DE102012025016B3 - Method for determining at least two individual signals from at least two output signals - Google Patents

Abstract

The invention relates to a method for determining at least two individual signals from at least two output signals which are formed from at least two source signals, the mixing ratios of at least two source signals to the output signals being determined, the output signals being multiplied by factors formed from the mixing ratio and from the output signals at least two subtraction signals are determined so that a source signal is eliminated in each subtraction signal, the subtraction signals are Fourier-transformed, which results in transformation signals, from the transformation signals a residual signal is determined, at least two individual signals are calculated on the basis of the transformation signals and the residual signal, and the individual signals by an inverse Fourier transform can be transformed.

Description

The invention relates to a method for determining at least two individual signals according to the preamble of claim 1. It is known to record two or more sound sources so that thereby a stereo signal can be formed. For this, level differences or differences in maturity are used. The stereo signals should create a spatial sound impression.

Known methods of stereophony are the AB method, the intensity stereophony in the form of the XY method or the MS method and mixed methods such as the ORTF method or the OSS method.

In recent years, more and more sound systems have come on the market, which include more than two speakers. In particular, such sound systems are already for many years, for example, in motor vehicles having at least two speakers in the side doors and two speakers in the inner region of the motor vehicle.

Therefore, methods have been developed to provide more than two individual signals, as is the case with stereophony. There are essentially two different approaches:
First, there are methods that can calculate out of a variety of output signals of each source signal. The source signal is understood to mean every instrument and every voice or speaking voice. In choirs, however, a plurality of singers can be considered as a source signal, for example, "the soprano" can be understood as a singing voice, although it includes, for example, twenty singers.

Overall, therefore, the problem consists in filtering out any number of source signals from two output signals as they are in stereo signals or even more output signals.

Such methods for source separation are led under the keyword "Blind ... Separation". There are essentially two types of procedures. Some work with statistical methods such as independence analysis, principal component analysis, the maximum-a-postariori method, the maximum likelihood method. In addition, it is also known to use recursive optimization methods. The known methods either allow a determination of any source signals from a smaller number of output signals with high computational complexity or require a real-time calculation, a number of output signals that is greater than or equal to the number of source signals.

The publication "Audio Engineering Society-Convention Paper 6924" describes a method for underdetermined source separation. It is described how subtraction signals can be formed. The processing of the signals by means of Fourier transformation is also disclosed here.

US patent application US2007 / 0076902A1 also describes the separation of audio signals. These are processed in the frequency domain with residual signals.

It is therefore an object of the present invention to further develop the method with the features of the preamble of claim 1 such that even with a number of output signals which is smaller than the number of source signals, a source separation in real time is made possible. This object is solved by the features of claim 1. Advantageous developments of the invention will become apparent from the dependent claims.

As the core of the invention, it is considered that subtraction signals are determined from the output signals, which are Fourier-transformed and individual signals are determined in the transformation signals thus obtained. By eliminating statistical methods and recursive methods, it is possible to determine the individual signals in real time. Real-time means that a resulting data stream with a marginal time offset arises when calculating the first block of signals, the signals to be reproduced can be provided without interruption. It is thus possible, for example, to extract from a recording a certain singing voice and, for example, the piano, to assign certain loudspeakers with a mixing ratio to be selected, whereby the output signals need not be preprocessed. It should thus be possible, for example, to insert a CD in a motor vehicle, to specify a song and possibly the distribution of the signals to be extracted as well as the signals to be extracted, and to start playing the song or the CD without it noticeable delay comes.

The mixing ratios of source signals to the output signals can be determined with a direction determination. For this purpose, the output signals are Fourier-transformed and the amplitude values are calculated. These amplitude values are combined into a histogram. For this purpose, pairs of dots are formed from the Fourier-transformed output signals, the pairs of points in the histogram being combined by means of the angle obtained. The angle of the pairs of points assumes values between 0 ° and 90 ° and is calculated as follows:

Here, X ~ _{1, org} denotes the Fourier-transformed first output signal X ₁ , X ~ _{2, org} the Fourier-transformed second output signal X ₂ and a _x and a _y vectors in which the amounts are stored. The letter l is the counting index of the output signals X ₁ and X ₂ and the Fourier transformed output signals X ~ _{1, org} and X ~ _{2, org} , by means of which the pairs of points are fixed. The first value of the Fourier transformed output signal X ~ _{1, org} and the first value of the Fourier transformed output signal X ~ _{2, org} , which are nothing else than vectors, thus form the first pair of points, with l = 1. Of course, the count index l can also be at 0 It then starts running to L-1. L denotes the number of Fourier-transformed points respectively of the output signals X ₁ and X ₂ , for example 4096. θ is an angle between 0 ° and 90 °. and (ψ _l the amount of the pair of points with index l.

The vector ψ _{l contains} the sum of the sums of the vectors a _x and a _y : ψ _l = a + a _{xl yl}

The Fourier transformation is performed block by block. In each case a power of two, ie a power to the base 2, is used as the input signal. It has been found that powers of 10, 11 or 12, ie 1024, 2048 or 4096 data points, are particularly efficient. Particularly preferred are 4096 data points, since in these the computing time is optimized in terms of computational effort.

The division of the histogram is preferably carried out in 1 ° increments, d. that is, the histogram contains 90 elements. The values of the angle θ are rounded to integers in order to narrow the value range of the histogram.

Then the histogram is smoothed to improve the detection of the maxima. For example, the following function is used as the smoothing function:

The parameter T is an integer and specifies how many neighbor points are included in the smoothing. So there is an averaging over several data points. At the boundaries of the histogram, where there are no neighboring points, the value 0 is used at the corresponding points to be supplemented. When calculating the first numerical value of the histogram, the value 0 must be set eight times on one side, while the existing numerical values are used on the other side. In the smoothed histogram, all local extreme values are determined and sorted according to the height of the numerical value, ie according to frequency. Each position in the histogram corresponds to an angle as described above, so each angle also corresponds to an angle. The corresponding angle is determined for the maxima determined and either a predefined number of maxima are used or all maxima whose frequency is above a predetermined threshold value.

The smoothed histogram vector thus results in

The problem may arise that a source signal does not appear in the output signals over the entire duration. For example, certain instruments or voices have pauses. In order for these pauses not to cause errors in the angle determination, it is possible to multiply the following histograms by a weighting function, such as a low pass, after determining two or more histograms and corresponding angle determination. The low pass can look like this: y (n) = a × x (n) + b × y (n-1), where a = 0.1 and b = 0.9. The index n is the index of the histogram, ie n = 1 for the first histogram or the first 4096 data points. The application of the low-pass filter yields the histogram h _{gl_TP} .

This weighting stabilizes the angle detection.

Starting from the determined angles, the mixing ratios of two source signals are determined by the angles γ _N = index (max (h _{gl_TP} )). be used in the following equation: V _N = tan (γ _N ).

If a maximum of the histogram is, for example, 18 °, this results in a mixing ratio of V = 0.325.

mit N = 1, 2, .... N ist der Index des auszufilternden Quellsignals.Based on the mixing ratios, subtraction signals are calculated, which result for two output signals as follows:

with N = 1, 2, .... N is the index of the source signal to be filtered out.

Depending on whether the mixing ratio is greater or less than 1, the corresponding subtraction signal is calculated. It is possible to use more than two output signals, but this only leads to an increased computational effort. If there are not two but more output signals as in the case of a stereo signal, then those two output signals in which the source signal is most strongly represented are preferably selected for the extraction of a source signal.

In the case of the subtraction signals thus determined, a source signal is hidden in each case.

These subtraction signals are then Fourier transformed. This happens block by block, whereby subsequent blocks always start with a distance that corresponds to half the size of the previously transforming data points. That is, the first half of a block has already been Fourier transformed as the second part of the previous block.

This allows continuous signal processing and is known under the name overlap-add method.

To minimize the leak effect, the input blocks are multiplied by a window, for example a Hanning window. The window function f (n) for N data points is:

From the Fourier-transformed subtraction signals X ~, referred to below as transformation signals, a residual signal is determined. For two transform signals X ~, the residual signal results as a simple subtraction of the second transform signal from the first: X ~ ₃ = X ~ ₁ - X ~ ₂ .

In the following, it is further assumed that two transformation signals X ~ ₁ and X ~ ₂ and a residual signal X ~ ₃ , resulting in a total of three signals. To extract a single signal, these three signals are then compared.

For each data point of the signals X ~ ₁ X ~ ₂ and X ~ _3, usually, each signal 4096 data points are calculated, the extreme values of the amplitudes of the three signals.

The starting point is an array with 3 × 4096 data points. The number 3 indicates the number of transform signals and the residual signal, and the 4096 indicates the number of Fourier transformed data points in a block. If one considers the first data point or the first frequency bin of the vectors X ~ ₁ , X ~ ₂ and X ~ ₃ , three numerical values stand for comparison. In place of the minimum value of these three values, the maximum value of the other two values is set and the other values are set to zero.

A numerical example for clarification:
Let the first value of X ~ ₁ 5 be the first value of X ~ ₂ 10 and the first value of X ~ ₃ 15. Then place 15 in the place of 5 and the first value of X ~ ₂ and X ~ ₃ 0. The values are therefore considered column by column. One obtains an array of 4096 columns and three rows in which two-thirds of the values are zero. The values unequal to zero are distributed irregularly over the individual vectors. The individual vectors for X ~ ₁ and X ~ ₂ are called S ~ ₁ and S ~ ₂ and are the Fourier transforms of the calculated source signals S ₁ and S ₂ . The resulting vector of the residual signal X ~ ₃ has no further meaning.

The determination of S ~ ₁ and S ~ ₂ is given by the following formula:

K is the counting index of the data points or frequency bins and passes through the values 1 to 2048 for 4096 data points. Only half of the frequency bins need to be traversed, since the data points occur twice for reasons of symmetry in the course of the Fourier transformation. In the example above, k = 1.

If one takes the lines thus converted, which have belonged to the signals X ~ ₁ and X ~ ₂ , namely the individual signals S ~ ₁ and S ~ ₂ , one can use them to determine the calculated source signals S ₁ and S ₂ by an inverse Fourier transformation. As a phase, the phase of the signals X ~ ₁ and X ~ _{2 can} also be used directly. S ~ ₁ and S ~ ₂ is thus assigned the respective phase of the vectors X ~ ₁ and X ~ ₂ . The assignment is of course dependent on the counting index k.

The individual signals S ~ ₁ and S ~ ₂ or the Fourier-transformed individual signals S ₁ and S ₂ may differ slightly from the source signals due to computational inaccuracies and rounding errors. This means that a complete reproduction of a source signal is not possible, but the differences are so small that they are usually not noticeable.

To improve the separation of the individual signals, the following steps are possible:
In order to avoid jumps in the minima detection it can be provided that the definition of a minimum in the signals X ~ ₁ , X ~ ₂ and X ~ ₃ depends on the detection of preceding minima. For example, a conditional lowpass filter can be used:

P t / hold (k) is the value of a frequency bin k to remember, k again being the count index. The parameter b is freely adjustable between 0 and 1, whereby the note of the frequency is switched off at b = 0.

Der Parameter η (0 ≤ η ≤ 1) gibt vor, wie stark das tiefpass-gefilterte Signal in die Einzelsignale S ~_m, m = 1, 2, 3, ... eingeht.The determination of S ~ ₁ and S ~ ₂ is then given by the following formula:

The parameter η (0 ≤ η ≤ 1) specifies how much the low-pass filtered signal enters into the individual signals S _m , m = 1, 2, 3,.

Furthermore, the minima of the transformation signals X ~ _m , m = 1, 2, 4, 5,... Can be compared separately with the residual value signal X ~ ₃ , ie the minimum determination E _min (k), zero occupancy or the maximum value of Column E _max (k), etc. are each performed between a transform signal X ~ _m and the residual value signal X ~ ₃ . Thus, the vectors E _min1 , E _min2 , E _max1 and E _{max2 are} determined. The minima are multiplied by a factor β (0 ≤ β ≤ 2). Depending on the choice of the factor, different effects result. For β <1 unwanted frequencies are suppressed and for β> 1 results in a more harmonious sound.

The individual signals arise too

In addition, the signals can be separated based on the phase angle. If the amplitude of the transform signals X ~ _m (k) is substantially identical and has ~ ₃ in the residual signal X (k) is a minimum, the phase is considered. If this is the same, the maximum S ~ ₃ (k) is assigned, otherwise S ~ ₁ (k) and S ~ ₂ (k). Of course, this consideration is to be performed separately for each frequency bin k.

It applies accordingly:

In addition, the Fourier-transformed output signals X ~ _{m, org} can furthermore be taken into account. If there is a minimum at X ~ _{1, org} (k), this is also assigned to S ~ _{1, org} (k):

The invention is explained in more detail with reference to embodiments in the drawing figures. These show:

1 a block diagram of the method according to the invention for a stereo signal,

2 a block diagram of the method according to the invention in a second embodiment,

3 a flow chart for determining the mixing ratios,

4 a flow chart for source separation,

5 an arrangement for recording stereophonic signals,

6 a scatterplot of data pairs,

7 a scatter plot of FT data pairs,

8th a histogram,

9 the overlap-add method,

10 a 3D amplitude spectrum of two transformation and one residual signal,

11 a 3D amplitude spectrum of the individual signals and

12 Transformation signals and individual signals in vector form

5 shows an arrangement for receiving a stereo signal. By way of example only, an arrangement for recording the source signals by means of XY stereophony is shown; in principle, however, the method according to the invention can be used not only in all other stereophonic methods, but also in methods in which more than two output signals are generated.

Shown are four signal sources, each a source signal 1 . 2 . 3 and 4 produce. For source signal 1 it is, for example, a singing voice, so a singer or a singer, with source signal 2 around the background choir, consisting of a plurality of singers, but playing the same text and notes, in the source signal 3 around an instrument, for example a piano and with source signal 4 a group of instruments that, however, reproduce the same notes as the choir. An example would be a set of violins playing the same melody. This is to show that a source signal can be formed not only by a single singer or a single singer or by a single instrument, but also by a plurality of singers or instruments. Due to the divergent directivity of the microphones 5 and 6 become the source signals 1 . 2 . 3 and 4 recorded at different levels, so the mixing ratio of the source signals 1 . 2 . 3 and 4 always different.

From the source signals 1 . 2 . 3 and 4 Thus, the two output signals of the stereo signal are obtained. The output signals are those signals which form the starting point of the method according to the invention, the original source signals are no longer available.

Of course, more source signals can be used to generate the output signals X _m , but in order to carry out the method, it is necessary to have at least two source signals.

In the following, reference is frequently made to two output signals X ₁ , X ₂ . The inventive method is not limited to stereo signals, in principle, any number of output signals X _m , m = 1, 2, 3, ... are available.

Dabei steht N für den jeweiligen Index des Quellsignals. 1 shows a block diagram of the method according to the invention in a first embodiment. In this case, two output signals X ₁ and X ₂ are used and the mixing ratio for two source signals, for example the source signals 1 and 2 , certainly. A possible method for determining the mixing ratios is explained in detail below. For the source signal 1 For example, this results in a mixing ratio V ₁ and for the source signal 2 a mixing ratio V ₂ . From the output signals X ₁ and X ₂ are then subtraction signals X ^ ₁ and X ^ ₂ calculated by the output signals X ₁ and X ₂ are subtracted as follows from a mixing ratio:

N stands for the respective index of the source signal.

The thus calculated subtraction signals X ^ ₁ and X ^ ₂ are Fourier transformed according to the overlap-add method.

The output signals X ₁ and X ₂ are of course digital signals, which accordingly correspond to pure sequences of numerical values or data points. One could also represent an output signal as a vector with a very large number of numerical values, usually many tens of thousands. This also applies to the subtraction signals. In order to keep the computational requirements small and in particular to keep the time until the provision of first individual signals low, the output signals X ₁ and X ₂ and the subtraction signals X ^ ₁ and X ^ ₂ are further processed block by block. The Fourier transform is applied, for example, to the first 4,096 data points of the subtraction signal X ^ ₁ and X ^ ₂ . Preferably, powers of two of data points are Fourier-transformed, since the fast Fourier transformation (FFT) can be used for these. The number 4,096 represents an optimum value with regard to the used computing time and the used computing resources. It is also possible to take smaller or larger data blocks, for example data blocks of 1024 or 2048 data points. Of course, these are always consecutive data points. By the Fourier transformation of the subtraction signals X ^ ₁ and X ^ ₂ , the transformation signals X ~ ₁ and X ~ _{2 are obtained} . By subtracting the transformation signal X ~ ₂ from the transformation signal X ~ ₁ , the residual signal X ~ _{3 is obtained} .

The residual signal X ~ ₃ contains exactly as many data points as the transformation signals X ~ ₁ and X ~ ₂ , for example 4096 data points. Because these data points are in the frequency domain, they are also commonly called frequency bins. A frequency bin is therefore a data point of a transformation or residual signal. In the example, each transformation residual signal therefore has 4096 frequency bins.

In the signals X ~ ₁ , X ~ ₂ and X ~ ₃ then minima are searched, since these are synonymous with the hidden signals. For this purpose the signals for each frequency bin from the amplitudes X ~ ₁ X ~ ₂ and X ~ ₃ calculates the minima and set the maximum values of the respective frequency bins of these minimum points, the other values for this frequency bin to zero. The phases to the non-zero values are obtained from the In this way one holds the individual signals S ~ ₁ and S ~ ₂ . These must be transformed back into the time domain, whereby the calculated source signals S ₁ and S _{2 are} obtained.

2 shows an embodiment for determining more than two calculated source signals S ₁ and S ₂ S. For this purpose, more than two mixing ratios are determined from the output signals X ₁ , X ₂ , X ₃ and X ₄ , whereby more subtraction signals and thus more transformation signals are obtained. Also in the transformation signals X ~ ₁ , X ~ ₂ , X ~ ₃ and X ~ ₄ thus obtained and the residual signal X ~ ₃ derived therefrom, a minimization determination follows and above this the determination of the individual signals S ~ ₁ , S ~ ₂ , S ~ ₃ and S ~ ₄ and from this the calculation of the calculated source signals S ₁ , S ₂ , S ₃ and S ₄ .

In the following, a possibility for determining the mixing ratios is disclosed. In principle, all methods for determining the mixing ratios can be used.

ermittelt. 3 shows a flowchart for determining the mixing ratios based on a direction determination. In this case, the output signals X ₁ and X _{2 are} Fourier-transformed in step S1, whereby the transformed output signals X ~ _{1, org} and X ~ _{2, org} are obtained. In step S2, for each data point or frequency bin of the Fourier-transformed output signals _{X.about.1, org} and _X.about.2, the amplitude values are calculated using the formulas

determined.

In the next step S3, the calculation of the angle θ and of the absolute value ψ _{1 takes place} from the previously determined values. In this case, the magnitude values of the Fourier-transformed output signals X ~ _{1, org} and X ~ _{2, org can be} calculated by data point or vector, at least value pairs of angles θ and magnitude values ψ _{l are} to be determined therefrom.

In step S4, a histogram is calculated from the value pairs θ and ψ ₁ , which is smoothed in step S5.

In step S6, the determination of the maximums of the histogram follows, whereby either a predetermined number or all maxima above a threshold value are used.

Each of these maxima is assigned an angle, which is calculated in each case from the maximum values from the formula given above. In step S7, the determination of the desired mixing ratios then takes place on the basis of the determined angles.

4 shows a flow scheme for source separation. Starting from the transformation signals X ~ ₁ , X ~ ₂ , and possibly X ~ ₄ and X ~ ₅ and the residual value signal X ~ ₃ , the minima and maxima are calculated for each frequency bin (step S8). In a further embodiment, the Fourier transform of the output signals X ~ _{1, org} and X ~ _{2, org} and optionally X ~ _{3, org} and X ~ _{4, org} may additionally be taken into account.

In step S9, the maximum value of the frequency bin or of the respective column is set in each frequency bin at the location of the minimum value, all other values being either a zero value or the hold value P t / hold assigned as described above.

According to step 10 the respective phase of the transformation signals X ~ ₁ , X ~ ₂ , X ~ ₄ and X ~ _{5 is} assigned to each non-zero value of the individual signals S ~ ₁ , S ~ ₂ , S ~ ₄ and S ~ ₅ .

The assignment is based on the numbering of the frequency bins. If the frequency bin 28 of the individual signal S ~ _{1 has} a value other than zero, this receives the phase of the frequency bin 28 of the transformation signal X ~ ₁ . Due to the shift of the maximum values to the minimum values in each frequency bin and the zeroing of the remaining values, not a single value of a single signal is equal to the value of the associated transformation signal. Nevertheless, the phases can be taken over.

Instead of zeroing the non-minimum points, the _hold value ηP _hold can also be used. This prevents jumps in the individual signals.

6 shows a scatter plot of the amplitudes of two mixed output signals X ₁ and X ₂ , wherein the output signals X ₁ and X _{2 are} mutually shifted sinusoidal signals. A scatter plot represents pairs of values, whereby the value pairs are formed on the basis of the number of the data point, so to speak of the data bin. The first point of the data point of the output signal X ₁ has a first amplitude and the first data point of the output signal X ₂ an equal or a different amplitude. These two amplitudes are used to draw a point in the scatter plot 9 set. The use of a multiplicity of data points in each case of the output signal X ₁ and the output signal X ₂ results in the same number of data-point pairs. It is on the axis 10 the amplitude of the output signal X ₁ and on the axis 11 the amplitude of the output signal X ₂ indicated. By using, for example, 4096 data points on the output signal X ₁ and the output signal X ₂ , one obtains 4096 pairs of data points. These form a point cloud in the scatter diagram 12 , the points obtained from a plurality of the individual pairs of data points 13 is formed.

berechnet wurden. Entsprechend ist auf Achse 15 der Betrag der Amplitude von X ~_1,org, also der Fouriertransformierten des Ausgangssignals X₁, und auf Achse 16 der Betrag der Amplitude von X ~_2,org aufgetragen. Durch Berechnung der Steigung der Geraden 17 bzw. 18 erhält man jeweils die Mischungsverhältnisse. 7 shows a suitably formed scatter plot 14 However, the output signals X ₁ and X ₂ were Fourier transformed and the amplitudes of the signals according to

were calculated. Accordingly is on the move 15 the magnitude of the amplitude of X ~ _{1, org} , ie the Fourier transform of the output signal X ₁ , and on axis 16 the magnitude of the amplitude of X ~ _{2, org} applied. By calculating the slope of the line 17 respectively. 18 you get the mixing ratios.

In such a simple way, however, the mixing ratios can only be determined with sinusoidal signals that do not occur in real recordings. Instead of the formation of a scatter diagram and determining the slope of the resulting straight lines is after the Fourier transform of the output signals X ₁ and X ₂ of the pairs of points of the Fourier-transformed output signals X ~ _{1, org,} and X ~ _{2, org,} respectively an angle θ and a vector ψ calculated. Instead of a scatter plot, a histogram is determined from the pairs of angles θ and vector ψ, in which the angles are shortened to an integer and from this, corresponding frequencies at angles are determined. Each pair of points results in a single frequency for the histogram.

herangezogen werden, die weiter oben bereits beschrieben wurde.This histogram is smoothed with a smoothing function, reducing the number of local minima and maxima. As a smoothing function, for example, the function

be used, which has already been described above.

Such a smoothed histogram is in 8th shown. On the axis 19 are angles in degrees, from 0 ° to 90 °, while on the axis 20 the respective frequencies are shown. The histogram 21 has an absolute maximum 22 and several local maximums 23 . 24 and 25 ,

The number of frequencies sorted by has the maximum 22 the highest value, then the maxima follow 25 . 24 and 23 , Of these maxima, either a predefined number is selected starting at the maximum with the highest frequencies, for example the maximum for two maxima 22 and 25 , However, maxima can also be selected as long as the frequency is above a threshold value. If you use this, for example 10 on, then follow further calculations for the maxima 22 . 25 and 24 but not for the maximum 23 that is below this threshold.

Every maximum stands for an angle. The maximum 22 for example, for 18 ° and the maximum 25 for 72 °.

The indication of the angle can according to the formula γ _N = index (max (h _{gl_TP} )) respectively. From the thus determined angles results for each angle in each case a mixing ratio according to the formula V _N = tan (γ _N ).

N is the index of the source signal to be extracted. Thus, the determination of the mixing ratios is completed on the basis of a direction information.

The determination of the subtraction signals X ^ ₁ and X ^ ₂ is carried out according to the formula given above, in particular, the subtraction signals X ^ ₁ and X ^ _{2 can} also be determined block by block. Thus, in each case a predefined set of data points, for example 4096 data points each of the output signals X ₁ and X _2, can be calculated to form subtraction signals X ₁ and X ₂ using the mixing ratios become. The subtraction signals X ^ ₁ and X ^ ₂ are generated according to the in 9 shown overlap-transform Fourier transform.

Shown are data blocks 26 . 27 . 28 and 29 consisting of 2048 data points each of the subtraction signal X ^ ₁ and the subtraction signal X ^ ₂ . The numerical value 2048 results from the fact that it is half of the data points used for Fourier transformation. The number of data points of the data blocks 26 to 29 thus results from the number of data points of a data block 30 to 33 ,

The data block 30 consists of the data blocks 26 and 27 together and therefore has twice the number of data points of a data block 26 or 27 , This data block 30 is the data block that is Fourier transformed. The data block 31 consists of the data blocks 27 and 28 , the data block 32 from the data blocks 28 and the following data block. The data block 27 is in the data block 30 and 31 contain the data block 18 in the data block 31 and 32 ,

Before the Fourier transform, the data blocks become 30 . 31 . 32 and 33 still multiplied by a Hanning window. As a result, leakage effects in the Fourier transformation can be minimized.

10 shows a 3D amplitude spectrum of the transformation signals X ~ ₁ , X ~ ₂ and the residual value signal X ~ ₃ . On the axis 35 the respective number is a frequency bin, ie a numbered dot in the vector of a signal, while on axis 36 the amount value is specified. axis 37 indicates the respective amount values. Instead of 38 is the signal | X ~ ₂ |, in place 39 the signal | X ~ ₃ | and in place 40 the signal | X ~ ₁ |.

In the 10 shown signals were determined from two pure sine signals. For real signals, more or less all frequency bins are filled, but for purposes of illustration the sinusoidal signals are particularly suitable. From the illustration in 10 follows directly that the signals | X ~ ₁ |, | X ~ ₃ | and | X ~ ₃ | each have only three peaks that are different high, but otherwise have only zeros.

11 shows a 3D amplitude spectrum of the individual signals S ~ ₁ , S ~ ₂ and the residual signal mixture S ~ ₃ . The axis 35 again indicates the frequency bin and the axis 36 the amount. On the axis 42 On the other hand, the received individual signals are plotted. Instead of 43 is the single signal | S ~ ₁ | instead of 44 the residual signal | S ~ ₃ | and in place 45 the single signal | S ~ ₂ |. To the respective non-zero digits of the individual signals | S ~ ₁ | and | S ~ ₂ | From the transformation signals X ~ ₁ and X ~ ₂ the phases are still to be used in each case in order to obtain the individual signals | S ~ ₁ | and | S ~ ₂ | to be able to Fourier transform backwards.

12 schematically shows the extraction of the individual signals from the transformation signals X ~ ₁ and X ~ ₂ and the residual value signal X ~ ₃ . The vector 46 is a fragmentary of the transformation signal X ~ ₁ again, according to vector 47 the numerical values of the transformation signal X ~ ₂ , vector 48 the values of the residual signal X ~ ₃ and vector 49 the corresponding frequency bins.

Out of these, that goes into vector 50 shown single signal S ~ ₁ that in vector 51 shown single signal S ~ ₂ and that in vector 52 shown residue signal S ~ _{3 as} follows:
For frequency bin 1, the minimum is in vector 48 because the numbers 5 and 7 are greater than 1. In the frequency bin 1 of the corresponding vectors 50 . 51 and 52 Therefore, the following values are used: instead of the minimum value 1, the maximum value 7 is set. This is therefore at the frequency bin 1 of the vector 52 to put. The remaining values in frequency bin 1, namely in the vectors 50 and 51 , are set to zero. The minimum consideration thus takes place column by column, by data point or by frequency bin. These expressions are identical.

Similarly, the values of the frequency bin columns 2, 3, 4, 5, etc. are calculated so that the in 12 in each case.

In vector 50 the values or mimimum values become vector 46 collected, in vector 51 ones to vector 47 and in vector 52 ones to vector 48 ,

To the vectors 50 and 51 the individual signals S ~ ₁ and S ~ ₂ are subsequently assigned the phases of the transformation signals X ~ ₁ and X ~ ₂ . By way of example, this will be for the frequency bin 4 of the vector 50 described. For frequency bin 4 of the vector 50 the phase of the frequency bin 4 becomes vector 46 taken as the vector 50 the minimal parts of the vector 46 if there are numerical values. Accordingly, the phase of the identical frequency bins is transmitted.

In all embodiments in the figures, instead of explicitly mentioned two output signals, two transformation signals or individual signals, more than two signals can be used, furthermore all embodiments mentioned in the introduction to the description can also be used with regard to the description of the figures, unless this is expressly excluded.

LIST OF REFERENCE NUMBERS

1

source signal

2

source signal

3

source signal

4

source signal

5

microphone

6

microphone

7

Determination of mixing ratios

8th

signal separation

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scatterplot

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point cloud

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Just

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histogram

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3D amplitude spectrum

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3D amplitude spectrum

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Claims (20)

Method for determining at least two individual signals (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) from at least two output signals (X ₁ , X ₂ , X ₃ , X ₄ ) which comprise at least two source signals ( 1 . 2 . 3 . 4 ), characterized in that a) the mixing ratios (V ₁ , V ₂ , V ₃ , V ₄ ) of at least two source signals ( 1 . 2 . 3 . 4 ) to the output signals (X ₁ , X ₂ , X ₃ , X ₄ ) are determined, b) the output signals (X ₁ , X ₂ , X ₃ , X ₄ ) from the mixing ratio (V ₁ , V ₂ , V ₃ , V ₄ ) are multiplied and from the output signals (X ₁ , X ₂ , X ₃ , X ₄ ) at least two subtraction signals (X ^ ₁ , X ^ ₂ , X ^ ₃ , X ^ ₄ ) are determined, so that in each subtraction signal (X ^ ₁ , X ^ ₂ , X ^ ₃ , X ^ ₄ ) a source signal ( 1 . 2 . 3 . 4 ), c) the subtraction signals (X ^ ₁ , X ^ ₂ , X ^ ₃ , X ^ ₄ ) are Fourier transformed, resulting in transformation signals (X ~ ₁ , X ~ ₂ , X ~ ₄ , X ~ ₅ ), i ) from the transformation signals (X ~ ₁ , X ~ ₂ , X ~ ₄ , X ~ ₅ ) a residual signal (X ~ ₃ ) is determined, e) at least two individual signals (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) are calculated from the transform signals (X ~ ₁ , X ~ ₂ , X ~ ₄ , X ~ ₅ ) and the residual signal (X ~ ₃ ), and f) the individual signals (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) are transformed by an inverse Fourier transformation into calculated source signals (S ₁ , S ₂ , S ₃ and S ₄ ). A method according to claim 1, characterized in that the determination of the mixing ratios (V ₁ , V ₂ , V ₃ , V ₄ ) takes place via a direction determination. Method according to claim 1 or 2, characterized in that the determination of the mixing ratios (V ₁ , V ₂ , V ₃ , V ₄ ) comprises the following steps: - Fourier transformation of the output signals (X ₁ , X ₂ , X ₃ , X ₄ ), Calculation of the amplitude values of the Fourier transformed output signals (X ~ _{1, org} , X ~ _{2, org} , X ~ _{3, org} , X ~ _{4, org} ), and - determination of a histogram ( 21 ) from the amplitude values or determination of the slope of the straight line ( 17 . 18 ) of the amplitude values in a scatter plot ( 14 ). Method according to claim 3, characterized in that the histogram ( 21 ) is multiplied by a smoothing function. Method according to Claim 4, characterized in that the smoothing function is a Hanning window, in particular

is used. Method according to one of claims 3 to 5, characterized in that the angular distance in the histogram ( 21 ) Is 1 °. Method according to one of claims 3 to 6, characterized in that the local extreme values, in particular the local maxima ( 22 . 23 . 24 . 25 ), the histogram ( 21 ). Method according to claim 7, characterized in that starting with the absolute maximum ( 22 ) every maximum ( 22 . 23 . 24 . 25 ) an angle is assigned. A method according to claim 8, characterized in that the assignment of the angle is terminated at a predetermined number or falls below a threshold value. Method according to one of claims 3 to 9, characterized in that the histogram ( 21 ) is weighted with a low pass. A method according to claim 10, characterized in that the low pass is determined from temporally earlier determined histograms. Method according to one of the preceding claims, characterized in that the subtraction signal (X ^ ₁ , X ^ ₂ , X ^ ₃ , X ^ ₄ ) at two output signals (X ₁ , X ₂ ) is determined by the with the mixing ratio (V _N), multiplied second output signal (X ₂₎ from the first (X ₁₎ is subtracted when the mixing ratio (V _N) is less than 1, and otherwise the first output signal (X ₁₎ with the reciprocal value of the mixture ratio (1 / V _N) multiplied and subtracted from the second output signal (X ₂ ). Method according to one of the preceding claims, characterized in that a power of two at data points, in particular 1024, 2048 or 4096 data points are used for the Fourier transforms. Method according to one of the preceding claims, characterized in that the data points are used to the Fourier transforms quasi-continuous and after the overlap-add method. A method according to claim 13, characterized in that a residual value signal (X ~ ₃ ) is determined as a subtraction signal of the transformation signals Method according to one of the preceding claims, characterized in that a single signal (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) by means of an extreme value determination of at least one transformation signal (X ~ ₁ , X ~ ₂ , X ~ ₄ , X ~ ₅ ) and / or the residual value signal (X ~ ₃ ). Method according to one of the preceding claims, characterized in that the frequencies of a single signal (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) are detected by minimization. A method according to claim 16 or 17, characterized in that in the transformation signals (X ~ ₁ , X ~ ₂ , X ~ ₄ , X ~ ₅ ) and the residual value signal (X ~ ₃ ) for generating the individual signals (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) for each frequency bin ( 49 ) the minimum is determined, in place of which the maximum of the respective frequency bin ( 49 ) and the remaining values are set to zero. Method according to Claim 18, characterized in that the amplitude values of the individual signals (S ~ ₁ , S ~ ₂ , S ~ ₃ , S ~ ₄ ) are the respective phase values of the transformation signals (X ~ ₁ , X ~ ₂ , X ~ ₅ , X ~ ₄ ). Method according to one of the preceding claims, characterized in that the number of source signals to be calculated (S ₁ , S ₂ , S ₃ and S ₄ ) and / or the source signal or signals ( 1 . 2 . 3 . 4 ) yourself.

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