European Conference on Antennas and Propagation (EuCAP) (13th. 2019.  Krakow, Poland

García Fernández, María

Las Heras Andrés, Fernando Luis

Álvarez López, Yuri

English

Repositorio Institucional de la Universidad de Oviedo

Antenna measurement and diagnostics processing 
techniques using unmanned aerial vehicles 
 
María García Fernández, Yuri Álvarez López, Fernando Las-Heras Andrés 
Área de Teoría de la Señal y Comunicaciones, Universidad de Oviedo (TSC-UNIOVI), Gijón (Asturias), Spain,  
garciafmaria@uniovi.es, alvarezyuri@uniovi.es, flasheras@uniovi.es 
 
 
Abstract—In-situ antenna measurements using unmanned 
aerial vehicles (UAVs) has become a research topic of great 
interest thanks to recent developments in UAV hardware and 
antenna measurement post-processing techniques for arbitrary 
geometry acquisition domains. Improvements in UAV 
positioning and geo-referring systems have enabled in-situ 
antenna measurements in the near field (NF) region of the 
Antenna Under Test (AUT). These NF measurements can be 
post-processed for antenna diagnostics and for radiation 
pattern evaluation. This contribution focuses on the analysis 
and comparison of post-processing techniques for in-situ 
antenna measurement using amplitude-only information, and 
the impact of the NF measurement domain in the post-processed 
results, namely aperture fields and radiation pattern. Two 
iterative phase retrieval techniques are compared using an 
offset reflector antenna as AUT.  
Index Terms—in-situ antenna measurement, phaseless 
techniques, unmanned aerial vehicles, antenna diagnostics. 
I.  INTRODUCTION 
Unmanned Aerial Vehicles (UAVs)-based applications 
and services have experienced a significant development in 
the last years, contributing to advances in fields such as 
remote sensing, civil engineering, and security and defense. 
The cost reduction of UAV-related electronical devices and 
batteries has definitely contributed to the rapid growth of 
UAV applications [1]. 
In the area of antenna and electromagnetic 
measurements, UAVs have been proved to be of great 
interest for in-situ measurement of the radiated fields [2-4], 
allowing the evaluation of the impact of the environment 
surrounding the antenna (buildings, ground) on its 
performance (radiation pattern, coverage area).  
Current state-of-the-art systems mainly consist of power 
sensors or spectrum analyzers on board UAVs. Most of the 
developed systems are devoted to work in the far field (FF) 
region of the Antenna Under Test (AUT) due to the accuracy 
of the positioning and data geo-referring subsystem. This 
accuracy is usually limited by the performance of Global 
Navigation Satellite Systems (GNSSs), which is 1-2 m in 
best case scenarios. Recently, UAV-based measurement 
systems providing cm-level accuracy have been developed 
[3,4], introducing post-processing techniques capable of 
performing near-field to far-field (NF-FF) transformation or 
antenna diagnostics from measured amplitude-only 
information. The capability of in-situ antenna diagnostics is 
of interest for detecting malfunctioning elements in antenna 
arrays, incorrect antenna tilting, or defects and deformations 
in reflector antennas, avoiding the need of stopping operation 
of the communications system. 
Phaseless antenna measurement techniques have 
received attention in the last years due to the challenges 
presented by measurements at millimeter and sub-millimeter 
wavelengths, where thermal stability and phase errors 
involved in moving transmission lines of the measurement 
system make phase measurements difficult. 
Among the different techniques for phaseless 
measurements, iterative techniques based on the NF 
acquisition at two or more acquisition surfaces are suitable for 
in-situ antenna characterization using UAVs [5,6] as they 
allow using simple, low-cost hardware (e.g. a power detector). 
Besides, computational complexity associated to iterative 
techniques is not a major issue nowadays thanks to the 
advances in computational capabilities of conventional 
computers. However, these techniques are quite sensitive to 
measurement uncertainties and to the initialization (initial 
guess) of the iterative method. As an alternative, holographic 
techniques [7] exhibit greater accuracy than iterative methods, 
although at the expense of increasing hardware complexity. 
In this contribution a review of phaseless iterative 
techniques applied to UAV-based antenna measurement 
systems is presented. The proposed methodology can be used 
for a-priori assessment of the impact of different parameters 
in the performance and accuracy of the developed airborne-
based system [3,4].  
II. POST-PROCESSING TECHNIQUES 
A. Description of the methodology 
In-situ antenna measurement systems mounted on UAVs 
are affected by UAV positioning errors (with respect to the 
pre-defined flight path) that will result in a non-uniform 
acquisition domain [3]. Thus, it is needed to develop and/or 
employ antenna post-processing techniques capable of 
working with arbitrary geometry acquisition domains. In 
particular, iterative techniques based on recovering an 
equivalent currents model of the AUT from NF 
measurements have been proved to be successful when 
working with not only amplitude and phase, but also with 
phaseless data acquired on arbitrary geometry domains [5]. 
NF airborne-based antenna measurement systems require 
the definition of at least two acquisition surfaces (e.g. two 
cylindrical domains [3]), which can be set using waypoints. 
If the AUT is not well characterized, the definition of these 
domains, and thus the UAV flight path, may be inaccurate 
(that is, relevant features of the NF pattern might not be 
measured), requiring a trial-and-error procedure for this task. 
For this reason, enabling the possibility of a-priori 
assessment of the NF grid using an antenna model similar to 
the one to be measured would make this step easier. 
The antenna model can be obtained from computer 
simulation, or from previous measurements conducted in an 
antenna measurement facility. In this contribution, the antenna 
is modelled using an equivalent currents distribution 
calculated from NF measurements, as shown in Fig. 1. These 
equivalent currents allow evaluating the NF at any point, and 
thus, at the NF acquisition grids to be tested. Next, the 
amplitude of the NF evaluated at the acquisition grids is used 
as an input for the iterative phaseless retrieval techniques.  
 
Fig. 1. Scheme of the proposed methodology for the analysis of the 
airborne-based system for in-situ measurement system. 
B. Iterative phase retrieval techniques 
Two iterative phase retrieval techniques are compared, 
both based on the reconstruction of an equivalent magnetic 
currents distribution on the aperture plane of the AUT (which 
corresponds to the aperture fields of the AUT). In the first 
technique, a nonlinear cost function relating the amplitude of 
the measured NF, and the amplitude of the NF radiated by the 
equivalent magnetic currents distribution, both evaluated at 
two acquisition surfaces, is minimized. In the case of 
acquiring |Ex|,|Ey| at two planar domains, the integral equations 
relating Ex, Ey and Mx, My can be decoupled [5], as shown in 
Fig. 2.  
 
Fig. 2. Phase retrieval algorithm based on non-linear cost function 
minimization. 
 
Fig. 3. Phase retrieval algorithm based on an iterative forward-backward 
method (only algorithm for Ex-component retrieval is shown). 
Measured amplitudeInitial guess
Measured amplitude
Estimated 
phase
Complex electric field
Non-linear cost function minimization
=
=
NO
Measured amplitude Initial guess phase
Measured amplitude
Estimated phase
Measured amplitude Estimated phase
Stopping conditions 
reached?
Measured amplitude Estimated phase
Linear cost function minimization
Linear cost function minimization
Initial guess or solution 
from the previous iteration
YES
=
=
Estimated phase
Measured amplitude
The second algorithm, described in Fig. 3, consists on an 
iterative forward-backward procedure (similar to the Iterative 
Fourier Technique [7]) that minimizes a linear cost function 
that uses the measured amplitude and the estimated phase of 
the NF at two acquisition surfaces as input. At each iteration, 
the phase of the NF in one acquisition surface is estimated 
from the equivalent currents reconstructed using the estimated 
NF in the other acquisition surface. This algorithm is less 
computationally expensive than the first one, as it requires the 
minimization of a linear cost function. 
In both cases, several stopping criteria can be set, such as 
residual threshold, stagnation threshold, and maximum 
number of iterations. Besides, these iterative techniques 
require a first guess that can be generated from the theoretical 
distribution of the aperture fields of the AUT.  
As shown in Fig. 2 and 3, the output is the complex NF at 
the acquisition domain, formed by the acquired amplitude and 
the estimated phase. 
 
 
Fig. 4. Near field radiated by the AUT evaluated at two planar surfaces. 
Note that the main beam is tilted with respect to the z axis. 
It must be remarked that acquisition on planar surfaces is 
sufficient, in the case of directive antennas, for a proper 
characterization of the main beam and sidelobes. This also 
helps to keep the complexity of the measurement setup low. 
Besides, as mentioned before, integral equations can be 
decoupled, allowing independent (and thus faster) recovery of 
Ex and Ey components. In the case of circularly polarized 
antennas, ERHC and ELHC are calculated from Ex and Ey. 
III. APPLICATION EXAMPLE 
The proposed methodology has been evaluated using an 
offset reflector antenna as AUT, depicted in Fig. 1. The reason 
of choosing this AUT is the growing interest on in-situ testing 
of reflector antennas for radiocommunications and 
radioastronomy [8]. The reflector antenna dish has been 
distorted with a metallic plate to test the diagnostics 
capabilities. 
 
 
Fig. 5. Reconstructed field on the AUT aperture plane, copolar component 
(ERHC). (a) Using NF amplitude and phase information. (b) Using amplitude-
only information, nonlinear cost function minimization. (c) Using amplitude-
only information, iterative forward-backward algorithm. Dashed red line 
represents the contour of the reflector dish, and the solid black line represents 
the metallic plate attached to the dish. 
In this example, the reflector has been fed with a helix 
antenna to achieve circular polarization. A working frequency 
of f = 4.65 GHz has been selected, yielding a theoretical 
directivity of ~30 dB. 
The methodology depicted in Fig. 1 has been followed. 
First, the AUT has been measured at the spherical range in 
anechoic chamber of the University of Oviedo. Next, an 
equivalent currents model of the AUT has been retrieved so 
that the NF radiated by the AUT can be evaluated at different 
acquisition surfaces. 
A. Comparison of iterative phase retrieval techniques 
The two iterative phase retrieval techniques described in 
Section II.B have been compared. In this test, the NF is 
evaluated at two 4 m x 3 m planar surfaces, placed 3 m and 4 
m away from the AUT. As shown in Fig. 4, the reflector 
antenna main beam is tilted, so the measurement planes are 
off-centered in the y-axis. Sampling rate is 3 cm, resulting in 
13534 acquisition points on each plane.  
 
 
Fig. 6. Far field pattern, cut ϕ = 90º. Comparison between NF-FF 
transformation using amplitude and phase information, and using amplitude-
only information (dashed line: non-linear cost function minimization, dash-
dotted line: iterative forward-backward method). 
 From the evaluated NF at the two planar domains, the 
fields on the AUT aperture plane have been recovered. 
Reconstruction using amplitude and phase information (Fig. 5 
(a)) is taken as reference. Fig. 5 (b) shows the reconstructed 
aperture fields using the algorithm based on nonlinear cost 
function minimization, and Fig. 5 (c) corresponds to the 
aperture fields reconstructed using the iterative forward-
backward method. In all the cases, the asymmetry due to the 
presence of the metallic plate on the reflector dish can be 
noticed. 
Next, the radiation pattern is calculated from these 
aperture fields. The cut at ϕ = 90º is depicted in Fig. 6, 
comparing the radiation pattern from NF amplitude and phase 
measurements, with the pattern calculated from amplitude-
only acquisition. In the case of the copolar component (RHCP, 
blue lines), there is a good agreement within the FF angular 
margin of validity. 
B. Testing using in-situ acquisition grid data 
As aforementioned, the methodology described in Fig. 1 
enables a-priori assessment of the accuracy of the in-situ 
antenna measurement system, provided a realistic model of 
the AUT is given. For example, this methodology allows 
evaluating different measurement grids that will be later 
converted into waypoints for the airborne-based system. Thus, 
it can be used to select the grid that best fits (i.e. gives more 
accuracy) to measure a particular kind of antenna. 
In this example, the grid to be tested has been extracted 
from a former UAV flight path positions from the in-situ 
measurement of a 2-element horn antenna array [3]. The initial 
grid consisted of two 4 m x 2 m planes placed at z = 3 m and 
z = 4 m away from the AUT. In practice, UAV positioning 
errors resulted in a non-uniform measurement grid, as 
observed in Fig. 7. Nevertheless, positioning differences with 
respect to a canonical surface and a regular grid do not have a 
significant impact in the accuracy of the in-situ measurement 
system, provided that those measurement positions are 
accurately geo-referred [3,4]. 
 
Fig. 7. NF evaluated at the grid consisting on geo-referred flight path 
points. Average position in z for each measurement surface is shown. 
The NF radiated by the AUT has been evaluated at the 
geo-referred positions of the UAV flight path as depicted in 
Fig. 7. Then, the fields on the AUT aperture have been 
reconstructed: results considering amplitude and phase 
information (as a reference) and amplitude-only information 
are shown in Fig. 8. In this example, the algorithm based on 
nonlinear cost function minimization performed better (i.e. it 
had better convergence) than the forward-backward 
algorithm, so just the results for the former are shown. It can 
be noticed the agreement with the diagnostics results depicted 
in Fig. 5 using the regular grid. 
Finally, the far field pattern is calculated from the aperture 
fields. ϕ = 90º cut is plotted in Fig. 10, comparing the NF 
acquired on a regular grid using amplitude and phase and 
amplitude-only information, with the NF acquired on the 
UAV flight path points also using amplitude and phase and 
amplitude-only information. The main beam and the sidelobe 
at θ = 5º are in good agreement. It can be observed that both 
copolar and crosspolar components match if the phase of the 
NF is available regardless the NF acquisition domain. 
 
 
Fig. 8. Reconstructed field on the AUT aperture plane, copolar component 
(ERHC). (a) Using NF amplitude and phase information. (b) Using amplitude-
only information, nonlinear cost function minimization. 
IV. CONCLUSIONS 
Results presented in this contribution prove the capability 
of the implemented iterative phase retrieval techniques for 
antenna diagnostics and radiation pattern evaluation for a 
challenging problem consisting of a high directive circularly 
polarized off-centered reflector antenna. Even for non-
uniform acquisition domains, as in the case of airborne-based 
antenna measurements, it is possible to accurately estimate the 
radiation pattern from phaseless NF measurements taken at 
UAV flight path positions. 
ACKNOWLEDGMENT 
This work has been supported in part by the Ministerio 
de Economía, Industria y Competitividad of Spain/FEDER, 
under projects TEC2014-54005-P (MIRIIEM), TEC2015-
73908-JIN, Project TEC2014-55290-JIN, GRUPIN-18-
000191, and grant FPU15/06341. 
 
 
Fig. 9. Far field pattern, cut ϕ = 90º. Comparison between NF-FF 
transformation using amplitude and phase information, and using amplitude-
only information. Results considering NF measurement domains on Section 
III.A (regular grid) and Section III.B (UAV grid) are shown. 
REFERENCES 
[1] K. P. Valavanis G. J. Vachtsevanos UAV Applications: Introduction. 
In Handbook of Unmanned Aerial Vehicles. Springer, 2015. 
[2] G. Virone, A. M. Lingua, M. Piras, A. Cina, F. Perini, J. Monari, F. 
Paonessa, O. A. Peverini, G. Addamo, R. Tascone, “Antenna pattern 
verification system based on a micro unmanned aerial vehicle (UAV)”, 
IEEE Antennas and Wireless Propagation Letters, Vol, 13, pp. 169-
172, 2014. 
[3] M. G. Fernández, Y. A. López, A. Arboleya, B. González-Valdés, Y. 
R. Vaqueiro, M. E. de Cos Gómez, F. Las-Heras, “Antenna Diagnostics 
and Characterization using Unmanned Aerial Vehicles,” IEEE Access, 
Vol. 5, pp. 23563-23575, 2017. 
[4] Y. Alvarez, M. García, A. Arboleya, B. González, Y. R. Vaqueiro, A. 
Pino, F. Las-Heras, “Sistema aerotransportado y método para la 
caracterización y medida de antenas o sistemas radiantes,” Patent 
PCT/ES2018/000015. Priority date: 03/03/2017 (ES P201700209). 
[5] Y. Alvarez, F. Las-Heras, M. R. Pino, “The sources reconstruction 
method for amplitude-only field measurements,” IEEE Transactions 
on Antennas and Propagation, Vol. 58, No. 8, pp. 2776-2781, 2010. 
[6] S. F. Razavi, Y. Rahmat-Samii, “A new look at phaseless planar near-
field measurements: limitations, simulations, measurements, and a 
hybrid solution,” IEEE Antennas and Propagation Magazine, Vol. 49, 
No. 2, pp. 170-178, 2009.  
[7] J. L. Martínez, A. Arboleya-Arboleya, Y. Álvarez-López, C. García-
González, F. Las-Heras, “Phaseless antenna diagnostics based on off-
axis holography with synthetic reference wave,” IEEE Antennas and 
Wireless Propagation Letters, vol. 13, pp. 43-46, 2014. 
[8] C. Chang, C. Monstein, A. Refregier, A. Amara, A. Glauser, S. Casura, 
“Beam calibration of radio telescopes with drones,” Publications of the 
Astronomical Society of the Pacific, Vol. 127, No. 957, pp. 1131-1143, 
2015. 


Antenna measurement and diagnostics processing techniques using unmanned aerial vehicles

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Antenna measurement and diagnostics processing techniques using unmanned aerial vehicles

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