Methods and devices for detecting an interference signal

Description

[0001] The present invention relates to a method for detecting the presence of a jamming signal. The present invention also relates to an associated computer, a receiving device, a platform, a computer program product and a readable information medium.

[0002] In telecommunications, a transmitter seeks to transmit a signal to a recipient, called the receiver. Ideally, the receiver would receive an incident signal exactly equal to the transmitted signal.

[0003] However, this is not the case, the incident signal is distorted for several reasons: the incident signal interacts with the environment so that the incident signal propagates along multipaths, the incident signal is mixed with thermal noise produced by the receiver and the incident signal is likely to be jammed (the term "interference" is often used to refer to this last phenomenon). The sources of jamming can be multiple, one of the most frequent being the emission of another signal on another channel.

[0004] It is therefore desirable to be able to determine the different components of the signal, which are the useful signal, the thermal noise and the possible interference in order to be able to extract the useful signal.

[0005] An example of such extraction consists of developing a dedicated filter allowing, for the receiver considered, to filter out the non-useful components of the signal, namely thermal noise and possible interference.

[0006] However, such a technique requires precise knowledge of the receiver and its operation.

[0007] Examples of prior art can be found in documents EP2579063 and US2010 / 130133.

[0008] There is therefore a need for a method of detecting interference in an incident signal which can be implemented on any type of receiver.

[0009] To this end, a method is proposed for detecting the possible presence of an interference signal in a signal received by a reception device, the received signal comprising a useful component and a non-useful component, the reception device comprising N reception channels and a calculator, N being an integer greater than or equal to 2, the method being implemented by the calculator, the method comprising a step of obtaining at least one matrix from among an autocorrelation matrix of the signal received by each reception channel, and an autocorrelation matrix of the non-useful component to obtain at least one determined matrix, a step of calculating the eigenvalues ​​of the at least one determined matrix, a step of estimating the signal-to-interference-plus-noise ratio of the recombined signal, the recombined signal being obtained by recombination of the signals of each of the N reception channels,and a step of detecting the possible presence of an interference signal as a function of at least one of the calculated eigenvalues ​​and the estimated signal-to-interference plus noise ratio.

[0010] According to particular embodiments, the detection method comprises one or more of the following characteristics, taken in isolation or in all technically possible combinations: the detection step comprises the application of a function to at least one eigenvalue, the comparison with a threshold depending on the estimated signal-to-interference-plus-noise ratio, and a detection of the possible presence of interference as a function of the result of the comparison. the function is an identity function, a linear function, a trace function, a division function or a multiplication function. during the detection step, each eigenvalue is chosen from the list consisting of the largest eigenvalue of the autocorrelation matrix of the received signal, the largest eigenvalue of the autocorrelation matrix of the non-useful component, the smallest eigenvalue of the autocorrelation matrix of the received signal, the smallest eigenvalue of the autocorrelation matrix of the non-useful component.the method further comprises a step of an estimator of the power ratio between the power of the jamming signal and the power of the thermal noise of the receiving device, the estimator depending on the calculated eigenvalues.

[0011] The present description also relates to a calculator adapted to detect the possible presence of a jamming signal in a signal received by a reception device, the received signal comprising a useful component and a non-useful component, the reception device comprising N reception channels, N being an integer greater than or equal to 2, the calculator being able to obtain at least one matrix from among an autocorrelation matrix of the signal received by each reception channel, and an autocorrelation matrix of the non-useful component to obtain at least one determined matrix, to calculate eigenvalues ​​of the at least one determined matrix, to estimate the signal-to-interference plus noise ratio of the recombined signal, the recombined signal being obtained by recombination of the signals of each of the N reception channels,and detecting the possible presence of an interference signal based on at least one of the calculated eigenvalues ​​and the estimated signal-to-interference plus noise ratio.,

[0012] The present description also relates to a receiving device comprising a calculator as previously described.

[0013] The present description also relates to a platform comprising a reception device as previously described or a calculator as previously described.

[0014] The present description also relates to a computer program product comprising a readable information medium, on which is stored a computer program comprising program instructions, the computer program being loadable onto a data processing unit and adapted to cause the implementation of at least one step of a method as previously described when the computer program is implemented on the data processing unit.

[0015] The present description also relates to a readable information medium comprising program instructions forming a computer program, the computer program being loadable onto a data processing unit and adapted to cause the implementation of at least one step of a method as previously described when the computer program is implemented on the data processing unit.

[0016] Other features and advantages of the invention will become apparent upon reading the following description of embodiments of the invention, given by way of example only and with reference to the drawings which are: figure 1 , a schematic view of a platform, and figure 2 , a flowchart of an example implementation of a method for detecting a jamming signal.

[0017] A platform 10 is schematically illustrated on the figure 1 .

[0018] For example, platform 10 is an aircraft such as an airplane, helicopter, drone.

[0019] Alternatively, platform 10 is a non-flying craft.

[0020] The platform 10 comprises a set of elements including a receiving device 12.

[0021] The reception device 12 comprises N reception channels 14 and a computer 16.

[0022] N is an integer greater than or equal to 2.

[0023] Each reception channel is identified by a respective index i, the index i is an integer between 1 and N.

[0024] According to the example of the figure 1 , only three receiving channels 14 are shown for clarity.

[0025] Each reception channel 14 comprises an antenna 18 and a processing chain 20.

[0026] The antenna 18 is capable of converting an incident signal called a received signal into an analog signal.

[0027] The signal received by the antenna 18 is a radio frequency signal.

[0028] The signal received on the i-th reception channel 14 is denoted xi (t).

[0029] In the present example, the signal received on a reception channel 14 corresponds to the sum of three signal components, namely a useful signal component denoted si (t), a thermal noise component denoted bi (t) and an interference signal component denoted ji (t).

[0030] The interference signal component ji (t) is a jamming signal whose possible presence or absence is sought.

[0031] The set of thermal noise components denoted bi (t) and interference signal components denoted ji (t) forms a non-useful signal component.

[0032] This is written mathematically as: X t = S t + J t + B t = s 1 t ⋮ s i t ⋮ s N t + j 1 t ⋮ j i t ⋮ j N t + b 1 t ⋮ b i t ⋮ b N t

[0033] The useful signal component s i ( t ) is usually a sum of signals.

[0034] More precisely, the useful signal component s i ( t ) the sum of the different paths of the useful signal. In the general case, the expression of s i ( t ) is thus: s i t = ∑ p = 1 P h i , p ∗ s t − τ p

[0035] Or τ p is the path delay p and h i,p is the channel coefficient of path p of antenna i.

[0036] A maximum delay duration of a multipath is then considered depending on the propagation channel. This maximum value depends on the context of use (terrestrial, aerial), the environment (relief, presence of reflectors) and the frequency band used.

[0037] Considering a digital signal, such a maximum duration translates into a number of symbols. In this case, the previous relationship can be written in a matrix form: s i t = h i ∗ s t = h i , 1 … h i , p … h i , P s t ⋮ s t − p ⋮ s t − p + 1

[0038] Taking into account all N reception channels 14, the following equation is obtained: S t = H ∗ s t

[0039] Or H = h 1 ⋮ h i ⋮ h N is a matrix of size N*P (N antennas and P paths).

[0040] Similarly, the interference signal component denoted ji (t) usually comprises several independent interference signals. In the general case, we therefore have: j i t = ∑ k = 1 K j i , k t

[0041] Similar to the useful signal component, each interference signal component is multipath summed. It is also possible to implement signal digitization to lead to an expression similar to the previous formula.

[0042] The computer 16 is capable of collecting the measurements from each reception channel 14 to carry out processing operations enabling the useful signal to be extracted.

[0043] In particular, according to the example described, the calculator 16 is capable of forming vectors from the collected measurements.

[0044] More precisely, the computer 16 forms a received signal vector denoted X(t) from each of the signals received on the reception channels 14 which comprises three components, the useful signal component S(t), the thermal noise component B(t) and the interference component J(t).

[0045] Furthermore, the computer 16 is capable of implementing a method for detecting the presence of a jamming signal.

[0046] The computer 16 is an electronic computer suitable for manipulating and / or transforming data represented as electronic or physical quantities in system registers and / or memories into other similar data corresponding to physical data in memories, registers or other types of display, transmission or storage devices.

[0047] The computer 16 comprises a processor comprising a data processing unit, memories and an information medium reader. The computer also comprises a keyboard and a display unit.

[0048] As specific examples, the computer 16 includes a single-core or multi-core processor (such as a central processing unit (CPU), a graphics processing unit (GPU), a microcontroller, and a digital signal processor (DSP)), a programmable logic circuit (such as an application-specific integrated circuit (ASIC), a programmable gate array in situ (FPGA), programmable logic device (PLD) and programmable logic arrays (PLA)), a state machine, a logic gate and discrete hardware components.

[0049] The computer program product includes a readable information carrier.

[0050] A readable information medium is a medium readable by the computer 16, usually by the reader. The readable information medium is a medium suitable for storing electronic instructions and capable of being coupled to a bus of a computer system.

[0051] For example, the readable information medium is a floppy disk or flexible disk (from the English term "floppy disk"). floppy disk »), an optical disc, a CD-ROM, a magneto-optical disc, a ROM memory, a RAM memory, an EPROM memory, an EEPROM memory, a magnetic card or an optical card.

[0052] A computer program comprising program instructions is stored on the readable information carrier.

[0053] The computer program is loadable onto the data processing unit and is adapted to drive the implementation of the detection method.

[0054] The processing chain 20 is capable of implementing one or more operations on the received signal.

[0055] In particular, the processing chain 20 is capable of carrying out a digital conversion of the received analog signal.

[0056] The operation of the receiving device 12 is now illustrated with reference to the figure 2 which is an example of implementation of a method for detecting the presence of a jamming signal.

[0057] The method for detecting the presence of an interference signal aims to detect the presence of an interference signal in a signal received by a receiving device 12.

[0058] In other words, the detection method aims to detect whether the jamming signal J(t) is present.

[0059] The detection method is implemented by the computer 16.

[0060] The detection method comprises an obtaining step E50, a calculation step E52, an estimation step E54 and a detection step E56.

[0061] In the E50 obtaining step, two matrices are obtained.

[0062] The first matrix determined is the autocorrelation matrix of the received signal, this matrix being noted R xx .

[0063] By definition, R XX = E ( X ( t ). X ( t ) H< ) where E() is an averaging operation, “.” is a multiplication operation and “H<” is a Hermitian conjugation operation.

[0064] The second matrix determined is the autocorrelation matrix of the non-useful signal, this matrix being denoted R.

[0065] By definition, R = E B t + J t . B t + J t H

[0066] According to a first example, at the obtaining step E50, the two matrices are received by the calculator 16.

[0067] According to a second example, the obtaining step E50 comprises a sub-step of collecting the received signals, a training sub-step and a calculation sub-step.

[0068] In the collection sub-step, all signals received by each reception channel are collected.

[0069] In the training sub-step, the total signal vector X is formed from the collected signals.

[0070] In the calculation sub-step, the first matrix R xx is calculated by applying the previous formula to the total signal vector X.

[0071] The second matrix R is obtained by applying the previous formula to an estimate of the noise supplied to the calculator 16.

[0072] The noise estimate is, for example, provided by an estimate of the channel matrix H defined by the previous formula.

[0073] Such a channel matrix H is, for example, estimated by the use of reference sequences, a series of known symbols placed at known times of the received signal.

[0074] The channel matrixH is then used to calculate an estimate of the matrix R SS = E ( S ( t ) * S ( t ) H< ).

[0075] Obtaining an estimate of the matrix R is then obtained by the subtraction operation R = R XX - R SS .

[0076] Any other method for obtaining matrix estimates R XX , R And R SS is also possible.

[0077] During calculation step E52, the eigenvalues ​​of each of the determined matrices are calculated.

[0078] Any technique for determining eigenvalues ​​is possible in the calculation step, for example a triangularization technique.

[0079] At the end of the calculation step E52, a set of eigenvalues ​​is thus obtained for each of the matrices.

[0080] In particular, the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R), the smallest eigenvalue of the autocorrelation matrix of the non-useful signal λ N (R), the largest eigenvalue of the autocorrelation matrix of the total signal received λ 1 (R xx ) and the smallest eigenvalue of the autocorrelation matrix of the total signal received λ N (R xx ) are thus known.

[0081] The order relation (smaller or larger) is to be understood in absolute value. The largest eigenvalue is thus, for example, the largest value in absolute value.

[0082] The signal from each of the receiving channels 14 is then recombined to obtain a recombined signal.

[0083] For this, the principle of spatial adaptive processing is used.

[0084] The principle of spatial adaptive processing is to determine the weighting vector w with which the signal X(t) is recombined into a signal y in order to obtain a single-channel signal according to the formula: y t = w H ∗ X t

[0085] Where H< is the Hermitian transpose and * is the conjugate operation.

[0086] The quantity y(t) is here a scalar.

[0087] The previous formula is an application to spatial filtering only, resulting from the recombination of the antennas.

[0088] Alternatively, spatio-temporal structures are used which involve symbols from previous moments in the recombination.

[0089] Alternatively or additionally, antenna processing is performed in the frequency domain.

[0090] The calculation of the vector w is carried out in order to optimize the signal-to-interference plus noise ratio estimated in the following step.

[0091] In the estimation step E54, the signal-to-interference plus noise ratio is estimated.

[0092] Such a signal-to-interference-plus-noise ratio is more often referred to by the acronym SINR, which stands for "signal-to-interference-plus-noise ratio." In the following, the term "RSBI ratio" is used to refer to the signal-to-interference-plus-noise ratio.

[0093] The RSBI ratio corresponds to the power ratio between the useful signal S(t) on the one hand and the sum of the thermal noise B(t) and the interference component J(t) on the other hand. The RSBI ratio is thus defined by the relation: RSBI = P S P J + P B

[0094] Or P S is the power of the useful signal S(t), P B the thermal noise power B(t) and P J the power of the interference component J(t).

[0095] The instantaneous power of the total received signal is written according to the following formula: P X = X t H ∗ X t

[0096] A similar operation can be defined to obtain the values ​​of P S ,P J And P B .

[0097] In the case where the thermal noise is modeled by Gaussian white noise, it is customary to assimilate the power of the thermal noise P B à the variance of the random variable noted σ 2< .

[0098] In a particular example, the estimation of the RSBI ratio includes an estimate of the useful signal power made from calculations on the reference sequences of the received signal. This estimate constitutes the numerator of the previous formula.

[0099] The theoretical estimate of the noise power at the output of spatial processing by recombination according to the vector w is P J + P B = w H< R w .It is specified that this estimation step can be calculated directly from processing on the recombined signal y. Since this is single-channel, classic techniques for estimating the Signal to Noise Ratio (SNR) can be applied and will give similar values ​​of the SNR ratio.

[0100] At the end of the E54 estimation step, the RSBI report is thus known.

[0101] During the detection step E56, the presence or absence of interference is detected based on at least one calculated eigenvalue and the estimated RSBI ratio.

[0102] To implement such an E56 detection step, several techniques will be described, knowing that these techniques can be combined with each other.

[0103] For example, the presence of interference is detected only when both techniques indicate the presence of interference. If one technique indicates the presence of interference and the other does not, the absence of interference is detected.

[0104] According to a first technique, the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) is compared with a threshold S.

[0105] The S threshold depends on the RSBI ratio.

[0106] Simulations of the evolution of the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) with the value of the RSBI ratio estimated in the presence of interference and without interference make it possible to determine this threshold.

[0107] The threshold then corresponds to the minimum difference allowing discrimination between the two situations.

[0108] As a particular example, if the largest eigenvalue evolution of the autocorrelation matrix of the non-useful signal λ 1 (R) as a function of the RSBI ratio is, in the absence of interference, greater than a positive constant a, such that λ 1 (R)>a over the entire RSBI range considered while the evolution in the presence of interference is a decreasing linear function λ 1 (R) = a - b*RSBI with b a negative constant, the threshold S can be chosen as equal to 99% of a.

[0109] Another way to understand this mechanism is to consider the variation of the threshold as a function of the RSBI ratio.

[0110] This threshold S is, for example, constant depending on the RSBI ratio.

[0111] According to another example, the threshold S is an affine function of the RSBI ratio.

[0112] According to the example described, when the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) is strictly lower than the threshold S, the presence of an interference signal is detected.

[0113] Conversely, when the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) is strictly greater than the threshold S, the absence of an interference signal is detected.

[0114] According to a more elaborate variant, an interval of non-determination (zone of doubt) is provided taking into account a safety margin.

[0115] Thus, when the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) is strictly less than 110% of the threshold S, the presence of an interference signal is detected.

[0116] Conversely, when the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) is strictly greater than 90% of the threshold S, the absence of an interference signal is detected.

[0117] For cases where the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) is between 90% of the threshold S and 110% of the threshold S, it is not possible to discriminate between the presence and absence of an interference signal.

[0118] The 10% safety margin proposed as an example can be reduced or increased depending on the detection sensitivity.

[0119] According to a second technique, instead of comparing the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) with a threshold, it is the ratio between the largest eigenvalue of the autocorrelation matrix of the received signal λ 1 (R xx ) and the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) which is compared.

[0120] According to a third technique, instead of comparing the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) with a threshold, it is the ratio between the largest eigenvalue of the autocorrelation matrix of the received signal λ 1 (R xx ) and the smallest eigenvalue of the autocorrelation matrix of the non-useful signal λ N (R) which is compared.

[0121] Each technique thus corresponds to a series of the following operations: application of a function to at least one eigenvalue, comparison with a threshold depending on the estimated RSBI ratio and detection of the presence of interference based on the result of the comparison.

[0122] Examples have been shown for a function equal to an identity function or a division function.

[0123] However, other functions are possible, such as a multiplication function.

[0124] Furthermore, the eigenvalues ​​used in the examples are the extreme values.

[0125] However, the use of non-extreme eigenvalues ​​is also possible, notably a linear combination of these values.

[0126] Thus, as a variant or complement, the trace of the matrices (sum of the diagonal elements) is also used.

[0127] In each of the above cases, it is determined whether interference is absent or present (within a margin of doubt for certain embodiments).

[0128] The detection process therefore provides information on the possible presence of interference.

[0129] The method is based on digital processing of signals from several reception channels. The implementation of the method only involves a modification of the operation of the computer and no addition of additional hardware in the platform 10. The method, in fact, exploits a set of techniques conventionally implemented in a SIMO type system (acronym referring to the English term for "single input multiple output" literally meaning "single input, multiple outputs").

[0130] The process is therefore easy to implement.

[0131] Furthermore, the method does not require a priori knowledge of the antennas, particularly their position. In this sense, the method works independently of the antennas.

[0132] The method is applicable to any receiving device comprising several reception channels, even only two. In particular, the method can be used for systems other than satellite navigation systems.

[0133] Furthermore, the method is robust in that the method does not depend on the jammer waveform. The method is capable of detecting any jamming waveform such as a narrowband jammer, a wideband jammer, or a Gaussian additive white noise channel (more often referred to as BBAG).

[0134] Robustness also comes from the fact that the method also works for low signal-to-noise ratios, even when these signal-to-noise ratios are below the nominal operating points of the receiving device.

[0135] The present method also applies without limitations of use concerning the frequency band, and particularly in the HF (acronym for High Frequencies), UHF (acronym for Ultra High Frequencies) or C band (from 4 GHz to 8 GHz) bands.

[0136] Furthermore, the method has been presented in the context of SIMO processing but applies in an identical manner to MIMO processing (acronym referring to the English term "multiple input multiple output" literally meaning "multiple inputs, multiple outputs.

[0137] The method even allows the characteristics of the jammer to be analyzed by providing information on the power. In this sense, the detection method can be interpreted as a characterization method or an analysis method.

[0138] For this, for example, the method comprises a step of calculating an estimator of the power ratio RP between the power of the jamming signal J(t) and the power of the thermal noise B(t).

[0139] The estimator depends on at least one previously calculated eigenvalue.

[0140] For example, an estimator is the ratio between the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) and the smallest eigenvalue of the autocorrelation matrix of the non-useful signal λ N (R).

[0141] Such an estimator can be improved in the case where the noise level is known because it has been supplied to the calculator 16. The noise level is noted σ 2< and is linked to the noise factor of the reception chain.

[0142] In such a case, the method comprises an additional step of calculating an estimator of the power ratio RP as a function of the eigenvalues ​​and the noise level provided.

[0143] According to the described example, the estimator is considered to be equal to the ratio between the largest eigenvalue of the autocorrelation matrix of the non-useful signal λ 1 (R) and the noise level.

[0144] The detection method is thus also a method of characterizing a jamming signal when such a signal is present.

[0145] In some cases, the method is also suitable for giving an indication of the number of jammers (in the case where the number of antennas is in line with the number of jammers).

Claims

1. Method for detecting any presence of an interference signal in a signal received by a receiving device (12), the received signal comprising a wanted component and an unwanted component, the receiving device (12) comprising N receiving channels (14) and a computer (16), N being an integer greater than or equal to 2, the method being implemented by the computer (16), the method comprising a step for: - obtaining at least one matrix among an autocorrelation matrix of the signal received by each receiving channel (14), and an autocorrelation matrix of the unwanted component so as to obtain at least one determined matrix, - calculating the eigenvalues of the at least one determined matrix, - estimating the signal to interference plus noise ratio of the recombined signal, the recombined signal being obtained by recombination of the signals of each of the N receiving channels (14), and - detecting any presence of an interference signal as a function of at least one of the calculated eigenvalues and of the estimated signal to interference plus noise ratio.

2. Method according to claim 1, wherein the detection step comprises: - applying a function to at least one eigenvalue, to obtain a value, - comparison of the obtained value to a threshold depending on the estimated signal to interference plus noise ratio, and - detecting any presence of interference as a function of the result of the comparison.

3. Method according to claim 2, wherein the function is an identity function, a linear function, a trace function, a division function or a multiplication function.

4. Method according to any one of claims 1 to 3, wherein, during the detection step, each eigenvalue is chosen from the list made up of the largest eigenvalue of the autocorrelation matrix of the received signal, the largest eigenvalue of the autocorrelation matrix of the unwanted component, the smallest eigenvalue of the autocorrelation matrix of the received signal, the smallest eigenvalue of the autocorrelation matrix of the unwanted component.

5. Method according to any one of claims 1 to 5, wherein the method further includes a step for an estimator of the power ratio between the power of the interference signal and the power of the thermal noise of the receiving device (12), the estimator depending on the calculated eigenvalues.

6. A computer (16) adapted to detect any presence of an interference signal in a signal received by a receiving device (12), the received signal comprising a wanted component and an unwanted component, the receiving component (12) comprising N receiving channels (14), N being an integer greater than or equal to 2, the computer (16) being able to: - obtain at least one matrix among an autocorrelation matrix of the signal received by each receiving channel (14), and an autocorrelation matrix of the unwanted component so as to obtain at least one determined matrix, - calculate eigenvalues of the at least one determined matrix, - estimate the signal to interference plus noise ratio of the recombined signal, the recombined signal being obtained by recombination of the signals of each of the N receiving channels (14), and - detect any presence of an interference signal as a function of at least one of the calculated eigenvalues and of the estimated signal to interference plus noise ratio.

7. A receiving device (12) comprising a computer (16) according to claim 6.

8. A platform (10) comprising a receiving device (12) according to claim 7 or a computer (16) according to claim 6.

9. A computer program product including a readable information medium, on which a computer program is stored comprising program instructions, the computer program being able to be loaded on a data processing unit and suitable for driving the implementation of at least one step of a method according to any one of claims 1 to 5 when the computer program is implemented on the data processing unit.

10. A readable information medium including program instructions forming a computer program, the computer program being able to be loaded on a data processing unit and suitable for driving the implementation of at least one step of a method according to any one of claims 1 to 5 when the computer program is implemented on the data processing unit.