Method for characterizing an anechoic chamber and associated devices

Abstract

Method for characterizing an anechoic chamber and associated devices. The present invention relates to a method for characterizing an anechoic chamber (10), the method comprising a step of: - for several measurement points spatially arranged according to a circle, acquisition of a signal), - conversion of the acquired signals into components, each component being the value of a respective order of the decomposition of the sum of the acquired signals into phase modes, - filtering of each component by application of a compensation filter eliminating the frequency dependence, - estimation of the amplitude and direction of arrival of parasitic scatterers by solving a system of equations according to which each filtered component is equal to a sum of contributions of the parasitic scatterers, each depending on the amplitude and direction of arrival of the scatterer,and - determination of the characterization parameter from the estimated amplitudes and directions of arrival. Figure for the abbreviation: figure 1,

Description

Title of the invention: Method for characterizing an anechoic chamber and associated devices

[0001] The present invention relates to a method for characterizing a portion of an anechoic chamber. The present invention also relates to associated devices, namely a device for determining at least one parameter characterizing the portion, a system for characterizing the portion, and an anechoic chamber.

[0002] An anechoic chamber (or anechoic chamber) is a space specifically designed to emulate the propagation of a wave in free space. The space is enclosed by walls, whether metallic or not. Each wall (side, floor, or ceiling) is lined with materials that absorb electromagnetic waves. This is the lining of the anechoic chamber. This allows for a controlled electromagnetic environment for testing and measuring the performance of antennas or other electromagnetic devices.

[0003] A volume is often defined within the anechoic chamber in which these tests and performance measurements are to be carried out because this volume exhibits minimal amplitude and phase undulation. This volume is generally called the quiet zone. The residual undulation arises primarily from the presence of echoes insufficiently attenuated by the absorbers.

[0004] It is therefore desirable to be able to electromagnetically characterize the quiet zone of an anechoic chamber.

[0005] It is known to use a technique called VSWR (for the corresponding English name "Voltage Standing Wave Ratio") to determine the standing wave ratio. This technique is based on the principles of determining reflections in a microwave transmission line.

[0006] This technique assumes that the direct and reflected waves meet at a point along a line along which a probe moves. During the movement of the probe, the variation in the amplitude of the received signal produces a VSWR model, from which its reflectivity can be derived.

[0007] However, an interference pattern measured in a real chamber can be much more complex than the simple model assumed by the VSWR model. This is because the chamber environment can violate many of the assumptions on which the method is based, such as the presence of a coherent wavenumber strictly greater than 2, an insufficient probe displacement length for obtain at least one complete period (distance between 2 max or 2 min of the curve) of the amplitude ripple.

[0008] Furthermore, this requires moving an antenna along a translational axis for a given antenna orientation and polarization. An additional positioner is therefore added, which implies partially or completely removing the absorbers present on the ground. The measurement is thus distorted, since the nominal layout of the chamber is altered. This problem is exacerbated when the anechoic chamber itself is equipped with a positioner that does not easily allow the measurement probe to perform the desired spatial scanning.

[0009] There is therefore a need for a method of characterizing a part of an anechoic chamber which is easier to implement while allowing for a more precise characterization.

[0010] To this end, the description describes a method for characterizing a portion of an anechoic chamber, the characterization method comprising:

[0011] - an acquisition phase comprising:

[0012] - for several measurement points in the part, a signal acquisition step electromagnetic signals received by a sensor positioned at the measurement point, to obtain a plurality of acquired electromagnetic signals,

[0013] the measurement points being spatially arranged according to a circle,

[0014] - a phase of determining at least one parameter for characterizing the part Based on the acquired electromagnetic signals, the determination phase includes a step of:

[0015] - conversion of electromagnetic signals acquired at a given frequency into a set of components, each component being the value of a respective order of the decomposition of the sum of the acquired electromagnetic signals into phase modes,

[0016] - filtering of each component by applying a compensation filter on each component eliminating the frequency dependence of the component, to obtain filtered components,

[0017] - estimation of the amplitude and direction of arrival of each of the diffusers parasites present in the anechoic chamber by solving a system of equations according to which each filtered component is equal to a sum of contributions of the parasitic scatterers to the value of the filtered component, the contribution of a parasitic scatterer depending on the amplitude and direction of arrival of the scatterer, to obtain estimated amplitudes and estimated directions of arrival, and

[0018] - determination of the value of a characterization parameter at the given frequency based on estimated amplitudes and estimated arrival directions.

[0019] According to other advantageous aspects of the invention, the characterization method comprises one or more of the following features, taken individually or in all technically possible combinations:

[0020] - a single sensor is used during the implementation of the acquisition phase, the acquisition phase including a step of moving the sensor to each measurement point.

[0021] - each sensor is an antenna adapted to receive signals extending over a predefined frequency band, the predefined frequency band being included in the range extending between 30 MHz and 3,000 MHz.

[0022] - the characterization parameter is the standing wave rate or a parameter representative of the reflectivity of the anechoic chamber.

[0023] - during the determination phase, the conversion, filtering, estimation steps and determination are implemented for several frequencies to obtain the frequency variation of the characterization parameter.

[0024] - each contribution is equal to the product of the amplitude and an exponential complex whose argument is the direction of arrival.

[0025] - the estimation step involves the implementation of a matrix pencil technique to estimate the directions of arrival.

[0026] - the matrix pencil technique involves the use of a first matrix of Henkel and a second Henkel matrix, the first Henkel matrix being such that / ••• Ww-w •••

[0027] where:

[0028] - denotes the filtered component of order x,

[0029] - M denotes the maximum order of the components obtained in the conversion step, and

[0030] - L is the pencil parameter,

[0031] the second matrix H2 being such that jSW-M+] ••• - \sw M _ L ...sw M

[0032] - the matrix pencil technique includes a thresholding of the values ​​of each Henkel matrices to eliminate values ​​with noise, values ​​being eliminated when these values ​​do not meet a condition with respect to a predetermined threshold.

[0033] - the estimation step involves applying a least squares technique to estimate the amplitudes.

[0034] - a quiet zone is defined for the anechoic chamber, the part characterized by the characterization process being the quiet zone

[0035] The description also relates to a device for determining at least one parameter for characterizing a part of an anechoic chamber, the determination device being specific to:

[0036] - to obtain, for several measurement points in the part, an electromagnetic signal acquired, each electromagnetic signal being the electromagnetic signal received by a sensor positioned at the measurement point, the measurement points being spatially arranged in a circle,

[0037] - determine at least one parameter for characterizing the part from the signals acquired by:

[0038] - conversion of electromagnetic signals acquired at a given frequency into a a set of components, each component being the value of a respective order of the decomposition of the sum of the acquired electromagnetic signals into phase modes,

[0039] - filtering of each component by applying a compensation filter on each component eliminating the frequency dependence of the component, to obtain filtered components,

[0040] - estimation of the amplitude and direction of arrival of each of the diffusers parasites present in the anechoic chamber by solving a system of equations according to which each filtered component is equal to a sum of contributions of the parasitic scatterers to the value of the filtered component, the contribution of a parasitic scatterer depending on the amplitude and direction of arrival of the scatterer, to obtain estimated amplitudes and estimated directions of arrival, and

[0041] - deduction of the value of a characterization parameter at the given frequency based on estimated amplitudes and estimated directions of arrival.

[0042] The description also describes a system for characterizing a portion of an anechoic chamber, the characterization system comprising:

[0043] - an acquisition device, the acquisition device comprising at least one sensor, the acquisition device being suitable for, for several measurement points in the part, acquiring an acquired electromagnetic signal, each electromagnetic signal being the electromagnetic signal received by a sensor positioned at said measurement point, the measurement points being spatially arranged in a circle, and

[0044] - a determining device, the determining device being such that previously described.

[0045] The description also relates to an anechoic chamber equipped with a system for characterizing a part of an anechoic chamber, the characterization system being as previously described.

[0046] In this description, the expression "specific to" means interchangeably "suitable for", "adapted to" or "configured for".

[0047] The invention will become clearer upon reading the following description, given solely by way of non-limiting example, and made with reference to the drawings in which:

[0048] - [Fig. 1] [Fig. 1] is a schematic cross-sectional representation of a chamber anechoic or anechoic chamber equipped with a system for characterizing a portion of the anechoic chamber,

[0049] - [Fig.2] [Fig.2] is a diagram representing the spatial arrangement of points of measurement forming a uniform circular network,

[0050] - [Fig.3] [Fig.3] is a flowchart illustrating an example of the implementation of a example of the implementation of a process for characterizing the part of the anechoic chamber,

[0051] - [Fig.4] [Fig.4] is a perspective diagram allowing the definition of quantities identifying the positioning of the measurement points in space, and

[0052] - [Fig.5][Fig.6][Fig.7][Fig.8] Figures 5 to 8 are graphs showing results obtained by simulation by the Applicant through the implementation of examples of a process for characterizing the part of the anechoic chamber.

[0053] An anechoic chamber 10 seen in section is shown in [Fig.1].

[0054] The anechoic chamber 10 comprises a floor 12, a ceiling 14 and side walls 16.

[0055] Each wall 12, 14 and 16 is covered with one or more absorber(s) 18 to absorb the incident waves transmitted by an emitter 19 located in an anechoic chamber 10 and thus make the medium contained in the space delimited by the walls close to a free space without echoes.

[0056] The anechoic chamber 10 is provided with a characterization system 20 of a part of the anechoic chamber 10.

[0057] The characterization system 20 is suitable for implementing a corresponding characterization process, this characterization process comprising two phases: an acquisition phase PI and a determination phase P2.

[0058] The characterization system 20 thus seeks to quantify the imperfections of the anechoic chamber 10 by determining at least one characterization parameter of a part of the anechoic chamber 10.

[0059] The characterization parameter is, for example, a parameter representative of the reflectivity, that is to say the proportion of electromagnetic energy reflected at the surface of the absorber 18 covering each wall 12, 14 and 16 of the anechoic chamber 10.

[0060] More specifically, in the example described, the representative parameter of reflectivity is the transfer function of the anechoic chamber 10.

[0061] The transfer function of the anechoic chamber 10 is the transfer function between a signal emitted by the transmitter 19 and a signal received by a sensor 28.

[0062] Preferably, the transfer function is a transfer function in both amplitude and phase.

[0063] Advantageously, the transfer function is given for different directions and different polarizations of the emitted electromagnetic waves.

[0064] Other characterization parameters are conceivable, such as the standing wave rate or the angle of arrival and the amplitude of the received waves.

[0065] Preferably, the part characterized by the characterization system 20 is the quiet zone 22. The quiet zone 22 is schematically delimited by dotted lines on [Fig.1].

[0066] The characterization system 20 comprises an acquisition device 24 and a determination device 26.

[0067] The acquisition device 24 comprises a sensor 28, an acquisition unit 29 and a positioner 30.

[0068] In the example described, the sensor 28 is an antenna adapted to receive signals extending over a predefined frequency band.

[0069] According to one example, the predefined frequency band is the very high frequency band which extends between 30 MHz and 300 MHz.

[0070] This frequency band is more often referred to as the VHF band, the abbreviation VHF referring to the corresponding English designation of "Very High Frequency" "

[0071] Sensor 28 is thus a VHF antenna.

[0072] According to another example, the predefined frequency band is the ultra-high frequency band which extends between 300 MHz and 3000 MHz.

[0073] This frequency band is more often referred to as the UHF band, the abbreviation UHF referring to the corresponding English name of "Ultra High Frequency".

[0074] Sensor 28 is thus a UHF antenna.

[0075] The positioner 30 is adapted to move the sensor 28 from one measuring point to another measuring point.

[0076] In the example described, the measurement points are arranged as seen in [Fig.2],

[0077] The measurement points comprise eight measurement points PMI to PM8.

[0078] The number I of measurement points is therefore 8 in this simple example but could to be much larger, for example more than 100.

[0079] The measurement points PMI to PM8 are spatially arranged according to a circle whose center is point O on the [Fig.2].

[0080] The positioner 30 is therefore a positioner adapted to perform a rotation around an axis of rotation passing through the center O. Such a positioner 30 is generally available in an anechoic chamber 10.

[0081] The radius of the circle is denoted R in what follows.

[0082] Moreover, in the example described, the distance between each pair of neighboring PMI to PM8 measurement points is identical.

[0083] The set of measurement points PMI to PM8 therefore forms a uniform circular network.

[0084] The number I of measurement points allows for the determination of an angular sampling of space. For an example of 360 measurement points, the sampling is 1°.

[0085] The sensor 28 is connected to the acquisition unit 29.

[0086] The acquisition unit 29 is a unit for acquiring the signal captured by the sensor 28 in order to obtain its amplitude and phase.

[0087] Thus, the acquisition device 24 is suitable for implementing the first phase PI of the characterization process, that is to say, for several measurement points PMI to PM8, acquiring the electromagnetic signal received by the sensor 28 positioned at said measurement point, in order to obtain a plurality of acquired electromagnetic signals.

[0088] The determination device 26 is suitable for determining at least one characterization parameter of the quiet zone 22 from the signals acquired by the acquisition device 24.

[0089] The determination device 26 is thus suitable for obtaining the measurements acquired by the acquisition device 24 and suitable for implementing a determination phase P2 of the characterization process which will be described later.

[0090] The determination device 26 is a calculator.

[0091] The determination device 26 is thus an electronic circuit designed to to manipulate and / or transform data represented by electronic or physical quantities in computer registers and / or memories into other similar data corresponding to physical data in register memories or other types of display devices, transmission devices or storage devices.

[0092] As specific examples, the determination device 26 is implemented in the form of a programmable logic component, such as an FPGA (Field Programmable Gate Array) or an integrated circuit, such as an ASIC (Application Specified Integrated Circuit).

[0093] Alternatively, when the determination phase P2 is carried out in the form of one or more software programs, i.e., in the form of a computer program, also called a computer program product, it is further suitable for being stored on a computer-readable medium, not shown. The computer-readable medium is by For example, a readable medium can be a medium capable of storing electronic instructions and being connected to a computer system bus. Examples of such a medium include an optical disc, a magneto-optical disc, ROM, RAM, any type of non-volatile memory (such as FLASH or NVRAM), or a magnetic card. A computer program containing software instructions is then stored on this readable medium.

[0094] The operation of the characterization system 20 is now described with reference to [Fig.3] which illustrates an example of implementation of a process for characterizing the quiet zone 22 of the anechoic chamber 10.

[0095] The characterization process seeks to characterize the quiet zone 22 by at least one characterization parameter.

[0096] In the example described, the characterization parameter is a parameter representative of the reflectivity of the anechoic chamber 10.

[0097] As previously indicated, in this example of implementation, the characterization process comprises two phases: an acquisition phase PI and a determination phase P2.

[0098] The PI acquisition phase comprises a succession of two steps: a displacement step E10 and an acquisition step E20.

[0099] The two movement steps E10 and acquisition steps E20 are implemented for each measurement point to be carried out in the quiet zone 22.

[0100] During the displacement step E10, the sensor 28 is positioned at the measurement point by the positioner 30.

[0101] The sensor 28 thus positioned then captures the signal to send it to the acquisition unit 29.

[0102] At the end of the PI acquisition phase, a plurality of acquired electromagnetic signals is thus obtained.

[0103] It is assumed that the quiet zone 22 can be modeled by a set of N parasitic diffusers emitting signals to the sensor 28 at each measurement point PMI to PM8.

[0104] Each parasitic diffuser (more simply diffuser hereafter) is a model of an imperfection in the anechoic chamber 10.

[0105] Each diffuser is identified by an integer n and has a complex amplitude denoted Bn.

[0106] Each diffuser n is also located at a distance dn from the central measurement point and at a distance dn>idu i-th measurement point PMi.

[0107] Therefore, the signal acquired at the i-th measurement point PMi can be written in the following form:

[0108] Si = + Wi

[0109] Where: d„j = av“et*”les l0"ï"udc' respectively i-th measurement point PMi and diffuser n and the colatitude of diffuser n (more commonly called the arrival direction), and • wi is the white noise contribution at the i-th measurement point PMi.

[0110] After a Taylor expansion on dni, the following equality is obtained: [°in] = )2

[0112] Assuming a far-field diffuser dn^ + œ, we obtain:

[0113] dn - d^ = Rsin (Gn) cos (- ¢.)

[0114] Thus, under this hypothesis, the signal received at the i-th measurement point PMi can be expressed as follows:

[0115] yN g gjkRsin(Ôn)cos(<^^ + 1 “11=1 n 1

[0116] The determination phase P2 aims to determine at least one characterization parameter of the quiet zone 22 from the acquired electromagnetic signals.

[0117] The determination phase P2 comprises a conversion step E30, a filtering step E40, an estimation step E50 and a determination step E60.

[0118] During the conversion step E30, the determination device 26 converts the electromagnetic signals acquired at a given frequency into a set of components.

[0119] Each component is the value of a respective order of the decomposition of the sum of the acquired electromagnetic signals into phase modes.

[0120] In the following, each component is denoted by the index m denoting the order of the phase mode.

[0121] The index m is a relative integer that can take values ​​between '00 and +oe.

[0122] In practice, the number of components calculated is finite.

[0123] It is assumed in what follows that the number of components is limited by a cutoff order M, so that the phase order components m are calculated for any value of m between -M and +M.

[0124] It should nevertheless be noted that it is possible to calculate more components and to consider only the components of a phase mode having an order less than or equal in absolute value to M during the estimation step E50.

[0125] The determination device 26 performs the conversion at least by applying an inverse Fourier transform to obtain the components.

[0126] The inverse Fourier transform is, for example, applied to a vector obtained by processing acquired signals.

[0127] The processing includes at least one sampling of the multiplication of the acquired signals.

[0128] In addition, the processing may also include filtering, in particular low-pass filtering, and / or conversion to a lower frequency band.

[0129] In fact, by definition, the component of the phase mode m is given by the following expression:

[0130] _ iyN m

[0131] The components of each phase mode are written as: 101321

[0133] Where: • j denotes the complex number such that y2 = -1, • Jp is the p-th Bessel function of the first kind, and • k is the wave number.

[0134] This expression is obtained by omitting Gaussian white noise to simplify the notation and by using the Jacobi-Anger identity according to which:

[0135] eikR^W^J^

[0136] The preceding expression for sm can be simplified by noting that y7 £22- _ 1 l 1 if only if p - m = Iz where z is any integer.

[0137] Now, the term J p ( Ofsin ( 0n ) ) decreases sharply towards 0 as z * 0. fl then comes for z = 0: 101381 = )^.

[0139] At the end of the conversion step E30, the determination device 26 therefore has a set of sm components.

[0140] The components thus obtained have the particularity of depending of the frequency (via the presence of the wavenumber).

[0141] The E40 filtering step aims to eliminate this frequency dependence.

[0142] For this purpose, during the filtering step E40, the determining device 26 applies on each component a compensation filter eliminating the frequency dependence of the component, to obtain filtered components.

[0143] The compensation filter is denoted W in the following and each filtered component is denoted swm.

[0144] In one embodiment, the applied compensation filter W is expressed as follows:

[0145] W =—J— m JJ^kR )

[0146] where Wm denotes the value of the filter applied to the component m.

[0147] It comes down like this:

[0148] swm=VF / nsm

[0149] The preceding expression thus corresponds to the following relation: 101501 sw„, = wj£^,j"j„(tKsin(M )e».

[0151] Assuming diffusers lie in the plane of the circle, i.e., 6n = 90° V n GN, the frequency-independent component for each phase mode can be written as: 101521

[0153] where z« are the poles such that zn = e^-

[0154] The IL compensation filter makes the components in phase mode dependent only on the complex amplitude Bn and the directions of arrival (]) without frequency dependence.

[0155] According to a more elaborate variant, the applied VF compensation filter is expressed as follows:

[0156] W -------1------ m

[0157] Where I denote the derivative of the m-th Bessel function of the first kind.

[0158] Such a VF compensation filter is particularly suitable for diffusers located outside the plane of the circle, that is to say when 0n £ 90 0 .

[0159] Following the conversion steps E30 and filtering E40, the determination device 26 thus has a set of filtered components for each phase mode order.

[0160] The estimation step E50 aims to obtain the characteristics of each diffuser n, namely the direction of arrival and the complex amplitudes Blt.

[0161] The estimation step E50 is implemented by solving a system of equations according to which each filtered component swm is equal to a sum of contributions of the diffusers to the value of the filtered component swm.

[0162] As will become clearer upon reading the following, this involves solving the system of equations formed by the M equations resulting from the following equality: 101631

[0164] Due to such a shape, such a resolution here amounts to the implementation of a pole-searching technique (the z's) called the matrix pencil method and a pre-filtering of the white noise (before the implementation of the search technique). solutions of the system of equations are the estimated amplitudes B„ and estimated arrival directions (J>n.

[0165] The contribution of a parasitic scatterer depends on the amplitude Bn and the direction of arrival <|)n of the scatterer.

[0166] As indicated previously, according to the example described, each contribution is equal to the product of the amplitude B„ by a complex exponential whose argument is the direction of arrival 0n.

[0167] This leads, for each filtered component, to an equation corresponding to a sum of complex exponentials, namely: 101681

[0169] In the case of [Fig.3], the estimation step E50 comprises two substeps, namely a search substep SE52 and a retrieval substep SE54.

[0170] During the SE52 search substep, the determination device 26 searches for the value of the poles by implementing a pole-finding technique.

[0171] In the example described, the pole-finding technique is a matrix pencil technique.

[0172] A matrix pencil technique allows information to be extracted, here the values ​​of the arrival directions, from a sum of complex exponentials (cissoids).

[0173] The matrix pencil technique seeks to estimate the generalized eigenvalues ​​of a pair of matrices. Such a generalized eigenvalue problem consists of finding a vector V satisfying:

[0174] =

[0175] Where: • Het are the two matrices that make up the matrix pair. These matrices are generally called Henkel matrices. • 2 is a scalar called the generalized eigenvalue of Hi and H2, and • V is the generalized eigenvector of Hi and H2.

[0176] The matrix pencil technique thus involves the use of a first Henkel matrix and a second Henkel matrix H2.

[0177] According to an example, the Henkel matrices H1 and H2 are constructed as follows.

[0178] The first matrix Hi is written as follows:

[0179] ... swLA\ \SWM-M ••• SWW-U

[0180] Where: • L is the pencil parameter. The pencil parameter L is, in general, taken to be equal to 0 because of the symmetrical indexing of the signal once transformed into phase modes.

[0181]

[0182]

[0183]

[0184]

[0185]

[0186]

[0187]

[0188]

[0189]

[0190]

[0191]

[0192]

[0193]

[0194]

[0195] The second matrix H2 is written as follows: ••• ™L\ Wtf-L ... SWM) It is then possible to show that, when -M + N <L<M-N, avec au minimum N < M, les valeurs propres généralisées de la paire de matrices [H2, Hl] sont les pôles 2«. The determination device 26 thus searches for the values ​​of the poles by calculating the generalized eigenvalues ​​of the pair of matrices [H2, H1]. In a more elaborate example, thresholding of the values ​​of each of the Henkel matrices to eliminate values ​​exhibiting noise, the values ​​being eliminated when these values ​​do not meet a condition with respect to a predetermined noise-related threshold. As an illustration of an example of the implementation of such a technique For thresholding, an intermediate matrix H is constructed as follows: s xi SM-Ll SL SM-1 A thresholding of singular values ​​above a certain threshold is performed, to eliminate the values ​​of the intermediate matrix H which are noisy (they are set to 0). For this reason, it is advantageous to choose a threshold inversely proportional to the ratio signal-to-noise ratio. The matrices and H2 then have zero values ​​for the noisy values. This technique makes it possible to effectively eliminate the presence of noise in signal acquisition. During the SE54 obtaining substep, the determination device 26 obtains the complex amplitudes Bn. To do this, the determination device 26 looks for the amplitude values complex numbers Bn allowing for a fit between the values ​​of the set of independent components of the frequency of a Part and the sum Any optimization technique that allows such an adjustment to be made is conceivable here. Thus, according to one example, the determination device 26 applies a least squares technique to estimate the amplitudes Bn.

[0196] At the end of the estimation step E50, the determination device 26 thus has, for each diffuser, an estimate of its amplitude Bn and its direction of arrival <|)n.

[0197] During the determination step E60, the determination device 26 deduces from the elements thus obtained a parameter for characterizing the quiet zone 22.

[0198] Here, the determination device 26 calculates the representative parameter of the reflectivity of the quiet zone 22 by determining the amplitudes of the waves present when the diffusers having the properties determined in the estimation step E50 are present.

[0199] More specifically, the determination device 26 here obtains the transfer function of the anechoic chamber 10.

[0200] According to the example described, the conversion steps E30, filtering E40, estimation E50 and determination E60 are implemented for several frequencies to obtain the frequency variation of the characterization parameter.

[0201] This is schematically represented by an arrow 70 on [Fig.3] and block 80 corresponding to the result, i.e. the frequency variation of the characterization parameter.

[0202] The frequencies used at each iteration are determined according to the frequency band that we wish to characterize for the quiet zone 22 to be characterized.

[0203] The characterization process just described allows good performance in characterizing the quiet zone 22 to be characterized.

[0204] This has been demonstrated by the Applicant through several simulations, the results of which are shown in Figures 5 to 8.

[0205] A first simulation aims to show that it is possible to achieve detection of several diffusers.

[0206] In this simulation, it is assumed that three diffusers are present in the far field in the plane of the circle, with respectively the angles (J^ = 0°, <|)? = -90° and <|>.= 135°.

[0207] The received signals are of the same constant complex amplitude over the entire band with a signal-to-noise ratio (SNR) of 20 dB.

[0208] The radius of the circle is 1.5 m with an angular sampling of 1°.

[0209] The frequency band of interest is from 50 MHz up to 300 MHz.

[0210] In this framework of diffusers in the plane of the circle, the compensation filter w---- fJnfkR)

[0211] is used.

[0212] The implementation of the process makes it possible to obtain the results of figure 5 which represents the estimation of the three angles (|)n on the frequency band of interest.

[0213]

[0214]

[0215]

[0216]

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224]

[0225]

[0226] The angle estimation is correctly performed over the considered frequency band. A few frequency points show a drop in the estimation; this stems from the filter's sensitivity to the presence of nuisance terms in the first-kind Bessel functions at certain points. A second simulation aims to study the influence of colatitude in the same setup as before. The second simulation is based on the presence of a single diffuser whose arrival angle is arbitrarily fixed at 0° and its elevation ©i varies from 90° to 180°. The estimation is done at a single frequency arbitrarily set at 100 MHz. But the results are not limited to this single frequency, thanks to the frequency stability demonstrated in connection with the first simulation (see [Fig.5]). In the second simulation, the following compensation filter is used: W =-------- This is justified by the fact that it is necessary to compensate for the elevation introduced by the variation of the colatitude 0i. The implementation of the process allows us to obtain the results of Figure 6, which represents the 100 MHz estimation of the arrival angle f|>} as a function of the colatitude 0i. It appears that for elevation angles up to 150°, the estimate is accurate. This demonstrates the robustness of the longitudinal component estimation compared to cases where the diffusers are not located in the plane of the circle. In other words, the method is applicable regardless of the diffusers' position (in or out of the plane of the circle). A third simulation was also carried out to determine the influence of noise, which had been neglected in some of the assumptions made previously. This third simulation is based on the observation that the first and second simulations were performed assuming a signal-to-noise ratio of 20 dB, which may not be the case in practice. The aim is therefore to analyze the variance of the estimator for a given broadcaster as a function of the signal-to-noise ratio. The diffusion model is similar to that of the second simulation except that the diffuser is assumed to be in the plane of the circle. The longitudinal part of the arrival direction is arbitrarily fixed at = 0°. 1000 Monte Carlo simulations are generated at each noise level considered. The signal-to-noise ratio varies from -10 dB to 25 dB, and the estimation is performed at 100 MHz.

[0227] Estimates of the direction of arrival as a function of the signal-to-noise ratio are shown in [Fig. 5]. As expected, the uncertainty in the estimation decreases as the signal-to-noise ratio increases. More precisely, the uncertainty is less than + / -25° for a signal-to-noise ratio of 5 dB and decreases to less than 1° when the signal-to-noise ratio is 25 dB.

[0228] Figure 7 illustrates the variation of the variance in the direction-of-arrival estimate as a function of the signal-to-noise ratio (crossed points). The Cramér-Rao bound is also shown in the same graph. This bound represents the theoretical limit of variance that can be obtained for an unbiased estimator. As the signal-to-noise ratio increases, the variance decreases, approaching the Cramér-Rao bound very closely for signal-to-noise ratios greater than 5 dB. The method therefore allows operation even with signals exhibiting a signal-to-noise ratio of 5 dB.

[0229] The characterization process thus allows a more precise evaluation of the chamber's performance and calibration of the test equipment.

[0230] Furthermore, the method allows for the accurate estimation of reflection parameters even in the presence of noise. Previous experiments have indeed demonstrated the method's robustness.

[0231] In fact, the characterization process is a process that can operate with high resolution, the number of measurement points can easily be increased.

[0232] The method is usable with narrowband antennas generally used for VHF or UHF frequencies.

[0233] In addition, the method uses a rotating positioner which is natively available in most anechoic chambers 10, so that the decalpinization operation (removing part of the absorbents 18) is not necessary.

[0234] The calculations to be carried out by the determination device 26 are, moreover, relatively time-efficient thanks in particular to the use of the matrix pencil technique.

[0235] As a result, the process is easier to implement while allowing for a more precise characterization of the quiet zone 22.

[0236] Other embodiments of the present process benefiting from these advantages are conceivable.

[0237] In particular, it would be possible for the measurement points to be arranged according to several concentric circles.

[0238] Alternatively, the measurement points are arranged according to several circles belonging to different planes, in particular parallel planes (the circles then being superimposed).

[0239] The method works for any type of sensor 28.

[0240] In particular, consideration may be given to physically realizing the circular network by positioning an antenna at each measurement point.

Claims

Demands

1. A method for characterizing a portion (22) of an anechoic chamber (10), the characterization method comprising: - an acquisition phase comprising: - for several measurement points (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8) in the portion (22), a step of acquiring an electromagnetic signal received by a sensor (28) positioned at said measurement point (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8), to obtain a plurality of acquired electromagnetic signals, the measurement points (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8) being spatially arranged in a circle, - a phase of determining at least one characterization parameter of the portion (22) from the acquired electromagnetic signals, the determination phase comprising a step of: - converting the acquired electromagnetic signals at a given frequency into a set of components,each component being the value of a respective order of the decomposition of the sum of the acquired electromagnetic signals into phase modes, - filtering of each component by applying a compensation filter to each component eliminating the frequency dependence of the component, to obtain filtered components, - estimation of the amplitude and direction of arrival of each of the parasitic scatterers present in the anechoic chamber (10) by solving a system of equations according to which each filtered component is equal to a sum of contributions of parasitic scatterers to the value of the filtered component, the contribution of a parasitic scatterer depending on the amplitude and direction of arrival of the scatterer, to obtain estimated amplitudes and estimated directions of arrival, and - determination of the value of at least one characterization parameter at the given frequency from the estimated amplitudes and estimated directions of arrival.

2. A characterization method according to claim 1, wherein a single sensor (28) is used during the implementation of the acquisition phase, the acquisition phase comprising a step of sensor (28) movement to each measurement point (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8).

3. A characterization method according to claim 1 or 2, wherein each sensor (28) is an antenna adapted to receive signals extending over a predefined frequency band, the predefined frequency band being included in the range extending between 30 MHz and 3,000 MHz.

4. A characterization method according to any one of claims 1 to 3, wherein the characterization parameter is the standing wave rate or a parameter representative of the reflectivity of the anechoic chamber (10).

5. A characterization method according to any one of claims 1 to 4, wherein, during the determination phase, the steps of conversion, filtering, estimation and determination are implemented for several frequencies to obtain the frequency variation of the characterization parameter.

6. A characterization method according to any one of claims 1 to 5, wherein each contribution is equal to the product of the amplitude by a complex exponential whose argument is the direction of arrival.

7. A characterization method according to any one of claims 1 to 6, wherein the estimation step includes the implementation of a matrix pencil technique to estimate the directions of arrival.

8. A characterization method according to claim 7, wherein the matrix pencil technique involves the use of a first Henkel matrix and a second Henkel matrix, the first Henkel matrix being such that / \ H — 1 \SWM-L-1 SWM-J where: • swx denotes the filtered component of order x, • M denotes the maximum order of the components obtained in the conversion step, and • L is the pencil parameter, the second matrix H2 being such that lsw-M+\ ••• ^lX. ™ml ... swM

9. A characterization method according to claim 8, wherein the matrix pencil technique includes thresholding the values ​​of each of the Henkel matrices to eliminate values ​​exhibiting noise, the values ​​being eliminated when these values ​​do not meet a condition with respect to a predetermined threshold.

10. A characterization method according to any one of claims 1 to 9, wherein the estimation step includes the application of a least squares technique to estimate the amplitudes.

11. A characterization method according to any one of claims 1 to 10, wherein a quiet zone (22) is defined for the anechoic chamber (10), the part characterized by the characterization method being the quiet zone (22).

12. Device (26) for determining at least one characterization parameter of a portion of an anechoic chamber (10), the device (26) being capable of: - obtaining, for several measurement points (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8) in the portion (22), an acquired electromagnetic signal, each electromagnetic signal being the electromagnetic signal received by a sensor (28) positioned at said measurement point (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8), the measurement points (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8) being spatially arranged in a circle, - determining at least one characterization parameter of the portion (22) from the acquired signals by: - ​​converting the acquired electromagnetic signals at a given frequency into a set of components, each component being the value of a respective order of the decomposition of the sum electromagnetic signals acquired in phase modes,- filtering of each component by applying a compensation filter to each component eliminating the frequency dependence of the component, to obtain filtered components, - estimation of the amplitude and direction of arrival of each of the parasitic scatterers present in the anechoic chamber (10) by solving a system of equations according to which each filtered component is equal to a sum of contributions of parasitic scatterers to the value of the filtered component, the contribution of a parasitic scatterer depending on the amplitude and direction of arrival of the, diffuser, to obtain estimated amplitudes and estimated arrival directions, and - deduction of the value of at least one characterization parameter at the given frequency from the estimated amplitudes and estimated directions of arrival.

13. A characterization system (20) for a portion (22) of an anechoic chamber (10), the characterization system (20) comprising: - an acquisition device (24), the acquisition device (24) comprising at least one sensor (28), the acquisition device (24) being capable of acquiring an acquired electromagnetic signal for several measurement points (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8) in the portion (22), each electromagnetic signal being the electromagnetic signal received by a sensor (28) positioned at said measurement point (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8), the measurement points (PMI, PM2, PM3, PM4, PM5, PM6, PM7, PM8) being spatially arranged in a circle, and - a determination device (26), the determination device (26) being according to claim 12.

14. Anechoic chamber (10) provided with a characterization system (20) of a part (22) of an anechoic chamber (10), the characterization system (20) being according to claim 13.

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