FR2818470A1 - METHOD FOR DEWORING, RECEIVING, A RADIOELECTRIC SIGNAL BROADCAST EMITTED - Google Patents

Abstract

In order to eliminate spurious signals in satellite radio navigation (GPS, GNSS1, GNSS2, GNSS3, GALILEO, GLONASS ) conventional techniques use frequency estimation of the sensed signal, estimation of interfering frequencies and elimination of said frequencies by filtering. The invention provides a different approach based on estimation of the time correlation matrix and on direct filtering of the signal without explicit estimation of interfering lines. Said technique offers the advantage of minimising adaptation time and the amount of calculation required. It proves to be well adapted to suppression of continuous wave (CW) and frequency modulated (FM) spurious signals. The direct filtering is advantageously carried out with a linear-phase adapted filter which minimises distortion products of the radio navigation signal.

Description

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RADIOELECTRIQUE EMIS EN BANDE ETALEE
La présente invention concerne le déparasitage, en réception, d'un signal radioélectrique émis en bande étalée au moyen d'une modulation par des codes binaires pseudo-aléatoires, tel que les signaux émis par les satellites d'un système de radionavigation du genre GNSS (sigle tiré de l'anglo-saxon"Global Navigation Satellite System"). Ces systèmes de radionavigation GNSS se composent de trois segments : un réseau de satellites défilants dont les orbites et positions sur leurs orbites sont connues à chaque instant avec précision et qui émettent des signaux de radionavigation permettant d'estimer leurs distances et vitesses radiales vis à vis d'un récepteur évoluant à la surface ou autour du globe terrestre, des stations au sol assurant le contrôle du réseau de satellites et des récepteurs qui reçoivent les signaux de radionavigation des satellites et permettent d'en déduire, par des opérations de triangulation, les positions et vecteurs vitesse de leurs porteurs. METHOD OF DEWORING, RECEIVING, A SIGNAL

RADIOELECTRIC TRANSMITTED IN BAND
The present invention relates to the deworming, on reception, of a radio signal transmitted in spread band by means of modulation by pseudo-random binary codes, such as the signals transmitted by the satellites of a GNSS radio navigation system. (acronym taken from the Anglo-Saxon "Global Navigation Satellite System"). These GNSS radionavigation systems are made up of three segments: a network of traveling satellites whose orbits and positions on their orbits are known at all times with precision and which emit radionavigation signals making it possible to estimate their distances and radial speeds with respect of a receiver evolving on the surface or around the terrestrial globe, of the ground stations ensuring the control of the network of satellites and of the receivers which receive the signals of radionavigation of the satellites and make it possible to deduce therefrom, by triangulation operations, the positions and velocity vectors of their carriers.

 The signals of radionavigation of the satellites which are emitted by on-board transmitters of low power and which have to travel long distances of the order of 20,000 Kms, are received with very low power levels, in an electromagnetic environment which can be congested with interfering signals, that is to say occupying the same bands, which are much more powerful because they originate from powerful ground transmitters (broadcasting transmitters, television transmitter, DME transmitter) often close to receivers.

 The problem of deworming consists in eliminating as much as possible the interference affecting reception, the radio navigation signals emitted by the GNSS satellites to avoid masking of the signals of the satellites rendering the processing of the receiver inoperative.

 The known solutions are essentially of two types: spatial filtering and spectral filtering with variants mixing the two solutions.

 Spatial filtering consists in playing on the differences between the directions of origin of the useful signals and interference signals, and more especially, in taking advantage of the fact that the useful signals come from sources

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satellites with a high site angle while the interference signals come from sources on the ground or close to the ground with a low site angle.
It consists in modeling the shape of the radiation pattern of the receiving antenna to place the sources of interference in the holes of this diagram and the sources of useful signals in main lobes. This technique is implemented using a directive reception antenna having a network of radiating elements associated with a more or less sophisticated pointing system.

 Spectral filtering consists in analyzing the frequency spectrum of the received signal, identifying in this spectrum the frequencies affected by interference and eliminating or reducing them as long as the interference lasts. The identification of the frequencies affected by interference is based on the expected form of the useful signals which are signals transmitted in spread band obtained by modulation of a carrier by means of pseudo-random binary sequences and which have the property of having in the frequency band whether they occupy or useful band, the properties of white noise with a flat frequency spectrum and a level of the order or lower than that of thermal noise due to the low emission powers and the distances traveled.

Spectral lines exceeding, in the received signal, an arbitrary threshold close to the thermal noise level, are considered to be due to interference and therefore to attenuate or even to eliminate.

 Spectral filtering is effective for narrow band interference, on the order of less than twenty percent of the wanted signal band, or for short-term interference, which is often the case with unintentional interference from 'human activity.

 The object of the present invention is to weaken and even eliminate a large category of interference affecting the reception of a radionavigation signal by satellites which is constituted by parasitic signals situated in the band of the radionavigation signal but not having like him a spectrum of white noise.

 It relates to a deworming method, on reception, of a radioelectric signal transmitted in spread band by modulation of a carrier by means of pseudo-random binary codes remarkable in that it

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 consists in subjecting said radio signal received on reception to a spectral whitening filtering rendering it its characteristics of white noise in the occupied band, by means of a spectral filter whose coefficients are deduced from an estimate of the coefficients of its matrix autocorrelation.

 This deworming process makes it possible to reduce, in large proportions, the interference caused, on a radio signal having the characteristics of white noise in the useful band as is the case with a radio navigation signal by satellites, by all parasitic signals which, not having a white noise spectrum, have a partly predictable shape.

(#f,n,p étant une erreur de modélisation de l'échantillon s,, assimilable à un bruit blanc si le modèle est fidèle et le coefficient a p, o étant égal à 1 par définition) qui sont déterminés de manière à minimiser l'erreur quadratique moyenne de modélisation. Advantageously, the whitening spectral filter used is a transverse filter of order p, with coefficients ap, corresponding to an autoregressive modeling of order p of the captured signal represented by a series of samples {}:

(# f, n, p being a modeling error of the sample s ,, comparable to a white noise if the model is faithful and the coefficient ap, o being equal to 1 by definition) which are determined so as to minimize l 'mean square error of modeling.

Ch étant le coefficient de la ième ligne et de la kième colonne de la matrice d'autocorrélation d'ordre p du signal capté qui ne dépend que de la valeur absolue de la différence k-i, le signal capté étant stationnaire, et qui est estimé de façon itérative au moyen de la relation : Advantageously, the coefficients ap of a transverse spectral filter of order p performing the bleaching are obtained by solving the system of equations:

Ch being the coefficient of the ith row and of the kth column of the autocorrelation matrix of order p of the picked up signal which depends only on the absolute value of the difference ki, the picked up signal being stationary, and which is estimated by iteratively using the relation:

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1 étant égal à : k-i, les oc,, étant des coefficients de pondération, * désignant le complexe conjugué, N étant l'instant d'estimation de la corrélation, l'instant initial 0 étant choisi arbitrairement, xn et xn+k-1 étant des échantillons du signal à déparasiter, et le système d'équations étant résolu avec la contrainte : ap A = 1
Avantageusement, le filtre de blanchiment est un filtre transverse d'ordre p à coefficients symétriques.

1 being equal to: ki, the oc ,, being weighting coefficients, * designating the conjugate complex, N being the instant of correlation estimation, the initial instant 0 being chosen arbitrarily, xn and xn + k- 1 being samples of the signal to be suppressed, and the system of equations being solved with the constraint: ap A = 1
Advantageously, the bleaching filter is a transverse filter of order p with symmetrical coefficients.

a'a-M-A+2.---a-1, (,, ,..., a,, aM (M étant un nombre entier tel que : p = 2M + 1), ses coefficients étant obtenus par résolution du système d'équations :

Ch et Ck+, étant des coefficients de la matrice d'autocorrélation d'ordre p du signal à déparasiter qui ne dépendent que des valeurs absolues de la différence k-i ou de la somme k+i, le signal considéré étant stationnaire et réel, et qui sont estimés de façon itérative au moyen de la relation :

Advantageously, when the bleaching filter is a transverse filter of order p with symmetrical coefficients with an odd number of coefficients identified by indices:

a'a-M-A + 2 .--- a-1, (,,, ..., a ,, aM (M being an integer such that: p = 2M + 1), its coefficients being obtained by solving the system of equations:

Ch and Ck +, being coefficients of the autocorrelation matrix of order p of the signal to be suppressed which depend only on the absolute values of the difference ki or of the sum k + i, the signal considered being stationary and real, and which are estimated iteratively using the relation:

1 étant égal à : k-i dans un cas et à k + i dans l'autre, les anl étant des coefficients de pondération, N l'instant d'estimation de la corrélation, l'instant initial 0 étant choisi arbitrairement,

1 being equal to: ki in one case and to k + i in the other, the anl being weighting coefficients, N the instant of correlation estimation, the initial instant 0 being chosen arbitrarily,

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X,, et Xn+k-i étant des échantillons du signal reçu, et le système d'équations étant résolu avec la contrainte : a p. o = h
D'autres caractéristiques et avantages de l'invention ressortiront de la description ci-après d'un mode de réalisation donné à titre d'exemple.

X ,, and Xn + ki being samples of the received signal, and the system of equations being solved with the constraint: a p. o = h
Other characteristics and advantages of the invention will emerge from the description below of an embodiment given by way of example.

 This description will be made with reference to the drawing in which a single figure schematically represents a deworming circuit according to the invention.

 In reception, a signal of radionavigation by satellites is received by a reception antenna, brought back in intermediate band or in base band by the stages of entry of a receiver to be able to be sampled and digitized at a reasonable rate without loss of information, sampled and digitized, then subjected to a digital processing having for object to extract information from it on the position and the speed vector of the carrier of the receiver. After sampling and digitization, it generally takes the form of a sequence x {n} of complex digital samples succeeding one another at a rate sufficient to respect Shannon's theorem, each sample having two components coming from a quadrature demodulation, a component from the phase 1 demodulation channel and a component from the Q quadrature demodulation channel

 The signal of radionavigation by satellites has the particularity of being transmitted in spread band by means of a carrier modulated by pseudo-random binary sequences, which gives its frequency spectrum, in the band which is allocated to it, the characteristics pseudo white noise, with a relatively constant spectral density implying that the signal in the useful band is difficult to predict.

 As a radio navigation signal by satellites is transmitted with low power, the electric power available on board a satellite being counted and the distance traveled by strong waves, the signal received in reception is received at or below the noise level thermal. Due to its low power, its operation by a receiver is easily disturbed by parasitic interference in its useful band, caused by radioelectric signals due to human activity and present in

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l'environnement du récepteur à des niveaux de puissance souvent très supérieurs. Une grande partie des interférences parasites que l'on trouve dans la bande utile d'un signal de radiocommunication par satellites provoque une rupture de l'uniformité de la densité spectrale du signal capté, ce qui a conduit à développer différentes techniques de déparasitage consistant à rétablir, par un filtrage spectrale, l'uniformité de densité spectrale du signal dans la bande utile avant de chercher à l'utiliser pour en extraire des informations sur la position et le vecteur vitesse du porteur du récepteur.

the receiver environment at often much higher power levels. A large part of the parasitic interference found in the useful band of a radiocommunication signal by satellites causes a break in the uniformity of the spectral density of the signal received, which has led to the development of different deworming techniques consisting of restore, by spectral filtering, the spectral density uniformity of the signal in the useful band before seeking to use it to extract information therefrom on the position and the speed vector of the carrier of the receiver.

 We propose here a deworming technique consisting in eliminating from the received signal, any predictable component which can only come from interference since the expected signal must have a uniform spectral density in the useful band. This deworming technique makes it possible to effectively combat any interference by a radio signal having more or less pure spectral lines such as a CW continuous wave signal or a FM frequency modulation signal.

où p est l'ordre du modèle, c'est-à-dire le nombre d'échantillons précédents pris en compte dans la prédiction, {ap,, l} une suite de p coefficients complexes définissant le modèle et une erreur de prédiction dans le sens direct, par le modèle d'ordre p, de l'échantillon Sn qui doit être assimilable à un bruit blanc si le modèle est fidèle. ou encore : An interfering signal s is supposed to be predictable when the value of one Sn of its samples can be deduced from a linear combination of the values of its np previous samples, that is to say that the sequence s {n} of its samples checks a prediction relationship in the direct sense of the form:

where p is the order of the model, ie the number of previous samples taken into account in the prediction, {ap ,, l} a series of p complex coefficients defining the model and a prediction error in the direct direction, by the model of order p, of the sample Sn which must be comparable to a white noise if the model is faithful. or :

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avec : a 0-1 La relation de prédiction (1) réalise une modélisation dite "autorégressive"car, en l'absence de bruit et d'erreurs de mesure sur les échantillons, elle est d'autant plus fidèle que l'ordre p du modèle est élevé.

with: a 0-1 The prediction relation (1) performs a so-called "autoregressive" modeling because, in the absence of noise and measurement errors on the samples, it is all the more faithful as the order p of the model is high.

de sorte que les coefficients de prédiction {ap,,} permettent de définir un filtre transverse à réponse impulsionnelle finie RIF permettant d'éliminer du signal capté, le signal interférent prédictible s. We notice that we have:

so that the prediction coefficients {ap ,,} make it possible to define a transverse filter with finite impulse response RIF making it possible to eliminate from the signal received, the predictable interfering signal s.

 We also note that the modeling of the predictive interfering signal can be done from the signal received itself since the useful signal is comparable to a noise in the same way as the prediction errors so that we can say that the modeling is also that of the signal received, the samples {sn} being able to be replaced in the prediction relation by the samples {xn} of the signal received.

 It remains to determine the prediction coefficients {ap, i}. A known method for determining these coefficients is the so-called least squares method.

The method of least squares is based on a minimization of the sum of squares of prediction errors in the forward direction ef for n varying from 0 to Np-1, the samples Sn being assumed to be zero outside the interval [1, N ]. We have, according to equation (2):

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Pour minimiser cette somme de carrés d'erreurs, il faut annuler ses dérivées par rapport à la suite {ap,} des coefficients de prédiction, ce qui se traduit par le système d'équations linéaires :

To minimize this sum of squares of errors, it is necessary to cancel its derivatives with respect to the sequence {ap,} of the prediction coefficients, which results in the system of linear equations:

Comme le signal utile est considéré comme un bruit, on peut remplacer, dans le système d'équations linéaires (3), les échantillons {sn} du signal interférant prédictible par les échantillons {Xn} du signal capté :

As the useful signal is considered as noise, one can replace, in the system of linear equations (3), the samples {sn} of the predictable interfering signal by the samples {Xn} of the captured signal:

Le système d'équations linéaires (4) peut encore s'écrire, puisque ap, o est égal à un par définition :

The system of linear equations (4) can still be written, since ap, o is equal to one by definition:

* étant l'opérateur conjugué.

En posant :

=. n C [c,,...., cJ A= [,....,

T étant l'opérateur de transposition, et :

Co CI C p-l p p= ci Co C,. C,-, p C Cp,.. c.

* being the conjugated operator.

By asking :

=. n C [c ,, ...., cJ A = [, ....,

T being the transposition operator, and:

Co CI C pl pp = ci Co C ,. C, -, p C Cp, .. c.

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on peut réécrire le système d'équations (3) sous une forme matricielle et aboutir à l'équation normale de Yule-Walker : =-C, d'où l'on tire la valeur du vecteur Ap des coefficients de prédiction d'ordre p : Ap =-'Cp (5) - 1 étant l'opérateur d'inversion.

we can rewrite the system of equations (3) in a matrix form and arrive at the normal Yule-Walker equation: = -C, from which we derive the value of the vector Ap from the order prediction coefficients p: Ap = - 'Cp (5) - 1 being the inversion operator.

 We note that #p is both the autocorrelation matrix of order p of the predictive interfering signal s that we are trying to suppress and that of the picked up signal {xn} since the wanted useful signal is comparable to white noise at same as the prediction error. The application of the method of least squares for the determination of the coefficients of prediction 'and therefore of the transverse filter with finite response allowing to eliminate the predictable interferences of the signal of radionavigation by satellites thus passes by the estimation of the matrix of autocorrelation of the received signal and its inversion.

ank étant des coefficients de pondération choisis pour atténuer l'effet de bord du à la troncature, N l'instant d'estimation de l'autocorrélation et 0 l'instant initial choisi arbitrairement. The estimation of the coefficients of the autocorrelation matrix of order p of the captured signal can be done in the following iterative manner:

ank being the weighting coefficients chosen to attenuate the side effect due to truncation, N the instant of estimation of the autocorrelation and 0 the initial instant arbitrarily chosen.

 The figure illustrates a deworming circuit implementing the method which has just been described. It has three modules: a first module 1 for estimating the autocorrelation matrix of the signal placed at the input and receiving the

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samples Xn of the signal to be suppressed, received and digitized by the input stages of a radio navigation satellite receiver, 'a second module 2 for calculating the bleaching filter coefficients operating from the correlation matrix coefficients estimated by the first module 1, and 'a third module 3 for bleaching filtering consisting of a digital filter which receives its coefficients from the second module
2 and processes the samples Xn of the signal to be suppressed before their use by the stages downstream of the radionavigation receiver by satellites to extract therefrom information on the position and the speed vector of the carrier of the receiver.

 The first module 1 for estimating the autocorrelation matrix receives the samples {xn} of the signal picked up while it has been placed in the intermediate frequency band or in the base frequency band by the input stages of the receiver. radionavigation by satellites but before demodulation and despreading. It applies to these samples the iterative method of estimating the coefficients of the autocorrelation matrix described relative to relation (6) to generate an estimate of these coefficients intended for the second module 2 for calculating the bleaching filter coefficients.

 The second module 2 for calculating the bleaching filter coefficients calculates prediction coefficients from the normal Yule-Walker equation by applying the relation (5) to the estimated coefficients of the autocorrelation matrix of the signal received, provided by the first module 1. To do this, it reverses beforehand the estimated autocorrelation matrix provided by the first module 1 for example by means of a Levinson-Durbin type matrix inversion technique.

 The third whitening filtering module 3 performs, on the samples (Xn) of the captured signal, the operations of a spectral filter of the transverse type with finite response FIR taking as coefficients the prediction coefficients provided by the second module 2 for calculating the whitening filter coefficients. The filtered signal it delivers is applied to the downstream stages of the satellite navigation receiver, either directly under

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 digital form, i.e. after switching to high frequency including a digital-analog conversion and an increase in frequency followed by a decrease in frequency and a second analog-to-digital conversion.

 As a variant, it is possible to impose on the filter implemented by the third whitening filtering module 3 a condition of symmetry on its coefficients giving it a linear phase law which is particularly appreciated for the exploitation of the radionavigation signal by satellites after the operation filtering since a linear phase law filter behaves as a simple delay from the point of view of the distortion brought to the radio navigation signal.

a-M -M+l'a-M+2'"-- a-0',t'-" M-lM (M étant un nombre entier tel que : p = 2M + 1). Elle devient alors : - = Sa prise en compte lors de l'application de la méthode des moindres carrés à la recherche des coefficients de prédiction, conduit à la résolution d'un système d'équations linéaires modifié par rapport à celui mentionné précédemment en (4). Ce nouveau système devient :

In the case of a bleaching filter with an odd number of coefficients, the condition of symmetry is better highlighted with the following indexing of the coefficients:

aM -M + a-M + 2 '"- a-0', t'-" M-1M (M being an integer such that: p = 2M + 1). It then becomes: - = Its taking into account during the application of the method of least squares in search of the prediction coefficients, leads to the resolution of a system of linear equations modified compared to that mentioned previously in ( 4). This new system becomes:

avec la contrainte : X ou encore :

with the constraint: X or again:

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toujours avec la contrainte : aO =S cj, et c, + étant des coefficients de la matrice d'autocorrélation d'ordre p du signal modélisé qui ne dépendent que des valeurs absolues de la différence j-i ou de la somme j + i
La solution de ce système d'équations linéaires s'obtient de la même façon que celle du système d'équations linéaires (4), comme solution d'une équation matricielle de type Yule-Walker combinant des matrices respectivement de type Toepliz et Hankel obtenues à l'aide des estimations des 2M+1 coefficients d'autocorrélation du signal capté.

always with the constraint: aO = S cj, and c, + being coefficients of the autocorrelation matrix of order p of the modeled signal which only depend on the absolute values of the difference ji or of the sum j + i
The solution of this system of linear equations is obtained in the same way as that of the system of linear equations (4), as solution of a matrix equation of Yule-Walker type combining matrices respectively of Toepliz and Hankel type obtained using estimates of 2M + 1 autocorrelation coefficients of the signal received.

 The deworming method which has just been described applies to the treatment of any type of parasite or high level radio interference for the reception of radio signals having a uniform spectrum in their useful band, as soon as the parasites or interference have somewhat predictable forms.

 To facilitate understanding, the deworming treatment has been represented and described as being executed by three separate modules, a module for estimating the coefficients of the autocorrelation matrix, a module for determining the coefficients of the whitening filter and a module for whitening filtering. It should not be concluded that this is necessarily the case in practice. Indeed, as we are dealing with digital signals, all the processing and functions carried out in these modules are done by means of one or more processors controlled by software, the distribution of tasks between one or more processors coming under the competence of the skilled person.

Claims (8)

1. A method of deworming, on reception, of a radio signal transmitted in a spread band by modulation of a carrier by means of pseudo-random binary codes, characterized in that it consists in subjecting said radio signal received on reception to filtering. whitening spectral rendering it its characteristics of white noise in the occupied band, by means of a spectral filter whose coefficients are deduced from an estimation of the coefficients of its autocorrelation matrix.  2. Method according to claim 1, characterized in that the spectral bleaching filtering is carried out by means of a transverse filter of order p, with coefficients ap k corresponding to an autoregressive modeling of order p of the captured signal represented by a series of samples {}:

 (fop being a modeling error of the sample xn and the coefficient ap 0 being equal to 1 by definition) which are determined so as to minimize the mean square error of modeling.  3. Method according to claim 2, characterized in that the coefficients ap, of the transverse filter of order p carrying out the bleaching filtering are obtained by solving the system of equations:

 ck-1 being the coefficient of the ith row and of the kth column of the autocorrelation matrix of order p of the picked up signal which depends only on the absolute value of the difference k-i, the picked up signal being stationary and real. <Desc / Clms Page number 14>  1 being equal to: k-i, the years! being weighting coefficients, N being the instant of correlation estimation, the initial instant 0 being chosen arbitrarily, xn and xn + k-1 being samples of the signal to be dewormed, and the system of equations being solved with the constraint: ap, = 1

 4. Method according to claim 3, characterized in that the coefficients CI. of the autocorrelation matrix of the received signal are estimated iteratively by means of the relation: 5. Method according to claim 2, characterized in that the spectral bleaching filtering is carried out by means of a transverse filter of order p with symmetrical coefficients.  6. Method according to claim 2, characterized in that the bleaching filtering is carried out by means of a transverse filter of order p with symmetrical coefficients with an odd number of coefficients identified by indices:

 a'l-M + 2 ..., a-I'aol ...--- aM (M being an integer such that: p = 2M + 1), its coefficients being obtained by solving the system of equations :

 Ck, and Ck +, being coefficients of the autocorrelation matrix of order p of the picked up signal which depend only on the absolute values of the difference k-i or of the sum k + i, the picked up signal being stationary and real.

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7. Method according to claim 6, characterized in that the coefficients CI. and c, +, of the autocorrelation matrix of the received signal are estimated iteratively by means of the relation:

 I being equal to: ki in one case and to k + i in the other, the &alpha; ni being weighting coefficients, N being the instant of correlation estimation, the initial instant 0 being chosen arbitrarily, Xn and, being samples of the received signal, and the system of equations being solved with the constraint: ap ,, = 8. Method according to claim 1, characterized in that the processed radio signal is a radio navigation signal by satellites.