METHOD FOR FORMING PARAMETERABLE EMISSION PATHWAYS AND ASSOCIATED DEVICES

Description

[0001] The present invention relates to a method for forming P multibeam emission paths from Q beams. It also relates to a computer, an emission path formation system, a computer program product, and a computer-readable medium involved in implementing the formation method.

[0002] In a multi-antenna system, each antenna receives a set of signals from multiple listening directions with delays that depend on both the angle θ of the listening direction and the position of the antenna within the antenna system.

[0003] Ideally, the beam should be formed in the direction θ consists of compensating for differences in delay between antennas to allow a coherent summation of the same signal between the different reception channels with the dual aim of gaining in spatial selectivity and signal-to-noise ratio.

[0004] An example of such a beamforming system or beamformer can be seen on the figure 1 The system comprises a set of antennas 1, each connected to a digital receiving chain 2 and a beamforming unit 3 allowing the generation of N beams.

[0005] Whether analog or digital, the realization of a beamformer capable of listening in different directions involves the realization of programmable delays, which, in practice, is very difficult to achieve.

[0006] Usually, the signals to be listened to are considered to be narrowband around a carrier f0 assumed to be known. In this case, "simple" phase shifts allow the formation of the listening beam; if τk is the delay to be compensated on the chain of index k, these phase shifts are equal to Φk = 2πf0τk.

[0007] However, as soon as the listening signal bandwidth increases, this method is no longer possible and beamforming involving the realization of "true" delays (as opposed to phase shift, more often referred to by the corresponding English term "true time delay") is then indicated.

[0008] Thus, the context of the present invention is that of so-called digital receiving chains whose output data are the digitized values ​​of periodic time samples of the signal at a rate denoted f ECH.

[0009] If the delay to be applied to the signal is a multiple of the sampling period TECH = 1 / fECH, the problem is simple since it only requires a numerical delay of an integer number of samples. However, if the delay, measured in sampling periods, includes a decimal part, or even a fractional part, the problem is more complex because it implicitly involves interpolating the signal.Indeed, on the one hand, the interpolation filter depends on the delay to be ensured (a different filter per delay) and, on the other hand, for a given precision, the duration of the time response of this filter is all the greater the closer the band in which we want to ensure this delay with precision is to the Nyquist band associated with the sampling (typically inversely proportional to the difference between the Nyquist band and the useful band); it is known that this is linked to the discontinuity at the limits of the sampling band of the response e -j2πfτ< associated with a delay τ when τ is not a multiple of the sampling period 1 / f ECH.

[0010] Furthermore, in any beamforming operation, the quality of the signal degrades when the receiving channels do not exhibit exactly the same response. It is well known that differences in response, both in spectral amplitude and spectral phase, must be corrected prior to achieving good beamforming; the correction data required for the amplitude and spectral phase of each channel is acquired through calibration and is commonly available in the spectral domain. This correction therefore constitutes channel-specific filtering.

[0011] However, as with the delay, the complex gain corresponding to this correction is generally neither continuous nor continuously differentiable at the limits of the sampling band, so that, again, the duration of the time response of this correction filter is all the greater the closer the band in which we want to ensure this correction with precision is to the Nyquist band associated with the sampling.

[0012] Furthermore, the bandwidth in which channel formation is desired often depends on the application mode. Thus, in a multimode system, the sampling frequency of the processed signals must, according to the Shannon criterion, be compatible with the largest of the covered bandwidths. In this case, for narrowband modes, maintaining the full input data rate is not desirable; decimation must then be performed, which involves filtering the useful bandwidth. This useful bandwidth can be centered at different points within the sampling bandwidth. Also in this case, it may be desirable to simultaneously form several beams covering the same useful bandwidth.

[0013] It may also be desirable, in other configurations, to simultaneously form a large number of narrow beams and a smaller number of wider beams. Ideally, it is then possible to carry, by multiplexing, indifferently and simultaneously on a set of output channels clocked at f ECH, sets of beams of the same band, the nth channel carrying K n multiplexed beams of band f ECH / K n (K can vary from one channel to another).

[0014] It is therefore desirable for a broadband, multimode beamformer to meet several distinct objectives.

[0015] It is necessary to form a set of beams with given and potentially different useful bands; this implies three different filtering operations: equalization of the receiving channels, inherently specific to each receiving channel; delay specific to each beam / receiving channel pair; and selection of the useful band, specific to each formed beam. As explained above, these filtering operations can correspond to very long time responses, which are achieved, in practice, in an approximate way by transverse filters with a priori finite impulse response, all of which are distinct. Such filters are often designated by the acronym FIR, referring to the Anglo-Saxon terminology " Finite Impulse Response » which stands for "finite impulse response." State-of-the-art FIR filters implement operations involving time-shifting of the signal, gain adjustments, and summations. The number of operations is equal to the length of the impulse response of the FIR filter under consideration (the length being expressed as the number of samples). Thus, the computational resources involved are so vast that they can quickly become prohibitive.

[0016] One objective is therefore to form groups of individually configurable beams with reduced resources involved.

[0017] In a dual manner, similar problems arise in optimizing the resources required to form emission paths intended to emit one or more beams simultaneously in one or more directions.

[0018] US document 5,671,168 A also describes such a process.

[0019] There is therefore a need for a process that can fulfill at least one of the aforementioned objectives, and ideally all three at once, particularly for broadband beams.

[0020] To this end, the description describes a process for forming P multibeam emission channels from Q multiplexed beams onto Q' beam groups indexed by q', where q' is an integer between 1 and Q', where Q' is an integer greater than 1, and the multiplexing ratio is 2 Kq'< , K q' each value of q' being an integer, the process being implemented by a computer of a beamforming system in transmission comprising P transmission channels each equipped with an antenna having a respective aperture, Q and P being two integers greater than or equal to 2, the process comprising: For each group q' of beams, the passage of the signals composing the multiplexed beam group into the spectral domain to obtain multiplexed spectra involves implementing operations in the spectral domain. These operations include pointing and interpolation, comprising: an operation to create as many replicas of the spectra as there are emission channels to be formed; for each replica corresponding to each of the P emission channels, an operation to generate a contribution to the corresponding emission channel by implementing, for each contribution, a multiplexed introduction operation. Kq'< of a set of 2 Kq'< delays, and a possible set of 2 Kq'< antenna aperture weightings, an integration operation on 2 Kq'< points, an interpolation operation by insertion of 2 Kq'< - 1 zero, and a summation operation of the contributions to a transmission channel corresponding to each beam group, the summation operation being performed for each transmission channel to be generated. The method further comprises, for each beam group, the formation of two calculation channels, the input signal of the first calculation channel being obtained by implementing the implementation of the beam signal shift by M points, M being an integer greater than or equal to 2x2 Kq'< to obtain a shifted signal and the calculation of the sum of the beam group signal and the shifted signal, and the input signal of the second calculation channel being obtained by implementing the shift of the beam group signal by M points to obtain a shifted signal and the calculation of the difference between the beam group signal and the shifted signal, this difference being frequency-translated by multiplicative application of a signal e[+j floor(n / 2 Kq'< )π / ( M / 2 Kq'< )] , n being an integer from 0 to M-1 and the floor function denoting the floor part function, M being an integer greater than or equal to 2x2 Kq'< .

[0021] Today beamforming is done with classic FIR architectures operating in the time domain, whereas here we use a FIR architecture working in the frequency domain which was the subject of requests FR 3049131, FR 3102264, FR 3102262 and FR 3102265, cleverly adapted to obtain a substantial gain in resources and individually configurable beam groups.

[0022] Upon reading what follows, the reader will understand that, in the case of beam formation with FIRs working in the frequency domain, two distinct gains are obtained: a gain on the calculation operators (multiplier in particular) and a gain on memory resources through pooling.

[0023] The reader will also understand that what has just been said applies equally to the formation of emission paths from received beams.

[0024] In specific embodiments, the training process comprises one or more of the following characteristics, taken individually or in all technically possible combinations: The operations performed in the spectral domain also include a channel equalization operation, which is performed after the pointing operations, these operations being carried out multiplicatively. The operations performed in the spectral domain also include a bandwidth limiting operation, which is performed before the pointing operations, these operations being carried out multiplicatively. The transition to the spectral domain is performed on each of the computing channels by applying a discrete Fourier transform to M / 2. Kq'< points multiplexed by 2 Kq'< . the process includes a return step in the time domain, the return step in the time domain comprising the application of a discrete inverse Fourier transform at M points on each of the calculation channels, the process comprising a spectral shift operation of the second calculation channel by multiplicative application of a signal e +jnPi / M< and a summation operation of the two outputs of the two calculation channels.

[0025] The description also describes a computer, in particular a programmable logic circuit, adapted to implement the operations of a training process as previously described.

[0026] The description also describes a system for forming P multibeam transmission channels from Q multiplexed beams on Q' subbeam groups indexed by q', q' being an integer ranging from 1 to Q', Q' being an integer greater than 2, a beamforming transmission system comprising P transmission channels each equipped with an antenna having a respective aperture, Q and P being two integers greater than or equal to 2, the formation system also comprising a computer as previously described.

[0027] The description also describes a computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out the operations of a process for forming P multibeam emission channels from Q multiplexed beams or a process for forming P multibeam emission channels from Q multiplexed beams, the process being as previously described.

[0028] The description also describes a computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the operations of a process for forming P multibeam emission channels from Q multiplexed beams or a process for forming P multibeam emission channels from Q multiplexed beams, the process being as previously described.

[0029] Features and advantages of the invention will become apparent from the following description, given solely by way of non-limiting example, and made with reference to the accompanying drawings, in which: there figure 1 is a schematic representation of a beamforming system, the figure 2 is a schematic representation of the resources of a long time-response filter architecture controlled in the spectrum, the figure 3 is a schematic representation of an example of architecture modified compared to the architecture represented in the figure 2 in which certain resources are communalized, the figure 4 is a schematic representation of another example of architecture modified from the architecture shown in the figure 2 in which certain resources are communalized, the figure 5 is a set of two graphs showing the time response of a Hilbert filter (real part at the top and imaginary part at the bottom), the figure 6 is a graph showing the frequency response of a Hilbert filter (real part at the top and imaginary part at the bottom), the figure 7 is a set of two graphs showing the total elimination effect of the second Nyquist band in the spectrum of a Hilbert filter, the figure 8 is a set of two graphs allowing comparison of the Hilbert filter of the figure 6 (left graph) with the filter required when the input signal is complex to avoid problems related to the discontinuity of the frequency response of the delay at the boundaries of the sampling band (right graph), the figures 9 And 10 are schematic representations of an example of a beamforming system comprising parts A to H, (the figure 9 corresponding to the left part and the figure 10 (on the right side), the figure 11 is a schematic representation of parts A to D of the beam formation system of the figures 9 And 10 , there figure 12 is a schematic representation of parts E to H of the beam formation system of the figures 9 And 10 , there figure 13 is a schematic representation of the decomposition of an M-point IFFT into a 2-point DFT and an M / 2-point IFFT, the figure 14 is a schematic representation of an example of a beamforming system with multiplexing of 2 beams decimated by 2, the figure 15 shows the modification of the IFFT to 2N< points for the multiplexing of 2K< beams decimated by 2K< , the figure 16 is a schematic representation of an example of a beamforming system with multiplexing of 2 K< beams decimated by 2 K< , the figure 17 is a schematic representation of a frequency-based recalibration device for the decimated band, the figure 18 is a schematic representation of another example of a beamforming system with multiplexing of 2 K< beams decimated by 2 K< , the figure 19 is a synoptic representation of beam formation, the figures 20 And 21 are a schematic representation of another example of a beamforming system with multiplexing of 2 K< beams decimated by 2 K< (the figure 20 corresponding to the left part and the figure 21 (on the right side), the figure 22 is a schematic representation of an example of a calibration device, the figure 23 is a schematic representation of an example of a time alignment device, the figure 24 shows the modification of the FFT at 2N< points for the multiplexed processing of 2K< decimated beams by 2K< , the figure 25 schematically represents a beamforming system in emission with multiplexing of 2 K< beams decimated by 2 K< , and the figure 26 represents a detail of a part of the system of the figure 24 , and the figure 27 represents a detail of another part of the system of the figure 24 .

[0030] To facilitate further reading, the description is divided into chapters and sections. However, the chapters and sections are not independent, and the concepts used in one chapter also apply to the others.

[0031] The following will be discussed in order: 1 - SOME PRELIMINARY CONCEPTS 1.1 - IMPLEMENTATION OF LONG TIME RESPONSE FILTERS 1.2 - IMPLEMENTATION OF A DELAY 1.3 - IQ DEMODULATION - HILBERT FILTERING 2 - DESCRIPTION OF EXAMPLES OF FORMATION PROCESSES 2.1 - GENERAL PRINCIPLE OF THE FORMATION PROCESS 2.2 - DESCRIPTION OF AN EXAMPLE OF A BEAM FORMATION PROCESS 2.2.1 - Case of figures 9 And 102.2.2 - Generalization 2.3 - DESCRIPTION OF AN EXAMPLE OF A BEAM FORMATION METHOD 2.3.1 - Decimation by 2 (e.g., conversion from real to I / Q) 2.3.2 - Case of bands not between 0 and -1 + 2 NK< 2.3.3 - Decomposition into successive partial beam formations 2.3.4 - General case 3 - DESCRIPTION OF A CALIBRATION METHOD 4 - TRANSPOSITION OF FORMATION METHODS TO EMISSION

[0032] In particular, with reference to paragraph 2.2, a method for forming Q beams by a computer of a beamforming system comprising P receiving channels, each suitable for receiving signals from a respective antenna, each antenna having a respective aperture, Q being an integer greater than or equal to 1 and P being an integer greater than or equal to 2, the method comprising: the passage in the spectral domain of signals from signals from each antenna, the implementation of operations in the spectral domain, the operations including pointing operations, the pointing operations including: for each receiving channel, a generation operation by duplication of a contribution to each of the Q beams to be generated, the implementation for each contribution of an operation of introducing a delay and a possible operation of weighting the antenna aperture, and an operation of summing the contributions to a beam to be generated from all receiving channels, the summing operation being carried out for each beam to be generated.

[0033] Depending on specific aspects, the Q-beam formation process includes one or more of the following characteristics, taken individually or in all technically possible combinations: The operations performed in the spectral domain also include a channel equalization operation, the equalization operation being performed before the pointing operations, these operations preferably being carried out multiplicatively. The operations performed in the spectral domain also include a bandwidth limitation operation, the bandwidth limitation operation being performed after the pointing operations, these operations preferably being carried out multiplicatively.The process comprises, for each receiving channel, the formation of two calculation channels, the input signal of the first calculation channel being obtained by implementing the offset of the signal received by the antenna by M points, M being an integer greater than or equal to 2 to obtain an offset signal and the calculation of the sum of the received signal and the offset signal, and the input signal of the second calculation channel being obtained by implementing the offset of the received signal by M points to obtain an offset signal and the calculation of the difference between the received signal and the offset signal, this difference being translated in frequency by multiplicative application of a signal e -jnPi / M< , n being an integer from 0 to M-1. . The transition to the spectral domain is achieved by applying a discrete Fourier transform to M points on each of the calculation channels. The process includes a step of returning to the time domain, the step of returning to the time domain comprising the application of an inverse discrete Fourier transform to M points on each of the calculation channels, the process comprising a spectral shift operation of the second calculation channel by multiplicative application of a signal e +jnPi / M< and an operation of summing the two outputs of the two calculation channels.

[0034] The description also includes: A computer, in particular a programmable logic circuit, adapted to implement the operations of a training process as previously described. A training system of Q beams comprising P receiving channels, each capable of receiving signals from a respective antenna, Q being an integer greater than or equal to 1 and P being an integer greater than or equal to 2, the training system comprising a computer as previously described. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to implement the operations of a process or a process as previously described. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to implement the operations of a process or a process as previously described.

[0035] It will also be discussed, with reference in particular to paragraph 2.3, a method for forming Q multiplexed bundles on Q' groups of bundles indexed by q', where q' is an integer varying between 1 and Q', where Q' is an integer greater than 1, and the multiplexing ratio is 2 Kq'< , K q' each value of q' being an integer, the process being implemented by a computer of a beamforming system comprising P receiving channels, each suitable for receiving signals from a respective antenna, each antenna having a respective aperture, Q and P being two integers greater than or equal to 2, the process comprising: the passage through the spectral domain of signals originating from each antenna, the implementation of a set of operations in the spectral domain, called pointing operations, the set of pointing operations comprising: for each receiving channel, a generation operation by duplication of a contribution to each of the Q' beam groups to be generated, for each contribution, a decimation operation by 2 Kq'< , and a maintenance on 2 Kq'< periods to form a group of 2 Kq'< contributions multiplexed by 2 Kq'< , the implementation for each group of contributions of a multiplexed introduction operation by 2 Kq'< of a set of 2 Kq'< delays, and a possible set of 2 Kq'< antenna aperture weighting operations, and a summation operation of the contributions to a beam to be generated, from all the receiving channels, multiplexed for each channel on Q' groups of contributions, the summation operation being carried out for each beam to be generated.

[0036] Depending on specific aspects, the process for forming Q multiplexed beams includes one or more of the following characteristics, taken individually or in all technically possible combinations: The operations performed in the spectral domain also include a channel equalization operation, the equalization operation being performed before the pointing operations, these operations preferably being carried out multiplicatively. The operations performed in the spectral domain also include a bandwidth limitation operation, the bandwidth limitation operation being performed after the pointing operations, these operations preferably being carried out multiplicatively.The method comprises, for each receiving channel, the formation of two processing channels. The input signal of the first processing channel is obtained by shifting the signal received by the antenna by M points, where M is an integer greater than or equal to 2, to obtain a shifted signal, and calculating the sum of the received signal and the shifted signal. The input signal of the second processing channel is obtained by shifting the received signal by M points to obtain a shifted signal, and calculating the difference between the received signal and the shifted signal. The transition to the spectral domain is performed by applying a discrete Fourier transform at M points to each of the processing channels. The method includes a step of returning to the time domain, the step of returning to the time domain comprising the application of 2. Kq'< discrete inverse Fourier transforms at M / 2 Kq'< points multiplexed by 2 Kq'< on each of the computing channels, the process includes a spectral shift operation of the second computing channel by multiplicative application of a signal e[+j floor(n / 2 Kq'< )π / ( M / 2 Kq'< )] , n being an integer from 0 to M-1 and the floor function denoting the integer part function, and an operation of summing the two outputs of the two calculation paths.

[0037] The description also includes: A computer, in particular a programmable logic circuit, adapted to implement the operations of a training process as previously described. A training system for Q multiplexed beams on Q' groups of beams indexed by q', q' being an integer ranging from 1 to Q', Q' being an integer greater than 2, Q' being an integer greater than 1, and the multiplexing ratio being 2 Kq'< , K q' where q' is an integer, the training system comprises P receiving channels, each capable of receiving signals from a respective antenna, Q and P being two integers greater than or equal to 2, and the training system comprises a computer as previously described. A computer program product comprises instructions which, when executed by a computer, cause the computer to carry out the operations of a process or method as previously described. A computer-readable medium comprises instructions which, when executed by a computer, cause the computer to carry out the operations of a process or method as previously described.

[0038] It will also be discussed, with reference in particular to paragraph 3, a calibration method for a beamforming system comprising P receiving channels, each capable of receiving signals from a respective antenna, Q being an integer greater than or equal to 1 and P being an integer greater than or equal to 2, the beamforming system comprising a computer capable of implementing the following steps: the conversion, using spectral analysis in the spectral domain, of signals from each antenna, the implementation of operations in the spectral domain, the calibration process comprising: for each receiving channel, the injection into the time domain of a replica of a digital signal used to create a calibration signal, this replica being synchronized with the spectral analysis means applied to the signals of the receiving channels, the injection being carried out identically for each receiving channel, for each receiving channel, the passage in the spectral domain of this digital signal by means identical to those applied to the signals of the receiving channels, said identical means being synchronized with each other, to create an identical reference signal on each receiving channel, the passage being carried out identically for each receiving channel, the measurement, for each receiving channel, of values ​​of the reference signal and of values ​​of the signal propagated on the receiving channel, and the deduction of the difference between the reference signal and the signal propagated on the receiving channel as a function of the measured values..

[0039] Depending on specific aspects, the calibration process includes one or more of the following characteristics, taken individually or in all technically possible combinations: The process further comprises the following steps: generation of a digital calibration signal, conversion of the calibration signal to analog, frequency transposition of the converted calibration signal, amplification of the transposed calibration signal, and balanced distribution to the different receiving channels. When several receiving channels are housed on the same electronic board, the reference signal is shared by all channels of the same board (a single generation of the reference signal per board). The measured values ​​include the power correlation between the spectra of the signal propagated on a receiving channel and the reference signal. The measured values ​​include the power spectral density of the reference signal and / or the power density of the signal propagated on the receiving channel. The measured values ​​are obtained by integration over several successive frames.The deduction step involves estimating the phase of the power correlation between the spectrum of the signal on a receiving channel and the reference signal, to obtain an estimated phase. The phase of the difference between a receiving channel and the reference signal is the estimated phase. The deduction step involves estimating the amplitude difference between a receiving channel and the reference signal by calculating the square root of the ratio between the power spectral densities of the signal on a receiving channel and the reference signal. The deduction step involves estimating the amplitude difference between a receiving channel and the reference signal by calculating the ratio between the power spectral density of the reference signal and the power correlation between the spectrum of the signal on said receiving channel and the reference signal. This operation is performed at a reduced cost. The reference signal is noise.

[0040] The description also includes: A calibration device for a Q-beamforming system comprising P receiving channels, each capable of receiving signals from a respective antenna, where Q is an integer greater than or equal to 1 and P is an integer greater than or equal to 2, the calibration device being capable of implementing a calibration method as described above. A computer program comprising instructions which, when executed by a computer, cause the computer to implement a calibration method as described above. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to implement a calibration method as described above.

[0041] It will also be discussed, with reference in particular to paragraph 4 and transposed to paragraph 2.2, a method for forming P multibeam transmission channels from Q beams, the method being implemented by a computer of a beamforming system in transmission comprising P transmission channels each equipped with an antenna, Q being an integer greater than or equal to 1 and P being an integer greater than or equal to 2, the method comprising: the passage in the spectral domain of signals from the beams, the implementation of operations in the spectral domain, the operations including pointing operations, the pointing operations including: an operation of generating for each beam a contribution for each of the P emission channels by implementing for each contribution an operation of introducing a delay and a possible weighting of the antenna opening, and an operation of summing the contributions of an emission channel corresponding to each beam, the summing operation being carried out for each emission channel to be generated.

[0042] Depending on specific aspects, the process for forming P emission channels includes one or more of the following characteristics, taken individually or in all technically possible combinations: The operations performed in the spectral domain also include a channel equalization operation, which is performed after the pointing operations, these operations being carried out multiplicatively. The operations performed in the spectral domain also include a bandwidth limiting operation, which is performed before the pointing operations, these operations being carried out multiplicatively.The process involves, for each beam, the formation of two computing channels. The input signal of the first computing channel is obtained by shifting the beam signal by M points, where M is an integer greater than or equal to 2, to obtain a shifted signal, and calculating the sum of the received signal and the shifted signal. The input signal of the second computing channel is obtained by shifting the beam signal by M points to obtain a shifted signal and calculating the difference between the received signal and the shifted signal. This difference is spectrally shifted by multiplicative application of a signal e - jnPi / M<, where n is an integer from 0 to M-1. The transition to the spectral domain is achieved by applying a discrete Fourier transform to M points on each of the computing channels.The process includes a return step in the time domain, the return step in the time domain comprising the application of a discrete inverse Fourier transform at M points on each of the computation channels, the process comprising a spectral shift operation of the second computation channel by multiplicative application of a signal e +jnPi / M< and a summation operation of the two outputs of the two computation channels.

[0043] The description also includes: A computer, in particular a programmable logic circuit, adapted to implement the operations of a training process as previously described. A training system for P multibeam transmission channels from Q beams, the training system comprising P transmission channels each equipped with an antenna, Q being an integer greater than or equal to 1 and P being an integer greater than or equal to 2, the training system comprising a computer as previously described. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to implement the operations of a training process for P multibeam transmission channels from Q beams or a training process for P multibeam transmission channels from Q beams as previously described.a computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the operations of a process for forming P multibeam emission channels from Q beams or a process for forming P multibeam emission channels from Q beams as previously described.

[0044] It will also be discussed, with reference in particular to paragraph 4 and transposed to paragraph 2.3, a method for forming P multibeam transmission channels from Q beams multiplexed onto Q' beam groups indexed by q', where q' is an integer varying between 1 and Q', where Q' is an integer greater than 1, and the multiplexing ratio is 2 Kq'< , K q' each value of q' being an integer, the process being implemented by a computer of a beamforming system in transmission comprising P transmission channels each equipped with an antenna having a respective aperture, Q and P being two integers greater than or equal to 2, the process comprising: For each group q' of beams, the passage of the signals composing the multiplexed beam group into the spectral domain to obtain multiplexed spectra involves implementing operations in the spectral domain. These operations include pointing and interpolation, comprising: an operation to create as many replicas of the spectra as there are emission channels to be formed; for each replica corresponding to each of the P emission channels, an operation to generate a contribution to the corresponding emission channel by implementing, for each contribution, a multiplexed introduction operation. Kq'< of a set of 2 Kq'< delays, and a possible set of 2 Kq'< antenna aperture weightings, an integration operation on 2 Kq'< points, an interpolation operation by insertion of 2 Kq'< - 1 zero, and a summation operation of the contributions to an emission channel corresponding to each group of beams, the summation operation being carried out for each emission channel to be generated.

[0045] Depending on specific aspects, the process for forming P emission channels includes one or more of the following characteristics, taken individually or in all technically possible combinations: The operations performed in the spectral domain also include a channel equalization operation, which is performed after the pointing operations, these operations being carried out multiplicatively. The operations performed in the spectral domain also include a bandwidth limitation operation, which is performed before the pointing operations, these operations being carried out multiplicatively. The method comprises, for each beam group, the formation of two computing channels, the input signal of the first computing channel being obtained by shifting the beam signal by M points, where M is an integer greater than or equal to 2x2. Kq'< to obtain a shifted signal and the calculation of the sum of the beam group signal and the shifted signal, and the input signal of the second calculation channel being obtained by implementing the shift of the beam group signal by M points to obtain a shifted signal and the calculation of the difference between the beam group signal and the shifted signal, this difference being frequency-translated by multiplicative application of a signal e[+j floor(n / 2 Kq'< )π / ( M / 2 Kq'< )] , n being an integer from 0 to M-1 and the floor function denoting the floor part function, M being an integer greater than or equal to 2x2 Kq'< . The transition to the spectral domain is performed on each of the computing channels by applying a discrete Fourier transform to M / 2 Kq'< points multiplexed by 2 Kq'< . the process includes a return step in the time domain, the return step in the time domain comprising the application of a discrete inverse Fourier transform at M points on each of the calculation channels, the process comprising a spectral shift operation of the second calculation channel by multiplicative application of a signal e +jnPi / M< and a summation operation of the two outputs of the two calculation channels.

[0046] The description also includes: a computer, in particular a programmable logic circuit, adapted to implement the operations of a beamforming process as previously described; a beamforming system of P multibeam transmission channels from Q multiplexed beams on Q' subbeam groups indexed by q', q' being an integer varying between 1 and Q', Q' being an integer greater than 2; a beamforming transmission system comprising P transmission channels each equipped with an antenna having a respective aperture, Q and P being two integers greater than or equal to 2; the beamforming system also comprising a computer as previously described.A computer program product comprising instructions which, when executed by a computer, cause the computer to carry out the operations of a process for forming P multibeam emission channels from Q multiplexed beams, or a process for forming P multibeam emission channels from Q multiplexed beams, the process being as previously described. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the operations of a process for forming P multibeam emission channels from Q multiplexed beams, or a process for forming P multibeam emission channels from Q multiplexed beams, the process being as previously described. 1 - QUELQUES NOTIONS PRELIMINAIRES

[0047] These preliminary notions are part of the technological background. 1.1 - REALISATION DE FILTRES A REPONSES TEMPORELLES LONGUES

[0048] When the time response lengths of a FIR filter are very long, implementing the filtering becomes problematic or even impossible due to the very large number of resources involved, especially if the FIR needs to be programmable. To circumvent this problem, one solution is to perform this operation in the spectrum. This is done by converting from the time domain to the frequency domain using a Fourier transform, making the filtering operation multiplicative, and then returning to the time domain using an inverse Fourier transform.

[0049] This allows us to define a generic filter architecture that was the subject of a patent application published under number FR 3 049 131 A1, the content of which is briefly summarized below, with further information contained in the description of this application. In accordance with the figure 2 which refers to a long time response filter architecture controlled in the spectrum, this architecture makes it possible to realize, using FFTs of durations N, an impulse response FIR of duration N entirely contained in the positive time domain.

[0050] As a reminder, a Fourier transform is implemented by a fast Fourier transform, often referred to by the acronym FFT for " Fast Fourier Transform » (Fast Fourier Transform in French). More precisely, the transition from the time domain to the frequency domain is achieved using an FFT, while the transition from the frequency domain to the time domain is achieved using an IFFT. The acronym IFFT refers to « Inverse Fast Fourier Transform » (Inverse Fast Fourier Transform in French).

[0051] In the FIR of the figure 2 The coefficients ρk represent the spectral density obtained by an FFT at 2N points of the FIR response, with negative times representing N zeros out of the 2N values ​​of the time frame: ρ k = ∑ n = 0 2 N − 1 a n e − j 2 πnk 2 N = ∑ n = 0 N − 1 a n e − j 2 πnk 2 N

[0052] Note that if the time response associated with the filtering is entirely contained within negative times (as occurs when filtering a signal using the conjugate spectrum), then the output recombination between the two channels (even and odd frequencies) is performed by subtraction instead of the addition indicated in the figure 2 .

[0053] We can see that, in this architecture, the block 1 + z -N< (moving from the position indicated 2 to the position indicated 3 on the figure 2 ) can be translated at will to any of the positions 1 to 5. It can also be translated to either position a or b, but only if it is replaced by a block 1 - z - N< . This allows for the definition of several equivalent architectures, including, in particular, the two proposed respectively on figure 3 and on the figure 4 and which allow the communalization of the memorization resources z -N< .

[0054] These FIR architectures are particularly interesting because they significantly reduce the computational resources required compared to a classic FIR as the number of coefficients increases, typically in a ratio of M to log(M); however, this comes at the cost of a definite increase in memory resources (a factor of 4 for both architectures). figures 3 And 4 And 5 for the architecture of the figure 2 ).

[0055] The computing resources required for a response with a maximum duration of N = 2M are: additions: 3 + 4 x 2 x M = 8M + 3 multiplications: 4 + 4 x M / 2 = 2M + 4 Eléments sur la décomposition en Radix

[0056] To understand the rest of the description, it is necessary to explain some generalities about the decomposition of a discrete Fourier transform (DFT) into Radix (x being the number of factorable points).

[0057] The discrete Fourier transform at N points of a sequence of N points xn (N being an integer) is: X m = ∑ n = 0 N − 1 x n e − j 2 π n × m N

[0058] In the case where N is the product N = N1 x N2 of two integers N1 and N2, it can be written: X m 1 N 2 + m 2 = ∑ n 1 = 0 N 1 − 1 ∑ n 2 = 0 N 2 − 1 x n 2 N 1 + n 1 e − j 2 π n 2 N 1 + n 1 × m 1 N 2 + m 2 N 1 N 2 = ∑ n 1 = 0 N 1 − 1 ∑ n 2 = 0 N 2 − 1 x n 2 N 1 + n 1 e − j 2 π n 1 × m 2 N 1 N 2 e − j 2 π n 1 × m 1 N 1 e − j 2 π n 2 × m 2 N 2

[0059] There are two ways to decompose the discrete Fourier transform, both corresponding to the cascade of a discrete Fourier transform with N 1 points and a discrete Fourier transform with N 2 points. It is the order in which these discrete Fourier transforms are performed that differs.

[0060] One of the discrete Fourier transforms involved is weighted by a local oscillator allowing a fine shift of the spectrum; the exponential term enabling this shift is called the "tweedle factor": tweedlefactor = e − j 2 π n 1 × m 2 N 1 N 2

[0061] By principle, the fastest-changing output index is m1, since it corresponds to the "fast" discrete Fourier transform (i.e., non-multiplexed). Thus, the output order of the frequencies is not the natural order: first, the m values ​​0 modulo N1 are output, then the m values ​​1, and so on down to the m values ​​N1 - 1, which are always 0 modulo N1. This order is called "bit reverse" because it corresponds to reversing the binary representation of the index to obtain the output rank (for a number of points that is a power of 2).

[0062] The implementation of the inverse discrete Fourier transform, which recovers the frequency data in "bit reverse", is carried out in a dual manner, by reversing the operations.

[0063] In the first case, the discrete Fourier transform with N 1 points ("fast") is followed by the Fourier transform with N 2 points ("multiplexed"), which corresponds to: X m 1 N 2 + m 2 = ∑ n 1 = 0 N 1 − 1 ∑ n 2 = 0 N 2 − 1 x n 2 N 1 + n 1 e − j 2 π n 2 N 1 + n 1 × m 1 N 2 + m 2 N 1 N 2 = ∑ n 2 = 0 N 2 − 1 e − j 2 π n 2 × m 2 N 2 × ∑ n 1 = 0 N 1 − 1 e − j 2 π n 1 × m 1 N 1 e − j 2 π n 1 × m 2 N 1 N 2 ︸ tweedle factor × x n 2 N 1 + n 1 ︸ FFTà N 1 points RadixN 1 ︸ FFTà N 2 points multiplexé par N 1 RadixN 2

[0064] The realization of the Fourier transform is carried out as a cascade of a non-multiplexed N1-point Fourier transform and a multiplexed N1-point N2-point Fourier transform. The "tweedle factor" is placed at the head before the first stage of the Fourier transform.

[0065] According to a second case, the discrete Fourier transform at N 2 points ("multiplexed") is followed by the Fourier transform at N 1 points ("fast"), which corresponds to: X m 1 N 2 + m 2 = ∑ n 1 = 0 N 1 − 1 ∑ n 2 = 0 N 2 − 1 x n 2 N 1 + n 1 e − j 2 π n 2 N 1 + n 1 × m 1 N 2 + m 2 N 1 N 2 = ∑ n 1 = 0 N 1 − 1 e − j 2 π n 1 × m 1 N 1 × e − j 2 π n 1 × m 2 N 1 N 2 ︸ tweedle factor × ∑ n 2 = 0 N 2 − 1 e − j 2 π n 2 × m 2 N 2 x n 2 N 1 + n 1 ︸ FFT à N 2 points multiplexé par N 1 RadixN 2 ︸ FFT à N 1 points RadixN 1

[0066] This time, the implementation is performed as a cascade of a discrete Fourier transform with N2 points multiplexed by N1 and a discrete Fourier transform with N1 points that is not multiplexed. The "tweedle factor" is placed between the two discrete Fourier transform stages. Since the first discrete Fourier transform performed is multiplexed, this decomposition accommodates parallelized input data; the multiplexing then becomes parallel processing.

[0067] Following one of the classical versions of radix2 decomposition, the 2M point FFT of this sequence an is written: b m = ∑ n = 0 2 M − 1 a n e − j 2 πnm / 2 M = ∑ n = 0 M − 1 a n e − j 2 πnm / 2 M + − 1 m ∑ n = 0 M − 1 a M + n e − j 2 πnm / 2 M

[0068] Especially : b 2 m + p = ∑ n = 0 M − 1 a n e − j 2 πnp / 2 M e − j 2 πnm / M + − 1 p ∑ n = 0 M − 1 a M + n e − j 2 πnp / 2 M e − j 2 πnm / M Où p = 0 1 either : b 2 m + p = FFT M a n e − jπnp / M + − 1 p FFT M a M + n e − jπnp / M where FFT M denotes the FFT at M points.

[0069] It should be noted that this spectral density can also be written in the following two ways, which will simplify its implementation: b 2 m + p = FFT M a n e − jπnp / M + FFT M a M + n e − jπ M + n p / M And b 2 m + p = FFT M − 1 p a n + a M + n e − jπ M + n p / M

[0070] By noting ρ m The spectral response of the filter is obtained by inverse transformation: c k = ∑ p = 0 1 ∑ m = 0 M − 1 b 2 m + p ρ 2 m + p e j 2 πk 2 m + p / 2 M = ∑ p = 0 1 e j 2 πkp / 2 M ∑ m = 0 M − 1 b 2 m + p ρ 2 m + p e j 2 πkm / M

[0071] The answer is calculated only for points 0 ≤ k ≤ M-1 (due to the aliasing inherent in the FFT) to finally obtain: c k = ∑ p = 0 1 e jπkp / M IFFT M b 2 m + p ρ 2 m + p where the IFFT M denotes the inverse FFT with M points. 1.2 - REALISATION D'UN RETARD

[0072] It is known that the complex gain corresponding to a delay τ is H(f) = e^(-j2πfτ). When attempting to perform this operation on a signal sampled for a delay other than a multiple of the sampling period, one encounters the problem of aliasing of the frequency response, which is, in principle, zero when F_ECH_τ is not an integer. Therefore, one must seek to implement a filter exhibiting a periodic complex gain of period f_ECH and a response H(f) = e^(-j2πfτ) over this period.

[0073] It can be recalled here that, in principle, shifting a digitized signal xm by a delay τ amounts to interpolating the signal x using the Shannon interpolating filter whose time response is sinc(f ECH t) where sinc(x) = sin(πx) / (πx) and replacing the sample number m with value xm by ym = x(m T ECH - τ). Mathematically, this can be written as: y m = ∫ − ∞ + ∞ sin πf ECH mT ECH − τ − t πf ECH mT ECH − τ − t ∑ − ∞ + ∞ x k δ t − kT ECH dt = ∑ − ∞ + ∞ x k sin πf ECH mT ECH − τ − kT ECH πf ECH mT ECH − τ − kT ECH

[0074] The time response of the digital filter providing the delay τ is therefore: h n = sin πf ECH nT ECH − τ πf ECH nT ECH − τ = sin πf ECH τ π × − 1 n f ECH τ − n

[0075] In principle, this filter is not feasible since its time response extends from -∞ to +∞. By truncating and weighting its response between -N and +N, we obtain a set of coefficients corresponding to a filter that provides a differential delay τ relative to a reference delay equal to NT ECH. The frequency response of this filter is then the foldback of the frequency response of the weighting.

[0076] In any case, the slow decay of hn with the index n (hn ~1 / n) leads to very large lengths when both wide bandwidth (close to the Nyquist band) and high dynamic range (good suppression of image bands) are sought.

[0077] The equations presented above indicate that this slowness is a direct consequence of the fact that the complex gain e-j2πfτ associated with a delay τ is discontinuous at the boundaries of the sampling band when τ is not a multiple of the sampling period 1 / fECH. Similarly, the complex gain corresponding to the equalization corrections of the receiving channels is generally neither continuous nor continuously differentiable at the boundaries of the sampling band, so that, again, the duration of the time response of this correction filter is greater the closer the band in which this correction is to be performed accurately is to the Nyquist band associated with the sampling.

[0078] It follows from all these observations that this filter leads to an infinite time response hn decreasing slowly with the index n due to the discontinuity at the edge of the band.

[0079] It is well known that weighting a response limits its extent in the dual space; indeed, it is common practice to weight a time-domain response to limit the spectral obstruction inherent in the discontinuity at the boundaries of the sampling domain. Similarly, weighting in the spectral domain, which corresponds to filtering, greatly limits the temporal extent associated with implementing a non-integer delay (in terms of sampling periods), by reducing, through filtering, the bandwidth in which the delay will be effective.

[0080] Thus, the wider the band in which the delay is precisely ensured, the greater the length of the time response of the FIR filter realizing it. 1.3 - DEMODULATION IQ - FILTRAGE DE HILBERT

[0081] Furthermore, it is possible to sample real signals on the carrier (and no longer in baseband after analog I / Q demodulation). In this case, by principle, the positive frequencies of the useful signal are strictly contained within one of the Nyquist bands of the sampling (i.e., between kfSCH / 2 and (k+1)fSCH / 2 where k is arbitrary). After sampling, the reconstruction of the analytical signal then involves filtering, known as Hilbert filtering, which eliminates the spectrum of negative frequencies. Usually, as indicated by the figure 5 representing the time response of a Hilbert filter (real and imaginary parts), the time response of this filter includes a real part limited to a single central coefficient and an antisymmetric imaginary part decreasing in 1 / n and of which one sample out of two is zero.

[0082] In doing so, as indicated on the figure 6 which illustrates the frequency response of a Hilbert filter, the complex gain is -6 dB at the zero frequency and at the Nyquist frequency; moreover, the level of rejection of negative frequencies is higher as the duration of the response is greater.

[0083] If the actual signal does not occupy the entire Nyquist band, or if the complex signal does not occupy the entire sampling band, it is common practice to filter the useful band (denoted BU on the...). figure 6 occupied by the signal to allow a subsequent decimation step aimed at bringing the sampling frequency as close as possible to the useful bandwidth. In this case, the filter's response resembles that of the Hilbert filter, except that its bandwidth is narrower. 2 - DESCRIPTION D'EXEMPLES DE PROCEDES DE FORMATION 2.1 - PRINCIPE GENERAL DU PROCEDE DE FORMATION

[0084] The signal formation process can be applied either directly to a real signal after analog-to-digital conversion, or to a complex signal after baseband conversion, I / Q demodulation, and partial decimation. The process is designed to simultaneously perform the various steps: equalization of the receive channels, delay and weighting associated with pointing, and limitation of the occupied bandwidth.

[0085] For this, the process is carried out by the filtering structures presented in the paragraph entitled "Realization of filters with long time responses", which allows control of the filtering in the spectral domain and makes the operations independent and multiplicative.

[0086] It is also possible to duplicate the delay operation as many times as necessary to create the contribution of a receive channel to as many beams as required.

[0087] It should be noted that it is desirable for the response of the Hilbert filter or the filter limiting the spectrum to the useful band to sufficiently filter out the discontinuities associated with the delay and equalization operations in order to prevent these operations from introducing noticeable artifacts caused by these spectral discontinuities. This is schematically represented on the figure 7 which shows the modification of the Hilbert filter for a total elimination of the second Nyquist band (left graph before modification and right graph after modification).

[0088] In cases where the input signal is complex and its spectrum occupies almost the entire sampling bandwidth (fECH), filtering is necessary to avoid problems related to the discontinuity of the frequency response of the delay at the sampling bandwidth boundaries. In this case, the filter's time response is a subsampling by a factor of 2 of that of a filter similar to the Hilbert filter, but designed at twice the frequency. figure 8 illustrates this by showing the filter required when the input signal is complex to avoid problems related to the discontinuity of the frequency response of the delay at the limits of the sampling band. 2.2 - DESCRIPTION OF AN EXAMPLE OF A BEAM FORMATION METHOD 2.2.1 - Case of figures 9 and 10

[0089] It is proposed to utilize the filter architectures presented in figures 2 has 4 as a constituent element of a beamforming system architecture.

[0090] The beam formation system is a system that forms Q beams, where Q is a non-zero integer.

[0091] Each beam can thus be identified by an index q, an index which is an integer between 1 and Q.

[0092] It should be noted that in a particular embodiment of this scenario, Q can be equal to 1.

[0093] The beamforming system comprises P receiving chains, each equipped with an antenna. P is an integer greater than or equal to 2.

[0094] A receiving chain is a set consisting of an antenna and a processing circuit.

[0095] The term "receiving path" is sometimes used for the processing circuit. This term will be used throughout the rest of the description.

[0096] Each of the P receiving channels is thus specific to receiving signals from a respective antenna.

[0097] Furthermore, each of the P reception channels includes means for performing operations that will be described later. In particular, each reception channel includes spectral analysis means; beamforming here has the particularity of involving operations in the spectral domain, and more specifically, beam steering operations.

[0098] Each receiving channel can be identified by an index p which is between 1 and P.

[0099] Note: Cp(m) is the complex correction to be applied to the receiving channel p in order to equalize it with the other receiving channels with a resolution equal to fEcH / (2M). The index m, which, modulo 2M, is between 0 and 2M-1, is representative of the frequency. τp(q) is the delay to be applied to the receiving channel p to form the beam q, and, if f0 is the carrier frequency reduced to DC after sampling, ϕp(q) (m) = -2π (f0 + mfEcH / (2M)). τp(q) is the corresponding spectral phase. αp(q) is a possible real weighting coefficient for the antenna aperture, for each index q of beam formed. The weighting law αp(q) is intended to improve the lobe levels of the directivity pattern of the antenna thus formed digitally. H(q)(m) is the complex gain. associated with the band limitation specific to each beam formed (Hilbert filter or spectrum limitation to the useful band);This complex gain is derived from a 2M-point FFT of its causal temporal response.

[0100] This can be interpreted as a frequency-dependent matrix operation that relates the vector of signals from the receiving channels to the vector of the formed beams. This operation can be decomposed as the product of three matrices, the first and last of which are diagonal: [C] the diagonal P x P matrix of equalization corrections of the receiving channels, [αe jϕ<] the full Q x P matrix of spectral phases associated with delays and aperture weighting coefficients, and [H] the diagonal Q x Q matrix of band-limiting filters.

[0101] If [X] is the vector P x 1 of the power spectral densities (sometimes referred to by the acronym DSP) of the receiving channels and if [Y] is the vector Q x 1 of the power spectral densities of the formed channels, the operation is then written: [Y] Qx1 = [H] QxQ x [αe jϕ<] QxP x [C] PxP x [X] Px1 (the matrices and vectors depend on the frequency of an antenna).

[0102] It should be noted that these three filtering functions, which are applied multiplicatively due to the filtering structure, since they operate in the spectral domain, follow each other in a very specific order, which is that of the matrix decomposition mentioned: the equalization of the channels [C] is applied first, after the FFTs which form the passage in the spectrum, then the delay as well as the antenna aperture weighting [ αe jϕ< ], operation duplicated on each receiving channel as many times as there are beams to be formed, and finally the specific band limitation [ H ] applied on each formed beam, that is to say after summation of the different contributions from all the receiving channels.

[0103] THE figures 9 And 10 describe a beamforming system in the special case where P and Q are equal (here equal to 4), that is, it is a 4-beam former from 4 receiving channels.

[0104] In these figures, for greater readability, the lines become increasingly wider depending on the index p or q considered.

[0105] The beamforming system is referenced as 10 and has 4 receiving channels 121, 122, 123, 124.

[0106] Schematically, the training system 10 comprises, for each reception channel 12, an input 14 operating in the time domain, a processing circuit 16 operating in the frequency domain and an output 18 operating in the time domain.

[0107] Input 14, processing circuit 16 and output 18 implement operations and can be interpreted as computer program products.

[0108] In particular, they can be implemented, at least in part, by a computer, such as a programmable logic circuit. Such a circuit is often referred to by the acronym FPGA, an English acronym for the expression “Field-Programmable Gate Array”, network of programmable doors on site.

[0109] In another example, they form an integrated circuit specific to an application. Such a circuit is often referred to by the acronym ASIC (acronym for the English “Application-Specific Integrated Circuit”, meaning "application-specific integrated circuit").

[0110] This means that these elements perform a beamforming function computationally, this function sometimes being referred to by the acronym FFC. The acronym DBF is sometimes used in reference to the corresponding English name of “Digital BeamForming”, meaning "digital beamforming").

[0111] In the example described, the processing circuit 16 has two computing channels 20 and 22 which are each connected to the input 14 by an FFT application unit M 24 and to the output 18 by an IFFT application unit M 26.

[0112] The two calculation paths 20 and 22 perform similar operations on points having respectively an even index (calculation path 20) and an odd index (calculation path 22).

[0113] Each channel contains an equalization unit 28, a delay and weighting unit 30 (shown in a larger format on parts A to H of the Figures 11 And 12 ), a summation unit 32 and a band limiting unit 34. These notations are only introduced on the first calculation channel 20 of the first reception channel 12 1 to ensure a certain readability of the figures 9 And 10 .

[0114] The equalization unit 28 applies the aforementioned matrix C, with the notation C p (2m) if it is the first lane 20 (referring to the fact that even indices are processed) and the notation C p (2m+1) if it is the second lane 22 (referring to the fact that odd indices are processed).

[0115] As seen on the Figures 11 And 12 The delay and weighting unit 30 applies delay and weighting coefficients as many times as there are bundles to be formed, i.e. 4 here.

[0116] The summation unit 32 of the first channel 20 sums the contributions obtained after the delay and weighting unit 30 from the first channels 20 of each receiving channel 12.

[0117] For the case of the first channel 20 of the first receiving channel 12 1, this means that the summation unit 32 sums the output of the delay and weighting unit 30 of the first channel 20 1 (the index 1 indicates that it is that of the first receiving channel 12 1), the output of the delay and weighting unit 30 of the first channel 20 2, the output of the delay and weighting unit 30 of the first channel 20 3 and the output of the delay and weighting unit 30 of the first channel 20 4.

[0118] Similarly, the summation unit 32 of the second channel 22 sums the contributions obtained after the delay and weighting unit 30 from the second channels 22 of each receiving channel 12.

[0119] For the case of the second channel 22 of the first receiving channel 12 1, this means that the summation unit 32 sums the output of the delay and weighting unit 30 of the second channel 22 1, the output of the delay and weighting unit 30 of the second channel 22 2, the output of the delay and weighting unit 30 of the second channel 22 3 and the output of the delay and weighting unit 30 of the second channel 22 4.

[0120] This being true for each summation unit 31, it is therefore clear that a relatively complex interconnection 36 is visible between the delay and weighting units 30 and the summation units 32.

[0121] The band-limiting unit 34 applies the H matrix and the same notations as for the C matrix are used.

[0122] Output 18 performs a recombination of the computation channels 20 and 22 using a shift unit 38 and an adder 40.

[0123] It should be noted that, depending on the application, the delay required on the different channels to deorient a beam can exceed one clock period. For example, for an antenna covering a relative bandwidth of 20%, with 32 x 32 (1024) elements, and a sampling frequency covering the entire antenna bandwidth, the maximum delay associated with beam formation in both directions is 2 x 16 x (1 / f₀ / 2) = 16 (f_ECH / B) x (B / f₀) / f_ECH = 6.4 / f_ECH. One might then imagine implementing the integer part of this delay numerically in the time domain, but this is no longer possible once the frequency domain is considered to simplify the simultaneous generation of several distinct beams. This delay must therefore be fully operated in the spectrum and it is necessary to plan for it in the design of the filters, in the sense that their increased time response of the max delay must remain less than N FFT / f ECH. 2.2.2 - Generalization

[0124] The elements that have just been described can easily be generalized, which leads to the training process now explained.

[0125] In a general case, the process of forming Q beams is implemented by a beamforming system comprising P receiving channels, each connected to a respective antenna, where Q is a non-zero integer and P is an integer greater than or equal to 2. For each receiving channel, the process includes the following steps: reception of a signal received by the antenna, generation of two calculation channels by sum and difference of the signal from the reception channel and of this same signal delayed by M periods, realization on the difference channel of a frequency shift of f ECH / 2M by multiplicative application of a signal e -jnPi / M< , n being an integer from 0 to M-1, M being an integer strictly greater than 2, implementation of first operations on the first calculation channel, the first operations including: the application of a discrete Fourier transform to M points on a signal from the transmitted signal to obtain M points in the spectrum of the signal from the transmitted signal, M being an integer strictly greater than 2, each point of the spectrum of the transmitted signal corresponding to even indices of a spectral analysis to 2*M points of the signal from the transmitted signal and being identified bijectively by an index which is an even number between 0 and 2*M-1 ,the application in the spectrum of a channel equalization function on the M points, to obtain equalized points, the application in the spectrum of a delay on the equalized points to generate Q series of M delayed points (via multiplication with a linear exponential in phase), and implementation of second operations on the second computational channel, the second operations comprising: the application of a discrete Fourier transform to M points on the signal from the transmitted signal to obtain M points in the spectrum of the signal from the transmitted signal, each point in the spectrum of the signal from the transmitted signal corresponding to odd indices of a spectral analysis of 2*M points of the signal from the transmitted signal and being identified bijectively by an index which is an odd number between 0 and 2*M-1, the application in the spectrum of a channel equalization function on the M points, to obtain equalized points,and the application in the spectrum of a delay on the equalized points to generate Q series of M delayed points (by means of multiplication with a linear exponential in phase), formation of each beam from the generated series of M delayed points, the formation comprising, for each beam: the implementation of third operations, the third operations comprising: the summation of the series of M delayed points from each first computational channel of a receiving channel, to obtain summed points, the application of a bandwidth-limiting function on the summed points to obtain limited points, and the application of an inverse discrete Fourier transform to M points on the limited points, to obtain a first output signal, the implementation of fourth operations, the fourth operations comprising: the summation of the series of M delayed points from each second computational channel of a receiving channel,To obtain summed points, a band-limiting function is applied to the summed points to be processed to obtain limited points, and a discrete inverse Fourier transform is applied to M points on the limited points to obtain a second output signal. The frequency translation of the second output signal then yields a translated output signal, followed by the recombination of the first output signal and the second translated output signal to obtain the formed beam.

[0126] In certain specific cases, the process may also exhibit the following properties: The first and second operations also involve applying an aperture weighting to the antenna of the receiving channel in question. Since the received signal is sampled at a sampling frequency, the equalization function has a resolution equal to the ratio of the sampling frequency to 2M; in a numbering system from 0 to 2M-1, even points are applied to the first calculation channel and odd points to the second calculation channel. The limiting function is obtained by applying a discrete Fourier transform to 2*M points of a time response of 2*M points exclusively contained in positive times (i.e., zero at the last M points). 2.3 - DESCRIPTION OF AN EXAMPLE OF A BEAM FORMATION METHOD

[0127] In this other example of a beamforming process, the process also optimizes the volume of output information by reducing the rate of each beam according to its useful bandwidth and by multiplexing, on the same output channel, beams of the same bandwidth lower than the channel rate.

[0128] Indeed, if the reception band of a given beam is significantly smaller than f ECH / 2 for real signals and f ECH for complex signals, it is desirable to decimate the signal by an integer or non-integer factor that can go up to the ratio of the bands; this is only possible in a simple way, of course, if this factor is an integer greater than 2 and preferably a power of 2. 2.3.1 - Decimation by 2 (for example, conversion from real to IlQ)

[0129] For example, when the input signal is real, it is common practice to halve the signal after Hilbert filtering in order to reduce the information flow; this is made possible by the fact that negative frequencies have been eliminated from the spectrum. Given this, we will focus on restoring the signal only for even-numbered times at the output of M-point IFFTs. If Hm is the IFFT input and hn its output, we can then write the following relationship, since the negative frequencies are eliminated by the filter at a level low enough to be considered zero in terms of instantaneous dynamics: h 2 n = ∑ 0 M − 1 H m e j 2 π 2 nm M = ∑ 0 M − 1 H m e j 2 π nm M / 2 = ∑ 0 M / 2 − 1 H m e j 2 π nm M / 2

[0130] This means that the even points, which are the only ones retained, consist of M / 2 IFFTs of only positive frequencies.

[0131] However, the natural output of the FFT is in "bit reverse," which, for an M-point FFT, consists of alternately outputting positive and negative frequencies, more precisely a point of positive frequency Hm immediately followed by the point of negative frequency Hm+M / 2. Restricting the FFT output to only positive frequencies then appears as a decimation of this output by 2, which means that outputting the spectrum in "bit reverse" is an expression of the duality that exists between subsampling by 2 in the time domain and positive / negative subbands in the spectrum.

[0132] This characteristic can then be advantageously used to time-multiply two different beams; this is made possible thanks to the internal architecture of the DFT with M = 2N points forming an IFFT. DFT is the acronym for the English name of " Discrete Fourier Transformwhich means "Discrete Fourier Transform".

[0133] Indeed, it is known to advantageously decompose the inverse DFT at 2N< points into N successive stages called "radix2", each forming a 2-point inverse DFT (which is identical to the 2-point DFT) and separated by time-varying phase rotation stages called "tweedle factors". In such a decomposition, these 2-point inverse DFTs operate on data whose multiplexing ratio increases along the IFFT (1 for the first stage, 2 for the second, 4 for the third, etc.).

[0134] Due to the reverse bit output, Hm and Hm+M / 2 are two points in the spectrum, one in the positive frequencies and the other in the negative frequencies, which are delivered successively at the output of the M-point FFT. Therefore, formally, the output of the M-point IFTFT is written as: h 2 n h 2 n + 1 = ∑ m = 0 − 1 + M / 2 e + j 2 π nm M ′ 2 × 1 × M m + H m + M / 2 e + jπ m M / 2 × M m − H m + M / 2

[0135] We observe that, indeed, the first step of this M-point IFFT consists of a DFT of the two consecutive points Hn and Hn+M / 2, the result of which, sum and difference, also emerges consecutively. This result is then multiplied by a different "tweedle factor" for the two points thus created.

[0136] We also observe that the two results thus multiplied form two interlaced series of points, each of which undergoes an IFFT at M / 2 points, leading to the scheme of the figure 13 , which illustrates the decomposition of an M-point IFFT into a 2-point DFT and an M / 2-point IFFT.

[0137] As shown by figure 13 , an M / 2 = 2 N< points IFFT can be considered as the cascade of a non-multiplexed 2-point DFT and a 2-multiplexed M / 2 = 2 N-1< points IFFT, which amounts to simultaneously performing 2 distinct M / 2 = 2 N-1< points IFFTs on two interlaced point series.

[0138] This therefore allows, by short-circuiting the 2-point DFT head stage and the "tweedle factor" stage which directly follows it, the use of an M-point IFFT operator, either as such, or as an M / 2-point IFFT operator multiplexed by 2, that is to say working in a multiplexed manner on 2 interlaced series of points.

[0139] It is this capability that can be advantageously implemented to multiplex two distinct beams, each decimated by two, onto the same output, as shown by the figure 14 which illustrates a beamforming system with multiplexing of 2 beams decimated by 2.

[0140] In this case, the digital local oscillator e +jπn / (M / 2)< is adapted to be maintained for 2 periods (multiplexing rate here). Decimation by 2 K< of the band between 0 and -1 + 2 NK<

[0141] By reproducing K times the decomposition presented in the previous paragraph, we can exploit the fact that at the output of an FFT with M = 2 N< points, the points of frequency H m+kM / 2K appear successively for 0 ≤ k ≤ -1 + 2 K< .

[0142] For example, by decomposing the M / 2 point IFFT in the same way into a 2 point DFT, a "tweedle factor" stage and an M / 4 point IFFT, we can also multiplex 4 series of interlaced points since only the frequencies from 0 to -1 + M / 4 are kept and we can therefore decimate by 4 after applying the anti-aliasing filtering which eliminates the other frequencies.

[0143] By generalizing this approach, it is possible to consider more generally that an IFFT at M = 2 N< points is the cascade of an inverse DFT at 2 K< points not multiplexed, a stage of "tweedle factors" and an IFFT at 2 NK< points multiplexed by 2 K<, which amounts to simultaneously performing 2 K< IFFT at 2 NK< distinct points on 2 K< interlaced point series.

[0144] Thus, step by step, by short-circuiting the inverse DFT stage with 2K< head points and the tweedle factor stage that directly follows it, it is also possible to multiplex 2K< series of interlaced points using the same IFFT multiplexed by 2K<, provided that only points with frequencies from 0 to -1 + M / 2K< are retained and can therefore be decimated by 2K<. The capability described previously for decimation by 2 and multiplexing of 2 beams can thus be extended to decimation by 2K< and multiplexing of 2K< different beams.

[0145] One way to achieve this is shown in the figure 15 which shows the modification of the IFFT to 2N< points for the multiplexing of 2K< beams decimated by 2K<. As this shows figure 15It suffices to equip the 2N< point IFTTT with a set of switches allowing, via appropriate addressing, entry into the IFTTT at the required location to perform IFTTT processing at 2NK< points operating on 2K< multiplexed data. The addressing of the different switches is done using the binary description of 2K< -1.

[0146] Such a block can be integrated into the training system of the figure 16 to make it work with a decimation / multiplexing rate of 2K<. The block is indicated by "block figure 15 » in the figure 16 which presents such a generalized training system. 2.3.2 - Case of bands not between 0 and -1 + 2 NK<

[0147] We will denote bit_reverse(k,K) the function which associates to k the integer given by reversing the bits of the description of k on K bits.

[0148] It can be noted that bit_reverse(bit_reverse) is the identity function.

[0149] Furthermore, we will have, for example: bit_reverse(0,K) = 0. bit_reverse(2 K-1< ,K) = 1 and, more generally, bit_reverse(2 KM< ,K) = 2M-1 for 1 ≤ M ≤ K, bit_reverse(2k+1,K) = bit_reverse(2k,K) + 2 K-1< for 0 ≤ k ≤ 2 K-1< - 1.

[0150] In general, the band of interest to keep, consisting of 2 NK< cells, m + kx 2 NK< and m - 1 + (k+1) x 2 NK< with 0≤ m ≤2 K< -1: The case m = k = 0 corresponds to the previous paragraph in which the band is between 0 and -1 + 2 NK< , if m = 0 and k ≠ 0, the band of interest corresponds to one of the natural sub-bands of the FFT; the cells that compose it then come out periodically but with a shift equal to bit_reverse(k,K). As soon as m ≠ 0, the different cells constituting the band of interest no longer come out periodically.

[0151] Although these three cases lead to differences in the behavior of the data output order, all three operating cases can nevertheless be grouped under a single operating mode.

[0152] All you need to do is: read the spectrum only at the instants corresponding to the frequency cells constituting the useful band, that is to say at the indices n such that: n MIN = m + k 2 N − K ≤ bit_reverse n , 2 N ≤ n MAX = m − 1 + k + 1 2 N − K maintain the value until the next sampled value, and resample the signal thus obtained at times nx 2 K< - 1.

[0153] An implementation of such a procedure is represented on the figure 17 which represents a frequency recalibration device for the decimated band including in particular a counter, a bit reverse unit and two sample-and-hold units.

[0154] This introduces a latency of 2K< clock cycles. In the example of the figure 17It is assumed that there is no processing latency, with such latencies potentially being addressed through the use of devices known to those skilled in the art. To avoid disrupting the synchronization of subsequent operations and resulting in a fixed latency regardless of the multiplexing ratio, this latency can be compensated, for example but not exclusively, by applying a complementary delay equal to 2N< -2K< clock cycles to the resulting signal.

[0155] This creates a folding of the useful band into the undersampled band [0 - f ECH / 2 K<]. Indeed, the order of the FFT output data is as follows: first the 2 K< samples 0 of each of the 2 K< sub-bands, these sub-bands appearing in the order fixed by bit_reverse(x,2 K< ), then the other samples, delivered in successive packets of 2 K< values ​​each corresponding to the same index in the set of sub-bands, the order of the indices being fixed by bit_reverse(x,2 KN< ).

[0156] Therefore, the first sample of interest (i.e., belonging to the useful band) to come out of the FFT is the sample such that (m + kx 2 NK< ) modulo 2π is zero, i.e. the 0th sample of the kth< sub-band in the case where m = 0 and of the (k+1)th< if m ≠ 0.

[0157] When m = 0, the samples traverse the kth sub-band; they are all spaced 2K apart. If m ≠ 0, the samples of interest belong either to the kth sub-band or to the (k+1)th sub-band.

[0158] However, it turns out that at the output of FFT the samples are presented in slices of 2K points, a slice representing all the sub-bands for the same given position within the sub-band.

[0159] Therefore, by sampling at the times corresponding to the output times of the 2 NK< points of the useful band and maintaining the value until the next frequency point, we have at the end of a slice, i.e. at t = nx 2 K< - 1, a frequency sample whose position in its original sub-band is indeed that corresponding to the slice in question.

[0160] In doing so, the last samples of the kth sub-band were placed at the end of the band thus created; this corresponds to the folding of the useful band, positioned straddling two sub-bands, into the undersampled band [ 0 - f ECH / 2 K< ].

[0161] This folding corresponds to a frequency transposition of -(k+1) f ECH / 2 NK< . Thus, the center of the processed band is located at [ 2 -N< (2m - 1) - 2 -K< ] / f ECH / 2 in the undersampled band [ 0 - f ECH / 2 K< ].

[0162] The subsequent evolution of the beamforming system with multiplexing of 2K< beams decimated by 2K< but now occupying the same band located arbitrarily within the sampling band is presented on the figure 18 , figure in which each block is marked "block of the figure 17 » includes the elements of the figure 17 .

[0163] It is then clear that, as will be presented in the following paragraphs, the pointing operations of these 2 K< multiplexed beams must also be carried out in a multiplexed manner as a set of 2 K< delays, and as a possible set of 2 K< antenna aperture weightings. 2.3.3 - Decomposition into successive partial beam formations

[0164] When the number of receiving channels becomes significant, it is not possible to perform all the calculations in a single device, both because of the number of inputs / outputs this implies and for reasons of computing power. In this case, it is necessary to distribute all the calculations across several devices. The natural break in this decomposition of calculations occurs at the summation of the contributions of the different channels, an associative operation by nature which also generally concentrates the data because the number of beams formed is very often much lower than the number of receiving channels, especially since, as soon as the useful bandwidth of a beam is reduced, it is advantageous to perform multiplexing as described earlier in this section.The receiving channels are then grouped into subgroups and the beamforming part that concerns them forms partial beams or subbeams, the additive recombination of which is also carried out in an additional grouping device, which can itself be split into several successive concentration stages if the number of inputs / outputs is too large.

[0165] This is represented on the one hand on the figure 19 which corresponds to a synoptic representation of the functioning and on the other hand on the Figures 20 And 21 which each represent a part of the beam formation system that would thus be obtained (an example is proposed here with four subbeam formers and two subbeam combination stages). 2.3.4 - General case

[0166] The elements that have just been described can easily be generalized, which leads to the training process now explained.

[0167] In a general case illustrated by the figure 19 The process of forming Q beams is implemented by a beamforming system comprising P receiving channels, each linked to a respective antenna, where Q is a non-zero integer and P is an integer greater than or equal to 2. The Q beams are implemented by Q' beam groups calculated in a multiplexed manner by the same operator as described previously. For each receiving channel, the process includes the following steps: The system establishes two processing channels by summing and subtracting the signal from the receiving channel and the same signal delayed by M periods. On the second processing channel (the difference channel), a frequency shift of nπ / 2M is applied multiplicatively to a signal e(-jnπ / M) (or e(-jnπ / M)< depending on the notation used, both denoting the same operation), where n is the current variable ranging from 0 to M-1. Applying FFTs with M points on each processing channel allows the system to enter the frequency domain. A multiplicative spectral correction function is then applied to equalize the receiving channels. By duplication, the Q' channels are created to form the Q' groups of multiplexed beams, also numbered q' between 1 and Q'. The operations are implemented, including possibly aperiodic sampling followed by resampling, according to the technique of... figure 15 , to achieve an effective decimation by 2 Kq'<of these Q' series of points maintained for 2 Kq'< periods, which allows for subsequent multiplexing of 2 Kq'< beams. Such multiplexing allows several beams formed in a given time to be passed, thus increasing capacity.

[0168] All of these operations are intended to obtain Q = sum of the 2 Kq'< on q' ranging from 1 to Q' contributions of the receiving channel to the formation of the Q beams.

[0169] Another way to present this process would be to use operations as proposed in section 2.2.1 (case of figures 9 And 10 ), this equivalent description is not repeated in what follows in order not to make the present description too cumbersome.

[0170] On each of these Q contributions, partially multiplexed into Q' processing channels, each comprising two calculation channels (even and odd frequencies of the spectrum), application of: a linear spectral phase delay and an amplitude weighting.

[0171] Then, the processing channels from each of the reception channels are summed to form Q partially multiplexed bundles into Q' processing channels. This summation operation can be carried out in accordance with paragraph 2.3.3 by creating intermediate sub-bundles.

[0172] On each of the two calculation paths of each of the Q' processing paths referenced by the index q': application of a multiplicative band-limiting function. application of an iFFT to M / 2 Kq'< points multiplexed by 2 Kq'<. on the second computing channels (odd frequencies), transposition of the spectrum by a frequency shift of nπ / 2M by multiplicative application of a signal e[+j floor(n / 2 Kq'< )π / ( M / 2 Kq'< )] , n being the current variable ranging from 0 to M-1 and the floor function denoting the floor function,

[0173] On each of the referenced processing channels, the two computational channels are summed to ultimately form the Q partially multiplexed bundles into Q' groups of bundles referenced by the index q' and multiplexed by 2 Kq'< . 3 - DESCRIPTION OF A CALIBRATION PROCESS

[0174] As mentioned, in any beamforming process, the quality of the signal degrades when the receiving channels do not exhibit exactly the same response. It is also known that differences in response, both in spectral amplitude and spectral phase, are corrected prior to any beamforming. This is achieved by the beamforming system via the equalization stage using the cp coefficients. These correction values ​​relate to the amplitude and spectral phase of the complex gain of each channel and are generally acquired through calibration.

[0175] In principle, beamforming does not require that the channels be equalized, that is to say that their responses be brought to the same flat response, but simply that they be recalibrated with respect to each other, that is to say that the complex gain differentials between channels are compensated so that all the receiving channels are brought to the same average response.

[0176] On the other hand, channel equalization, which is therefore not a requirement associated with channel formation, can be justified elsewhere, for example to ensure that the appropriate processing (pulse compression) is carried out with the desired filtering function.

[0177] Whether for equalization or simple recalibration, the principle of calibration consists of injecting the same test signal into the different channels and comparing the received signal to a reference.

[0178] Depending on whether the goal is equalization or simple recalibration, the calibration philosophy regarding this reference may vary: For equalization, which consists of calibrating each channel independently, comparison to the reference must be used to extract the response of each channel; for this, the reference, which is the test signal, must be known, but, as the calibrations of the different channels are independent, it is not required that the same signal be used for all channels, and for recalibration, only the knowledge of the response differential between the channels is sought, so that knowledge of the calibration signal is not required, since each channel is compared to the other channels; it is sufficient to inject, without needing to know it, the same signal into two channels to access the differential between these channels.

[0179] Regardless of the objective, whether equalization or recalibration, calibration involves comparing two signals. Traditionally, the signals used for calibration are sinusoidal signals, and their use provides gain, amplitude, and phase information to be realigned for each of the frequencies used.

[0180] But it is also possible to use noise when a spectral analysis is available in each receiving channel; this allows the measurement of the transfer function differential between two receiving channels.

[0181] For example, a method for determining the phase differential coefficient of two receiving channels, each comprising an analog-to-digital converter, can be considered. Each analog-to-digital converter is clocked at the same sampling frequency. According to industry standards, the receiving channels include, prior to sampling, filtering stages designed to limit the bandwidth of the received signals to a single Nyquist band of the sampling function. The method includes at least one step of: injection of a signal at the input of each of the receiving channels, the signal being an optionally white noise signal, to obtain output signals, obtaining the output signal of each analog-to-digital converter, spectral analysis, frame by frame, of each output signal, this spectral analysis allowing for a plurality of frequency channels, each channel being identified by an integer, estimation, by integration over several successive frames, of the power correlation between at least two channels of the same index from the spectrum of the signals from each of the analog-to-digital converters, the phase difference between two receiving channels being carried by the phase of this correlation, and on each of the receiving channels, estimation, by integration over several successive frames of the spectra obtained, of the DSP of the signal,The difference in amplitude between the two reception channels corresponds to the ratio of the DSPs thus estimated.

[0182] The signal to be injected can be obtained by implementing the following steps: the generation of a digital calibration signal, the conversion of the calibration signal to analog, the frequency transposition of the converted calibration signal, the amplification of the transposed calibration signal, and the balanced distribution to the different receiving channels.

[0183] Thus, such a process corresponds to using noise, not necessarily white, but which can be considered as the result of filtering white noise, allows us to trace back to the amplitude and phase differentials via the cross-correlation between channels of the same rank and via the DSP at the output of each channel (which is obtained as the variance of the output of the different channels).

[0184] It is also possible to replace the spectral analysis output of one of the two channels with the spectral analysis of a reference digital signal constituting the test signal after digital-to-analog conversion; with prior calibration of the transmission part, this allows the absolute calibration of a channel for the purpose of equalization.

[0185] In any case, whether the calibration is intended for equalization or recalibration, whether the type of signal used is coherent (sinusoidal) or not (noise), the calculation of correction coefficients requires raw data obtained by correlation and / or partial spectral analysis (a demodulation with low-pass filtering intended to calibrate a single frequency point is similar to a single-channel spectral analysis).

[0186] Moreover, particularly because beamforming has, in the past, only been practiced in a narrowband application setting which reduces the controls to simple sets of complex gains (phase and amplitude) independent of frequency, calibration has, until now, been carried out in the spectral domain with sinusoidal test signals (one calibration point per working frequency).

[0187] However, the need to form broadband beams requires that calibration also become broadband, which requires that the calibration signal itself be composed of several frequencies covering the working range, whether sequentially or instantaneously.

[0188] Two philosophies therefore exist regarding the nature of calibration.

[0189] According to one philosophy, the spirit of the old techniques is preserved by staying in the spectral domain and replacing the sinusoidal test signal with a succession of sinusoidal frames (this technique is sometimes also referred to by the corresponding English term "step frequency").

[0190] This involves in particular setting up a calibration process sequence involving both an agile generator for the synthesis of the test signal and all the reception channels for the measurement.

[0191] The sequencer must also handle the storage and transmission of data acquired during the measurement process to a computer. Synchronizing this process also takes into account the stabilization times of each frequency step, as well as the accurate timing of these measurements from one receiving channel to another. This last point is not a problem if all the receiving channels are located on a single circuit, but becomes one when these channels are distributed across multiple circuits.

[0192] In contrast to this first philosophy lies the use of broadband noise, in the sense that this type of signal instantaneously contains all the spectral components useful for calibration.

[0193] In this case, two approaches are possible: either time-based or frequency-based.

[0194] The time-domain approach involves calculating the covariance between a reference signal and a set of replicas of the received signal, each shifted by one clock cycle. This approach provides a time-domain response that would need to be deconvolved by autocorrelation of the reference signal, which is only feasible in practice if the reference signal is white noise. Therefore, this approach does not allow, in particular, for one channel to be used as a reference for another channel in order to measure a differential quantity.

[0195] Thus, the frequency approach is clearly preferable; this approach is described previously with the aforementioned determination method.

[0196] This approach describes the possibility of performing a differential measurement between two receiving channels, provided that these channels are equipped with spectral analysis. The technique consists of calculating, through frame-by-frame integration, the power spectral density pn(k) on each channel and the power correlation cn,m(k) between channels of the same rank k on each channel; the amplitude / phase difference between channels is then obtained as the normalization of the correlation by one of the DSPs. c n , m k / p n k ou c m , n k / p m k = c n , m k * / p m k

[0197] The advantage of this method is that it does not require any particular sequencing since all frequencies of the spectrum are processed simultaneously.

[0198] Another advantage is that the noise does not need to be white, as it is sufficient that it can be considered as the result of filtering white noise and that all the useful spectral components are present; thus a simple wideband noise generator (noise diode, chain of high-gain amplifiers) is sufficient, knowing that the analog receiving chains are responsible, in principle, for limiting its band to the useful band with a selectivity consistent with the need for instantaneous dynamics.

[0199] It will be easily understood that the 10 training system is adapted to this second philosophy, since it involves a spectral analysis on each reception channel and the resolution required for calibration is, in principle, that of this spectral analysis.

[0200] Furthermore, the presence of the first multiplier used for channel alignment can be leveraged, via a multiplexer, to perform the product inherent in the correlation calculation. The only additional resource required to ensure calibration is then a multiplexed integrator on M points (M being the length of the FFTs).

[0201] There figure 22 shows a calibration device for training system 10, the calibration device making some modifications to the receiving channels to ensure calibration: a multiplexer M for each channel taking as input the channel equalization function (coefficients C(2m) or C(2m+1) omitting the channel reference) and a reference signal denoted R, and a CC calibration circuit including a frame-to-frame integrator.

[0202] These resources are duplicated on the even frequency channel and on the odd frequency channel.

[0203] The calibration process described above allows for differential calibration between multiple receive channels by correlating the FFT outputs. This process is performed autonomously as long as all receive channels are located on the same circuit.

[0204] If this is not the case, as has been mentioned, then it is necessary to "pass" at least one reception channel from one circuit to another, which poses both a synchronization problem and increases the need for communication channels between circuits.

[0205] One solution to overcome this problem is to prefer absolute calibration, relative to a common numerical reference for all receiving channels.

[0206] For this, we will have two elements: A noise generator is used to synthesize calibration noise; the signal from this generator, or a decimation of this signal (it is desirable for the noise to be generated at a higher rate to avoid degradation by its transmission chain), constitutes the reference signal. A duplication of this reference generator on each circuit allows the formation of sub-beams from a subgroup of receive channels. Using these replicas eliminates the need to broadcast the reference signal to all circuits, simplifying interconnections and thus making each circuit completely autonomous. To facilitate synchronization between different circuits, care should be taken to ensure that the calibration noise generation performed by this generator is synchronous with the FFT frames.

[0207] A second aspect of the calibration process involves substituting a synchronization signal for the FFT signal during the calibration phase. Using the data path to carry this signal, which restores synchronization, allows it to be naturally directed to the grouping blocks. If grouping occurs via several sub-blocks, such a synchronization signal must be regenerated in each sub-block for the next, and finally, for the last sub-block, for the final block that performs filtering and time return.

[0208] The calibration process as described therefore requires no specific resources in terms of real-time signal transmission: neither distribution of the common reference, nor exchange of signals between the different subbeam formation circuits.

[0209] A very particular aspect of noise calibration processes via spectral analysis lies in the fact that the time lag between the measured channel and the reference signal tends to bias the measurement; this is due to the fact that the coherence between the two signals disappears at the edge of the frame.

[0210] Thus, the main effect of this partial decorrelation is a multiplicative amplitude bias equal to 1 - |τ| / T where τ is the time lag between the two signals and T is the duration of the spectral analysis, here 2N FFT / f ECH.

[0211] Other, less significant effects can also occur due to decentering, such as localized ripples primarily at the band edges. Even though this bias is similar for all receiving channels when calibration is performed using a reference signal (and not between channels), and therefore does not impact the channel differential, it is still advisable, to reduce this effect, to perform calibration in two steps: A first, short step is used to "rough out" the result in terms of delay: an order of magnitude of this delay is determined from the average phase slope, then rounded to the nearest multiple of 1 / f ECH. From this initial measurement, it is possible to digitally realign the signals using a realignment device placed upstream of the processing. A second, longer, and more precise step is then performed, with little or no bias because it processes time-realigned signals.

[0212] This implies, of course, that a time-registration device must be introduced at the beginning of the processing, before entering the spectral domain. Such a device, the schematic of which is presented by the figure 21 , includes an adjustable delay line, directly controlled by the result of the first calibration phase (delay rounded in number of sampling periods).

[0213] This device is directly controlled by the delay to be applied which can be indifferently positive or negative between -2 Q-1< and -1 + 2 Q-1< .

[0214] When the delay to be applied is zero, i.e., in the initial position, the absolute delay applied by the device is 2Q-1; the delays are applied relative to this reference absolute delay. Inverting the most significant bit allows this delay to be centered within the multiplexer's excursion.

[0215] It should be noted that the amplitude difference between the measured channel and the reference signal can also be calculated by taking the square root of the ratio of their respective power densities. This has the advantage of not being biased in amplitude but, conversely, the disadvantage of requiring additional dedicated computing resources to estimate the power density of the measured channel signal.

[0216] By reformulating what has just been described in a similar way to what was done previously for the training process, this section deals with a calibration process for the training system comprising: 1) the exploitation of the first part of the architecture previously described (see previous sections) to operate: a spectral analysis at 2M points distributed on two computing channels carrying respectively the even and odd frequencies of this analysis, and a multiplicative function in the spectral domain, 2) a replication of the calibration signal generator on each of the circuits allowing to form subbeams from a subgroup of reception channels, this generation being synchronized with the spectral analysis of point 1, 3) the spectral analysis of this calibration signal by a device identical to that of point 1.4) on each of the receiving channels, the calculation of the power correlation between the spectrum of a receiving channel and that of the calibration signal and the DSP of the calibration signal, and 5) the calculation of the correction to be applied to the channel as a ratio between the DSP of the calibration signal and the power correlation, or, alternatively, the exploitation of only the phase of this ratio and the ratio of the DSP of the reference signal and the signal of the measured channel.

[0217] Since the replication of each calibration signal is synchronized with the spectral analysis of point 1 for each receiving channel, by construction, the calibration process ensures that the receiving channels are recalibrated with each other. 4 - TRANSPOSITION OF TRAINING PROCESSES TO BROADCASTING

[0218] Beam formation in transmission, which could more accurately be called transmission path formation in a multibeam context, is generally based on the same principles as those described for reception.

[0219] We have several groups of 2K< signals sampled at fECH / 2K< and multiplexed, the 2K< sampling / multiplexing rank being specific to each group and each signal being intended for a transmission beam generated by an array of antennas. These different signals are complex and are, by principle, included in the undersampled band (i.e., [0 - fECH / 2K<]); their transmission therefore requires that they be interpolated to be brought down to fECH on each transmission channel.

[0220] However, due to potential undersampling by 2K<, an ambiguity of a multiple of fECH / 2K<, which is a fundamental ambiguity, remains regarding the actual position of these signals in the final sampling band [0 - fECH]. Furthermore, it is possible to take advantage of the beamforming operation to perform a frequency shift specific to each beam group.

[0221] In parallel with beamforming at the receiver, the formation of the various beams consists of applying certain filters to the signals: an interpolation adapted to the different signals, then the application of delays corresponding to the different beam-transmission channel pairs, accompanied by antenna weighting and followed by beam transposition, then additive groupings intended to form the transmission channels, then the application of equalization corrections to the transmission channels.

[0222] All of these operations correspond to the reversal of the operations performed in beam formation at reception.

[0223] In this context, it is the FFT that is modified to adapt to the multiplexing rate of the input data; this modification, which is the dual of the modification made to the IFFT on the figure 15 , is the subject of the figure 24 .

[0224] The proposed multibeam emission path formation system is schematically represented on the figure 25 .

[0225] This system includes, in particular: the partial formation of pathways for multiplexed bundles corresponding to the so-called "dual" block of the block of the figure 17 which is described on the figure 26This operation, which can be interpreted as a transposition, consists of integrating all the multiplexed beams that have been previously weighted and delayed. This operation is accompanied by sampling and resetting at the end of each slice (a slice of 2K< samples corresponding to a frequency of 2K< multiplexed beams) and holding for the duration of one frame. The interpolation (x2K<) at f ECH of the partial channels thus formed is described in the figure 27 : this step consists of inserting zeros for all frequencies outside the useful band. Using the same notation as in the section dedicated to beamforming at the receiver, if n is the current index, the useful frequencies correspond to n MIN ≤ bit_reverse(n,2N) ≤ n MAX with n MIN = m + k 2 NK< and n MAX = m - 1 + (k+1) 2 NK< .

[0226] Considering all the elements described so far, and again reformulating, a first embodiment of a corresponding process is a process for forming P multibeam emission channels from Q partially multiplexed beams on Q' beam groups indexed by q' (between 1 and Q') for multiplexing ratios equal to 2 Kq'< with Q = Σ q' 2 Kq'<

[0227] The process includes, for each group of beams, the following steps: generation of two channels by summing and subtracting the signal and the same signal delayed by M periods, realizing a frequency shift of nπ / (M / 2 Kq'< ) by multiplicative application of a signal e[-jnπ / (M / 2 Kq'< )], n being an integer from 0 to M / 2 Kq'< -1 , M / 2 Kq'< being an integer strictly greater than 2, implementation of operations on each of the calculation channels, the operations including: the application of a discrete Fourier transform to M / 2 Kq'< points multiplexed by 2 Kq'< to obtain M / 2 Kq'< points in the spectrum, each point in the spectrum corresponding to even indices in a spectral analysis at 2* M / 2 Kq'< points of the signal resulting from the formed signal and being identified bijectively by an index which is an even number between 0 and 2*M / 2 Kq'< -1 ,The application of a band-limiting function to points in the spectrum to obtain limited points, the formation by duplication of as many replicas as there are transmission channels to be formed (if this number is large, this replication can extend over several different computing boards), for each replica formed on each computing channel and for each multiplexed beam: the application of the delay to contribute to forming the transmission channel associated with the replica, the application of amplitude weighting, the partial formation of the transmission channel by integration of the 2 Kq'< Multiplexed points and maintenance on 2 Kq'< periods ( figure 26 ), the application of the interpolation process may be accompanied by a frequency shift through resampling and insertion of 0s ( figure 27 ), And

[0228] At this stage, in the spectral domain, for each channel to be formed, we have Q' partially formed channels.

[0229] The process then includes summing the signals from these Q' partial channels to form an emission channel available on a first calculation channel for even frequencies of the spectrum and on a second calculation channel for odd frequencies of the spectrum.

[0230] For each of the calculation methods of each path formed: application of frequency equalization correction for the transmission channels, application of an M-point IFFT on the second calculation channel, realization of a linear transposition of the spectrum,

[0231] The process then involves a final additive grouping operation of the two calculation channels to obtain the time signal of the channel formed. Conclusion

[0232] The described processes enable the execution, through a single device, of all operations associated with beamforming at reception and multibeam channel formation at transmission. To achieve this, they utilize specific FIR filter architectures that are driven within the spectrum.

[0233] By operating in the frequency domain, these architectures reduce the implementation of any delay to a simple multiplication by a complex exponential with linear phase; they simultaneously ensure: the filtering associated with the delay function, at reception, the Hilbert filtering intended for I / Q demodulation if the input signal is real and / or the filtering of the useful band associated with the formed beam, at transmission, the interpolation filtering in the case of narrowband beams, and the filtering associated with the equalization of the reception or transmission channels.

[0234] In this architecture, a pass through the spectrum is performed, and all the aforementioned filtering operations take place within this domain; this pass through the spectrum is carried out: At reception, at the level of each receiving channel, the time feedback occurs at the level of each beam formed; at transmission, at the level of each beam, the time feedback occurs at the level of each channel formed.

[0235] When the useful bandwidth is smaller than the sampling bandwidth, it is possible, thanks to the inherent nature of FFT and IFFT architectures which consists of a decomposition into successive radix-2 stages, to multiplex several beams occupying the same useful bandwidth; this is done naturally via a simple adaptation of this architecture.

[0236] At reception, the output of such a beamformer therefore allows one to have indifferently a beam of band f ECH / 2 or f ECH depending on whether the input signal is real or complex (i.e. from an I / Q demodulation process with decimation by 2) or 2 K< multiplexed beams of band f ECH / 2 K<.

[0237] By multiplying the training operations and output paths, it is also possible to simultaneously have on different outputs a set of beams as described but presenting different bands on each output n with the relation B nx N n = f ECH / 2 or f ECH depending on the type of input signal, B n being the band of the beams carried by the output n and N n their number.

[0238] In transmission, this type of architecture is applicable in a dual manner to transmission with a few adaptations associated with the fact that beams are multiplexed at reception and de-multiplexed at transmission.

[0239] Since this beam and / or channel formation is very wideband, the present methods are suitable for any receiving (respectively transmitting) system comprising several digital receiving chains whose combination allows improved listening in one direction (respectively several transmitting chains whose combination allows simultaneous transmission of several beams in different directions).

Claims

1. Method of forming P multi-beam transmission paths from Q beams multiplexed on Q' groups of beams indexed by q', q' being an integer varying between 1 and Q', Q' being an integer greater than 1, and the multiplexing rate being 2kq', Kq, being a respective integer for each value of q', the method being implemented by a computer of a transmission beamforming system comprising P transmission paths, each equipped with an antenna having a respective aperture, Q and P being two integers greater than or equal to 2, the method comprising: - for each group q' of beams, the passing to the spectral domain of the signals making up the group of multiplexed beams, to obtain multiplexed spectra, - the implementation of operations in the spectral domain, said operations comprising pointing and interpolation operations comprising: - an operation to form as many replicas of the spectra as there are transmission paths to be formed, - for each replica corresponding to each of the P transmission paths, an operation to generate a contribution to the corresponding transmission path by the implementation, for each contribution, of an operation multiplexed by 2Kq' for the introduction of a set of 2kq' delays, and of a possible set of 2kq' antenna aperture weighting operations, - an integration operation on 2kq' points, - an interpolation operation by insertion of 2kq' - 1 zeros, and - an operation for the summation of the contributions to a transmission path corresponding to each group of beams, the summation operation being carried out for each transmission path to be generated, the method being characterised in that it comprises, for each group of beams, the formation of two calculation paths, the input signal of the first calculation path being obtained by offsetting the signal from the beam by M points, M being an integer greater than or equal to 2x2kq', to obtain an offset signal, and the calculation of the sum of the signal from the group of beams and the offset signal, and the input signal of the second calculation path being obtained by offsetting the signal from the group of beams by M points to obtain an offset signal, and the calculation of the difference between the signal from the group of beams and the offset signal, said difference being frequency translated by multiplicative application of a signal e[+j floor(n / 2kq')π / (M / 2kq')], n being an integer ranging from 0 to M-1 and the floor function designating the integer part function, M being an integer greater than or equal to 2x2kq', e designating the exponential function, and j designating the complex number such that j2=-1.

2. Forming method according to claim 1, wherein the operations implemented in the spectral domain additionally comprise a path equalisation operation, the equalisation operation being implemented after the pointing operations.

3. Forming method according to claim 1 or 2, wherein the operations implemented in the spectral domain additionally comprise a band limiting operation, the band limiting operation being implemented before the pointing operations.

4. Forming method according to any one of claims 1 to 3, wherein the passing to the spectral domain is carried out on each of the calculation paths by application of a discrete Fourier transform at M / 2kq' points multiplexed by 2kq'.

5. Forming method according to any one of claims 1 to 4, wherein the method comprises a step of returning to the time domain, the step of returning to the time domain comprising the application of an M-point inverse discrete Fourier transform on each of the calculation paths, the method comprising an operation of spectral offset of the second calculation path by multiplicative application of a signal e+jnPi / M and an operation for the summation of the two outputs of the two calculation paths.

6. Computer, in particular a programmable logic circuit, capable of implementing the operations of a forming method according to any one of claims 1 to 5.

7. System for forming P multi-beam transmission paths from Q beams multiplexed on Q' groups of sub-beams indexed by q', q' being an integer varying between 1 and Q', Q' being an integer greater than 2, transmission beamforming system comprising P transmission paths, each equipped with an antenna having a respective aperture, Q and P being two integers greater than or equal to 2, the forming system also comprising a computer according to claim 6.

8. Computer program product comprising instructions which, when the program is executed by a computer, cause the computer to implement the operations of a method according to any one of claims 1 to 5.

9. Computer-readable medium comprising instructions which, when executed by a computer, cause the computer to implement the operations of a method according to any one of claims 1 to 5.