Superposed signal identification method based on energy characteristics

Abstract

The invention relates to a superposed signal identification method based on energy characteristics, and the method comprises the following steps: S1, carrying out the preprocessing of a multi-channel energy amplitude value, and obtaining the energy stability AmpSta1 (t) at a moment t and the energy amplitude mean value Ampmean (t) at x moments before the moment t; s2, preprocessing the multi-channel phase value to obtain a phase difference variable quantity PhaSta1m (t) between a t-1 moment and a t moment and a standard deviation sigma Pha of phase differences at x moments before the t moment; s3, judging the stability of the energy value by utilizing the energy stability AmpSTa1 (t) and the energy amplitude mean value Ampmean (t) obtained in the S1, wherein the energy stability AmpSTa1 (t) and the energy amplitude mean value Ampmean (t) are obtained in the S1; s4, judging the stability of the phase difference by using the phase difference variable quantity PhaSta1m (t) obtained in the S2 and the standard deviation sigma Pha of the phase difference; and S5, recognizing the superposed signals according to the judgment results of the S3 and the S4, and judging whether the superposed signals exist or not. The method can make full use of the abrupt change characteristic of the energy value after signal superposition, identifies whether there is a superposed signal, and is high in accuracy, small in operand and easy for engineering realization.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and in particular to a superposition signal recognition method based on energy characteristics. Background Art

[0002] With the rapid development of radar systems, software radio systems, communication systems and other fields, the electromagnetic environment has become increasingly complex, the electromagnetic spectrum has become increasingly crowded, and the co-frequency interference phenomenon in the real environment has become increasingly serious. Due to the superposition of target signals and interference signals, radar detection capabilities may fail, indoor equipment positioning fails, and communication bit error rates increase. Therefore, the receiver must have the ability to recognize superimposed signals. Therefore, designing a superimposed signal recognition method with stronger adaptability and less computational complexity is an urgent problem to be solved.

[0003] It should be understood that the above statements merely provide background technology related to the present invention and do not necessarily constitute prior art. Summary of the invention

[0004] The purpose of the present invention is to provide a superposition signal recognition method based on energy characteristics to achieve rapid recognition of superposition signals.

[0005] In order to achieve the above-mentioned purpose, the present invention provides a superposition signal recognition method based on energy characteristics, comprising the following steps: S1, preprocessing the multi-channel energy amplitude values ​​to obtain the energy stability Amp_Sta1(t) at time t and the energy amplitude mean Amp_mean(t) at x times before time t; S2, preprocessing the multi-channel phase values ​​to obtain the phase difference change Pha_Sta1_m(t) between time t-1 and time t and the standard deviation σ_Pha of the phase difference at x times before time t; S3, using the energy stability Amp_Sta1(t) and the energy amplitude mean Amp_mean(t) obtained in S1 to judge the energy value stability; S4, using the phase difference change Pha_Sta1_m(t) and the standard deviation σ_Pha of the phase difference obtained in S2 to judge the phase difference stability; S5, identifying the superposition signal according to the judgment results of S3 and S4, and judging whether there is a superposition signal.

[0006] Preferably, the S1 comprises the following steps:

[0007] S11, input the energy amplitude value Amp_(t) of each channel at time t into the multi-channel average processing module to obtain the energy amplitude average value Amp(t) at time t, the formula is as follows:

[0008] Amp_(t)=(Amp_1(t)+Amp_2(t)+…+Amp_m(t)+…t+Amp_M(t)) / M;

[0009] Where Amp_(t) is the mean energy amplitude at time t; Amp_m(t) is the energy amplitude value of the mth channel at time t, m = 1, 2…, M, M is the number of channels;

[0010] S12, input the energy amplitude mean value Amp_(t) at time t into the differential module, and perform differential calculation with the energy amplitude mean value Amp_(t-1) at time t-1, solve the relative ratio, and obtain the energy stability Amp_Sta1(t) at time t, the formula is as follows:

[0011] Amp_Sta1(t)=Amp_(t) / Amp_(t-1);

[0012] S13, input the energy amplitude mean Amp_(t) at time t into the sliding mean calculation module, and take time t as the end point, slidingly calculate the energy amplitude mean Amp_mean(t) of x moments before time t, the formula is as follows:

[0013] Amp_mean(t)=(Amp_(t)+Amp_(t-1)+...t+Amp_(tx)) / x.

[0014] Preferably, the selection of the value x is determined according to the sensitivity of the actual system calibration, and the condition to be satisfied is that the mean energy amplitude of the signal required by the system index at the value x is greater than the system noise amplitude value.

[0015] Preferably, the step S2 comprises the following steps:

[0016] S21, input the phase value of each channel at time t into the channel phase difference calculation module, and make a difference based on the phase value Pha_1(t) of channel 1 to obtain the phase difference of each channel. The formula is as follows:

[0017] Diff_Pha_m(t)=Pha_m(t)-Pha_1(t);

[0018] Where Diff_Pha_m(t) is the phase difference of channel m at time t; Pha_m(t) is the phase value of channel m at time t;

[0019] S22, input the phase difference of each channel at time t into the phase difference variation calculation module, and perform difference calculation with the phase difference at time t-1 to obtain the phase difference variation Pha_Sta1_m(t) between time t-1 and time t, the formula is as follows:

[0020] Pha_Sta1_m(t)=Diff_Pha_m(t)-Diff_Pha_m(t-1);

[0021] S23, input the phase difference of each channel at time t into the phase difference standard deviation calculation module, and take time t as the end point, slide and calculate the standard deviation of the phase difference at x times before time t, and obtain the phase difference standard deviation σ_Pha, the formula is as follows:

[0022] Diff_Pha_mean_m(t)=(Diff_Pha_m(t)+Diff_Pha_m(t-1)+…+

[0023] Diff_Pha_m(tx)) / M;

[0024] Where Diff_Pha_mean_m(t) is the mean phase difference of the mth channel at x moments before moment t;

[0025]

[0026] Wherein, σ_Pha(m) is the standard deviation of the phase difference at time x before time t of the mth channel;

[0027] σ_Pha=(σ_Pha(2)+σ_Pha(3)+…+σ_Pha(M)) / (M-1).

[0028] Preferably, the energy stability Amp_Sta1(t) at time t calculated in S1 and the energy amplitude mean Amp_mean(t) at x times before time t are input into the first comparator to jointly determine whether there is a jump in the energy amplitude value at time t. The specific determination method is as follows:

[0029]

[0030] Among them, Amp_noise is the system noise amplitude value.

[0031] Preferably, the phase difference variation Pha_Sta1_m(t) and the phase difference standard deviation σ_Pha calculated in S2 are input into the second comparator to jointly determine whether there is a phase difference jump at time t. The specific determination method is as follows:

[0032]

[0033] Among them, Pha_noise is the standard deviation of the system noise phase difference, and σ_1 is the standard deviation of the single signal phase difference at the sensitivity point.

[0034] Preferably, the energy stability determination result Amp_Sta(t) and the phase difference stability determination result Pha_Sta(t) in S3 and S4 are input into a decision device to jointly determine whether there is signal superposition at time t.

[0035] Among them, the specific judgment criteria are: if the energy stability judgment result is 1, and the phase difference stability judgment result is also 1, there is signal superposition at time t, there is a single signal before time t, and there is a superposition signal segment after time t, otherwise there is no signal superposition at time t.

[0036] In summary, compared with the prior art, the present invention provides a superposition signal recognition method based on energy characteristics, which can make full use of the energy value mutation characteristics after signal superposition, continuously detect energy jump points in the time domain, and judge whether there is a jump in the signal. In order to avoid the influence of noise on the recognition signal, the relationship between the energy value and the noise is judged while judging the energy jump, thereby reducing the false alarm probability. At the same time, the inconsistent phase difference characteristics between channels caused by the inconsistent position relationship between the target signal, the superposition signal and the system are utilized, and the identification and distinction of the single signal and the signal superposition segment are completed in the spatial domain through the judgment of the phase difference stability. The method has high accuracy, small computational complexity, and is easy to implement in engineering, and has great practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of the implementation method of the present invention;

[0038] Figure 2 This is a schematic diagram of the principle of preprocessing multi-channel energy values ​​in the present invention;

[0039] Figure 3 This is a schematic diagram of the principle of preprocessing multi-channel phase values ​​in the present invention;

[0040] Figure 4 This is a schematic diagram of the principle of energy value stability determination according to the present invention;

[0041] Figure 5 This is a schematic diagram of the principle of the present invention for determining the stability of the phase difference;

[0042] Figure 6 This is a schematic diagram of the principle of the present invention for performing superposition signal recognition based on the discrimination result. DETAILED DESCRIPTION

[0043] The following is combined with Figures 1 to 6 , the present invention is further explained by describing a preferred specific embodiment in detail.

[0044] It should be noted that the drawings are in a very simplified form and use non-precise proportions. They are only used to conveniently and clearly assist in explaining the embodiments of the present invention, and are not used to limit the conditions for the implementation of the present invention. Therefore, they have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical content disclosed by the present invention.

[0045] It should be noted that, in the present invention, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only the elements explicitly listed, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0046] like Figure 1 As shown, the present invention provides a superposition signal recognition method based on energy characteristics, which specifically comprises the following steps:

[0047] S1. Preprocess the multi-channel energy amplitude values ​​to obtain the energy stability Amp_Sta1(t) at time t and the energy amplitude mean Amp_mean(t) at x moments before time t;

[0048] S2. Preprocess the multi-channel phase values ​​to obtain the phase difference change Pha_Sta1_m(t) between time t-1 and time t and the standard deviation σ_Pha of the phase difference at x times before time t;

[0049] S3, using the energy stability Amp_Sta1(t) and energy amplitude mean Amp_mean(t) obtained in S1 to determine the energy value stability;

[0050] S4, using the phase difference variation Pha_Sta1_m(t) obtained in S2 and the standard deviation σ_Pha of the phase difference to determine the phase difference stability;

[0051] S5. Identify the superimposed signal according to the determination results of S3 and S4 to determine whether the superimposed signal exists.

[0052] Further, such as Figure 2 As shown, the S1 specifically includes the following steps:

[0053] S11, input the energy amplitude value Amp_(t) of each channel at time t into the multi-channel mean processing module 101, and obtain the energy amplitude mean value Amp(t) at time t, the formula is as follows:

[0054] Amp_(t)=(Amp_1(t)+Amp_2(t)+…+Amp_m(t)+…+Amp_M(t)) / M;

[0055] Where Amp_(t) is the mean energy amplitude at time t; Amp_m(t) is the energy amplitude value of the mth channel at time t, m = 1, 2…, M, M is the number of channels;

[0056] S12, input the energy amplitude mean value Amp_(t) at time t into the difference module 102, and perform a difference calculation with the energy amplitude mean value Amp_(t-1) at the previous time (i.e., time t-1), solve the relative ratio, and obtain the energy stability Amp_Sta1(t) at time t, the formula is as follows:

[0057] Amp_Sta1(t)=Amp_(t) / Amp_(t-1);

[0058] S13, input the energy amplitude mean Amp_(t) at time t into the sliding mean calculation module 103, and take time t as the end point, slidingly calculate the energy amplitude mean Amp_mean(t) of x moments before time t, the formula is as follows:

[0059] Amp_mean(t)=(Amp_(t)+Amp_(t-1)+…+Amp_(tx)) / x;

[0060] It should be noted that the selection of the value x is determined according to the sensitivity of the actual system calibration, and the condition to be met is that the average energy amplitude of the signal required by the system index at the value x is greater than the system noise amplitude value.

[0061] Further, such as Figure 3 As shown, the S2 specifically includes the following steps:

[0062] S21, input the phase value of each channel at time t into the channel phase difference calculation module 201, and make a difference based on the phase value Pha_1(t) of channel 1 to obtain the phase difference of each channel, the formula is as follows:

[0063] Diff_Pha_m(t)=Pha_m(t)-Pha_1(t);

[0064] Where Diff_Pha_m(t) is the phase difference of channel m at time t; Pha_m(t) is the phase value of channel m at time t;

[0065] S22, input the phase difference of each channel at time t into the phase difference variation calculation module 202, and perform difference calculation with the phase difference at the previous time (i.e., time t-1), to obtain the phase difference variation Pha_Sta1_m(t) between time t-1 and time t, the formula is as follows:

[0066] Pha_Sta1_m(t)=Diff_Pha_m(t)-Diff_Pha_m(t-1);

[0067] S23, input the phase difference of each channel at time t into the phase difference standard deviation calculation module 203, and take time t as the end point, slide and calculate the standard deviation of the phase difference at x times before time t, and obtain the phase difference standard deviation σ_Pha, the formula is as follows:

[0068] Diff_Pha_mean_m(t)=(Diff_Pha_m(t)+Diff_Pha_m(t-1)+…+

[0069] Diff_Pha_m(tx)) / M;

[0070] Where Diff_Pha_mean_m(t) is the mean phase difference of the mth channel at x moments before moment t;

[0071]

[0072] Wherein, σ_Pha(m) is the standard deviation of the phase difference at time x before time t of the mth channel;

[0073] σ_Pha=(σ_Pha(2)+σ_Pha(3)+…+σ_Pha(M)) / (M-1).

[0074] It should be noted that the value of x is consistent with the value of x in the above step S13.

[0075] Further, such as Figure 4 As shown, in S3, the energy stability Amp_Sta1(t) at time t calculated in S1 and the energy amplitude mean Amp_mean(t) at x times before time t are input into the first comparator 301 to jointly determine whether there is a jump in the energy amplitude value at time t, that is, whether the energy amplitude value is stable; wherein the specific determination method is shown in the following formula:

[0076]

[0077] Among them, Amp_noise is the system noise amplitude value, which is obtained based on actual system measurements.

[0078] Further, such as Figure 5 As shown, in S4, the phase difference variation Pha_Sta1_m(t) and the phase difference standard deviation σ_Pha calculated in S2 are input into the second comparator 401 to jointly determine whether there is a phase difference jump at time t, that is, whether the phase difference between channels is stable, wherein the specific determination method is shown in the following formula:

[0079]

[0080] Among them, Pha_noise is the standard deviation of the system noise phase difference, and σ_1 is the standard deviation of the single signal phase difference at the sensitivity point, both of which are obtained based on actual system measurements.

[0081] Further, such as Figure 6 As shown, in S5, the specific method is: input the energy stability determination result Amp_Sta(t) and the phase difference stability determination result Pha_Sta(t) in S3 and S4 into the decision device 501, and jointly determine whether there is signal superposition at time t, wherein the specific determination criterion is:

[0082] If the energy stability judgment result is 1 and the phase difference stability judgment result is also 1, there is signal superposition at time t, that is, there is a single signal before time t and a superposition signal segment after time t; otherwise, there is no signal superposition at time t.

[0083] In summary, the present invention provides a superposition signal recognition method based on energy characteristics, which can make full use of the energy value mutation characteristics after signal superposition, continuously detect energy jump points in the time domain, and judge whether the signal has a jump. In order to avoid the influence of noise on the recognition signal, the relationship between the energy value and the noise is judged while judging the energy jump, thereby reducing the false alarm probability. At the same time, the inconsistent phase difference characteristics between channels caused by the inconsistent position relationship between the target signal, the superposition signal and the system are utilized, and the identification and distinction of the single signal and the signal superposition segment are completed in the spatial domain through the judgment of the phase difference stability. The method has high accuracy, small calculation amount and is easy to implement in engineering.

[0084] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A superposition signal recognition method based on energy characteristics, characterized in that: The following steps are involved: S1. Preprocess the multi-channel energy amplitude values ​​to obtain the energy stability Amp_Sta1(t) at time t and the energy amplitude mean Amp_mean(t) at x moments before time t; S2. Preprocess the multi-channel phase values ​​to obtain the phase difference change Pha_Sta1_m(t) between time t-1 and time t and the standard deviation σ of the phase difference at x times before time t _ Pha; S3, using the energy stability Amp_Sta1(t) and energy amplitude mean Amp_mean(t) obtained in S1 to determine the energy value stability; S4, using the phase difference change Pha_Sta1_m(t) obtained in S2 and the standard deviation σ of the phase difference _ Pha determines the phase difference stability; S5. Identify the superimposed signal according to the determination results of S3 and S4 to determine whether the superimposed signal exists.

2. The superposition signal recognition method based on energy characteristics according to claim 1, characterized in that: The S1 includes the following steps: S11, the energy amplitude value Amp of each channel at time t _ (t) is input into the multi-channel average processing module to obtain the energy amplitude mean Amp(t) at time t, and the formula is as follows: Amp _ (t)=(Amp _ 1(t)+Amp _ 2(t)+…+Amp_m(t)+…+Amp_M(t)) / M; Where Amp_(t) is the mean energy amplitude at time t; Amp_m(t) is the energy amplitude value of the mth channel at time t, m = 1, 2…, M, M is the number of channels; S12, the energy amplitude mean Amp at time t _ (t) is input into the difference module and is compared with the energy amplitude mean Amp at time t-1 _ (t-1) perform differential calculation, solve the relative ratio, and obtain the energy stability Amp_Sta1(t) at time t. The formula is as follows: Amp_Sta1(t)=Amp_(t) / Amp_(t-1); S13, the energy amplitude mean Amp at time t _ (t) is input into the sliding mean calculation module, and with time t as the end point, the sliding calculation of the energy amplitude mean Amp_mean(t) of x moments before time t is performed. The formula is as follows: Amp_mean(t)=(Amp_(t)+Amp_(t-1)+…+Amp_(tx)) / x.

3. The superposition signal recognition method based on energy characteristics as claimed in claim 2, characterized in that: The selection of the value x is determined according to the sensitivity of the actual system calibration, and the condition to be met is: the average energy amplitude of the signal required by the system index at the value x is greater than the system noise amplitude value.

4. The superposition signal recognition method based on energy characteristics as claimed in claim 3 is characterized in that: The S2 comprises the following steps: S21, input the phase value of each channel at time t into the channel phase difference calculation module, and make a difference based on the phase value Pha_1(t) of channel 1 to obtain the phase difference of each channel. The formula is as follows: Diff_Pha_m(t)=Pha_m(t)-Pha_1(t); Where Diff_Pha_m(t) is the phase difference of channel m at time t; Pha_m(t) is the phase value of channel m at time t; S22, input the phase difference of each channel at time t into the phase difference variation calculation module, and perform difference calculation with the phase difference at time t-1 to obtain the phase difference variation Pha_Sta1_m(t) between time t-1 and time t, the formula is as follows: Pha_Sta1_m(t)=Diff_Pha_m(t)-Diff_Pha_m(t-1); S23, input the phase difference of each channel at time t into the phase difference standard deviation calculation module, and take time t as the end point, slide and calculate the standard deviation of the phase difference at x moments before time t, and obtain the phase difference standard deviation σ _ Pha, the formula is as follows: Diff_Pha_mean_m(t)=(Diff_Pha_m(t)+Diff_Pha_m(t-1)+…+ Diff_Pha_m(tx)) / M; Where Diff_Pha_mean_m(t) is the mean phase difference of the mth channel at x moments before moment t; Among them, σ _ Pha(m) is the standard deviation of the phase difference at time x before time t for the mth channel; σ_Pha=(σ_Pha(2)+σ_Pha(3)+…+σ_Pha(M)) / (M-1).

5. The superposition signal recognition method based on energy characteristics as claimed in claim 3, characterized in that: The energy stability Amp_Sta1(t) at time t calculated in S1 and the energy amplitude mean Amp_mean(t) at x times before time t are input into the first comparator to jointly determine whether there is a jump in the energy amplitude value at time t. The specific determination method is as follows: Among them, Amp_noise is the system noise amplitude value.

6. The superposition signal recognition method based on energy characteristics according to claim 4, characterized in that: The phase difference variation Pha_Sta1_m(t) calculated in S2 and the phase difference standard deviation σ_Pha are input into the second comparator to jointly determine whether there is a phase difference jump at time t. The specific determination method is as follows: Among them, Pha_noise is the standard deviation of the system noise phase difference, and σ_1 is the standard deviation of the single signal phase difference at the sensitivity point.

7. The superposition signal recognition method based on energy characteristics according to claim 1, characterized in that: The energy stability determination result Amp_Sta(t) and the phase difference stability determination result Pha_Sta(t) in S3 and S4 are input into the decision device to jointly determine whether there is signal superposition at time t; Among them, the specific judgment criteria are: if the energy stability judgment result is 1, and the phase difference stability judgment result is also 1, there is signal superposition at time t, there is a single signal before time t, and there is a superposition signal segment after time t, otherwise there is no signal superposition at time t.

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