Dual-channel high-sensitivity signal power estimation method and device and storage medium

Abstract

The invention provides a dual-channel high-sensitivity signal power estimation method and device and a storage medium, and the method comprises the steps: obtaining first signal data and second signal data, the first signal data being collected through a first data collection device, and the second signal data being collected through a second data collection device; determining a correlation peak detection result and an oversampling multiple according to the cross-correlation condition of the first signal data and the second signal data; and calculating target signal power according to the correlation peak detection result and the oversampling multiple. The signal data is acquired through the two data acquisition channels, and power estimation is performed according to the signal data of the different data acquisition channels, so that the power of the weak signal hidden in the environmental noise can be estimated, and a better frequency spectrum monitoring effect is provided.

Description

Technical Field

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

[0002] Faced with an increasingly complex electromagnetic environment, spectrum monitoring technology is widely used in the Global Navigation Satellite System (GNSS). However, traditional spectrum monitoring methods cannot effectively monitor weak signals that are drowned by noise. Missed detection and false alarms of weak signals will affect the utilization efficiency of spectrum resources, thereby limiting the application and development of wireless communication technology. Summary of the invention

[0003] In order to solve the above technical problems, the embodiments of the present application provide a dual-channel high-sensitivity signal power estimation method, device, equipment 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 scheme is as follows: In a first aspect, an embodiment of the present application provides a dual-channel high-sensitivity signal power estimation method, comprising: 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; The target signal power is calculated according to the correlation peak detection result and the oversampling multiple.

[0004] According to a specific implementation of the embodiment of the present application, determining the correlation peak detection result and the oversampling multiple according to the mutual correlation between the first signal data and the second signal data includes: 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; An oversampling analysis is performed according to the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple.

[0005] According to a specific implementation of the embodiment of the present application, 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.

[0006] According to a specific implementation of the embodiment of the present application, 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.

[0007] According to a specific implementation of the embodiment of the present application, 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.

[0008] According to a specific implementation of the embodiment of the present application, 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.

[0009] According to a specific implementation of the 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; 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.

[0010] In a second aspect, an embodiment of the present application provides a dual-channel high-sensitivity signal power estimation device, comprising: 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 is used to calculate the target signal power according to the correlation peak detection result and the oversampling multiple.

[0011] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the dual-channel high-sensitivity signal power estimation method described in the first aspect.

[0012] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium, which 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 the first aspect above.

[0013] 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 based on the cross-correlation of the first signal data and the second signal data; and calculating the target signal power based on the correlation peak detection result and the oversampling multiple. This application obtains signal data through two data acquisition channels, and performs power estimation based on signal data from different data acquisition channels, so as to estimate the power of weak signals hidden in environmental noise and provide better spectrum monitoring effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] 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 described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 A schematic diagram of a flow chart of a dual-channel high-sensitivity signal power estimation method provided in an embodiment of the present application; Figure 2 A schematic diagram of a process flow for determining a correlation peak detection result and an oversampling multiple provided in an embodiment of the present application; Figure 3 A simulation schematic diagram of peak detection provided in an embodiment of the present application; Figure 4 A schematic diagram of the steps for calculating the cross-correlation results provided in an embodiment of the present application; Figure 5 A schematic diagram of a process flow for searching for correlation peak detection results provided in an embodiment of the present application; Figure 6 A schematic diagram of the steps of analyzing the oversampling multiple provided in an embodiment of the present application; Figure 7 A schematic diagram of a device module of a dual-channel high-sensitivity signal power estimation device provided in an embodiment of the present application; Figure 8It is a frequency domain simulation diagram after fast Fourier transform (fft) of the first original signal data (ModeData1) when the signal-to-noise ratio (snr) is -20 decibels (db); Fig. 9 This is a frequency domain simulation diagram of the first signal data (rxSig1) after fast Fourier transform (fft) when the signal-to-noise ratio snr is -20 (db); Fig.10 This is a frequency domain simulation diagram of the second original signal data (ModeData2) after fast Fourier transform (fft) when the signal-to-noise ratio snr is -20 (db); Fig.11 This is a frequency domain simulation diagram of the second signal data (rxSig2) after fast Fourier transform (fft) when the signal-to-noise ratio snr is -20 (db); Fig.12 This is a frequency domain simulation diagram of the first original signal data (ModeData1) after fast Fourier transform (fft) when the signal-to-noise ratio (snr) is 15 (db); Fig.13 This is a frequency domain simulation diagram of the first signal data (rxSig1) after fast Fourier transform (fft) when the signal-to-noise ratio SNR is 15 (db); Fig.14 This is a frequency domain simulation diagram of the second original signal data (ModeData2) after fast Fourier transform (fft) when the signal-to-noise ratio (snr) is 15 (db); Fig.15 This is a frequency domain simulation diagram of the second signal data (rxSig2) after fast Fourier transform (fft) when the signal-to-noise ratio SNR is 15 (db); Fig.16 The signal-to-noise ratio (snr) simulation diagram for the error introduced by the oversampling multiple (Nsample); Fig.17 This is a simulation diagram of the signal-to-noise ratio (snr) without introducing errors due to the oversampling multiple (Nsample); Fig.18 This is a frequency domain simulation diagram of the first signal data (rxSig1) after fast Fourier transform (fft) when the signal-to-noise ratio SNR is -15 (db); Fig.19 This is a frequency domain simulation diagram of the second signal data (rxSig2) after fast Fourier transform (fft) when the signal-to-noise ratio snr is -15 (db); Fig. 20 This is a simulation diagram of the cross-correlation result after the cross-correlation operation is performed on the first signal data (rxSig1) and the second signal data (rxSig2) when the signal-to-noise ratio snr is -15 (db); Fig.21 This is a simulation diagram of the cross-correlation result after the first signal data (rxSig1) and the second signal data (rxSig2) are cross-correlated when the signal-to-noise ratio SNR is 15 (db). DETAILED DESCRIPTION

[0016] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0017] The following describes the implementation methods of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents 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 methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the absence of conflict, the following embodiments and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present application.

[0018] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. 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 merely illustrative. Based on the present application, it should be understood by those skilled in the art that an 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 aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0019] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. The drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0020] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0021] In related technologies, spectrum monitoring is mainly used to monitor and analyze electromagnetic waves within a specific frequency range in real time to determine the use and distribution of frequencies. In the fields of wireless communications, television broadcasting, aviation navigation, radar, etc., spectrum, as a limited resource, needs to be reasonably planned and allocated to different communication systems. Spectrum monitoring helps to plan, manage, optimize and share spectrum resources.

[0022] For the Global Navigation Satellite System (GNSS), the development of a highly sensitive spectrum monitoring system can support GNSS's real-time monitoring and analysis of complex and changeable electromagnetic environments, thereby ensuring the effective management and optimal use of spectrum resources, and safeguarding communication security and the security of electromagnetic space. In actual application scenarios, the navigation signal sent by GNSS has greatly attenuated its signal strength after traveling over extremely long distances, and is easily interfered by other signals. Therefore, even weak interference signals can affect the performance of GNSS. In addition, the complex and changeable electromagnetic environment in space can also affect the performance of GNSS.

[0023] Power estimation, especially power spectrum estimation, is an important part of signal processing. The power spectrum describes the distribution of signal power at each frequency point. The power of the signal can be obtained by integrating the power spectrum in the frequency domain. In practical applications, such as spectrum monitoring, it may be necessary to use power spectrum estimation technology to analyze the power distribution of the signal. However, the existing signal power estimation system is 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 will not be able to achieve high-sensitivity spectrum monitoring.

[0024] 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 equipment and a main control computer device. Among them, the data acquisition equipment includes a digital acquisition board and a signal receiving antenna.

[0025] 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.

[0026] The digital acquisition board includes a prefilter, a preamplifier, a mixer and an analog-to-digital converter. In actual applications, the digital acquisition board receives all visible signals through the signal receiving antenna, filters and amplifies the signals through the prefilter and preamplifier, and then down-converts the signals into intermediate frequency signals through the mixer, and finally converts the intermediate frequency signals into discrete-time digital intermediate frequency signals through the analog-to-digital converter.

[0027] The main control computer device includes control software of the digital acquisition board, and the main control computer is connected to the digital acquisition board for controlling the digital acquisition board to perform corresponding signal acquisition operations through preset control instructions. The digital acquisition board transmits the converted digital intermediate frequency signal to the main control computer device, so that the main control computer device can further execute the signal power estimation method.

[0028] refer to Figure 1 The present application embodiment provides a dual-channel high-sensitivity signal power estimation method, which is described by taking the method applied to the main control computer device in the above embodiment as an example, including the following steps: S101, 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, 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 collected 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.

[0029] In this embodiment, the first data acquisition device and the second data acquisition device are two different sets of data acquisition devices, and the first data acquisition device and the second data acquisition device constitute two different data acquisition channels of the power estimation system.

[0030] The first signal data and the second signal data are respectively obtained through two different data acquisition channels, and then 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, thereby effectively improving the sensitivity of signal monitoring. In this embodiment, both the target signal source and the target signal can be customized 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 receiving the same satellite signal, different data acquisition channels will receive different environmental noise and thermal noise due to the different environments in which they are located, and then obtain signal data with different noises.

[0031] In this embodiment, before acquiring 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 time synchronization operations. 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.

[0032] 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. The error is in units of us. For example, the error can be set in Within 5us. In this embodiment, the first data acquisition device and the second data acquisition device use the precise time signal provided by the satellite navigation system to perform high-precision clock training, thereby achieving time synchronization. After time synchronization, the time synchronization state value in the information reported by the digital acquisition board is set to 1. After receiving the reporting 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 the time synchronization state by identifying the time synchronization state value.

[0033] In this embodiment, the preset acquisition parameters include sampling rate, sampling bandwidth, sampling bit number, acquisition time and data storage mode, etc. 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.

[0034] S102, determining a correlation peak detection result and an oversampling multiple according to the mutual correlation between the first signal data and the second signal data.

[0035] 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 collection channels can be obtained, that is, the cross-correlation between the first signal data and the second signal data can be obtained.

[0036] In this embodiment, by calculating the cross-correlation values ​​of the first signal data and the second signal data at different time delays, the most similar time points of the two signals can be found, and then the most similar signal data can be obtained.

[0037] In a specific embodiment, by performing peak detection on the cross-correlation value, a correlation peak detection result can be obtained. The correlation peak detection result is the maximum amplitude point, and the amplitude of the maximum amplitude point is much larger than the amplitude of other points. Based on the correlation peak detection, a signal with extremely high similarity in two signals can be obtained.

[0038] In this embodiment, an oversampling analysis is performed based on the correlation peak detection result, and the oversampling multiple can be calculated.

[0039] S103, calculating the target signal power according to the correlation peak detection result and the oversampling multiple.

[0040] In this embodiment, the power estimation step may be to perform a reverse calculation using the correlation peak value and the oversampling multiple to obtain the target signal power.

[0041] In the specific application process, the calculation formula of the target signal power is as follows: 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.

[0042] In summary, this embodiment provides a dual-channel high-sensitivity signal power estimation method, which collects satellite signals respectively through two sets of data acquisition equipment, and then performs correlation analysis based on the two satellite signals collected by the two sets of data acquisition equipment to obtain the peak value in the cross-correlation value, and obtains the oversampling multiple based on the analysis of the correlation peak detection result. Finally, the correlation peak value and the oversampling multiple are used to perform reverse calculation to obtain the target signal power. It can realize the effective collection and analysis of weak signals in the electromagnetic environment, perform power estimation on weak signals, and calculate the distribution of the signal power of weak signals at each frequency point, thereby realizing high-sensitivity spectrum monitoring, which can ensure the effective use of spectrum resources by GNSS and effectively protect the communication security and the security of electromagnetic space.

[0043] According to a specific implementation of the 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.

[0044] The step of controlling the first data acquisition device and the second data acquisition device to synchronously acquire signal data according to preset acquisition parameters includes: The first digital acquisition board is controlled to perform preset data processing on the satellite signal received by the first signal receiving antenna to obtain 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 second signal data, wherein the preset data processing includes filtering processing, amplification processing, mixing processing and analog-to-digital conversion processing.

[0045] In this embodiment, the first digital acquisition board and the second digital acquisition board both include a prefilter, a preamplifier, a mixer and an analog-to-digital converter. The prefilter, the preamplifier, 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 prefilter, amplified by the preamplifier, mixed by the mixer, and converted by the analog-to-digital converter to obtain the final intermediate frequency digital signal for the main control computer device to perform power estimation.

[0046] According to a specific implementation of the embodiment of the present application, Figure 2As shown, according to the mutual correlation of the first signal data and the second signal data, determining the correlation peak detection result and the oversampling multiple includes: S201, performing a cross-correlation operation on the first signal data and the second signal data to obtain a cross-correlation result.

[0047] S202, 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.

[0048] S203, performing oversampling analysis according to the cross-correlation result and the correlation peak detection result to obtain an oversampling multiple.

[0049] In this embodiment, a cross-correlation operation is performed on the first signal data and the second signal data to obtain a cross-correlation value of the first signal data and the second signal data, that is, a cross-correlation result. The cross-correlation result can be used to reflect the similarity between the signals collected by the two channels.

[0050] In this embodiment, the peak detection method may be a traversal search method, which searches for correlation peak detection results by traversing the cross-correlation results. Specifically, the peak detection simulation is as follows: Figure 3 As shown, the horizontal axis sampling point Indicates the corresponding sampling time The sampling point of the ordinate 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 delay between the two signals, and the mutual delay can be calculated by 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 delay, threshold value and target signal power of the two data acquisition channels.

[0051] According to a specific implementation of the embodiment of the present application, Figure 4 As shown, a cross-correlation operation is performed on the first signal data and the second signal data to obtain a cross-correlation result, including: S401, determining the length of the cross-correlation operation according to the signal sampling rate, and determining the length of the sliding traversal operation according to the signal sampling duration.

[0052] S402, performing 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 a cross-correlation result.

[0053] In this embodiment, the sampling rate is assumed to be When the first signal data is and the second signal data is , is the sampling time, . Then the cross-correlation calculation formula of the two signals is: in, Indicates the length of the cross-correlation operation, usually 1ms long data is used for the operation, that is, the sampling rate is When the cross-correlation operation length , The larger the value, the higher the sensitivity of the cross-correlation operation; is the sampling duration, that is, the length of the sliding traversal operation.

[0054] According to a specific implementation of the embodiment of the present application, Figure 5 As shown, peak detection is performed on the cross-correlation result to obtain a correlation peak detection result, including: S501, performing modulus processing on the cross-correlation result to obtain a correlation modulus value.

[0055] In this embodiment, the calculation formula for performing modulo processing on the cross-correlation result is: in, is the relevant modulus value, The first signal data and the second signal data The cross-correlation results.

[0056] S502, traverse the relevant modulus values, and search to obtain the relevant peak detection result.

[0057] In this embodiment, the peak measurement traverses and searches for the relevant peak modulus value, and records the peak position of the relevant peak modulus value. The peak position of the relevant peak modulus value is set to , the peak amplitude is , through the peak position The relative delay of the two data acquisition channels can be calculated .

[0058] In this embodiment, by calculating the relative time delay, the time points at which two signals are most similar can be calculated, which greatly improves the accuracy of signal power estimation and further improves the sensitivity of spectrum monitoring.

[0059] like Figure 6 As shown, oversampling analysis is performed based on the cross-correlation results and the correlation peak detection results to obtain oversampling multiples, including: S601, determining a threshold value according to a peak amplitude and a preset coefficient.

[0060] S602, obtaining a target modulus value quantity according to the threshold value and the related modulus value, wherein the target modulus value is a related modulus value greater than the threshold value.

[0061] S603, calculating an oversampling multiple according to the target module value quantity.

[0062] In this embodiment, the oversampling calculation threshold is set according to the measured correlation peak modulus value: in, is the threshold value, is the peak amplitude of the relevant peak modulus value. The preset coefficient is a constant and can be set to 0.3 or other values ​​according to the needs of the actual application scenario.

[0063] In this embodiment, the relevant module values ​​are traversed , to search for the target modulus value. Specifically, the statistics are greater than the threshold value The target modulus value , and further calculate the oversampling multiple based on the following oversampling multiple calculation formula. The oversampling multiple calculation formula is: in, Indicates the oversampling multiple, Indicates rounding. The target modulus value .

[0064] 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 provide better spectrum monitoring effects.

[0065] 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 dual-channel high-sensitivity signal power estimation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more dual-channel high-sensitivity signal power estimation device embodiments provided below can refer to the limitations of the dual-channel high-sensitivity signal power estimation method above, and will not be repeated here.

[0066] In one embodiment, reference 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, wherein: An acquisition module 700 is used to 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; A determination module 710, 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; The calculation module 720 is used to calculate the target signal power according to the correlation peak detection result and the oversampling multiple.

[0067] In one embodiment, the determination module 710 is specifically used 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 an oversampling analysis based on the cross-correlation result and the correlation peak detection result to obtain the oversampling multiple.

[0068] In one embodiment, the determination module 710 is specifically used 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.

[0069] In one embodiment, the determination module 710 is specifically used to perform modulus processing on the cross-correlation result to obtain a correlation modulus value; and traverse the correlation modulus value to search for the correlation peak detection result.

[0070] In one embodiment, the determination module 710 is specifically used to determine the threshold value based on the peak amplitude and the preset coefficient; obtain the target module value quantity based on the threshold value and the related module value, wherein the target module value is a related module value greater than the threshold value; and calculate the oversampling multiple based on the target module value quantity.

[0071] In summary, this embodiment provides a dual-channel high-sensitivity signal power estimation device, which collects satellite signals respectively through two sets of data acquisition equipment, and then performs correlation analysis based on the two satellite signals collected by the two sets of data acquisition equipment to obtain the peak value in the cross-correlation value, and obtains the oversampling multiple based on the analysis of the correlation peak detection result. Finally, the correlation peak value and the oversampling multiple are used to perform reverse calculation to obtain the target signal power. It can realize the effective collection and analysis of weak signals in the electromagnetic environment, perform power estimation on weak signals, and calculate the distribution of the signal power of weak signals at each frequency point, thereby realizing high-sensitivity spectrum monitoring, which can ensure the effective use of spectrum resources by GNSS and effectively protect the communication security and the security of electromagnetic space.

[0072] Figure 7 The specific implementation of the device shown can refer to the specific implementation of the aforementioned method embodiment, which will not be repeated here.

[0073] In addition, an embodiment of the present application further provides an electronic device, the electronic device comprising: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the dual-channel high-sensitivity signal power estimation method in the aforementioned method embodiment.

[0074] In a more detailed embodiment, a simulation verification is performed in MATLAB software based on the dual-channel high-sensitivity signal power estimation method provided in the above embodiment to prove that the dual-channel high-sensitivity signal power estimation method provided in this embodiment can realize the effective collection and analysis of weak signals in the electromagnetic environment and perform power estimation on weak signals.

[0075] For the specific simulation verification process, please refer to Figure 8-Figure 21 As shown in the figure, fft / Hz represents frequency resolution and snr represents signal-to-noise ratio. The specific implementation process is as follows: In matlab, the orthogonal amplitude modulation function (qammod() function and genqammod() function) is used to generate the modulated signal as the basic signal data modData. Then, two sets of noise signal data noise1 and noise2 are generated through the random function (randn() function). At the same time, based on modData and introducing the signal-to-noise ratio snr and noise-related parameters, two sets of original signal data ModeData1 and ModeData2 are generated. The two sets of original signal data are resampled resample(), where the resampling multiple is Msample, and the oversampled data are ModeData1t and ModeData2t.

[0076] At this time, the powers of noise1, noise2, ModeData1t, and ModeData2t are powOfNoise1, powOfNoise2, powOfModeData1t, and powOfModeData2t, respectively. Then ModeData1t is recorded with noise1, and ModeData2t is recorded with 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 (the two data channels can also be moved by a few data points to simulate the slight synchronization deviation caused by environmental or equipment factors, which is not introduced here).

[0077] Then set the correlation calculation length N to perform cross-correlation calculation and obtain the correlation peak data: Correlation peak peakVal , exceeds the threshold ThrVal The relevant value points Npeak . This is how to calculate the oversampling factor Nsample= ( Npeak+1 ) / N , and further find the target signal power powMean =( peakVal*Nsample ) / N .

[0078] The signal-to-noise ratio SNR is changed from -20 (db) to 15 (db) for simulation, and the final output error is: res=10*log10( powMean )-( powOfModeData1t+ powOfModeData2t) / 2 Among them, the error res is the target signal power obtained ( powMean ) and the power of the analog signal (powOfModeData1t + powOfModeData2t).

[0079] In introducing NsampleIn the case of , the technical method of target signal power is powMean =( peakVal* Nsample ) / N , without introducing Nsample In the case of, the signal power is calculated as ( peakVal ) / N .

[0080] Through simulation, we can see the frequency domain diagrams of each signal after fast Fourier transform (FFT) at snr=-20 (db), -15 (db), and 15 (db). Fig. 9 , Fig.11 , Fig.18 and 19 As shown in FIG. 1 , when snr = -15 (db) or -20 (db), the weak signals in the first signal data rxSig1 and the second signal data rxSig2 are submerged in the noise. Fig.13 and Fig.15 As shown, when snr=15 (db), it can be seen from the frequency domain amplitude that there are weak signals in the first signal data rxSig1 and the second signal data rxSig2. Fig. 20 As shown, when snr=-15 (db), there is still a small correlation peak, which shows that weak signals can be detected. When snr=15 (db), the correlation peak is extremely obvious. It can be seen that the stronger the signal, the larger the correlation peak, and the weaker signal can be detected more obviously.

[0081] like Fig.16 and Fig.17 As shown 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 the error is basically stable when the signal-to-noise ratio is larger, and the detection error has converged at -15 (db), which can verify the effectiveness of the method proposed in this embodiment.

[0082] For easier understanding, please refer to Fig.18 , Fig.19 , Fig. 20 as well as Fig.21 In the frequency domain simulation diagram of the signal data collected by a single data acquisition device, the weak signal cannot be seen, and the weak signal has been covered by the environmental noise and thermal noise in the satellite signal. However, by using the dual-channel high-sensitivity signal power estimation method provided by this embodiment to perform signal detection, the correlation peak value of the weak signal can be clearly calculated to further perform the subsequent power estimation step.

[0083] An embodiment of the present application also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the dual-channel high-sensitivity signal power estimation method in the aforementioned method embodiment.

[0084] 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-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.

[0085] It should be noted that the computer-readable medium mentioned above in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media 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.

[0086] In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0087] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0088] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: obtains 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; determines a correlation peak detection result and an oversampling multiple based on the mutual correlation between the first signal data and the second signal data; and calculates the target signal power based on the correlation peak detection result and the oversampling multiple.

[0089] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0090] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0091] The units involved in the embodiments described in the present application may be implemented by software or hardware. The name of the unit does not limit the unit itself in some cases. For example, the first acquisition unit may also be described as a "unit for acquiring at least two Internet Protocol addresses".

[0092] It should be understood that various parts of the present application can be implemented by hardware, software, firmware or a combination thereof.

[0093] The above is only a specific implementation 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 a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on 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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