A novel multi-magnetometer facility for on-ground characterization of spacecraft equipment

Measurement 146 (2019) 948–960

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A novel multi-magnetometer facility for on-ground characterization of spacecraft equipment S. Tsatalas a, D. Vergos a, S.T. Spantideas b,⇑, N.C. Kapsalis b, S.-D.J. Kakarakis b, N.A. Livanos a, S. Hammal a, E. Alifragkis a, A. Bougas a, C.N. Capsalis b, A. Junge c a b c

EMTECH SPACE P.C., 32 Korinthou St. & S. Davaki, 14451 Metamorphosi, Attiki, Greece National Technical University of Athens, 9, Iroon Polytechniou Str., Athens 15780, Greece European Space Agency – European Space Research and Technology Centre (ESA-ESTEC), Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands

a r t i c l e

i n f o

Article history: Received 11 April 2019 Received in revised form 18 June 2019 Accepted 4 July 2019 Available online 8 July 2019 Keywords: Electromagnetic compatibility Magnetic cleanliness Magnetic field measurements Magnetometers Magnetic dipole modeling Multi-magnetometer facility

a b s t r a c t This paper aims to provide the research and development activities of ESA contract 4000111736/14/NL/ GLC on Multi-Magnetometer Methods for Magnetic Dipole Modelling awarded to a consortium, consisting of EMTECH SPACE P.C. and National Technical University of Athens. In the frame of this activity, the rotational magnetic measurements of a unit under test are replaced by an increasing number of fixed magnetic field sensors, intended to perform a snap-shot measurement of its DC magnetic field. The scope of the research is to identify the most efficient number of magnetometers and their spatial geometry in order to effectively characterize magnetic sources consisting of several dipoles and quadrupoles. At later stages of the activity, the construction of a novel Multi-Magnetometer Facility was realized. The mechanical design of the facility is extensively illustrated and its capability to characterize magnetic field signatures is validated with a set of a-priori known magnetic sources. Ó 2019 Elsevier Ltd. All rights reserved.

1. . Introduction The measurement of the magnetic fields surrounding the Earth, other planets, the Sun, or other astronomical objects is amongst the key objectives of former and upcoming space missions of the European Space Agency (ESA) [1–4]. These space missions usually include sensitive magnetic field sensors that need to operate in a ‘‘magnetically clean” environment, i.e. the ambient magnetic noise that is present at the sensors’ position shall be effectively minimized in order to ensure the validity of the measured field data [5]. In space, the main part of the magnetic field noise is generated by the spacecraft itself, since the distance between the vehicle and the sensors (usually some meters) is very small compared to the object of interest. A space mission commonly includes platform equipment (for instance solar array, power electronics, flywheels, etc.) that contribute to the overall generated magnetic field with their individual magnetic signature. These contributions typically emerge both from current paths and from magnetic materials that ⇑ Corresponding author. E-mail addresses: [email protected] (S. Tsatalas), sspantideas@ central.ntua.gr (S.T. Spantideas), [email protected] (S.-D.J. Kakarakis), nikolaos. [email protected] (N.A. Livanos), [email protected] (S. Hammal), [email protected] (E. Alifragkis), [email protected] (A. Bougas), [email protected] (C.N. Capsalis). https://doi.org/10.1016/j.measurement.2019.07.016 0263-2241/Ó 2019 Elsevier Ltd. All rights reserved.

are incorporated in their design [6]. The vectorial superposition of the fields originating from all these potential magnetic sources is consequently present at the location of the sensors and may possibly interfere with the measured data. In order to effectively distinguish between the actual valuable data and the interference from the spacecraft, individual units are subjected to extensive onground verification tests concerning the magnetic cleanliness requirements. These tests are performed in Mobile Coil Facilities (MCF) and aim at capturing the DC magnetic signature of each individual piece of equipment and characterizing it by providing an equivalent model [5,7]. Then, the model can be used for various trade-off simulation scenarios in order to determine and analyze the magnetic budget of the space mission, i.e. assessing the contribution of each unit to the total static magnetic field noise at the location of the sensors, evaluate the spatial distribution of the field around the space vehicle, implement design changes to equipment exhibiting significant magnetic signature, etc. [7]. The Multiple Dipole Modeling (MDM) is a well-acknowledged method for modeling the magnetic data produced by an Equipment Under Test (EUT), i.e. determining multiple dipoles and quadrupoles that can reproduce the measured field. The discrete inverse problem of identifying the parameters of the equivalent magnetic sources may be solved by various optimization techniques, both deterministic and randomized [8–12].

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Magnetic noise is also present, however, during the on-ground magnetic characterization in the MCF facilities. Such field disturbances typically originate from the magnetic contribution of nearby technical equipment (e.g. power network, turntable with motor drive) and from the ambient magnetic field (e.g. random AC variations of the geomagnetic field) during the test [7]. The disturbances of the ambient field during the procedure may require repetition of the measurements, which can result in low reliability and repeatability of the test results. Specifically, since the MCF is designed to compensate the external magnetic field, there are various parameters affecting the measurements, i.e. stability of the DC current supplies, power line disturbances of 500 lA variations and offsets that produce magnetic field changes in the order of 65 nT, variations of Earth’s magnetic field (typically 10–100 nT/h), etc. [13]. The scope of the present ESA activity is to study, develop and implement novel measurement and modeling techniques in order to minimize the measurement susceptibility to the aforementioned variations and increase the reliability of the test results. In the frame of this activity, the measurement concept of the EUT rotation that is usually applied in the existing MCF facilities is replaced by an increased number of fixed magnetic field sensors. According to this innovative measurement philosophy, the magnetometers form a mesh of measurement points around the EUT and simultaneously capture its magnetic field. Therefore, interference that typically occurs during the measurement procedure (turntable rotation) is avoided and an instant snap-shot measurement of the magnetic signature of an EUT is obtained. The rationale supporting the current work is principally the need of more accurate and efficient testing of spacecraft units to provide a better estimation of the residual spacecraft magnetic field. The present paper outlines the research and development activities aiming to realize a novel Multi Magnetometer Facility (MMF) consisting of several magnetometers. The target of the facility is to perform snap-shot measurements of the magnetic signature of spacecraft equipment, but also considerably reduce the required test time and necessary operator expertise. Moreover, existing MDM methods on using multiple magnetometers for multiple dipole modeling are examined, complemented and applied to the MMF facility, i.e. capturing the near magnetic field from an EUT and model the measured magnetic field data from several sensors with multiple equivalent magnetic sources. The mechanical characteristics of the prototype MMF facility and the associated software application are extensively demonstrated. Finally, its functionality in measuring and modeling DC magnetic fields is assessed by a set of dipole and quadrupole magnetic sources. In Section II, the design requirements of the facility are presented and a brief mathematical analysis regarding the modeling and assessment methodologies is formulated. In Section III, the hardware, mechanical construction and electrical parts of the facility are presented and the software application, called RIBOSOME, is illustrated. Finally, in Section IV the MMF facility is validated via real measurements and the estimated dipole and quadrupole models are verified with a set of a-priori known magnetic sources.

2. Mathematical formulation In the present section, the design requirements of the facility are presented and the discrete inverse problem is analyzed. Finally, the evaluation criteria in order to assess the resulting equivalent dipole models are formulated. The first principal activity of this work is to study different possible multi magnetometer test setups with the following targets: (i) at first, a snap-shot of the magnetic field generated by an EUT is obtained, while keeping measurement time below 1 s (ii) sec-

ondly, the optimum number and position of magnetometers and/ or gradiometers and the parameters affecting the reproducibility of test results are identified. The design requirements of the facility can be summarized: (i) The facility shall ensure a positioning accuracy of ±1 mm and an orientational accuracy of 0.5° between the EUT and any magnetometer. (ii) The mechanical support of the EUT and any magnetometer shall be insensitive to vibrations during the measurement to ensure position stability better than ±1 mm. (iii) Any mechanical support for magnetometers and EUT shall be non-magnetic and copper-beryllium shall be avoided. (iv) The mechanical support of the EUT shall be able to support equipment with dimensions 60 cm
60 cm
30 cm (in any orientation) and weight 50 kg (on the full area and restricted to 30 cm
30 cm). (v) The test coordinate system (TCS) of the facility shall be a right-handed orthogonal Cartesian coordinate system, with axes labelled x, y and z-axis. The z-axis of the TCS shall be vertical, perpendicular to the Earth surface and oriented upwards. (vi) The mechanical support for the EUT shall provide mechanical elements for a reproducible displacement of the EUT along three orthogonal directions, e.g. x, y, and z-axes in TCS. (vii) The magnetometer position shall be continuously adjustable and should vary between 10 cm and 1 m with respect to the center of an EUT. Moreover, the verification requirements in terms of accuracy of the predicted models can be expressed: (i) Relative deviation between measured and modeled magnetic field in excess of known and quantified measurement uncertainty shall be less than ±10%. (ii) Deviation of positions of test objects relative to magnetometers as derived from magnetic field measurements shall be less than 5 mm compared to position as measured with metering rule or laser rangefinder. 2.1. Mathematical background The static magnetic field vector Bij at a measurement point rj , j ¼ 1; 2;    N MAG that is generated by a dipole source can be expressed [14]:

h

2

i

3



 0 0 ^ l0 43 rj  r i rj  r i A  mi mi 5 Bij ¼     4p  rj  r0 i  5 rj  r0 i 3 D

ð1Þ

th

where r0 i denotes the position of i dipole source (i ¼ 1; 2;    M), mi denotes its magnetic moment, l0 is the magnetic permeability of free space and NMAG is the number of measurement points. It should be noted that the dipole approximation is valid for magnetic field contributions emerging from localized sources. For instance, small (compared to the measurement distance) closed current paths and magnetic material inside an EUT are sources that may be considered and modeled as magnetic dipoles [14,15]. The magnetic field from multiple dipole sources i ¼ 1; 2;    M may be calculated at an observation point in components as the superposition of the individual dipole contributions (Fig. 1), taking into account that the measurements are obtained with tri-axial magnetic sensors and assuming Cartesian coordinate system:

Bj D ¼

M X i¼1

bþ Bxij x

M X i¼1

bþ Byij y

M X i¼1

z Bzij b

ð2Þ

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2.2. Measurement setup and evaluation criteria

Fig. 1. Geometry of the problem under consideration.

The MDM problem that is considered in the present work involves the determination of the parameters of the magnetic dipole sources, namely their position vectors r0 i ¼ ðxi ; yi ; zi Þ and
their magnetic moment vectors mi ¼ mix ; miy ; miz ), from the measured magnetic field components Bxj ; Byj ; Bzj at the measurement
 points rj ¼ xj ; yj ; zj . For solving the discrete inverse problem, deterministic or stochastic optimization methods may be implemented. Randomized techniques (Particle Swarm Optimization, Genetic Algorithms, Differential Evolution, etc.) are generally considered more efficient for these type of nonlinear inverse problems [9]. The direct implementation of the Particle Swarm Optimization (PSO) stochastic technique in the MDM problem by employing several measuring sensors can be found in [16]. In principle, all MDM solver methods employ the magnetic dipole Eq. (1) in order to estimate 6 parameters for each magnetic dipole (3 for the position and 3 for the magnetic moment of the source), that may be then used to reproduce the measured magnetic signature of an EUT. Furthermore, the field generated by quadrupole magnetic sources is also investigated. A quadrupole source is equivalent to two identical dipole sources in close proximity with opposite magnetic moments [17]. Similarly to the dipole analysis, the magnetic field generated by a quadrupole source located at r0 i ¼ ðxi ; yi ; zi Þ may be expressed:

"

Bij

Q

l 15 6 T ¼ 0  7 dij dij Q i dij   5 Q i dij 4p dij  dij 

# ð3Þ C rel

where dij ¼ r0j  r0 i denotes the distance between the observation point and the source and the quadrupole moment tensor Q i may be described by the use of 5 independent scalar parameters (q1 to q5 ), taking into account its symmetric and traceless properties:

2
2 6 Qi ¼ 4

3

q1  13 q4
1  q
21 2  q 2 3





1 2

q2



 13 q1 þ 23 q4
1  q 2 5


1




Since the parameters to be estimated are 6 for each dipole source and 8 for each quadrupole source and each tri-axial magnetometer provides the magnetic field components (3 field values Bx ; By ; Bz ), the use of multiple magnetometers that simultaneously capture a snap-shot magnetic signature of the EUT is imperative. In practice, complex EUTs may be modeled by several magnetic dipoles and quadrupoles. Based on the above and concerning the composite nature of several spacecraft units, in the present work 12 three-axial fluxgate magnetometers are considered adequate to provide a reliable MDM of the snap-shot magnetic signature of an EUT consisting of several magnetic sources [16]. As far as the geometry of the magnetometers around the EUT is concerned, the magnetometers are positioned at different angles, heights and radii (uncorrelated measurements regarding the location of the sensors) to capture the magnetic signature from various angles due to the nonsymmetrical spatial distribution of the static magnetic field. Several configurations of measurement setup that can be realized with the MMF facility are shown in section III. Furthermore, one of the issues that may introduce uncertainty during the measurement procedure is the accuracy of the relative distance between the EUT and the magnetometers. According to the design requirements of the facility, a positioning accuracy of ±1 mm and an orientational accuracy of 0.5° between the EUT and any magnetometer is essential. For the purposes of quantifying the uncertainty related to this relative distance, the sensors’ positions were randomly displaced up to a maximum of 1 mm. The mean difference percentage between the magnetic field values of Eq. (1) generated at the ‘‘original” and the displaced magnetometers positions is 1.46%. Since the only uncertainty source quantified via this procedure is the relative distance between the EUT and the magnetometers and other possible sources of uncertainty (for instance magnetometer noise, temperature, humidity, background field noise, etc.) are not taken into account, a fair assumption is that a maximum distortion percentage of 5% in the magnetic data values is sufficient to simulate the uncertainty related with the measurement procedure [18–20]. The resulting dipole and quadrupole models are assessed via the verification requirements that are used as evaluation criteria and can be mathematically expressed: (i) The relative deviation between the total measured and modeled magnetic fields – Relative Goodness of Fit (%):


21

q3



3



7

q 5 2 5   13 q1  13 q4

ð4Þ

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi uNMAG   uP 2 2 2 u u i¼1 DBxj þ DByj þ DBzj ¼u u NP  ; MAG  t Bx2j þ Byj 2 þ Bzj 2

ð5Þ

i¼1

where Bxj , Byj and Bzj stand for the measured magnetic field components at the j-th observation point and DBxj , DByj and DBzj denote the difference between the measured and the model’s field components. An additional metric that is typically employed to evaluate the resulting dipole and quadrupole model is the Absolute Goodness of Fit (nT):

C abs

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi uNMAG   uP u DBxj 2 þ DByj 2 þ DBzj 2 t i¼1 ; ¼ 3  NMAG

ð6Þ

In this case, the parameters of the magnetic source to be determined are the quadrupole’s position (x; y; z) and its magnetic tensor parameters ðq1 ; q2 ; q3 ; q4 ; q5 Þ from the near magnetic field measurements. Similarly to Eq. (2), the magnetic field of multiple quadrupole sources can be calculated as superposition of the individual sources at a measurement point and consequently, the total

(ii) Deviation of position of test object relative to magnetometers as derived from magnetic field measurement. This is equivalent to the difference between the original and MDM models’ positions (Dx, Dy, Dz), and it is calculated as follows:

magnetic field Bj D;Q may be determined as a vectorial sum of dipole and quadrupole sources’ contributions.

C pos ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Dx2 þ Dy2 þ Dz2 ;

ð7Þ

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According to the verification requirements and the uncertainty related to the measurement procedure, the following threshold restrictions shall hold for the evaluation criteria: (i) C rel < 10% (ii) C pos < 5 mm, indicating that the resulting model can virtually represent the measured magnetic signature of the unit. 3. Description of prototype multi-magnetometer facility and software application Based on the analysis mentioned in Section II, a prototype multi-magnetometer facility (proto-MMF) has been developed and manufactured in order to provide the capability to implement several possible measuring configuration setups. The main elements of the facility are: (i) Measurement instrumentation consisting of 12 fluxgate magnetometers, and the required Data Acquisition system (DAQ) to collect the EUT magnetic signature. (ii) The mechanical support system consisting of a common panel structure (CP) to support all the mechanical elements used to host the magnetometers and provide radial and vertical (z-axis) movement capability and finally, the EUT support table. (iii) A software application, called RIBOSOME, to control the operation of proto-MMF and to provide the predicted MDM. 3.1. Measurement instrumentation & data acquisition system The main characteristic of the test methodology of the MultiMagnetometer Facility is to perform a snap-shot measurement of the EUT’s magnetic field and provide these data to an MDM solver in order to produce the predicted magnetic dipole model of the unit. In general, the measurement procedure consists of a sequence of the following measurements: (i) Ambient B-field measurement (AMBbefore) (ii) EUT snap-shot field measurement (EUT + AMB) (iii) Ambient B-field measurement (AMBafter) Proto-MMF collects measurements from all magnetometers within 1 s for each of the above measurements. These successive measurements should be performed as fast as possible (in the order of 1 min in total) to reduce effects of ambient field variation during the measurement process. The operator should insert and remove the EUT on the support table as fast as possible to retain short total measurement time. The proto-MMF with 12 fluxgate magnetometers obtains an instant snap-shot measurement of the magnetic field and avoids the uncertainty related to angular resolution of the rotating turntable, thus accomplishing a significant reduction of the measurement sensitivity to environment variations, which in turn, results in increasing the accuracy and the repeatability of the test results. The typical variation of the ambient field of the MMF during the 3 step measurement procedure in 1 min was repeatedly tested, measured and found that follows a normal distribution with zero mean and standard deviation of approximately 1 nT. Based on the measurement philosophy and the test procedure, the proto-MMF magnetometers incorporate high performance fluxgate sensors (10 units Bartington Mag-03 MS100 and 2 units Bartington Mag-03 MSL100) with integral electronics and provide precision measurements of static and alternating magnetic fields

in three axes (Bx ; By ; Bz ). They are powered from special power supply units containing also the necessary excitation circuit. Their outputs are in the form of three analogue voltages from 0 to ±10 V, proportional to Bx ; By and Bz . The Data Acquisition System of the Multi-Magnetometer Facility consists of two identical bus-powered, isolated, National Instruments (NI) USB 6289, (M Series) multifunction data acquisition (DAQ) modules optimized for superior accuracy at fast sampling rates. A block diagram of the proto-MMF data acquisition system is depicted in Fig. 2. The NI USB DAQ configuration was adapted to the measurement procedure requirements. The resulting main characteristics are: (i) Supports data acquisition from 12x3 analogue input channels, 36 in total. (ii) Provides 18 bits resolution. (iii) Supports multiple snap-shots acquisition within 1 s. (iv) Interfaces with RIBOSOME software application which is running on a laptop. 3.2. Mechanical support system The target of the mechanical support for magnetometers and EUT turntable is to provide a stable and accurate operation resulting to better quality measurements. The concept includes a common panel (based on a rigid frame) carrying the displacement mechanisms of the magnetometers and the EUT turntable subsystem. The magnetometer test setup implemented by protoMMF is shown in Fig. 3. The setup includes six (6) vertical planes at a 60° circular array. Two magnetometers lie on each plane, forming a pair. The magnetometers are free to slide horizontally and vertically. The main characteristics of the mechanical construction of proto-MMF are: (i) It hosts 12 magnetometers at pre-fixed angles (600 between successive magnetometers pairs of support frames) to implement a certain type of magnetometers arrangement. (ii) The magnetometers’ horizontal displacement range is 0– 100 cm from the turntable center. The magnetometers vertical displacement (against the turntable top surface) range is 24 cm – 70 cm, depending on the z-axis position of the turntable and their vertical support rail length.

Magnetometers and Power Supply Units

Mag 1

MagPSU 1

Mag 2

MagPSU 2

Analog Signals

Mag n

Collection of Data. Data Acquisition System A/D, Signal Conditioning

MagPSU n

Power Supply

Conditioned Analog Signals (Basic filtering)

USB interface Digital interface Noise free Error free

Fig. 2. Measuring System Block Diagram.

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Fig. 4. Proto-MMF mechanical design overview.

Fig. 3. Magnetometers’ operating planes above the common panel and around the turntable.

(iii) EUT support table (turntable) has a vertical (z-axis) elevation capability of a 20 cm range. (iv) EUT support table (turntable) has a rotational capability independent to the elevation one. The angular displacement is measured by an engraved ruler with a 2.5° step. The turntable has also a one-direction horizontal displacement capability to reach one construction’s edge and facilitate heavier or larger EUT placement. (v) EUT support table (turntable) includes an array of threaded inserts at a 5 cm rectangular step allowing accurate EUT displacement on the table. (vi) It is estimated that a 0.5° angular accuracy has been accomplished between the magnetometer radial axis and the turntable center. This estimation is based on the design philosophy and the mechanical calibration procedure. The horizontal and vertical positioning accuracy is 1 mm. (vii) The diameter of the EUT support table is 50.5 cm. (viii) The EUT maximum weight is 20 kg. By using special turntable support bars the EUT weight capability of the turntable is increased to 50 kg. (ix) Rulers are placed to describe the exact position of each magnetometer in relation to the turntable centre, vertically and radially. (x) There are six areas around the common panel for physical access to the turntable. Two of them allow better accessibility. (xi) All materials used are non-magnetic. (xii) Proto-MMF has a diameter of 2.4 m and maximum height of 1.65 m.

(ii) An EUT support system consisting of a turntable and its support mechanism (Fig. 5). The turntable rotational capability might be of practical interest to account for intermediate EUT angular positions. (iii) Twelve magnetometer supporting sub-assemblies, movable along direction pointing to the turntable center (Fig. 6). The magnetometers can also slide on the vertical z-axis. As the only constrain is that every pair of magnetometers is lying in predefined vertical planes referred earlier, this construction allows the implementation of several measuring test setups. 3.3. Configurations of the measurement setup As already mentioned, the flexibility of the MMF facility enables the implementation of different possible measuring setup configurations. The fluxgate sensors have the capability of sliding both horizontally and vertically depending on the dimensions of the EUT and the Signal to Noise Ratio (SNR) of its magnetic signature measurement, with negligible position related uncertainty. In this subsection, the geometrical configurations of three indicative measuring setups are presented. (i) Two plane configuration: The magnetic field sensors form 2 circles at fixed planes above and below the turntable. The height of each plane and the radii of the circles (radial displacement relative to the center of the turntable) may be adjusted according to the dimensions and signature of the EUT. In Fig. 7, the two plane configuration setup is depicted with radius 20 cm for both circles, while the sensors are positioned 10 cm above and below the turntable respectively.

Moreover, the test coordinate system (TCS) of the facility is a right-handed orthogonal Cartesian coordinate system, with axes labelled x,y and z-axis which is vertical, perpendicular to the Earth surface and oriented upwards. An overview of the mechanical construction is provided in Fig. 4. The multi-magnetometer mechanical construction consists of three (3) sub-assemblies: (i) A common panel (CP) based on a profile rod frame. The purpose of the common panel construction is to provide a rigid support system for the magnetometers and the EUT support systems.

Fig. 5. EUT table sub-assembly.

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heights are z = (0, 4, 8, 12, 16, 20) cm for the 6 upside magnetometers (upper plane of the helix) and z = (10, 6, 2, 2, 6, 10) cm for the downside magnetometers (lower plane of the helix). This setup enables the acquisition of the EUT’s magnetic field signature at several vertical positions above and below the EUT. (iii) Gradiometer configuration: this measuring setup involves the formation of 2 circles above the turntable with different radii and different heights. The sensors’ pair at each vertical plane (00, 600, 1200, 1800, 2400 and 3000) are located in close proximity and they additionally enable the estimation of the magnetic field fall off, similarly to the dual magnetometer technique [21]. The configuration is shown in Fig. 9 with radius r = 20 cm and height z = 10 cm for the downside magnetometers and r = 30 cm and z = 20 cm for the upside magnetometers respectively. Fig. 6. Magnetometer support system.

3.4. Software application description

Fig. 7. Two plane configuration.

(ii) Helicoidal configuration: The magnetometers form a double helix (in pairs) around the turntable that the EUT is placed. In Fig. 8 the helicoidal configuration is shown for radius 30 cm from the center of the table and their respective

Fig. 8. Helicoidal configuration.

RIBOSOME software application facilitates the new magnetic measurement process of proto-MMF, from data acquisition to report generation. RIBOSOME is based on the MCF-MAGNET software [1,22] that has been used for years in the current MCF facility at ESTEC and incorporates a set of additional capabilities and features required by the new measurement concept. The solving methods (PSO, GA, etc.) of the adapted MCF software were extensively tested in several simulated and real data test cases and the analysis of the modeling algorithms’ outputs indicate a consistency and repeatability of the results, thus validating the robustness of the modeling solving techniques, as indicatively reported in [9– 12,16,17]. The aforementioned methods were tested in a personal computer i5 with 8 GB RAM and the computing time is less than 1 sec. Finally, the initialization of these stochastic methods does not have a significant impact on the estimated output of the algorithm, since random initialization is applied [10]. The software application incorporates and re-uses the existing MDM solver (towards finding the minimum number of magnetic sources capable to reproduce the measured magnetic signature) but also incorporates all necessary functionality to control the execution of the new measurement test procedure and also the magnetometers measurement data acquisition and their necessary filtering. Fig. 10 depicts the building modules of RIBOSOME. The software application inputs, the implemented modules and its outputs are described below:

Fig. 9. Gradiometer configuration.

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Fig. 12. Snap-shot Measurement Window. Fig. 10. RIBOSOME module overview.

1) Inputs: RIBOSOME takes into account the following inputs: (i) Magnetometer/gradiometer positions and relative offsets (Fig. 11). (ii) EUT dimensions within the facility (on the turntable). (iii) Solving method. The solver implemented in the framework of previous works embeds different solving methods (Genetic Algorithms, PSO, etc.). RIBOSOME cooperates with all of them. (iv) Parameters of the chosen solving method. Such parameters may include maximum number of iterations, fitness function threshold, etc. (v) Number of dipoles and quadrupoles composing the Magnetic Dipole and Quadrupole Model (MDQM). The solver is able to model the EUT with different numbers of dipoles and quadrupoles. (vi) Number of snap-shots. RIBOSOME collects various measurements from all selected magnetometers taken in the order of 1 s (Fig. 12). 2) Modules: RIBOSOME software application implements the following modules: (i) Common interface between the software and different solvers. (ii) Adaptation of the different solvers to the chosen measurement setup. The software takes into account the magnetometers’ positions of the corresponding setup.

(iii) Implementation of calibration procedure to define the positions of the magnetometers using information from the rulers located in proto-MMF. (iv) Implementation of snap-shot measurement procedure. The procedure includes the removal of the Earth’s and ambient magnetic field. (v) Measurements data processing, including oversampling & filtering. Digital filters are implemented in the software application (real time, user selected) that include a lowpass filter to remove disturbances and noise, a 50/60 Hz frequency rejection filter to reject main frequencies and a 16.7 Hz frequency rejection filter. Moreover, there are analog filters implemented in the magnetometers power supply units (low pass) but also in the DAQ unit Analog Input (low pass also). These filters can also be enabled or disabled by the user. (vi) Interfacing with the DAQ units for configuration and data acquisition. (vii) Measurements reporting and storing. 3) Outputs: RIBOSOME outputs are the following: (i) Measurement data from each magnetometer (in analytical & graphic format). (ii) Parameters of the MDQM. (iii) RMS result between the measured and the model’s magnetic field. 3.5. Facility constraints

Fig. 11. Magnetometers settings window.

As this is a prototype measuring facility there are some operational constraints that may limit the functionality, even if most of the design details have been extensively discussed and addressed based on good engineering practices within reasonable limits. The novel multi magnetometer facility includes twelve fluxgate sensors in order to guarantee an adequate coverage of the magnetic signature of an EUT and additionally provide to the MDM solving algorithms sufficient magnetic field data to predict a reliable model even in complex cases. The radial displacement of all twelve sensors, however, should be minimum in cases of EUTs generating weak magnetic field signatures in order to achieve acceptable SNR. Therefore, the magnetometers of all vertical planes should be placed relatively close to each other, converging towards the center of the turntable and leaving less space for the operator to access the center of the facility and place/remove the EUT.

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4. Verification of the facility with real measurement data For purposes of validating the test measurement methodology, procedure and operation of the proto-MMF, as well as assessing the resulting dipole and quadrupole models against the evaluation criteria, several known magnetic sources were measured and modeled. The test cases include (i) one dipole with small calibrated magnetic moment, (ii) one dipole with strong magnetic moment – Ulysses MCF reference magnet, (iii) two dipoles with parallel, (iv) two dipoles with antiparallel magnetic moments, (v) one current fed coil and (vi) two dipoles with antiparallel magnetic moments, separated by approximately 7 mm, thus forming a collocated quadrupole and dipole. These magnetic sources generate a well-defined magnetic signature and were measured and modeled in the MMF facility on several occasions in order to investigate the repeatability of the test results. Furthermore, various configurations of the measuring setup were tested, as described in Section III, to additionally analyze the reproducibility of the models. In all test measurement scenarios, the resulting models – dipoles and quadrupoles – exhibit negligible deviation from the real EUT position (x; y; z), while they are consistent in terms of estimated dipole
 moment vector mx ; my ; mz and quadrupole tensor parameters ðq1 ; q2 ; q3 ; q4 ; q5 Þ. Finally, C rel and C pos evaluation criteria are fulfilled in all measured test cases. The indicative verification results demonstrated in the present section involve the use of two plane configuration of the measuring setup. The 6 magnetometers form an upper plane above the turntable, positioned at a step of 60°, while the remaining 6 sensors form a lower plane below the turntable, as depicted in Fig. 13.

Fig. 14. Calibrated dipole with weak magnetic moment.

4.1. Calibrated dipole source with weak magnetic moment The test object of the first validation scenario is depicted in Fig. 14. For purposes of obtaining significant magnetic field values generated by the dipole source, the 12 magnetic field sensors are slid radially towards the center at a distance of 10 cm, while their arrangement is fixed (two plane configuration and 60° between successive magnetometers pairs) at a height of z = 10 cm above and below the turntable. The dipole moment of the calibrated magnetic source is 2 mAm2 and aligned towards the z-direction, i.e. insignificant values of mx and my . The magnetic dipole source is placed on the turntable at a well determined position of (2.5, 2.5, 2.1) cm in TCS and the test measurement methodology of the MMF facility is used to capture its magnetic signature and provide the data to the stochastic solver. In Fig. 15, the measured and the model generated

Fig. 15. Measured vs modeled magnetic field components of the calibrated dipole source (upper figure) and residual magnetic field (lower figure).

Fig. 13. Two plane configuration with radius r = 20 cm.

magnetic field components are compared at the twelve measurement points (sensors), while the predicted variables of the dipole model and the metrics of this test scenario are presented in Tables 1 and 2.

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Table 1 Model Prediction – Calibrated Dipole with weak magnetic moment.

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m|(mAm2)

Theoretical Model

Predicted Model

2.5 2.5 2.1 0 0 2 2

2.4 2.4 2.2 0.022 0.018 1.931 1.931

Table 2 Evaluation Criteria – Calibrated Dipole with weak magnetic moment. Goodness of Fit Relative Goodness of Fit C rel [%] Absolute Goodness of Fit C abs [nT] Position Deviation C pos [mm]

4.1 1.926 1.73

Evidently, the deviation between the identified and the theoretical (test object’s position on the turntable) models’ positions is less than 2 mm, while the relative deviation between the measured and modeled magnetic fields is 4.1%, designating that the estimated parameters of the dipole model can essentially reproduce the magnetic signature of the calibrated dipole source.

4.2. Ulysses dipole with strong magnetic moment The Ulysses MCF reference magnet is used as an EUT. This dipole magnet (shown in Fig. 16) has a strong magnetic moment
 oriented towards all directions mx ; my ; mz , but the magnitude of the magnetic moment is unknown. The two plane configuration is used as a measuring setup and the radial distance of the fluxgate sensors is fixed at 20 cm (the magnet generates a strong magnetic field in terms of SNR) from the center of the turntable. The Ulysses MCF reference magnet is placed at (0, 0, 3.3) cm in TCS, its magnetic signature is captured with the MMF facility and the measured field data are employed to estimate a dipole model. The magnetic field components generated by the model are compared to the measured signature in Fig. 17 at the twelve magnetometers and the resulting model and the evaluation criteria are presented in Tables 3 and 4 respectively.

Fig. 17. Measured vs modeled magnetic field components of Ulysses MCF reference magnet (upper figure) and residual magnetic field (lower figure).

Table 3 Model Prediction – Ulysses dipole with strong magnetic moment.

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m|(mAm2)

Theoretical Model

Predicted Model

0 0 3.3 unknown unknown unknown unknown

0 0 3.2 501 491.4 415 815.3

Table 4 Evaluation Criteria – 2 dipoles with parallel magnetic moments. Goodness of Fit Relative Goodness of Fit C rel [%] Absolute Goodness of Fit C abs [nT] Position Deviation C pos [mm]

Fig. 16. Ulysses dipole with strong magnetic moment.

1.2 5.006 2.23

The relative deviation between the measured and modeled magnetic fields (2.4%) and the position deviation (1 mm) eventually confirm the ability of the predicted dipole model to recreate the measured data and represent the Ulysses MCF reference dipole magnet.

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4.3. Two dipoles with parallel magnetic moments Two similar dipoles with aligned magnetic moments (their strongest magnetic moment component is z-oriented and approximately 30 mAm2), separated by 20 cm have been measured in the MMF facility and modeled employing the RIBOSOME software and the MDM solver. The spatial separation of the two dipoles enables the modeling of their measured magnetic signature as two distinct sources, since the quadrupole moment tensor (product of magnetic dipole moment and separation interval) is negligible at comparable measurement distances. The measured magnetic field data that are provided to the MDM solver include the superposition of both dipoles’ contributions (Eq. (2)) and the modeling algorithm is capable of identifying 12 parameters (6 variables for each individual magnetic source). It should be noted that the location of the dipole sources on the turntable during the measurements may be determined with high accuracy (less than ±1 mm), while their magnetic moments are a priori unknown. Results for an indicative test scenario are provided in Fig. 18 and in Tables 5 and 6. The relative deviation between the measured and modeled magnetic fields is less than 2% and the maximum deviation between the theoretical and the predicted positions of the EUT is approximately 2.2 mm. Thus, the results clearly signify that the demonstrated measurement methodology that manifests the

Table 5 Model prediction – 2 dipoles with parallel magnetic moments.

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m|(mAm2)

Theoretical Model

Predicted Model

Dipole 1

Dipole 2

Dipole 1

Dipole 2

2.5 12.5 0.1 unknown unknown unknown unknown

2.5 7.5 0.1 unknown unknown unknown unknown

2.6 12.3 0.1 3.599 0.41 28.03 28.266

2.3 7.6 0.1 0.202 2.439 30.85 30.948

Table 6 Evaluation criteria – 2 dipoles with parallel magnetic moments. Goodness of Fit Relative Goodness of Fit C rel [%] Absolute Goodness of Fit C abs [nT] Position Deviation C pos [mm]

1.2 5.006 2.23

multiple sensor ‘‘snap-shot” measurement concept, as well as the modeling procedure, achieve reliable resulting models in cases of more complex EUTs. 4.4. Two dipoles with antiparallel magnetic moments The same dipoles configured with antiparallel magnetic moments (one of the dipoles is flipped in the z-direction) are separated by 20 cm and used as EUT. The results that are presented in Fig. 19 and in Tables 7 and 8 are acceptable in terms of relative goodness of fit value (<2%) and deviation between the theoretical and the modeled EUT’s position (approximately 3 mm for dipole 2). 4.5. Current-fed coil A closed loop of electric current is shown in Fig. 20. The circular coil has small dimensions and may be considered as a magnetic dipole source when DC current is supplied by a twisted-wire pair. The current loop has an inner diameter of 54 mm, while its width is approximately 3.5 mm and is composed of 280 (±1%) turns. The coil is connected to a DC power supply providing a steady current of 100 mA. According to magnetostatics, the magnetic dipole moment of the current loop emerges perpendicular to the direction of the current, i.e. z-oriented when the coil is placed at the xy plane and is negligible towards x and y directions. Moreover, the magnitude of the magnetic moment can be calculated to an approximate value of 68.7 mAm2 due to the characteristics of the dipole source [14]. The current loop is placed on the turntable, its magnetic field is captured with the MMF facility and the parameters of the modeling dipole are estimated. The modeled vs measured magnetic signatures at the twelve measuring sensors are shown in Fig. 21. Finally, the resulting dipole model and its metrics are presented in Tables 9 and 10 respectively. The relative deviation between the measured and modeled magnetic fields (C rel evaluation criterion) is approximately 3% and the deviation between the theoretical and the predicted positions of the EUT (C pos evaluation criterion) is 2.45 mm, eventually confirming the accuracy of the model prediction. 4.6. Collocated dipole and quadrupole

Fig. 18. Measured vs modeled magnetic field components of two dipoles with parallel magnetic moments (upper figure) and residual magnetic field (lower figure).

Finally, two dipoles with antiparallel magnetic moments, separated by approximately 7 mm, thus forming a collocated dipole and quadrupole, are used as EUT. The dipoles’ separation is oriented towards the x-direction, while the strongest component of

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Fig. 20. Current fed coil.

Fig. 19. Measured vs modeled magnetic field components of two dipoles with antiparallel magnetic moments (upper figure) and residual magnetic field (lower figure).

Table 7 Model Prediction – 2 dipoles with Antiparallel magnetic moments.

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m|(mAm2)

Theoretical Model

Predicted Model

Dipole 1

Dipole 2

Dipole 1

Dipole 2

7.5 2.5 0.1 unknown unknown unknown unknown

12.5 2.5 0.1 unknown unknown unknown unknown

7.4 2.4 0.2 0.211 3.149 31.81 31.97

12.2 2.6 0.1 0.758 3.734 28.23 28.49

Table 8 Evaluation Criteria – 2 dipoles with Antiparallel magnetic moments. Goodness of Fit Relative Goodness of Fit C rel [%] Absolute Goodness of Fit C abs [nT] Position Deviation C pos [mm]

1.6 5.92 3.16

their magnetic moments (about 30 mAm2) is z-oriented. The dipoles’ configuration is shown in Fig. 22. The magnetic field contribution generated by this source is measured in components with

Fig. 21. Measured vs modeled magnetic field components of the current fed coil (upper figure) and residual magnetic field (lower figure).

the use of the developed facility and the measured data are provided to the MDM solver. The estimated model parameters and the model metrics are shown in Tables 11 and 12 respectively, while the measured vs modeled magnetic field components are depicted in Fig. 23.

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Table 9 Model Prediction – Current fed coil.

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m|(mAm2)

Theoretical Model

Predicted Model

12.5 7.5 2.1 0 0 68.7 68.7

12.4 7.3 2 0.064 0.522 68.65 68.65

–

Collocated

Dipole

and

Goodness of Fit Relative Goodness of Fit C rel [%] Absolute Goodness of Fit C abs [nT] Position Deviation C pos [mm]

2.3 2.419 1.41

Table 10 Evaluation Criteria – Current fed coil. Goodness of Fit Relative Goodness of Fit C rel [%] Absolute Goodness of Fit C abs [nT] Position Deviation C pos [mm]

3.1 23.982 2.45

Fig. 22. Collocated quadrupole and dipole.

Evidently, the resulting model metrics validate the accurate model prediction since the relative goodness of fit criterion C rel is 2.3% and the position deviation criterion C pos is 1.41 mm. Moreover, the estimated quadrupole moment tensor verifies the accuracy in the prediction of the EUT configuration, since it exhibits its strongest value in the xz component (separation of dipoles is in x-direction and their magnetic moments are z-oriented), while the values of other components are negligible. Finally, it should be noted that the developed facility, test measurement methodology and MDM solver are capable of successfully identifying the model parameters of composite magnetic sources that exhibit more complex magnetic signatures.

Fig. 23. Measured vs modeled magnetic field components of the collocated dipole and quadrupole source (upper figure) and residual magnetic field (lower figure).

Table 11 Model Prediction – Collocated Dipole and quadrupole. Theoretical Model

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m| (mAm2)

Predicted Model

Dipole 1

Dipole 2

Dipole

0.35 0 0.9 unknown unknown unknown unknown

0.35 0 0.9 unknown unknown unknown unknown

x (cm) y (cm) z (cm) mx (mAm2) my (mAm2) mz (mAm2) |m| (mAm2)

Quadrupole 0.1 0 0.8 2.598 2.588 0.611 3.718

x (cm) y (cm) z (cm) Q11 (mAm3) Q12 (mAm3) Q13 (mAm3) Q22 (mAm3) Q23 (mAm3) q (mAm3)

g

0.1 0 0.8 0.008 0.009 0.095 0 0 0.096 0.995

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5. Conclusion The scope of this paper is to analyze the research and development activities leading to the construction of a novel MMF facility that targets to measure and characterize the DC magnetic signature of space equipment. The facility is extensively illustrated and its capability to accurately characterize magnetic field signatures is demonstrated with a set of known magnetic sources. Based on the validation results performed at ESA-ESTEC by employing the test verification scenarios, it is evident that the estimated dipole and quadrupole models comply in all cases with the evaluation criteria. Moreover, the facility operates remarkably well according to the design specifications and its functionality and usability are considered exceptional, especially regarding mechanical parts operation. Various disadvantages of the MMF facility, however, have been already identified. The facility does not have the capability to perm/deperm a spacecraft unit, feature that is usually very useful in EMC measurement campaigns. Regarding the mechanical design, the construction is somewhat complex, not effortlessly portable and requires increased man effort for installation, calibration and verification of its operation. Although the mechanical structure requires gentle physical approaching, due to the dimensioning requirements and constraints, the mechanical flexibility of several parts allows for physical contact without any damage up to a reasonable level. Finally, the central turntable elevation system is designed to preferably operate at a room temperature of about 20 °C. On the contrary, the proto-MMF has multiple advantages in comparison to existing facilities. The facility can handle up to 50 kg EUT load, which could be a small satellite (MCF turntable may lose stability with such loads) and a cylindrical space of about 2 m diameter is available for EUT placement, provided that that the sensors are radially moved to their outer position. The accuracy of the magnetometers’ positioning is guaranteed to a much higher level than in MCF, because of the common panel structure design. The structure calibration verifies the inherent positioning precision, in contrast to MCF sensors that are mounted on brackets and their tolerance (position uncertainty) depends on the relevant positioning between the sensors and the EUT turntable. The increased accuracy of the facility, combined with the fast measurement procedure, results in more reliable and repeatable test results. Furthermore, a calibration test with a well-defined source (e.g. the current fed coil) may a-priori be performed in order to verify the reliability of the measurements to be acquired. If the calibrated measuring setup configuration is maintained, magnetic signature measurements of different EUTs can be directly realized. Finally, the fluxgate magnetometers may be replaced by different types of sensors (e.g. search or air coils) in order to additionally measure time varying magnetic fields and supplementary characterize the AC magnetic signature of space EUTs. The MMF facility is currently installed at the premises of ESAESTEC and already utilized to measure and characterize static magnetic signatures generated by spacecraft equipment.

6. Recommendations In the present section, suggestions and recommendations for scientists who will work on this issue are presented. Firstly, the proto-MMF facility requires careful physical approaching and handling, cautious tighten-untighten of the screws that fix the sensors (no over-tightening) and preferably operates at a room temperature of approximately 20 °C. The operator should not be close to the facility during each step of the measurement procedure (1 s measurement time of each step) in order to secure the reliability of the acquired test data. Moreover, the positioning of the magne-

tometers is a crucial issue; while the sensors’ positions shall guarantee a good SNR of the measured magnetic signature, their distance to the center of the turntable shall nonetheless be approximately 3–5 times the largest dimension of the EUT in order to ensure the dipole approximation. Finally, the positions of the sensors may be calibrated prior to measurements with a current fed coil in order to verify the reliability of the EUTs’ DC magnetic signature measurements for purposes of magnetic cleanliness in space applications. Acknowledgements The authors would like to express their gratitude to ESA ESTEC personnel for their valuable contribution and support throughout the project. This innovative Multi Magnetometer Facility has been developed in the frame of ESA contract 4000111736/14/NL/GLC on Multi-Magnetometer Methods for Magnetic Dipole Modelling. References [1] E. Friis-Christensen, H. Lühr, G. Hulot, Swarm: A constellation to study the Earth’s magnetic field, Earth Planets Space 58 (4) (2006) 351–358. [2] K.H. Glassmeier, H. Boehnhardt, D. Koschny, E. Kührt, I. Richter, The Rosetta mission: flying towards the origin of the solar system, Space Sci. Rev. 128 (1–4) (2007) 1–21. [3] O. Grasset, M.K. Dougherty, A. Coustenis, E.J. Bunce, C. Erd, D. Titov, M. Blanc, A. Coates, P. Drossart, L.N. Fletcher, H. Hussmann, JUpiter ICy moons Explorer (JUICE): An ESA mission to orbit Ganymede and to characterise the Jupiter system, Planet. Space Sci. 78 (2013) 1–21. [4] A. Anselmi, G.E. Scoon, BepiColombo, ESA’s Mercury cornerstone mission, Planet. Space Sci. 49 (14) (2001) 1409–1420. [5] A. Junge, F. Marliani, in: August. Prediction of DC Magnetic Fields for Magnetic Cleanliness on Spacecraft, IEEE, 2011, pp. 834–839. [6] A. Morrish, H., The Physical Principles of Magnetism, John Wiley & Sons, New York, 1965. [7] ECSS-E-HB-20-07A Space Engineering, Electromagnetic Compatibility Handbook, Requirements & Standards Division, Noordwijk, The Netherlands, 2012. [8] Mehlem, K., Wiegand, A. and Weickert, S., 2012, May. New developments in magnetostatic cleanliness modeling, in: Aerospace EMC, 2012 Proceedings ESA Workshop on (pp. 1-6). IEEE. [9] E. Carrubba, A. Junge, F. Marliani, A. Monorchio, Particle swarm optimization to solve multiple dipole modelling problems in space applications, in: Aerospace EMC, 2012 Proceedings ESA Workshop on, IEEE, 2012, pp. 1–6. [10] N.C. Kapsalis, S.D.J. Kakarakis, C.N. Capsalis, Prediction of multiple magnetic dipole model parameters from near field measurements employing stochastic algorithms, Prog. Electromag. Res. Lett. 34 (2012) 111–122. [11] S.D.J. Kakarakis, N.C. Kapsalis, C.N. Capsalis, A semianalytical heuristic approach for prediction of eut’s multiple dipole model by reducing the number of heuristics, IEEE Trans. Electromagn. Compat. 57 (1) (2015) 87–92. [12] S.T. Spantideas, C.N. Capsalis, Validation of a source identification method for prediction of low-frequency magnetic fields in space missions, IEEE Magn. Lett. 9 (2018) 1–5, https://doi.org/10.1109/LMAG.2017.2775185. [13] A. Junge. Ulysses Mobile Coil Facility Specification, ESA – ESTEC, Noordwijk, Netherlands, TEC-EEE/2007.184/AJ, 2007. [14] J.D. Jackson, Classical Electrodynamics, John Wiley & Sons, 2007. [15] D.J. Griffiths, Introduction to Electrodynamics, Prentice Hall, New Jersey, 1962. [16] S. Spantideas, N. Kapsalis, Magnetic dipole modeling for DC and low frequency AC magnetic fields in space missions, in: C. Nikolopoulos (Ed.), Electromagnetic Compatibility for Space Systems Design, IGI Global, Hershey, PA, 2018, pp. 71–114, doi:10.4018/978-1-5225-5415-8.ch003. [17] S. Spantideas, N.C. Kapsalis, S.D.J. Kakarakis, C.N. Capsalis, A method of predicting composite magnetic sources employing particle swarm optimization, Prog. Electromag. Res. M 39 (2014) 161–170. [18] BIPM, I., IFCC, I., IUPAC, I. and ISO, O., 2008. Evaluation of measurement data— guide for the expression of uncertainty in measurement. JCGM 100: 2008. Citado en las, p.167. [19] M. Nicoletto, D. Boschetti, I. Marziali, F. Pennecchi, V. Basso, A. Malengo, A. Junge, Assessment of uncertainty affecting equivalent magnetic dipole models, in: Aerospace EMC (Aerospace EMC), 2016 ESA Workshop on, IEEE, 2016, pp. 1–6. [20] S.J. Kakarakis, S.T. Spantideas, N.C. Kapsalis, C.N. Capsalis, A. Junge, A softwarebased calibration technique for characterizing the magnetic signature of EUTs in measuring facilities, IEEE Trans. Electromagn. Compat. 59 (2) (2017) 334– 341, https://doi.org/10.1109/TEMC.2016.2615132. [21] C. Güttler, O. Hillenmaier, U. Auster. Measurement of magnetic field emissions at low frequencies, ESA Workshop on Aerospace EMC, Florence, Italy, 2009. [22] S. Engelke, K. Bubeck, A. Kistner, L. Trougnou. Soft- and hardware upgrade of the mobile coil facility, 2016 ESA Workshop on Aerospace EMC (Aerospace EMC), Valencia, 2016, pp. 1-6. doi: 10.1109/AeroEMC.2016.7504539.