. As the frequency band is pushed higher, such as in the Kaband, there is existing interest to understand the scattering properties of trees. With the advancement of technology, the effectiveness of the Kaband for radar applications has been demonstrated. Additionally, several Kaband satellite missions and instrument concepts have been proposed or are even under development. In this paper, a set of experimental measurements was conducted at the Kaband using a groundbased scatterometer. A reference measurement was taken in the anechoic chamber, and a conducting sphere and a set of corner reflectors were used as calibration targets to ensure the measurement capabilities of this system. In situ measurements were performed within the categories of deciduous and coniferous trees. The organization of this paper is as follows: Section 2 describes the radar equation for distributed targets to invert the backscattering coefficient. The measurement setup and reference calibration are presented in Section 3. In Section 4, the backscattering coefficient as a function of the frequency and incident angle for deciduous and coniferous trees is discussed. Finally, in Section 5, conclusions and future studies are addressed to close the paper.
2. Formula from Radar Equation for the Backscattering Coefficient
2.1. Radar Equation for the Distribution Target
According to the radar equation, the returned power is related to the measurement system, including transmitted power, transmitting and receiving antenna gains, and the propagation path between the antenna and the target. When distributed targets are illuminated by a radar system, the average returned power for a monostatic system is given by [5, 10]where is the bore sight angle of the transmitting and receiving antenna, is the distance to the illuminated area, is the transmitted power, is the differential radar cross section, and is the antenna gain pattern. If the tile of a surface among observation targets can be neglected, the differential unit of area on the radar scattering plane in Figure 1 is given by
Letting be the radar to target distance at normal incidence, then
Now, equation (1) becomes
2.2. Reference Measurement for Calibration
A reference target can be applied to provide a known radar cross section to obtain the absolute calibration [10]. In this study, a conducting sphere was set as a target to take a reference measurement at normal incidence. The returned power from the sphere is expressed aswhere is the transmitted power for calibration and is the distance from the antenna to the sphere. Under Mie scattering, the RCS of the calibration target can be approximated as in the high frequency range, where is the radius of conducting sphere.
Equation (4) may be normalized by division as in equation (5), yielding the normalized average power aswhere .
2.3. Narrow Beam Approximation
If the RCS does not change significantly over the illuminated patch on the target, equation (1) may be simplified by shifting out from the integral. Additionally, by assuming the constant range R, the scattering coefficient can be expressed aswhere contours of constant gain on the scattering plane can be approximated as an ellipse (Figure 2):
In particular, if we define as the effective antenna beam width, then we may write the expression for the backscattering coefficient as
3. Measurement Setup
Figure 3 shows a simplified block diagram of the coherent radar system. A vector network analyzer, N5245A PNAX, was utilized as a transceiver, and the specification of the vector network analyzer is listed in Table 1. A pair of wideband antennas with 2.9° of 3 dB beam width covering 26.5 GHz to 40 GHz was used as the transmitter and receiver. Additionally, the specifications of the Kaband antenna are shown in Table 2.


3.1. Reference Measurement
In a real system, under nonideal conditions such as polarization crosstalk errors and channel imbalance between the transmitter and receiver, polarimetric calibration is required. We employed three reference targets with known measured scattering matrices for polarimetric calibration. A trihedral and dihedral corner reflector can offer two equations for copolarization, and a 45° rotated dihedral corner reflector provides two equations in crosspolarization. Based on the relationship between the measured and theoretical scattering matrices, the reference targets can be used to solve the calibration matrix. After the calibration matrix has been determined, the scattering matrices of the reference targets can be calibrated. In addition, the scattering matrices of unknown targets can be calibrated. To evaluate the effectiveness of the calibration technique, the amplitude error and phase error are calculated according towhere represents the calibrated scattering matrices of point targets and represents the theoretical scattering matrices of point targets.
Because the polarimetric calibration is primarily concerned with channel imbalance and crosstalk between the transmitter and receiver, it is preferable to take normalization with respect to a reference channel, for example, HH polarization or HV polarization whichever is applicable. As a result, the amplitude error and phase error are within 0.2 dB and 2.5°, respectively, which is regarded acceptable. A detailed calibration procedure followed is given in [15]. As an illustration, a conducting sphere with a 5 inch radius was set as a calibration target and put 1.6 m away from transmitted and receive antennas. The returned powers from 28 GHz to 36 GHz were acquired at a normal incidence. The setup of the measurement is shown in Figure 4(a), and the HH, VV, and HV polarized returned signals after the polarimetric calibration are plotted in Figure 4(b). Very close values of copolarized HH and VV and much lower values of crosspolarized HV were seen, as expected.
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3.2. Outdoor Measurement Sites
Kaband radar measurements were conducted on banyan tree and pine tree canopies, and the measurement scene and two types of trees are shown in Figure 5. A receiver was placed either under the tree canopy or outside it, and for additional assurance, a NLOS with the transmitter was placed on top of a 20 m pole above the ground. The major characteristics including the basal diameter, canopy diameter, and canopy height are illustrated in Table 3. Random samples were collected by moving the receiver. The slant range between the transmitter and the receiver was measured by laser distance in meters. Note that the windinduced Doppler shift can be ignored due to wide bandwidth used in the receiver. To obtain a backscattering coefficient for trees, the measured system was mounted on the top of a 15 m height platform from which the radar had an unobstructed view of selected target trees. The banyan and pine trees were substantially larger than the footprint of the 2.9° of antenna beam width. Target trees were selected where adjacent (ground and tree) scatterers could be conveniently rejected by range gating in the time domain. For each measurement, the ensemble average of two thousand samples was taken to estimate the mean returned power. Then, by utilizing the radar equation, the backscattering coefficient as a function of frequency and incident angle can be calculated.
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4. Results and Discussion
The backscattering coefficients of the banyan tree for HH, HV, and HH polarizations from 30 to 80 degrees of incidence are shown in Figure 6. The dynamic ranges of the backscattering coefficients for HH, HV, and VV were approximately 8.7 dB, 7 dB, and 4.7 dB, respectively. The dynamic ranges of HV polarizations returned close to the levels of VV and HH polarizations for the banyan tree. Among the three polarizations, the HH polarization maintains stronger angular dependence. In general, for higher frequencies, backscattering is marginally stronger for all three polarizations, and the smaller the incidence, the stronger the backscattering. The frequency responses for HV and VV polarizations show bumpy fluctuations in terms of incidence variations, perhaps implicitly indicating higher radar clutter.
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Figure 7 displays the backscattering coefficient of the pine tree for VV, HV, and HH polarizations at an incident angle from 30 to 80 degrees, with a frequency from 28 GHz to 36 GHz. The dynamic ranges of the backscattering coefficients of VV, HV, and HH polarizations were approximately 4.7 dB, 8.7 dB, and 5.5 dB, respectively. The dynamic range of the HV polarized returns was clearly higher than the VV and HH polarizations for the pine tree.
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Comparing the backscattering coefficients for banyan and pine trees, due to the leaf stems of the pine trees constituting a larger portion of the beam area, the HV polarization backscattering is larger for the pine tree than for the banyan tree. Table 4 indicates the dynamic ranges of pine trees and banyan trees from 28 GHz to 36 GHz for VV, HV, and HH polarizations at different angles of incidence.

Figure 8 plots the dynamic range of the backscattering from trees. It shows that the dynamic range in the HV polarized state is higher than in HH and VV states for the pine tree. However, for the banyan tree, the dynamic range of crosspolarization is close to the level of the copolarization.
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Figures 9 and 10 present the angular response of the backscattering coefficient for the banyan tree and pine tree. The results show that the coefficients of VV and HH polarization are at the same level, but the value of HH is slightly higher than that of VV. The HV backscattering is weaker than that of HH and VV.
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The angular patterns of backscattering coefficients in the HH, HV, and VV polarizations are shown in Figure 11 for the banyan tree. The results illustrate the dynamic range of backscattering coefficients in HH polarization varies from 4.3 dB to 7.3 dB, the dynamic range of backscattering coefficients changes from 3.4 dB to 5.3 dB for HV polarization, and the dynamic range of backscattering coefficients in VV polarization changes from 2.4 dB to 6.7 dB.
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Similarly, Figure 12 presents the angular pattern of the backscattering coefficients of the pine tree in three polarized states. The results indicate that the dynamic range changes from 2.8 dB to 4.7 dB in HH polarization, the dynamic range changes from 1.6 dB to 2.9 dB for VV polarization, and the dynamic range for HV polarization varies from 5.4 dB to 6.8 dB, increasing almost 3 dB.
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The detailed values of the dynamic range for the angular response from banyan and pine trees are listed in the Table 5.

5. Conclusions
Backscattering measurements at the Kaband for deciduous and coniferous trees were taken via vegetation monitoring. A coherent groundbased scatterometer was utilized to record the backscattering signal within HH, VV, and HV polarizations from 28 GHz to 36 GHz at an angle of incidence from 30 to 80 degrees. A reference measurement was taken using a metal sphere at normal incidence in an anechoic chamber to ensure the measurement capabilities of this system were satisfactory. Both the frequency and angle corresponding to the backscattering coefficients were analyzed and discussed.
At the Kaband, the wavelength (1.1 cm∼0.7 cm) is much smaller than most leaves and branches. For the banyan tree, the leaf stems constitute a very small percentage of the visible surface and can be reasonably ignored. In the pine tree, the leaf stems constitute a large percentage of the visible surface, and contributions from multiple scattering reflections are larger than those in banyan trees. For example, at a 30 GHz angle of incidence, the pine tree backscattering is −13.8 dB for VV, −18.7 dB for HV, and −12.9 dB for VV, which are slightly larger than those of the banyan tree at −14.7 dB for VV, −19.2 dB for HV, and −13.2 dB for VV. The factors that affect the properties of backscattering include frequency, polarization, incidence angle, and canopy parameters. The results indicate that crosspolarized returns generally present higher dynamic ranges over the frequency and angular dependencies. By applying characteristics and statistics, the results can be used to identify the category of tree so that the effective propagation constant can be determined.
Data Availability
The experimental data used to support the findings of this study are included within the article.
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this paper.
Acknowledgments
This work was sponsored by the Ministry of Science and Technology, Taiwan, Grant Nos. MOST 1072116M027003, 1082116M027003, and 108A27A.
References
 S. R. Saunders, Antennas and Propagation for Wireless Communication Systems, Wiley, Chichester, UK, 1999.
 J. Goldhirsh and W. J. Vogel, “Mobile satellite system fade statistics for shadowing and multipath from roadside trees at UHF and Lband,” IEEE Transactions on Antennas and Propagation, vol. 37, no. 4, pp. 489–498, 1989. View at: Publisher Site  Google Scholar
 A. Ishimaru, Wave Propagation and Scattering in Random Media, Academic Press, San Francisco, CA, USA, 1978.
 F. T. Ulaby, R. K. Moore, and A. K. Fung, Microwave Remote Sensing: Fundamentals and Radiometry, vol. 1, Artech House, Deham, MA, USA, 1981.
 F. T. Ulaby, R. K. Moore, and A. K. Fung, Microwave Remote Sensing: From Theory to Applications, vol. 2, Artech House, Deham, MA, USA, 1982.
 L. Tsang, J. A. Kong, and R. T. Shin, Theory of Microwave Remote Sensing, John Wiley, New York, NY, USA, 1985.
 F. T. Ulaby, R. K. Moore, and A. K. Fung, Microwave Remote Sensing: From Theory to Applications, vol. 3, Artech House, Deham, MA, USA, 1986.
 A. A. Chukhlantsev, Microwave Radiometry of Vegetation Canopies, Springer, Dordrecht, Netherlands, 2006.
 A. K. Fung and K. S. Chen, Microwave Scattering and Emission Models for Users, Artech House, Norwood, MA, USA, 2010.
 F. T. Ulaby, D. G. Long, W. J. Blackwell et al., Microwave Radar and Radiometric Remote Sensing, University of Michigan Press, Ann Arbor, MI, USA, 2014.
 F. T. Ulaby, K. Sarabandi, K. McDonald, M. Whitt, and M. C. Dobson, “Michigan microwave canopy scattering model,” International Journal of Remote Sensing, vol. 11, no. 7, pp. 1223–1253, 1990. View at: Publisher Site  Google Scholar
 L. Tsang, I.S. Koh, T.H. Liao et al., “Active and passive vegetated surface models with rough surface boundary conditions from NMM3D,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 3, pp. 1698–1709, 2013. View at: Publisher Site  Google Scholar
 F. T. Ulaby, M. W. Whitt, and M. C. Dobson, “Measuring the propagation properties of a forest canopy using a polarimetric scatterometer,” IEEE Transactions on Antennas and Propagation, vol. 38, no. 2, pp. 251–258, 1990. View at: Publisher Site  Google Scholar
 K. Kimura, Y. Yamaguchi, and H. Yamada, “PiSAR image analysis using polarimetric scattering parameters and total power,” in Proceedings of 2003 IEEE International Geoscience and Remote Sensing Symposium, vol. 1, pp. 425–427, Toulouse, France, July 2003. View at: Google Scholar
 M. Satake, T. Umehara, A. Nadai et al., “Development of polarization selective corner reflectors and its experiment for calibration of airborne polarimetric synthetic aperture radar,” in Proceedings of 2001 IEEE International Geoscience and Remote Sensing Symposium, pp. 417–419, Sydney, Australia, July 2001. View at: Google Scholar
Copyright
Copyright © 2019 ChiungShen Ku et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.