A Dual-channel High-sensitivity Signal Power Estimation Method, Device and Storage Medium

Abstract

The present invention provides a dual-channel high-sensitivity signal power estimation method, device and storage medium, including: obtaining first signal data and second signal data, wherein the first signal data is collected by a first data acquisition device, and the second signal data is collected by a second data acquisition device; determining a correlation peak detection result and an oversampling multiple according to the cross-correlation situation of the first signal data and the second signal data; calculating the target signal power according to the correlation peak detection result and the oversampling multiple. The present application obtains signal data through two data acquisition channels, and performs power estimation according to the signal data of different data acquisition channels, and can estimate the power of weak signals hidden in environmental noise, providing a better spectrum monitoring effect.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a dual-channel high-sensitivity signal power estimation method, apparatus, and storage medium. Background Art

[0002] In the face of an increasingly complex electromagnetic environment, spectrum monitoring technology is widely used in the Global Navigation Satellite System (GNSS for short). However, traditional spectrum monitoring methods cannot effectively monitor weak signals submerged by noise. The missed detection and false alarm of weak signals will affect the utilization efficiency of spectrum resources, and further limit the application and development of wireless communication technologies. Summary of the Invention

[0003] To solve the above technical problems, embodiments of the present application provide a dual-channel high-sensitivity signal power estimation method, apparatus, device, and medium that can improve the sensitivity of spectrum monitoring in a complex electromagnetic environment and effectively monitor weak signals submerged by environmental noise. The specific solutions are as follows:

[0004] In a first aspect, embodiments of the present application provide a dual-channel high-sensitivity signal power estimation method, including:

[0005] Obtain first signal data and second signal data, where the first signal data is collected by a first data acquisition device, the second signal data is collected by a second data acquisition device, the first signal data and the second signal data are signal data with different noises generated by different data acquisition devices collecting a target signal emitted by a target signal source, the first data acquisition device and the second data acquisition device are different data acquisition devices, and both the first data acquisition device and the second data acquisition device include a digital acquisition board and a signal receiving antenna;

[0006] Determine a correlation peak detection result and an oversampling ratio according to the cross-correlation situation between the first signal data and the second signal data;

[0007] Calculate the target signal power according to the correlation peak detection result and the oversampling ratio.

[0008] According to a specific implementation manner of an embodiment of the present application, the determining a correlation peak detection result and an oversampling ratio according to the cross-correlation situation between the first signal data and the second signal data includes:

[0009] Perform a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result;

[0010] Perform peak detection on the cross-correlation result to obtain a cross-correlation peak detection result, where the cross-correlation peak detection result includes a peak amplitude and a peak position;

[0011] Perform oversampling analysis based on the cross-correlation result and the cross-correlation peak detection result to obtain the oversampling ratio.

[0012] According to a specific implementation manner of an embodiment of the present application, the performing cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result includes:

[0013] Determine the length of the cross-correlation operation according to the signal sampling rate, and determine the length of the sliding traversal operation according to the signal sampling duration;

[0014] Perform cross-correlation operation on the first signal data and the second signal data according to the length of the cross-correlation operation and the length of the traversal operation to obtain the cross-correlation result.

[0015] According to a specific implementation manner of an embodiment of the present application, the performing peak detection on the cross-correlation result to obtain a cross-correlation peak detection result includes:

[0016] Perform modulus processing on the cross-correlation result to obtain a cross-correlation modulus value;

[0017] Traverse the cross-correlation modulus value to search for the cross-correlation peak detection result;

[0018] The performing oversampling analysis based on the cross-correlation result and the cross-correlation peak detection result to obtain the oversampling ratio includes:

[0019] Determine a threshold value according to the peak amplitude and a preset coefficient;

[0020] Obtain the number of target modulus values according to the threshold value and the cross-correlation modulus value, where the target modulus value is a cross-correlation modulus value greater than the threshold value;

[0021] Calculate the oversampling ratio according to the number of target modulus values.

[0022] According to a specific implementation manner of an embodiment of the present application, the calculating the target signal power according to the cross-correlation peak detection result and the oversampling ratio includes:

[0023]

[0024] Wherein, is the target signal power, is the peak amplitude of the cross-correlation peak detection result, is the oversampling ratio, is the signal sampling duration.

[0025] According to a specific implementation manner of an embodiment of the present application, before acquiring the first signal data and the second signal data, the method includes:

[0026] Controlling the first data acquisition device and the second data acquisition device to perform time synchronization;

[0027] When it is determined that both the first data acquisition device and the second data acquisition device are in a time synchronization state, controlling the first data acquisition device and the second data acquisition device to synchronously acquire signal data according to preset acquisition parameters.

[0028] According to a specific implementation manner of an embodiment of the present application, the first data acquisition device includes a first signal receiving antenna and a first digital acquisition board, and the second data acquisition device includes a second signal receiving antenna and a second digital acquisition board;

[0029] The controlling the first data acquisition device and the second data acquisition device to synchronously acquire signal data according to preset acquisition parameters includes:

[0030] Controlling the first digital acquisition board to perform preset data processing on the satellite signal received by the first signal receiving antenna to obtain the first signal data;

[0031] Controlling the second digital acquisition board to perform preset data processing on the satellite signal received by the second signal receiving antenna to obtain the second signal data, where the preset data processing includes filtering processing, amplification processing, mixing processing, and analog-to-digital conversion processing.

[0032] In a second aspect, an embodiment of the present application provides a dual-channel high-sensitivity signal power estimation device, including:

[0033] An acquisition module, configured to acquire first signal data and second signal data, where the first signal data is acquired by a first data acquisition device, the second signal data is acquired by a second data acquisition device, the first signal data and the second signal data are signal data with different noises generated by different data acquisition devices acquiring a target signal emitted by a target signal source, the first data acquisition device and the second data acquisition device are different data acquisition devices, and both the first data acquisition device and the second data acquisition device include a digital acquisition board and a signal receiving antenna;

[0034] A determination module, configured to determine a correlation peak detection result and an oversampling multiple according to the cross-correlation situation between the first signal data and the second signal data;

[0035] A calculation module, configured to calculate a target signal power according to the correlation peak detection result and the oversampling multiple.

[0036] In a third aspect, an embodiment of the present application provides an electronic device, which includes:

[0037] At least one processor; and,

[0038] A memory communicatively connected to the at least one processor; wherein,

[0039] The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the dual-channel high-sensitivity signal power estimation method described in the foregoing first aspect.

[0040] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium, which stores computer instructions for causing the computer to execute the dual-channel high-sensitivity signal power estimation method described in the foregoing first aspect.

[0041] In summary, this embodiment provides a dual-channel high-sensitivity signal power estimation method, device, equipment and medium, including: obtaining first signal data and second signal data, wherein the first signal data is collected by a first data acquisition device, and the second signal data is collected by a second data acquisition device; determining a correlation peak detection result and an oversampling multiple according to the cross-correlation situation of the first signal data and the second signal data; calculating a target signal power according to the correlation peak detection result and the oversampling multiple. The present application obtains signal data through two data acquisition channels and performs power estimation based on the signal data of different data acquisition channels, and can estimate the power of weak signals hidden in environmental noise, providing a better spectrum monitoring effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic flowchart of a dual-channel high-sensitivity signal power estimation method provided by an embodiment of the present application;

[0044] Figure 2 It is a schematic flowchart of the steps for determining the correlation peak detection result and the oversampling multiple provided by an embodiment of the present application;

[0045] Figure 3 It is a simulation schematic diagram of peak detection provided by an embodiment of the present application;

[0046] Figure 4 Schematic diagram of the steps for calculating the cross-correlation result provided by the embodiment of the present application;

[0047] Figure 5 Schematic diagram of the steps for searching the relevant peak detection result provided by the embodiment of the present application;

[0048] Figure 6 Schematic diagram of the steps for analyzing the oversampling ratio provided by the embodiment of the present application;

[0049] Figure 7 Schematic diagram of the device modules of a dual-channel high-sensitivity signal power estimation device provided by the embodiment of the present application;

[0050] Figure 8 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the first original signal data (ModeData1) when the signal-to-noise ratio SNR is -20 decibels (dB);

[0051] Figure 9 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the first signal data (rxSig1) when the signal-to-noise ratio SNR is -20 (dB);

[0052] Figure 10 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the second original signal data (ModeData2) when the signal-to-noise ratio SNR is -20 (dB);

[0053] Figure 11 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the second signal data (rxSig2) when the signal-to-noise ratio SNR is -20 (dB);

[0054] Figure 12 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the first original signal data (ModeData1) when the signal-to-noise ratio SNR is 15 (dB);

[0055] Figure 13 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the first signal data (rxSig1) when the signal-to-noise ratio SNR is 15 (dB);

[0056] Figure 14 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the second original signal data (ModeData2) when the signal-to-noise ratio SNR is 15 (dB);

[0057] Figure 15Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the second signal data (rxSig2) when the signal-to-noise ratio snr is 15 (dB);

[0058] Figure 16 Signal-to-noise ratio (snr) simulation diagram for introducing the error of oversampling factor (Nsample);

[0059] Figure 17 Signal-to-noise ratio (snr) simulation diagram for not introducing the error of oversampling factor (Nsample);

[0060] Figure 18 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the first signal data (rxSig1) when the signal-to-noise ratio snr is -15 (dB);

[0061] Figure 19 Frequency-domain simulation diagram after performing fast Fourier transform (FFT) on the second signal data (rxSig2) when the signal-to-noise ratio snr is -15 (dB);

[0062] Figure 20 Cross-correlation result simulation diagram after performing cross-correlation operation on the first signal data (rxSig1) and the second signal data (rxSig2) when the signal-to-noise ratio snr is -15 (dB);

[0063] Figure 21 Cross-correlation result simulation diagram after performing cross-correlation operation on the first signal data (rxSig1) and the second signal data (rxSig2) when the signal-to-noise ratio snr is 15 (dB). Specific implementation manner

[0064] The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0065] The following specific examples illustrate the implementation manners of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0066] Note that the following description relates to various aspects of embodiments within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is illustrative only. Based on this application, those skilled in the art should understand that one aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of the aspects set forth herein may be used to implement an apparatus and / or practice a method. Additionally, this apparatus and / or method may be implemented using other structures and / or functionality in addition to, or instead of, one or more of the aspects set forth herein.

[0067] It should also be noted that the diagrams provided in the following embodiments merely illustrate the basic concept of this application schematically. The diagrams only show the components related to this application and are not drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation may be arbitrarily changed, and the component layout type may also be more complex.

[0068] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the aspects may be practiced without these specific details.

[0069] In the related art, spectrum monitoring is mainly used to monitor and analyze electromagnetic waves in a specific frequency range in real time to determine the usage and distribution of frequencies. In fields such as wireless communication, television broadcasting, air navigation, and radar, the spectrum, as a limited resource, needs to be reasonably planned and allocated to different communication systems. Spectrum monitoring helps with tasks such as spectrum resource planning, management, optimization, and sharing.

[0070] For the Global Navigation Satellite System (GNSS), developing a high-sensitivity spectrum monitoring system can support the real-time monitoring and analysis of the complex and changing electromagnetic environment by GNSS, thereby ensuring the effective management and optimal utilization of spectrum resources and safeguarding communication security and the security of the electromagnetic space. In actual application scenarios, after the navigation signals sent by GNSS have propagated over extremely long distances, the signal strength has been greatly attenuated and is extremely vulnerable to interference from other signals. Therefore, weak interference signals can also affect the performance of GNSS. Moreover, the complex and changing spatial electromagnetic environment can also affect the performance of GNSS.

[0071] Power estimation, especially power spectrum estimation, is an important part in signal processing. The power spectrum describes the distribution of signal power at each frequency point. Integrating the power spectrum in the frequency domain can obtain the power of the signal. In practical applications, such as in spectrum monitoring, it may be necessary to use power spectrum estimation techniques to analyze the power distribution of signals. However, existing signal power estimation systems are difficult to detect weak signals that are submerged by environmental noise and the thermal noise of the acquisition equipment itself. If the signal power estimation system cannot effectively collect weak signals, it is impossible to achieve high-sensitivity spectrum monitoring.

[0072] Based on the above problems, this embodiment provides a power estimation system that can implement a dual-channel high-sensitivity signal power estimation method. The power estimation system provided in this embodiment includes at least two sets of data acquisition devices and a main control computer device. Among them, the data acquisition device includes a digital acquisition board and a signal receiving antenna.

[0073] In this embodiment, the signal receiving antenna is used to sense various electromagnetic field signals and interference signals including all visible GPS satellite signals, and has the ability to extract satellite signals in a complex electromagnetic environment.

[0074] The digital acquisition board includes a pre-filter, a pre-amplifier, a mixer, and an analog-to-digital converter. In the actual application process, the digital acquisition board receives all visible signals through the signal receiving antenna. After the signals are filtered and amplified by the pre-filter and the pre-amplifier, the signals are down-converted into intermediate-frequency signals by the mixer, and finally the intermediate-frequency signals are converted into discrete-time digital intermediate-frequency signals by the analog-to-digital converter.

[0075] The main control computer device includes the control software of the digital acquisition board. The main control computer is communicatively connected to the digital acquisition board and is used to control the digital acquisition board to perform corresponding signal acquisition operations through preset control instructions. The digital acquisition board transmits the converted digital intermediate-frequency signals to the main control computer device for the main control computer device to further execute the signal power estimation method.

[0076] Reference Figure 1 , this application embodiment provides a dual-channel high-sensitivity signal power estimation method. Taking the application of this method to the main control computer device in the foregoing embodiment as an example, the method includes the following steps:

[0077] S101. Obtain first signal data and second signal data. Herein, the first signal data is collected by a first data acquisition device, and the second signal data is collected by a second data acquisition device. The first signal data and the second signal data are signal data with different noises attached, which are generated by different data acquisition devices collecting the target signal emitted by a target signal source. The first data acquisition device and the second data acquisition device are different data acquisition devices, and both the first data acquisition device and the second data acquisition device include a digital acquisition board and a signal receiving antenna.

[0078] In this embodiment, the first data acquisition device and the second data acquisition device are two different data acquisition devices. The first data acquisition device and the second data acquisition device form two different data acquisition channels of the power estimation system.

[0079] Obtain the first signal data and the second signal data through two different data acquisition channels. Furthermore, the weak signal in the electromagnetic environment received by the signal receiving antenna can be analyzed based on the first signal data and the second signal data, effectively improving the sensitivity of signal monitoring. In this embodiment, the target signal source and the target signal can both be custom-configured according to the needs of the actual application scenario. The first signal data and the second signal data are signal data obtained by different data acquisition devices capturing the same satellite signal sent by the same signal source. When different data acquisition channels receive the same satellite signal, due to the different environments, different environmental noises and thermal noises will be received, and thus signal data with different noises attached will be obtained.

[0080] In this embodiment, before obtaining the first signal data and the second signal data, the main control computer device needs to first control the first data acquisition device and the second data acquisition device to perform a time synchronization operation. When it is determined that both the first data acquisition device and the second data acquisition device are in a time synchronization state, then control the first data acquisition device and the second data acquisition device to synchronously collect signal data according to the preset acquisition parameters.

[0081] It should be noted that the time synchronization between the signals of the two data acquisition channels directly affects the performance and accuracy of the dual-channel high-sensitivity signal power estimation method. The digital acquisition board in this embodiment has the ability to measure high-precision time from satellite signals, and the error is in the unit of μs. For example, the error can be set within 5 μs. In this embodiment, the first data acquisition device and the second data acquisition device perform high-precision clock taming using the precise time signal provided by the satellite navigation system to achieve time synchronization. After time synchronization, the time synchronization status value in the reported information of the digital acquisition board is set to 1. After receiving the reported information sent by the digital acquisition board, the main control computer device can determine whether the first data acquisition device and the second data acquisition device are in a time synchronization state by identifying the time synchronization status value.

[0082] In this embodiment, the preset acquisition parameters include parameters such as sampling rate, sampling bandwidth, sampling bits, acquisition duration, and data storage method. The main control computer sets the acquisition parameters through the digital acquisition board control software to control the data acquisition device to perform signal acquisition.

[0083] S102. Determine the correlation peak detection result and the oversampling multiple according to the cross-correlation situation between the first signal data and the second signal data.

[0084] In this embodiment, by performing a cross-correlation operation on the first signal data and the second signal data, a metric that can reflect the similarity between the two signals collected by the two signal acquisition channels can be obtained, that is, the cross-correlation situation between the first signal data and the second signal data is obtained.

[0085] In this embodiment, by calculating the cross-correlation values of the first signal data and the second signal data at different time delays, the time point when the two signals are most similar can be found, and then the most similar signal data can be obtained.

[0086] In a specific embodiment, by performing peak detection on the cross-correlation values, the correlation peak detection result can be obtained. The correlation peak detection result is the point with the largest amplitude, and the amplitude of the point with the largest amplitude is much larger than the amplitudes of other points. Based on the correlation peak detection result, signals with extremely high similarity in the two signal paths can be obtained.

[0087] In this embodiment, according to the correlation peak detection result, oversampling analysis is performed, and the oversampling multiple can be calculated.

[0088] S103. Calculate the target signal power according to the correlation peak detection result and the oversampling multiple.

[0089] In this embodiment, the power estimation step can be to perform inverse calculation using the correlation peak and the oversampling multiple to obtain the target signal power.

[0090] In the specific application process, the calculation formula for the target signal power is as follows:

[0091]

[0092] Among them, is the target signal power, is the peak amplitude of the correlation peak detection result, is the oversampling multiple, is the signal sampling duration.

[0093] In summary, this embodiment provides a dual-channel high-sensitivity signal power estimation method. Satellite signals are collected by two sets of data acquisition devices respectively, and then correlation analysis is performed based on the two-way satellite signals collected by the two sets of data acquisition devices to obtain the peak value in the cross-correlation value. The oversampling multiple is analyzed based on the correlation peak detection result. Finally, the target signal power is calculated by inverse deduction using the correlation peak and the oversampling multiple. It can effectively collect and analyze weak signals in the electromagnetic environment, estimate the power of weak signals, calculate the distribution of the signal power of weak signals at each frequency point, and then achieve high-sensitivity spectrum monitoring, ensure the effective utilization of spectrum resources by GNSS, and effectively guarantee communication security and the security of the electromagnetic space.

[0094] According to a specific implementation manner of an embodiment of the present application, the first data acquisition device includes a first signal receiving antenna and a first digital acquisition board, and the second data acquisition device includes a second signal receiving antenna and a second digital acquisition board.

[0095] The step of controlling the first data acquisition device and the second data acquisition device to synchronously collect signal data according to preset acquisition parameters includes:

[0096] Control the first digital acquisition board to perform preset data processing on the satellite signal received by the first signal receiving antenna to obtain first signal data. Control the second digital acquisition board to perform preset data processing on the satellite signal received by the second signal receiving antenna to obtain second signal data, where the preset data processing includes filtering processing, amplification processing, mixing processing, and analog-to-digital conversion processing.

[0097] In this embodiment, both the first digital acquisition board and the second digital acquisition board include a pre-filter, a pre-amplifier, a mixer, and an analog-to-digital converter. Among them, the pre-filter, the pre-amplifier, the mixer, and the analog-to-digital converter are connected in sequence. The satellite signal received by the digital acquisition board is filtered by the pre-filter, amplified by the pre-amplifier, mixed by the mixer, and subjected to analog-to-digital conversion by the analog-to-digital converter to obtain the final intermediate-frequency digital signal for the main control computer device to perform power estimation.

[0098] According to a specific implementation manner of an embodiment of the present application, as Figure 2 shown, determining the correlation peak detection result and the oversampling multiple according to the cross-correlation situation between the first signal data and the second signal data includes:

[0099] S201, perform a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result.

[0100] S202, perform peak detection on the cross-correlation result to obtain the cross-correlation peak detection result, where the cross-correlation peak detection result includes peak amplitude and peak position.

[0101] S203, perform oversampling analysis based on the cross-correlation result and the cross-correlation peak detection result to obtain the oversampling multiple.

[0102] In this embodiment, by performing cross-correlation operation on the first signal data and the second signal data, the cross-correlation value of the first signal data and the second signal data, that is, the cross-correlation result, can be obtained. The cross-correlation result can be used to reflect the similarity between the signals collected by two channels.

[0103] In this embodiment, the peak detection method can be a traversal search method, and the cross-correlation peak detection result is obtained by traversing the cross-correlation result. Specifically, the peak detection simulation is as Figure 3 shown, where the abscissa sampling point represents the sampling point corresponding to the sampling moment , the ordinate amplitude is the data amplitude of the sampling point, the peak point (X1, Y5894.18) represents the sampling point with the largest amplitude, that is, the maximum peak point, the abscissa X1 of the peak point represents the peak position of the peak point, and the ordinate Y5894.18 of the peak point represents the peak amplitude of the peak point. Among them, the peak position reflects the mutual time delay between the two signals, and the mutual time delay can be calculated from the peak position and the signal sampling rate. The peak position and peak amplitude of the maximum peak point can be used to participate in subsequent calculations, such as calculating the relative time delay, threshold value, and target signal power of two data acquisition channels.

[0104] According to a specific implementation manner of the embodiment of the present application, as Figure 4 shown, performing cross-correlation operation on the first signal data and the second signal data to obtain the cross-correlation result includes:

[0105] S401, determine the length of the cross-correlation operation according to the signal sampling rate, and determine the length of the sliding traversal operation according to the signal sampling duration.

[0106] S402, perform cross-correlation operation on the first signal data and the second signal data according to the length of the cross-correlation operation and the length of the traversal operation to obtain the cross-correlation result.

[0107] In this embodiment, when the sampling rate is , the first signal data is and the second signal data is , is the sampling moment, . Then the cross-correlation operation formula for the two signals is:

[0108]

[0109] Among them, represents the length of the cross-correlation operation. Usually, data with a duration of 1 ms is used, that is, when the sampling rate is , the length of the cross-correlation operation , The larger it is, the higher the sensitivity of the cross-correlation operation; is the sampling duration, that is, the length of the sliding traversal operation.

[0110] According to a specific implementation manner of an embodiment of the present application, as Figure 5 shown, peak detection is performed on the cross-correlation result to obtain a correlation peak detection result, including:

[0111] S501, perform modulo operation on the cross-correlation result to obtain a correlation modulus value.

[0112] In this embodiment, the calculation formula for performing modulo operation on the cross-correlation result is:

[0113]

[0114] Among them, is the correlation modulus value, is the first signal data and the second signal data of the cross-correlation result.

[0115] S502, traverse the correlation modulus value and search to obtain the correlation peak detection result.

[0116] In this embodiment, peak measurement traverses and searches for the peak modulus value of the correlation peak, and records the peak position of the peak modulus value of the correlation peak. Let the peak position of the peak modulus value of the correlation peak be , the peak amplitude is , and the relative time delay of the two data acquisition channels can be calculated through the peak position .

[0117] In this embodiment, by calculating the relative time delay, the time point when the two signals are most similar can be calculated, greatly improving the accuracy of signal power estimation, and further improving the sensitivity of spectrum monitoring.

[0118] As Figure 6 shown, oversampling analysis is performed according to the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple, including:

[0119] S601, determine the threshold according to the peak amplitude and the preset coefficient.

[0120] S602, obtain the number of target modulus values according to the threshold and the correlation modulus value, where the target modulus value is the correlation modulus value greater than the threshold.

[0121] S603, Calculate the oversampling multiple based on the number of target modulus values.

[0122] In this embodiment, according to the measured relevant peak modulus values, set the oversampling calculation threshold value:

[0123]

[0124] Among them, is the threshold value, is the peak amplitude of the relevant peak modulus value, and the preset coefficient is a constant, which can be set to 0.3, or can be set to other values according to the needs of the actual application scenario.

[0125] In this embodiment, traverse the relevant modulus values , to search for the target modulus value. Specifically, count the number of target modulus values greater than the threshold value , and further calculate the oversampling multiple based on the following oversampling multiple calculation formula. The oversampling multiple calculation formula is:

[0126]

[0127] Among them, represents the oversampling multiple, represents rounding, is the number of target modulus values .

[0128] In summary, compared with the traditional power estimation method that can only intuitively estimate the power of the overall signal, this embodiment provides a dual-channel high-sensitivity signal power estimation method, which can estimate the power of weak signals submerged in environmental noise and can provide better spectrum monitoring effects.

[0129] Based on the same inventive concept, the embodiment of the present application also provides a dual-channel high-sensitivity signal power estimation device for implementing the above-mentioned dual-channel high-sensitivity signal power estimation method. The implementation solution provided by this device to solve the problem is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the following dual-channel high-sensitivity signal power estimation device can refer to the limitations on the dual-channel high-sensitivity signal power estimation method in the above text, and will not be repeated here.

[0130] In one embodiment, referring to Figure 7 , this embodiment also provides a dual-channel high-sensitivity signal power estimation device 700, including: an acquisition module 710, a determination module 720, and a calculation module 730, where:

[0131] An acquisition module 700 is configured to acquire first signal data and second signal data, where the first signal data is acquired by a first data acquisition device, and the second signal data is acquired by a second data acquisition device;

[0132] A determination module 710 is configured to determine a correlation peak detection result and an oversampling multiple according to the cross-correlation situation between the first signal data and the second signal data;

[0133] A calculation module 720 is configured to calculate a target signal power according to the correlation peak detection result and the oversampling multiple.

[0134] In one embodiment, the determination module 710 is specifically configured to perform a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result; perform peak detection on the cross-correlation result to obtain a correlation peak detection result, where the correlation peak detection result includes a peak amplitude and a peak position; perform oversampling analysis according to the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple.

[0135] In one embodiment, the determination module 710 is specifically configured to determine the length of the cross-correlation operation according to the signal sampling rate, and determine the length of the sliding traversal operation according to the signal sampling duration; perform a cross-correlation operation on the first signal data and the second signal data according to the length of the cross-correlation operation and the length of the traversal operation to obtain the cross-correlation result.

[0136] In one embodiment, the determination module 710 is specifically configured to perform a modulo operation on the cross-correlation result to obtain a correlation modulus value; traverse the correlation modulus value to search for the correlation peak detection result.

[0137] In one embodiment, the determination module 710 is specifically configured to determine a threshold according to the peak amplitude and a preset coefficient; obtain a target modulus value quantity according to the threshold and the correlation modulus value, where the target modulus value is a correlation modulus value greater than the threshold; calculate the oversampling multiple according to the target modulus value quantity.

[0138] In summary, this embodiment provides a dual-channel high-sensitivity signal power estimation device. The satellite signals are collected by two sets of data acquisition devices respectively, and then the correlation analysis is performed based on the two-way satellite signals collected by the two sets of data acquisition devices to obtain the peak value in the cross-correlation value. The oversampling ratio is analyzed based on the correlation peak detection result. Finally, the target signal power is calculated by inverse deduction using the correlation peak and the oversampling ratio. It can effectively collect and analyze weak signals in the electromagnetic environment, estimate the power of weak signals, calculate the distribution of the signal power of weak signals at each frequency point, and then achieve high-sensitivity spectrum monitoring, ensure the effective utilization of spectrum resources by GNSS, and effectively guarantee communication security and the security of the electromagnetic space.

[0139] Figure 7 The specific implementation manner of the device shown may refer to the specific implementation manner in the foregoing method embodiment and will not be elaborated herein.

[0140] In addition, this embodiment of the present application also provides an electronic device, which includes:

[0141] At least one processor; and,

[0142] A memory communicatively connected to the at least one processor; wherein,

[0143] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the dual-channel high-sensitivity signal power estimation method in the foregoing method embodiment.

[0144] In a more detailed embodiment, based on the dual-channel high-sensitivity signal power estimation method provided in the foregoing embodiment, simulation verification is performed in MATLAB software to prove that the dual-channel high-sensitivity signal power estimation method provided in this embodiment can effectively collect and analyze weak signals in the electromagnetic environment and estimate the power of weak signals.

[0145] The specific simulation verification process can be referred to Figures 8 - 21 As shown, in the figure, fft / Hz represents the frequency resolution, and snr represents the signal-to-noise ratio. The specific implementation process is as follows:

[0146] In Matlab, use the quadrature amplitude modulation functions (qammod() function and genqammod() function) to generate a modulated signal as the basic signal data modData. Then, generate two sets of noise signal data noise1 and noise2 through the random function (randn() function). At the same time, based on modData and introducing the signal-to-noise ratio snr and the relevant parameters of the noise, generate two sets of original signal data ModeData1 and ModeData2. And perform resampling (resample()) on the two sets of original signal data, where the resampling multiple is Msample, and the oversampled data are ModeData1t and ModeData2t.

[0147] At this time, the powers of noise1, noise2, ModeData1t, and ModeData2t are powOfNoise1, powOfNoise2, powOfModeData1t, and powOfModeData2t respectively. Then, combine ModeData1t and noise1, and combine ModeData2t and noise2 to obtain the first signal data rxSig1 and the second signal data rxSig2, to simulate the signal data collected by two synchronous acquisition devices (it is also possible to shift the two-channel data by several data points to simulate the slight synchronization deviation caused by environmental or equipment factors, which is not introduced here).

[0148] Then, set the relevant calculation length N to perform cross-correlation calculation to obtain data such as correlation peaks: correlation peak values peakVal , the number of correlation values exceeding the threshold ThrVal . Based on this, calculate the oversampling multiple Npeak . Then, further calculate the target signal power Nsample = ( Npeak + 1 ) / N , and further calculate the target signal power powMean = ([[]] peakVal * Nsample ) / N .

[0149] Perform simulation with the signal-to-noise ratio snr ranging from -20 (dB) to 15 (dB), and finally output the error:

[0150] res = 10 * log10( powMean ) - (powOfModeData1t + powOfModeData2t) / 2

[0151] Among them, the error res is the difference between the obtained target signal power ( powMean ) and the power of the analog signal (powOfModeData1t + powOfModeData2t).

[0152] In the case of introducing Nsample , the technical method of the target signal power is powMean = ( peakVal * Nsample ) / N . In the case of not introducing Nsample , the calculation method of the signal power is ( peakVal ) / N .

[0153] Through simulation, it can be seen that the frequency-domain diagrams of the signals at snr = -20 (dB), -15 (dB), and 15 (dB) after performing the fast Fourier transform fft. Among them, as Figure 9 , Figure 11 , Figure 18 and 19 show, when snr = -15 (dB) or -20 (dB), the weak signals in the first signal data rxSig1 and the second signal data rxSig2 have been submerged under the noise. And as Figure 13 and Figure 15 show, when snr = 15 (dB), weak signals can be seen from the frequency-domain amplitude in the first signal data rxSig1 and the second signal data rxSig2. As Figure 20 shows, when snr = -15 (dB), there are still relatively small correlation peaks appearing, indicating that weak signals can be detected. When snr = 15 (dB), the correlation peaks are extremely obvious, indicating that the stronger the signal, the larger the correlation peak value, and weak signals can be detected more clearly.

[0154] As Figure 16 and Figure 17 show, in the error result diagram, there is a certain gap between introducing the oversampling multiple Nsample and not introducing the oversampling multiple Nsample. However, it can be seen that in the case of a larger signal-to-noise ratio, the error basically tends to be stable, and at -15 (dB), the detection error has converged, which can verify the effectiveness of the method proposed in this embodiment.

[0155] For easy understanding, reference can be made to Figure 18 , Figure 19 , Figure 20 and Figure 21 . In the frequency-domain simulation diagram of the signal data collected by a single data acquisition device, weak signals cannot be seen, and the weak signals have been masked by the environmental noise and thermal noise in the satellite signal. By using the dual-channel high-sensitivity signal power estimation method provided in this embodiment for signal detection, the correlation peak value of the weak signal can be significantly calculated to further perform the subsequent power estimation steps.

[0156] The embodiments of the present application also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the dual-channel high-sensitivity signal power estimation method in the foregoing method embodiments.

[0157] The electronic devices in the embodiments of the present application may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.

[0158] It should be noted that the computer-readable medium in the present application may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may, for example, but is not limited to, be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0159] In the present application, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0160] The above computer-readable medium may be included in the above electronic device; or it may exist separately without being assembled into the electronic device.

[0161] The above computer-readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: obtain first signal data and second signal data, wherein the first signal data is collected by a first data collection device and the second signal data is collected by a second data collection device; determine a correlation peak detection result and an oversampling multiple according to the cross-correlation situation between the first signal data and the second signal data; and calculate a target signal power according to the correlation peak detection result and the oversampling multiple.

[0162] Computer program code for performing the operations of this application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partially on the user's computer, execute as a stand-alone software package, execute partially on the user's computer and partially on a remote computer, or execute entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by connecting through the Internet using an Internet service provider).

[0163] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0164] The units involved in the embodiments described in this application may be implemented in software or in hardware. Among them, the name of the unit does not constitute a limitation on the unit itself in some cases. For example, the first acquisition unit may also be described as "the unit for acquiring at least two Internet protocol addresses".

[0165] It should be understood that each part of the present application can be implemented by hardware, software, firmware, or a combination thereof.

[0166] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A dual-channel high-sensitivity signal power estimation method, characterized in that: include: Acquire first signal data and second signal data, wherein the first signal data is acquired by a first data acquisition device, and the second signal data is acquired by a second data acquisition device, the first signal data and the second signal data are signal data with different noises generated by a target signal emitted by a target signal source acquired by different data acquisition devices, the first data acquisition device and the second data acquisition device are different data acquisition devices, and both the first data acquisition device and the second data acquisition device include a digital acquisition board and a signal receiving antenna; Determine a correlation peak detection result and an oversampling multiple according to the mutual correlation between the first signal data and the second signal data; Calculate the target signal power according to the correlation peak detection result and the oversampling multiple; The determining of the correlation peak detection result and the oversampling multiple according to the mutual correlation between the first signal data and the second signal data comprises: Performing a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result; Performing peak detection on the cross-correlation result to obtain a correlation peak detection result, wherein the correlation peak detection result includes a peak amplitude and a peak position; Performing oversampling analysis according to the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple; The calculating the target signal power according to the correlation peak detection result and the oversampling multiple includes: in, is the target signal power, is the peak amplitude of the correlation peak detection result, is the oversampling factor, is the signal sampling duration.

2. The method according to claim 1, characterized in that The performing a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result includes: The length of the cross-correlation operation is determined according to the signal sampling rate, and the length of the sliding traversal operation is determined according to the signal sampling duration; A cross-correlation operation is performed on the first signal data and the second signal data according to the length of the cross-correlation operation and the length of the traversal operation to obtain the cross-correlation result.

3. The method according to claim 1, characterized in that The performing peak detection on the cross-correlation result to obtain a correlation peak detection result includes: Performing modulus processing on the cross-correlation result to obtain a correlation modulus value; Traversing the correlation modulus values, searching for the correlation peak detection result; The performing oversampling analysis according to the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple includes: Determine a threshold value according to the peak amplitude and a preset coefficient; According to the threshold value and the related modulus value, obtaining a target modulus value quantity, wherein the target modulus value is a related modulus value greater than the threshold value; The oversampling multiple is calculated according to the target module value quantity.

4. The method according to claim 1, characterized in that: Before acquiring the first signal data and the second signal data, the method includes: Controlling the first data acquisition device and the second data acquisition device to perform time synchronization; When it is determined that the first data acquisition device and the second data acquisition device are both in a time synchronization state, the first data acquisition device and the second data acquisition device are controlled to synchronously acquire signal data according to preset acquisition parameters.

5. The method according to claim 4, characterized in that The first data acquisition device includes a first signal receiving antenna and a first digital acquisition board, and the second data acquisition device includes a second signal receiving antenna and a second digital acquisition board; The controlling the first data acquisition device and the second data acquisition device to synchronously acquire signal data according to preset acquisition parameters comprises: Controlling the first digital acquisition board to perform preset data processing on the satellite signal received by the first signal receiving antenna to obtain the first signal data; The second digital acquisition board is controlled to perform preset data processing on the satellite signal received by the second signal receiving antenna to obtain the second signal data, wherein the preset data processing includes filtering processing, amplification processing, mixing processing and analog-to-digital conversion processing.

6. A dual-channel high-sensitivity signal power estimation device, characterized in that: include: An acquisition module, used for acquiring first signal data and second signal data, wherein the first signal data is acquired by a first data acquisition device, and the second signal data is acquired by a second data acquisition device, and the first signal data and the second signal data are signal data with different noises generated by a target signal emitted by a target signal source acquired by different data acquisition devices, and the first data acquisition device and the second data acquisition device are different data acquisition devices, and both the first data acquisition device and the second data acquisition device include a digital acquisition board and a signal receiving antenna; A determination module, configured to determine a correlation peak detection result and an oversampling multiple according to a mutual correlation between the first signal data and the second signal data; A calculation module, used for calculating the target signal power according to the correlation peak detection result and the oversampling multiple; a determination module, specifically configured to perform a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result; perform peak detection on the cross-correlation result to obtain a correlation peak detection result, wherein the correlation peak detection result includes a peak amplitude and a peak position; perform oversampling analysis based on the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple; The calculating the target signal power according to the correlation peak detection result and the oversampling multiple includes: in, is the target signal power, is the peak amplitude of the correlation peak detection result, is the oversampling factor, is the signal sampling duration.

7. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the dual-channel high-sensitivity signal power estimation method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the dual-channel high-sensitivity signal power estimation method described in any one of claims 1 to 5.

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