A short wave weak signal detection method based on array distribution type collection

Abstract

This invention provides a shortwave weak signal detection method based on array-distributed acquisition, belonging to the field of shortwave communication reconnaissance technology. The method includes: using M antennas spaced at a predetermined interval to receive shortwave signals and acquire M synchronous parallel signal data; setting up two time-staggered sliding detectors to segment the M synchronous parallel data; merging the signals of each segment according to the maximum signal-to-noise ratio principle to obtain a synthesized first signal and a second signal; performing signal synchronization sequence correlation detection on the first signal and the second signal respectively, recording the correlation peak times when the correlation peak value is greater than a threshold th as the first peak value and the second peak value respectively; and combining the detection results of the two signals to output the final detection result. This method can effectively address multipath fading caused by time-varying ionospheric channels, significantly improve weak signal detection capabilities, and combines accuracy and timeliness, making it applicable to array-distributed acquisition shortwave systems.

Description

Technical Field

[0001] This invention belongs to the field of shortwave communication reconnaissance technology, and specifically relates to a method for detecting weak shortwave signals based on array distributed acquisition. Background Technology

[0002] Currently, array-based distributed acquisition, also known as multi-antenna diversity technology, utilizes multiple antennas to receive signals diversely within a certain spatial domain. This improves signal reception quality in complex electromagnetic environments and offers advantages such as anti-fading and flexible deployment, thus better ensuring signal reception. Compared to traditional array signal processing methods, diversity reception offers advantages such as flexible array element deployment, diverse antenna selection, and good spatial complementarity.

[0003] After synchronously acquiring target signals using multiple antennas, there are two signal combining schemes: a synthesis scheme based on synchronous demodulation and a synthesis scheme based on signal waveforms. The former requires each antenna to perform carrier tracking and symbol synchronization separately, completing the synthesis simultaneously with signal demodulation, and demanding that the signal-to-noise ratio of a single signal reach the synchronization threshold. The latter synthesizes the original signals from each antenna; to ensure correlation, the signals require time delay compensation, frequency compensation, and phase adjustment before synthesis. Considering the detection of weak signals in complex fading channels, the signal waveform-based synthesis scheme is more suitable. In practical applications, signal synthesis can employ different criteria and methods, mainly including maximum ratio combining (MRC), equal gain combining (EGC), selective combining (SC), and switching combining. Among these, maximum ratio combining has the optimal combining gain, but it requires high signal stability and is difficult to handle signal fading fluctuations caused by time-varying ionospheric channels.

[0004] Therefore, how to provide a method for detecting weak shortwave signals based on array distributed acquisition has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a method for detecting weak shortwave signals based on array distributed acquisition, including:

[0006] Step S1: Use M antennas spaced at a preset interval to receive shortwave signals and acquire M synchronous parallel signal data, where M≥2;

[0007] Step S2: Set up two time-displaced sliding detectors, a first sliding detector D1 and a second sliding detector D2. The duration of both the first sliding detector D1 and the second sliding detector is T, and their start times are displaced by T / 2.

[0008] Step S3: Using the sliding detector D1, the M synchronous parallel data are segmented, and each segment is merged according to the maximum signal-to-noise ratio principle to obtain the synthesized first signal S1;

[0009] Step S4: Using the sliding detector D2, the M synchronous parallel data are segmented. For each segment, the signals are merged according to the principle of maximum signal-to-noise ratio to obtain the synthesized second signal S2.

[0010] Step S5: Perform signal synchronization sequence correlation detection on the first signal S1 and the second signal S2 respectively, and record the correlation peak time when the correlation peak value is greater than the threshold th as the first peak value T. d1 Second peak T d2 ;

[0011] Step S6: Detection results T of the two signals d1 T d2 Perform synthesis and output T d This is the final test result.

[0012] Optionally, in step S1, the preset spacing is greater than 3 times the signal wavelength.

[0013] Optionally, in step S2, the duration T is greater than twice or more the duration of the synchronization sequence of the signal.

[0014] Optionally, a synchronization sequence detection method can be used for detection. The signal synchronization sequence can be modulated to obtain the reference sequence Q, as follows:

[0015]

[0016] q n The value is the sampled value of the nth signal.

[0017] Optionally, a point-by-point sliding window detection is performed on the acquired M-channel synchronous parallel signal data using a reference sequence Q. The signal sequence is as follows:

[0018]

[0019] Where k is the sliding start point and p is the oversampling rate;

[0020] Calculate Q point by point From the Pearson correlation coefficient, we can obtain:

[0021]

[0022] Set a threshold th when the correlation coefficient... When the maximum value V is greater than th, a signal is considered to have been detected; the larger V is, the better the detection effect.

[0023] The Pearson correlation coefficient, also known as the Pearson correlation coefficient, is a statistical indicator that measures the degree of linear correlation between two variables.

[0024] Signals are received using multiple antenna elements distributed in space, with the M branch signals being respectively... , … The merge signal is:

[0025]

[0026] in, The weighting coefficients for the k-th branch signal need to be normalized, i.e. ;

[0027] Instantaneous signal-to-noise ratio of each of the M branch signals With average signal-to-noise ratio :

[0028]

[0029]

[0030] in, Unit signal energy; Let be the signal amplitude of the i-th channel; This represents the average noise power. This indicates the expectation value.

[0031] Optionally, the maximum ratio combining method is used to combine the signals to maximize the signal-to-noise ratio of the output signal, and the branch weighting coefficients are adjusted accordingly. It is directly proportional to the envelope and inversely proportional to the noise power;

[0032] The weighting coefficient of the k-th branch can be expressed as: ,in, Denotes the envelope of the k-th branch. The noise power of the k-th branch is given, thus the signal envelope of the output under maximum ratio combining can be obtained. for:

[0033]

[0034] If the signal received by each branch is represented as: Then the weighting coefficients can also be expressed as: ,in, Indicates the amplitude of the received signal. This represents the phase of the received signal, where e is the base of the natural logarithm and j is the imaginary unit. In maximum ratio combining mode, with... This represents the sum of the signal-to-noise ratios of all branches:

[0035]

[0036] In a Rayleigh distribution, the square of the envelope follows a sequence with 2 degrees of freedom. Distribution, from which we can derive The probability distribution function is:

[0037]

[0038] Apply this formula to Taking the derivative, we can obtain the probability density function as:

[0039]

[0040] The average signal-to-noise ratio (SNR) of the sum of the SNRs of each branch after merging is:

[0041]

[0042] In maximum ratio combining, the average signal-to-noise ratio is proportional to the number of diversity branches M. Therefore, the diversity gain under maximum ratio combining can be derived as follows:

[0043]

[0044] Therefore, it can be concluded that the maximum ratio merging can achieve the optimal gain.

[0045] Optionally, it must be ensured that the signal does not change during the merging period.

[0046] Optionally, in step S6, the time difference must be ≤ The two results are merged, and the result with the larger correlation peak is retained.

[0047] Optionally, in step S1, a 128-antenna array is used to synchronously acquire signal data.

[0048] Optionally, the aperture of the antenna array is greater than 1 km.

[0049] As can be seen from the above scheme, the embodiments of the present invention provide a shortwave weak signal detection method based on array distributed acquisition, which has the following beneficial effects:

[0050] This invention addresses the spatially varying fading characteristics of shortwave multipath fading signals by employing multi-antenna spatially spaced diversity reception. Based on signal protocol characteristics, two staggered sliding detectors with a duration equal to or greater than twice the signal synchronization sequence duration are used, and multi-channel signals are combined according to the maximum ratio principle. The two combined signals are then subjected to correlation detection and result aggregation to obtain the final detection result. This method effectively addresses multipath fading caused by time-varying ionospheric channels, significantly improves weak signal detection capabilities, and combines accuracy with timeliness. It can be applied to array-based distributed acquisition shortwave systems. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of a shortwave weak signal detection method based on array distributed acquisition provided according to an embodiment.

[0052] Figure 2 This is a schematic diagram illustrating the principle of a shortwave weak signal detection method based on array distributed acquisition, according to an embodiment.

[0053] Figure 3 This is a schematic diagram of the M110A signal frame structure in a shortwave weak signal detection method based on array distributed acquisition provided according to an embodiment;

[0054] Figure 4 This is a schematic diagram of a sliding detector in a shortwave weak signal detection method based on array distributed acquisition provided in an embodiment;

[0055] Figure 5 This is a schematic diagram illustrating the implementation principle of maximum ratio combining in a shortwave weak signal detection method based on array distributed acquisition, according to an embodiment.

[0056] Figures 6(a)-6(c) show the M110A signal detection effect of a shortwave weak signal detection method based on array distributed acquisition provided in the embodiment. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0058] like Figure 2The diagram shows the design principle of a shortwave weak signal detection method based on array distributed acquisition according to the present invention. The main application scenario of the method of the present invention is shortwave communication signal reconnaissance. After completing multi-channel synchronous acquisition of signals, two time-displaced sliding detectors are first constructed according to the specific signal protocol. After data segmentation, maximum ratio merging, and signal detection, the results of the two sliding detectors are combined to output the signal detection result.

[0059] like Figure 1 As shown, this application provides a method for detecting weak shortwave signals based on array distributed acquisition, including:

[0060] Step S1: Use M antennas spaced at a preset interval to receive shortwave signals and acquire M synchronous parallel signal data, where M≥2;

[0061] Preferably, the M antennas are consistent, and using the M antennas to receive shortwave specific protocol signals meets the requirements of synchronous acquisition;

[0062] The preset spacing is greater than 3 times the signal wavelength.

[0063] The M110A is a representative signal in shortwave digital communication, employing 8PSK modulation with a symbol rate of 2400 bps. The data rate can be selected from 75 to 2400 bps depending on transmission requirements. The M110A's synchronization preamble consists of multiple 200ms synchronization sequences, repeated 3 times for short interleaving and 24 times for long interleaving. Each synchronization sequence contains 480 symbols, with the first 288 symbols fixed and the remaining symbols containing waveform parameters. The data segment follows the synchronization preamble, with each data segment having the same duration as the synchronization preamble. Figure 3 This is a schematic diagram of the M110A signal frame structure.

[0064] Step S2: Set up two time-displaced sliding detectors, a first sliding detector D1 and a second sliding detector D2. The duration of both the first sliding detector D1 and the second sliding detector is T, and their start times are displaced by T / 2. The duration T is greater than twice or more the duration of the signal's synchronization sequence.

[0065] Step S3: Using the sliding detector D1, the M synchronous parallel data are segmented, and each segment is merged according to the maximum signal-to-noise ratio principle to obtain the synthesized first signal S1;

[0066] Step S4: Using the sliding detector D2, the M synchronous parallel data are segmented. For each segment, the signals are merged according to the principle of maximum signal-to-noise ratio to obtain the synthesized second signal S2.

[0067] Step S5: Perform signal synchronization sequence correlation detection on the first signal S1 and the second signal S2 respectively, and record the correlation peak time when the correlation peak value is greater than the threshold th as the first peak value T. d1 Second peak T d2 ;

[0068] Step S6: Detection results T of the two signals d1 T d2 Perform a synthesis, where the time difference is ≤ The two results are merged, and the result with the larger correlation peak is retained. The output is T. d This is the final test result.

[0069] The detection method employs a synchronization sequence detection approach. The reference sequence Q is obtained by modulating the signal synchronization sequence, as detailed below:

[0070] ;

[0071] q n The value is the sampled value of the nth signal.

[0072] Using the reference sequence Q, point-by-point sliding window detection is performed on the acquired M-channel synchronous parallel signal data. The signal sequence is as follows:

[0073]

[0074] Where k is the sliding start point and p is the oversampling rate;

[0075] Calculate Q point by point From the Pearson correlation coefficient, we can obtain:

[0076]

[0077] Set a threshold th when the correlation coefficient... When the maximum value V is greater than th, a signal is considered to have been detected; the larger V is, the better the detection effect.

[0078] The Pearson correlation coefficient, also known as the Pearson correlation coefficient, is a statistical indicator that measures the degree of linear correlation between two variables.

[0079] Signals are received using multiple antenna elements distributed in space, with the M branch signals being respectively... , … The merge signal is:

[0080]

[0081] in, The weighting coefficients for the k-th branch signal need to be normalized, i.e. ;

[0082] Instantaneous signal-to-noise ratio of each of the M branch signals With average signal-to-noise ratio :

[0083]

[0084]

[0085] in, Unit signal energy; Let be the signal amplitude of the i-th channel; This represents the average noise power. This indicates the expectation value.

[0086] The maximum ratio combining method is used to maximize the signal-to-noise ratio of the output signal, and the branch weighting coefficients are... The signal-to-noise ratio (SNR) of the output signal is directly proportional to the envelope and inversely proportional to the noise power. Maximum ratio combining is the optimal combining method; the weighting coefficients in this method are adjusted according to certain rules to maximize the SNR of the output signal. The branch weighting coefficients are directly proportional to the envelope and inversely proportional to the noise power; the basic principle is as follows: Figure 5 As shown.

[0087] The weighting coefficient of the k-th branch can be expressed as: ,in, Denotes the envelope of the k-th branch. The noise power of the k-th branch is given, thus the signal envelope of the output under maximum ratio combining can be obtained. for:

[0088]

[0089] If the signal received by each branch is represented as: Then the weighting coefficients can also be expressed as: ,in, Indicates the amplitude of the received signal. This represents the phase of the received signal, where e is the base of the natural logarithm and j is the imaginary unit. In maximum ratio combining mode, with... This represents the sum of the signal-to-noise ratios of all branches:

[0090]

[0091] In a Rayleigh distribution, the square of the envelope follows a sequence with 2 degrees of freedom. Distribution, from which we can derive The probability distribution function is:

[0092]

[0093] Apply this formula to Taking the derivative, we can obtain the probability density function as:

[0094]

[0095] The average signal-to-noise ratio (SNR) of the sum of the SNRs of each branch after merging is:

[0096]

[0097] In the maximum ratio combining method, the average signal-to-noise ratio is proportional to the number of diversity branches M.

[0098] Therefore, the diversity gain under maximum ratio merging can be derived as:

[0099]

[0100] Therefore, maximum ratio combining can achieve optimal gain, but this combining method requires high signal stability, ensuring that the signal remains unchanged during the combining period. However, practical shortwave communication channels are easily affected by ionospheric time-varying effects, leading to severe fading fluctuations in the received signal and lacking a fixed signal-to-noise ratio. To improve the combining effect, the combining time must be reduced. However, reducing the time may cause discontinuities between adjacent combining segments, resulting in a decrease in the correlation detection peak value.

[0101] This invention fully considers the time-varying characteristics of the ionospheric channel and shortens the merging time as much as possible. In order to avoid signal discontinuity, two time-staggered sliding detectors are used for parallel detection. Figure 4 The diagram shows a sliding detector in an embodiment of the present invention. The duration of the two detectors is T, and they are offset by T / 2. The duration of T can be set to twice the duration of the signal synchronization sequence. This sliding detection ensures that the signal synchronization sequence appears completely within one detector window, achieving short-time maximum ratio merging and correlation detection, and obtaining the optimal detection effect.

[0102] Furthermore, in some specific embodiments, the processing effect of the above method on the actual sampled M110A detection is as follows: Figures 6(a) to 6(c)As shown, the test sample used 128 antennas for synchronous acquisition, with an antenna array aperture greater than 1km and antenna structures including cages and dipoles. Figure 6(a) shows the peak values ​​after correlation detection of 128 single channels. Due to the varying reception of long-distance skywave signals at different points in the airspace, the detected correlation peak values ​​differ, mostly ranging from 0.2 to 0.4, with the largest correlation peak value being 0.57. Using the above method for detection, Figure 6(b) shows the correlation detection results of sliding detector D1, with a maximum correlation peak value of 0.79; Figure 6(c) shows the correlation detection results of sliding detector D2, with a maximum correlation peak value of 0.83. Both are significantly better than the highest single-channel detection correlation peak, proving that the signal detection capability is greatly improved after processing by the sliding detector of this invention.

[0103] The method proposed in this invention is also effective for other shortwave-specific protocol signals, such as M110B and 3G-ALE. In the description of this specification, specific features or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0104] In summary, this invention addresses the spatially varying fading characteristics of shortwave multipath fading signals by employing multi-antenna spatially spaced diversity reception. Based on signal protocol characteristics, two staggered sliding detectors with a duration equal to or greater than twice the signal synchronization sequence duration are used, and multi-channel signals are combined according to the maximum ratio principle. The two synthesized signals are then subjected to correlation detection and result aggregation to obtain the detection result. This method effectively addresses multipath fading caused by time-varying ionospheric channels, significantly improves weak signal detection capabilities, and combines accuracy and timeliness, making it applicable to array-based distributed acquisition shortwave systems.

[0105] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for detecting weak shortwave signals based on array-distributed acquisition, characterized in that, include: Step S1: Use M antennas spaced at a preset interval to receive shortwave signals and acquire M synchronous parallel signal data, where M≥2; Step S2: Set up two time-displaced sliding detectors, a first sliding detector D1 and a second sliding detector D2. The duration of both the first sliding detector D1 and the second sliding detector is T, and their start times are displaced by T / 2. Step S3: Using the sliding detector D1, the M synchronous parallel data are segmented, and each segment is merged according to the maximum signal-to-noise ratio principle to obtain the synthesized first signal S1; Step S4: Using the sliding detector D2, the M synchronous parallel data are segmented. For each segment, the signals are merged according to the principle of maximum signal-to-noise ratio to obtain the synthesized second signal S2. Step S5: Perform signal synchronization sequence correlation detection on the first signal S1 and the second signal S2 respectively, and record the correlation peak time when the correlation peak value is greater than the threshold th as the first peak value T. d1 Second peak T d2 ; Step S6: Detection results T of the two signals d1 T d2 Perform synthesis and output T d This is the final test result.

2. The shortwave weak signal detection method based on array distributed acquisition according to claim 1, characterized in that, In step S1, the preset spacing is greater than 3 times the signal wavelength.

3. The shortwave weak signal detection method based on array distributed acquisition according to claim 2, characterized in that, In step S2, the duration T is greater than twice or more the duration of the synchronization sequence of the signal.

4. The shortwave weak signal detection method based on array distributed acquisition according to claim 3, characterized in that, The detection method employs a synchronization sequence detection approach. The reference sequence Q is obtained by modulating the signal synchronization sequence, as detailed below: q n For the first n Signal sampling values.

5. The shortwave weak signal detection method based on array distributed acquisition according to claim 4, characterized in that, Using the reference sequence Q, point-by-point sliding window detection is performed on the acquired M-channel synchronous parallel signal data. The signal sequence is as follows: Where k is the sliding start point and p is the oversampling rate; Calculate Q point by point From the Pearson correlation coefficient, we can obtain: Set a threshold th when the correlation coefficient... When the maximum value V is greater than th, a signal is considered to have been detected; the larger V is, the better the detection effect. Signals are received using multiple antenna elements distributed in space, with the M branch signals being respectively... , … The merge signal is: in, The weighting coefficients for the k-th branch signal need to be normalized, i.e. ; Instantaneous signal-to-noise ratio of each of the M branch signals With average signal-to-noise ratio : in, Unit signal energy; Let be the signal amplitude of the i-th channel; This represents the average noise power. This indicates the expectation value.

6. The shortwave weak signal detection method based on array distributed acquisition according to claim 5, characterized in that, The maximum ratio combining method is used to maximize the signal-to-noise ratio of the output signal, and the branch weighting coefficients are... It is directly proportional to the envelope and inversely proportional to the noise power; The weighting coefficient of the k-th branch can be expressed as: ,in, Denotes the envelope of the k-th branch. The noise power of the k-th branch is given, thus the signal envelope of the output under maximum ratio combining can be obtained. for: If the signal received by each branch is represented as: Then the weighting coefficients can also be expressed as: ,in, Indicates the amplitude of the received signal. This indicates the phase of the received signal, where e is the base of the natural logarithm and j is the imaginary unit. Under the maximum ratio merging method, with This represents the sum of the signal-to-noise ratios of all branches: In a Rayleigh distribution, the square of the envelope follows a sequence with 2 degrees of freedom. Distribution, from which we can derive The probability distribution function is: Apply this formula to Taking the derivative, we can obtain the probability density function as: The average signal-to-noise ratio (SNR) of the sum of the SNRs of each branch after merging is: In the maximum ratio combining method, the average signal-to-noise ratio is proportional to the number of diversity branches M; Therefore, the diversity gain under maximum ratio merging can be derived as: Therefore, it can be concluded that the maximum ratio merging can achieve the optimal gain.

7. The shortwave weak signal detection method based on array distributed acquisition according to claim 6, characterized in that, It is necessary to ensure that the signal does not change during the merging period.

8. The shortwave weak signal detection method based on array distributed acquisition according to claim 7, characterized in that, In step S6, the time difference must be ≤ The two results are merged, and the result with the larger correlation peak is retained.

9. The shortwave weak signal detection method based on array distributed acquisition according to claim 8, characterized in that, In step S1, a 128-antenna array is used to synchronously acquire signal data.

10. The shortwave weak signal detection method based on array distributed acquisition according to claim 9, characterized in that, The aperture of the antenna array is greater than 1 km.

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