RU2485692C1 - Method to detect signals without carrier - Google Patents

Abstract

FIELD: radio engineering, communications.

SUBSTANCE: received and digitised signal is divided into fragments of equal length. Then the second fragment is element-by-element added to the first fragment, and in the sum produced a time count of highest module is identified and saved. Afterwards in the second fragment the counts are shifted by one position so that the first one occupies the position of the second one, and the last one - of the first one, and after summation again the time count of highest modulation is identified and saved. The specified actions are repeated until the first count occupies the position of the last one, and the last one - of the last but one. Then the sum is chosen, to which the maximum of the saves values corresponds. Then the remaining fragments are similarly added to the selected sum. In the resulting summary fragment the negative and positive values of maximum module are defined as parameters of a digitised signal, which are compared with the threshold value of the noise level equal to the tripled value of the mean square value of time counts of the summary fragment. The decision on signal detection is made, if at least one of the identified parameters exceeds the value of the specified threshold.

EFFECT: possibility to detect short-term single signals without a carrier.

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Description

The invention relates to radio engineering, and in particular to methods for detecting signals under conditions of a priori uncertainty about the time of their radiation and can be used in radio monitoring systems operating in conditions of additive noise of high intensity.

A known method for detecting signals implemented in the detectors described in the book of Levine B.R. Theoretical Foundations of Statistical Electrical Engineering, Moscow: Sov. Radio, 1968, p. 345-346, Fig. 26.

The method is based on non-linear processing of the implementation of the input sample and consists in the following. The input implementation is decomposed into quadrature components, which are filtered using two filters, matched with the signal components. Then the sums and differences of the input values are formed in each group of filters, which are subjected to biannual quadratic detection. The detection results are summarized and compared with a threshold level. The decision to detect a signal is made if the sum of the detected threshold level values is exceeded.

The disadvantage of the analogue method is that it is acceptable only in cases of detection of signals with known parameters.

A known method for detecting narrowband signals implemented in the signal detector according to patent RU No. 2110150 C1 6 H04B 1/10, G01S 7/292 from 01/23/97

In the known method, an analog signal is received, digitized, for which the operations of sampling, quantization and coding are sequentially performed. Then, the parameters of the digitized signal are calculated, for which a digitized signal is formed, shifted from the original one clock cycle, and the correlation coefficient between the original signal and its shifted version is calculated. The results of correlation processing are selected as parameters of the digitized signal. After that, the calculated parameters of the digitized signal are compared with the decision threshold, which is calculated using additional information about the expected value of the detected signal, the noise variance, and the threshold value. The decision on the fact of signal detection is made if the parameters of the digitized signal exceed the decision threshold.

The disadvantage of this method is the narrow scope, since its implementation is possible only with known parameters of noise and detected signals.

The closest analogue in technical essence to the claimed one is the method for automatic detection of narrowband signals described in the patent of the Russian Federation No. 2382495 C1 of 02/20/2010

In the closest analogue, an analog signal is received, digitized, for which the operations of sampling, quantization and coding are sequentially performed. Then, the parameters of the digitized signal are calculated, for which they form their spectral representation by performing the Fourier transform on it. After that, the threshold noise level is calculated by calculating the double value of the sample average components of the spectral representation and the levels of each of the spectral components from the sequence of the spectral representation are estimated by comparing them with the calculated threshold noise level. Then form the first and second sequences, respectively, of spectral components that exceed the threshold noise level and do not exceed it. After that, the components in the first and second sequences are separately summed and the ratio of the found sums is calculated. Then, the ratio of the found amounts is compared with a predetermined threshold value. The decision on the fact of signal detection is made provided that the ratio of the found sums exceeds a predetermined threshold value.

The disadvantage of this method is the relatively narrow scope of its application, since it does not allow reliable detection of single short-term signals without a carrier under conditions of a priori uncertainty about the time of their radiation within each frame [Chelyshev VD, Potapov SG, Fokin A. ABOUT. UWB - initial representations in the time and spectral domains // Information. Space No. 1, 2007, S. 45-59]. A frame represents a time fragment within which there is only one useful detectable signal without a carrier.

The purpose of the claimed technical solution is to develop a method that expands its scope for short-term single signals without a carrier under conditions of a priori uncertainty about the time of their radiation within each frame in high-intensity additive noise.

This goal is achieved by the fact that in the known method for automatically detecting narrowband signals, a sample of an analog signal is received, digitized, for which the operations of sampling, quantization and coding are performed sequentially, the threshold noise level is calculated, the parameters of the digitized signal are extracted, they are evaluated and evaluated according to the evaluation results. decision on the fact of signal detection. To highlight the parameters of the digitized signal, divide the sample of the digitized signal into fragments of equal length. Then, the second fragment is added element-wise to the first fragment of the digitized signal, and at the end of the summation of the fragments, the maximum positive and negative values of the time samples are determined in absolute value, which are determined as the current parameters of the digitized signal and the largest of them is stored. After that, the second fragment is shifted by discrete time samples by one position in such a way that the first sample takes the second position, and the last - the first, and the first and second fragments are added element by element again, and from the current parameters of the digitized signal selected as a result of their summation, the largest . The indicated actions are repeated until the first time sample of the second fragment takes the position of the last sample and the last of the penultimate one. Then, among the combinations of the sums of the first and second fragments obtained at various time position shifts, the sum is selected that corresponds to the maximum modulo of the previously stored values of the current parameters of the digitized signal. After that, the selected combination of the sums of the first and second fragments is similarly sequentially summed with all the following fragments, and the selected current parameters of the digitized signal of the fragment representing the resulting sum of all fragments are selected as parameters of the digitized signal, the threshold noise level value is chosen equal to the triple value of the rms time value samples of the fragment obtained by summing all the fragments of the digitized signal, and the solution signal detection is received if at least one of the selected parameters of the digitized sample signal obtained by summing all fragments of the digitized signal exceeds the threshold noise level.

Owing to a new set of essential features consisting in dividing a continuous signal into fragments of equal duration, highlighting the current parameters of the digitized signal for each summation of the next fragment, choosing to further summarize the combination of the sum of the fragments to which the highest modulus value of the current parameters of the digitized signal corresponds, in selecting as parameters of the digitized signal the current parameters of the digitized signal of the fragment representing the resulting the sum of all fragments, choosing as the value of the threshold noise level a value equal to the triple value of the mean square value of the time samples of the sample obtained by summing all the fragments, it is possible to detect short-term single signals without a carrier under conditions of a priori uncertainty about the time of their emission in high-intensity additive noise , which indicates the expansion of the scope of the claimed method and the possibility of its use in radio monitoring systems.

The claimed method is illustrated by drawings, which show:

figure 1. A sample of 1536 discrete samples of the signal z _i (hereinafter i = 1, 2, ..., the serial number of the time sample) without noise, including 3 fragments (512 samples each) with a useful signal duration s _i within each fragment equal to 9 reports (for the 1st fragment with 158 samples of 167 each), and the plotted values of the threshold noise level G and -G;

figure 2. A sample of 1536 discrete samples of signal z _i in noise (signal-to-noise ratio (SNR) 0 dB), including 3 fragments (512 samples each) with a useful signal duration s _i within each fragment equal to 9 reports and plotted threshold level values noise G and -G;

figure 3. The spectrum of the sample F _j (hereinafter j is the serial number of the spectral component) of the discrete samples of the signal z _i , presented in figure 2, in noise (SNR = 0 dB);

figure 4. The sampling spectrum F _{j of the} discrete samples of the signal z _i shown in FIG. 1, without noise;

figure 5. A temporary representation of the total fragment formed by the elementwise addition of three fragments under conditions of incoherent addition of useful signals, with plotted values of the threshold noise level G and -G;

Fig.6. A temporary representation of the total fragment formed by the elementwise addition of three fragments, under the conditions of coherent addition of useful signals, with plotted values of the threshold noise level G and -G;

Fig.7. Time sampling of the analog signal z (t) received from the output of the low-frequency channel of the radio receiver;

Fig.8. Time sampling of discrete samples of the signal z _i , divided into 3 fragments of equal length;

Fig.9. The principle of element-wise summation of the first z1 _i and second z2 _i fragments without shifting the elements of the second fragment and the temporary total fragment ⁰ z12 _i ;

figure 10. The principle of element-wise summation of the first fragment z1 _i and the second fragment ¹ z2 _i with a shift of its elements by one position and a temporary total fragment ¹ z12 _i ;

11. The principle of element-wise summation of the first fragment z1 _i and the second fragment ^M-1 z2 _i with a shift of its elements to the M-1 position and the temporary total fragment ^M-1 z12 _i .

In the absence of noise x (t), it is not difficult to make a decision on the presence of a useful signal s (t) in the processed sample z (t) (z (t) = s (t)), which consists of several fragments, if, as parameters digitized signal, select the maximum absolute positive D11 and negative D12 values of the time samples of the signal. As an example, figure 1 presents a sample of discrete samples of the signal z _i = s _i without noise, including 3 fragments, with plotted values of the threshold noise level G and -G. The decision to detect a useful signal is made if at least one of the parameters of the digitized signal D11 or D12 exceeds the value of the threshold noise level G or -G, respectively. Hereinafter, the values of the threshold noise level G and -G are calculated by the formulas:

,

,

Here M is the number of time samples of the processed sample signal z _i ; z _cp - the average value of the processed sample signal z _i , which is calculated by the formula

The choice of the threshold noise level according to formula (1) will provide with a probability of 0.997 the fact that the noise does not exceed the values of G and -G [Borovikov, V. STATISTICA. The art of data analysis on a computer: For professionals / V. Borovikov - St. Petersburg: Peter, 2003. - 688 s].

The existing problem of automatic detection of short-term single signals without a carrier arises in conditions of high-intensity noise.

As an example, figure 2 shows a sample of discrete samples, including 3 fragments, but already in the conditions of additive noise of high intensity. For the case under consideration, the application of the values of the threshold noise level G and -G calculated by formula (1) does not allow us to decide on the presence of a useful signal s (t) in the processed sample z (t) = s (t) + x (t), since D11 <G, and -G> D12 in absolute value.

The transition to the frequency domain for short-term signals without a carrier does not allow, based only on the analysis of the spectral components, to unambiguously decide on their detection. As an example, figure 3 presents the spectrum of the processed sample z (t) = s (t) + x (t) (see figure 2), on which there are no pronounced spectral components that allow us to judge the presence of a useful signal s (t). This is because the useful signal s (t), which is a collection of pulses whose emission time within the fragment is random, has a uniform distribution density of the frequency components. As an example, figure 4 shows the spectrum of the processed sample z (t) = s (t) without noise.

The element-wise summation of fragments without taking into account the start of the emission time of the useful signal s (t) within each of them also does not make it possible to decide on the presence or absence of s (t) in the processed sample z (t). For example, figure 5 shows the total fragment generated by the elementwise incoherent summation of the three fragments of the processed sample shown in figure 2, with plotted values of the threshold noise level G and -G. For the case under consideration, D11 <G, and -G> D12 in absolute value.

If, by element-wise summation, the fragments are folded in such a way that the components of the detected signals of each of the fragments are added coherently at each stage of summation, then in this case the parameters of the digitized signal will be maximum and exceed the threshold noise level G or -G.

The indicated effect is achieved due to the fact that, within the fragment, the time noise samples will be incoherent, as a result of which their average value will tend to zero. While the time samples of the detected signal will add up coherently, and their average values will increase. For example, figure 6 shows the total fragment generated by the elementwise coherent summation of the three fragments of the processed sample shown in figure 2, with the values of the threshold noise level G and -G. Moreover, D11> G, which indicates the presence of the signal s (t) in the sample z (t) = s (t) + x (t).

The implementation of the claimed method is explained as follows.

A sample of the analog signal z (t) is received, for example, from an intermediate or low frequency path of a radio receiver (see Fig. 7). The operation of receiving analog signals is known and described, for example, in the method for detecting narrowband signals according to patent RU No. 2110150 C1 6 Н04В 1/10, G01S 7/292 from 01/23/97.

Then, the received analog signal z (t) is digitized, for which the operations of sampling, quantization, coding are sequentially performed (see Fig. 8). These operations are known and described, for example, in a method for automatically detecting narrowband signals according to the patent of the Russian Federation No. 2382495 of 02.20.2010.

After that, the sample of discrete samples of the signal is divided into N fragments of equal length M (Fig. 8 shows the boundaries of N = 3 fragments). The result is the first fragment z1 _i = z1 ₁ , z1 ₂ , ..., z1 _m , ..., z1 _M , the second fragment z2 _i = z2 ₁ , z2 ₂ , ..., z2 _m , ..., z2 _M , and so on to N- of the first fragment zN _i = zN ₁ , zN ₂ , ..., zN _m , ..., zN _M , where i = 1, 2, ..., m, ..., M. Then, the total sample ⁰ z12 _i = ⁰ z12 ₁ , ⁰ z12 ₂ , ..., ⁰ z12 _m , ..., ⁰ z12 _M (here the index 0 indicates the absence of a shift in the elements of the second sample). Each element of the total sample ⁰ z12 _{i is} calculated as the sum of the corresponding elements of the first and second sample ⁰ z12 ₁ = z1 ₁ + z2 ₁ , ⁰ z12 ₂ = z1 ₂ + z2 ₂ , ..., ⁰ z12 _m = z1 _m + z2 _m , ⁰ z12 _M = z1 _M + z2 _M. The principle of calculating the total sample of ⁰ z12 _{i is} shown in Fig. 9 for elements ⁰ z12 ₇ , ⁰ z12 ₈ and ⁰ z12 ₉ . Then, among the elements ⁰ z12 _i , the maximum in absolute value negative ⁰ D12 and positive ⁰ D11 temporary values are selected, which are determined as the current values of the parameters of the digitized signal and remember the largest, in this case ⁰ D12. The operation of extracting the maximum absolute values of negative ⁰ D12 and positive ⁰ D11 temporal values (an index of zero indicates that the elements in the summed second fragment are not shifted relative to the first) can be implemented by sequentially comparing the values of the elements of the total sample ⁰ z12 ₁ , ⁰ z12 ₂ , ... , ⁰ z12 _m , ..., ⁰ z12 _M.

After that, the elements of the second fragment are shifted by one count so that the first element z2 ₁ takes the place of the second z2 ₂ , the second z2 ₂ takes the third z2 _3, and so on, until the _Mth element z2 _M takes the place of the first z2 ₁ . The result is a sequence of elements of the second fragment shifted by one position ¹ z2 _i = z2 _M , z2 ₁ , ..., z2 _m-1 , ..., z2 _M-1 (index 1 indicates that the elements of the fragment are shifted by one position).

Then calculate ¹ z12 _i = ¹ z12 ₁ , ¹ z12 ₂ , ..., ¹ z12 _m , ..., ¹ z12 _M - the total sample as the sum of the elements z1 _i and ¹ z2 _i : ¹ z12 ₁ = z1 ₁ + ¹ z2 _M , ¹ z12 ₂ = z1 ₂ + ¹ z2 ₁ , ..., ¹ z12 _m = z1 _m + ¹ z2 _m-1 , ¹ z12 _M = z1 _M + ¹ z2 _M-1 . The principle of summation of the elements z1 _i and ¹ z2 _{i is} shown in FIG. 10 for elements ¹ z12 ₇ , ¹ z12 ₈ and ¹ z12 ₉ .

After that, among the elements ¹ z12 _i , the maximum absolute values of negative ¹ D12 and positive ¹ D11 are selected, which are determined as the current values of the parameters of the digitized signal and remember the largest of them, in this case ¹ D12. The operation of highlighting and storing the maximum absolute values of negative ¹ D12 and positive ¹ D11 temporal values (index 1 indicates that the elements in the summed second fragment are not shifted relative to the first) can be implemented in a similar way to the previous step.

The operations of shifting the positions of the elements of the second fragment, calculating the total fragments and extracting the current values of the parameters of the digitized signal are carried out until the first element takes the position of the Mth element and the Mth element is the position of the M-1st element.

11 shows the principle of element-wise summation of the first and second fragments for elements ^M-1 z12 ₇ , ^M-1 z12 ₈ and ^M-1 z12 ₉ with a shift of the elements of the second fragment to the M-1 position and the temporary total fragment.

After that, the largest of the memorized current parameters of the digitized signal is compared with each other and the total fragment of the mth shift ^m z12 _i corresponding to the maximum of the memorized current parameters of the digitized signal is selected for summing with the third fragment z3 _i (here, as an example, the index m denotes the shift, in which one of the parameters of the digitized signal is the maximum among all parameters selected as a result of sequential summation of the first and second fragments with different shifts, The indicated index m is not associated with the examples shown in Figs. 9-11). The summation of the fragments ^m z12 _i and z3 _{i is} carried out in a similar manner for the summation of the fragments z1 _i and z2 _i . The indicated operations of summing the fragments are carried out until the summation of the last Nth fragment zN _i is performed. Then, the current parameters of the digitized signal are extracted from the resulting total fragment in the same way for ¹ z12 _i , the maximum of which are determined as parameters of the digitized signal.

After that, the values of the threshold noise level are calculated from the time samples of the total fragment. The specified procedure can be implemented in accordance with formula (1).

Then a decision is made to detect a signal if at least one of the parameters of the digitized signal exceeds the corresponding threshold noise level. The specified procedure can be implemented by comparing the values of the threshold noise level and the parameters of the digitized signal.

On Fig shows the values of G and -G of the threshold noise level, it also shows the excess of the parameters of the digitized signal over the values of the noise level D11> G and D12> -G (here -G and D12 represent the module of their values).

The experiment confirmed the legitimacy of the choice of the threshold value of the noise level calculated according to the formula (1). The experiment was carried out in accordance with the requirements for obtaining statistical estimates [G. Korn, T. Korn. Math reference. Per. from English - M .: Nauka, 1977. p. 638-643].

Thus, thanks to a new set of essential features consisting in dividing a continuous signal into fragments of equal duration, highlighting the current parameters of the digitized signal for each summation of the next fragment, choosing for further summation the combination of the sum of the fragments that corresponds to the largest modulus of the current parameters of the digitized signal, in the choice of the parameters of the digitized signal of the current parameters of the digitized signal of the fragment representing the resulting sum of all fragments, choosing as a value of the threshold noise level a value equal to a triple value of the mean square value of the time samples of the sample obtained by summing all the fragments, provides the detection of short-term single signals without a carrier under conditions of a priori uncertainty about the time of their emission in high-noise additive noises intensity, which indicates the expansion of the scope of the claimed method and the possibility of its use in radio systems warning light.

Claims (1)

A method for detecting signals without a carrier, which consists in taking a sample of an analog signal, digitizing it, for which the operations of sampling, quantization and coding are performed sequentially, the threshold noise level is calculated, the parameters of the digitized signal are extracted, they are evaluated and the decision is made the fact of signal detection, characterized in that to extract the parameters of the digitized signal, the sample of the digitized signal is divided into fragments of equal length, then to the first fragment the digitized signal is added element by element the second fragment, and at the end of the summation of the fragments, the maximum positive and negative values of the time samples are determined, which are determined as the current parameters of the digitized signal and the largest of them is memorized, after which the discrete time samples are shifted by one position in the second fragment so in such a way that the first counting takes the second position, and the last - the first, and again the first and second fragments are added element-by-element, and from the selected as a result of summing up the current parameters of the digitized signal, the largest one is remembered again, the indicated steps are repeated until the first time sample of the second fragment takes the position of the last sample, and the last one of the penultimate, then among combinations of the sums of the first and second fragments obtained at various time position shifts, choose the sum that corresponds to the maximum in absolute value from previously stored values of the current parameters of the digitized signal, after which the selected combination of the sums of the first o and the second fragments are similarly sequentially summed with all the following fragments, and the selected current parameters of the digitized signal of the fragment representing the resulting sum of all fragments are selected as parameters of the digitized signal, the threshold noise level is chosen to be equal to the triple value of the rms value of the time samples of the fragment obtained in the result of summing all the fragments of the digitized signal, and the decision to detect the signal is made, if at least one of the selected parameters of the digitized sample signal obtained by summing all fragments of the digitized signal exceeds the threshold noise level.

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