Real-time control and acquisition management system for pulse electromagnetic signal detection device

Abstract

The invention discloses a real-time control and acquisition management system for a pulse electromagnetic signal detection device, which relates to the technical field of electromagnetic signal detection and comprises a signal acquisition module, a time-frequency domain combined processing module, a real-time control module and a data storage and management module, according to the method, time domain and frequency domain characteristics of pulse electromagnetic signals can be accurately analyzed in real time through dynamic signal processing based on time domain and frequency domain combination, transient changes of the signals can be accurately captured by the system through self-adaptive adjustment of the time-frequency resolution, reflected signals of a target can be more accurately detected, and the accuracy of the target is improved. Target misjudgment or missed judgment caused by inaccurate signal detection is reduced, the detection precision and reliability of a radar system are greatly improved, useful signals and interference signals can be effectively distinguished for communication signal detection in a complex electromagnetic environment, the communication stability and the data transmission accuracy are ensured, and the detection accuracy is improved. And a powerful guarantee is provided for communication quality.

Description

Technical Field

[0001] The present invention relates to the technical field of electromagnetic signal detection, and in particular to a real-time control and acquisition management system for a pulse electromagnetic signal detection device. Background Art

[0002] In today's era of rapid technological development, electromagnetic signal detection technology plays a vital role in many fields, such as radar detection, communication systems, electronic countermeasures, and electromagnetic detection in biomedicine. With the continuous progress of these fields, higher and higher requirements are placed on the accuracy, speed and reliability of pulse electromagnetic signal detection.

[0003] Traditional pulse electromagnetic signal detection methods usually perform time domain and frequency domain analysis separately, which has obvious limitations when facing complex electromagnetic environments and diverse pulse signals. In time domain analysis, fixed sampling rates and resolutions are difficult to adapt to rapid signal changes and weak feature capture; in frequency domain analysis, static spectrum analysis methods cannot track the dynamic changes of signal frequency components in a timely manner, and when the signal is partially missing or interfered with, traditional technologies lack effective reconstruction methods, resulting in signal loss or misjudgment, which seriously affects the accuracy and integrity of detection and cannot meet the needs of modern applications for high-precision, high-reliability pulse electromagnetic signal detection.

[0004] In summary, traditional pulse electromagnetic signal detection methods show obvious shortcomings when facing complex electromagnetic environments and rapidly changing signal characteristics. Therefore, the development of a new type of pulse electromagnetic signal detection device that can realize dynamic signal capture and reconstruction in the time and frequency domains is of great significance for improving the accuracy of signal detection and system stability. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and to provide a real-time control and acquisition management system for a pulse electromagnetic signal detection device, which can simultaneously perform real-time analysis on the time domain and frequency domain characteristics of the pulse electromagnetic signal during the detection process, accurately capture the transient changes of the signal by adaptively adjusting the time and frequency resolution, and reconstruct the original signal with high fidelity by using the redundant information in the time and frequency domains when the signal is partially missing or interfered with, thereby improving the detection and restoration capabilities of complex modulated pulse signals and signals in multipath fading environments.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a real-time control and acquisition management system for a pulse electromagnetic signal detection device, the components of which include: a signal acquisition module, a time-frequency domain joint processing module, a real-time control module, and a data storage and management module;

[0007] The signal acquisition module uses a pulse electromagnetic signal detection device to detect the initial sampling rate fs , continuously collect pulse electromagnetic signals, convert the collected pulse electromagnetic signals into digital signals, and transmit them to the time-frequency domain joint processing module in real time;

[0008] The time-frequency domain joint processing module is used to perform dynamic signal processing on the digital signal in the time domain and frequency domain to analyze the signal;

[0009] The signal is framed and FFT and STFT transforms are applied to each frame length N to obtain the time-frequency domain representation of the signal. At the same time, the characteristic parameters of the signal energy distribution E(n), time domain change rate Δt(n) and frequency domain change rate Δf(n) are monitored in real time. According to the changes of the characteristic parameters, the time-frequency resolution is adaptively adjusted, that is, the time-frequency resolution adjustment formula is: Among them, k1 and k2 are adjustment constants and 0 <k1,k2<2,E th and Δf th are the thresholds of energy distribution and frequency domain change rate, respectively;

[0010] The real-time control module dynamically adjusts the sampling rate of the signal acquisition module and the characteristic parameters of the time-frequency domain joint processing module according to the feedback information of the time-frequency domain joint processing module. At the same time, the real-time control module is also responsible for communicating with external devices to realize data transmission and interaction;

[0011] The data storage and management module is used to store and manage the collected signal data and processed feature information.

[0012] Furthermore, the pulse electromagnetic signal detection device in the signal acquisition module includes a sensor array, and the layout of the sensor array is as follows:

[0013] The detection area is divided into a three-dimensional space of I×J×K cubic units. At the center of each cubic unit, the number and position distribution of sensors are based on the objective function Optimize, where s ijk is the signal strength actually collected at the (i,j,k) cube unit position, is the ideal signal strength at the location predicted by the pulse electromagnetic signal detection device;

[0014] At the same time, considering the signal attenuation factor α, reflection coefficient β and scattering coefficient γ, for the signal propagation path from the emission source to the (i, j, k) cube unit, its ideal signal strength is Among them, s0 is the signal strength of the transmitting source, d ijk is the distance from the source to the cube unit, R ijk is the number of reflections on the path, S ijkis the scattered signal intensity. By continuously adjusting the position and number of sensors, the objective function value is minimized, thereby determining the optimal layout of the sensor array for signal acquisition.

[0015] Furthermore, the frame processing process in the time-frequency domain joint processing module is as follows: Let the total length of the signal be L. First, according to the initial sampling rate f s and the frame overlap rate r, where 0 < r < 1, calculate the number of effective data points N eff for each frame as: where denotes rounding down. Starting from the beginning of the signal, sequentially intercept data segments of length N as one frame. The adjacent frames overlap by N - N eff data points. For each intercepted frame, number it and perform FFT, STFT transforms, and calculations of the energy distribution E(n) and the frequency change rate Δf(n) on the signal of this frame.

[0016] Furthermore, the energy distribution E(n) in the time-frequency domain joint processing module is: where x n (i) is the data of the i-th sampling point in the n-th frame signal.

[0017] Furthermore, when calculating the frequency change rate Δf(n) in the time-frequency domain joint processing module, first perform a frequency domain transform on the n-th frame signal, that is, the time signal x[n], n = 0, 1, …, N - 1. After the frequency domain transform, it becomes where k = 0, 1, …, N - 1, and X[k] represents the k-th frequency component of the signal in the frequency domain. Find the peak position k peak in the frequency domain data X[k] to determine the main frequency Then the frequency change rate Δf(n) is: where is the time length of each frame.

[0018] Furthermore, when the time-frequency domain joint processing module detects that part of the signal is missing and interfered, it starts the signal reconstruction program. According to the time-frequency domain characteristics of the signal, set the measurement matrix as Φ, the sparse basis as Ψ, and use the known signal segments and time-frequency domain redundant information to reconstruct and restore the waveform s(t) and characteristic parameters of the original signal: where y is the measurement vector, x is the coefficient vector of the original signal in the sparse basis, e is the noise vector, and λ is the regularization parameter used to balance the weights of the two terms to obtain the estimated value of the original signal and then through obtain the reconstructed signal

[0019] Furthermore, when constructing the measurement matrix Φ, the time-frequency domain joint processing module should make the elements Φ in the matrix ij satisfy: Where m is the number of measurements, p is the probability parameter, and with probability p means that signal loss and interference occur with probability p.

[0020] Furthermore, the selection of the sparse basis Ψ is determined according to the time-frequency domain characteristics of the signal, specifically:

[0021] For each frame of signal, calculate the standard deviation σ of its frequency domain energy distribution f (n) and the average frequency μ f (n), the average frequency μ f The calculation formula for (n) is: The standard deviation σ of the frequency domain energy distribution f The calculation formula for (n) is: When σ is satisfied f (n)<σ th and where σ th is the frequency domain energy standard deviation threshold, P th is the frequency domain energy ratio threshold, then it is determined that the pulse signal has obvious frequency components. At this time, the discrete cosine transform basis is used as the sparse basis. The discrete cosine transform basis converts the discrete signal from the time domain to the orthogonal transform basis of the frequency domain. For a discrete signal x(n) with a length of N, its forward DCT transform is; Where k = 0, 1, ..., N-1, when k = 0, When k≠0, The forward DCT transform concentrates the energy of the signal on the low-frequency coefficients, making the signal of the frequency component appear sparse in the DCT domain.

[0022] Furthermore, the real-time control module dynamically adjusts the frame length N according to the time-frequency resolution requirements of the signal, and adjusts it to k6 is the proportional coefficient. In addition, the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula are controlled to achieve dynamic optimization and precise control of the entire detection process.

[0023] Compared with the prior art, the real-time control and acquisition management system of the pulse electromagnetic signal detection device has the following beneficial effects:

[0024] 1. The present invention can analyze the time domain and frequency domain characteristics of pulse electromagnetic signals in real time and accurately by utilizing dynamic signal processing in the time and frequency domains. By adaptively adjusting the time and frequency resolution, the system can accurately capture the transient changes of the signal and more accurately detect the reflected signal of the target, thereby reducing the misjudgment or missed judgment of the target due to inaccurate signal detection, thereby greatly improving the detection accuracy and reliability of the radar system. In addition, for communication signal detection in complex electromagnetic environments, it can also effectively distinguish useful signals from interference signals, ensure the stability of communication and the accuracy of data transmission, and provide a strong guarantee for communication quality.

[0025] 2. When the present invention detects that the signal is partially missing or interfered, the system uses a signal reconstruction program to restore the waveform and characteristic parameters of the original signal with high fidelity, restore the accurate original signal, thereby improving the positioning accuracy and stability, and reducing system failures or performance degradation caused by signal quality problems.

[0026] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 This is an operation step diagram of a real-time control and acquisition management system for a pulse electromagnetic signal detection device;

[0029] Figure 2 The present invention is a block diagram of the composition of a real-time control and acquisition management system for a pulse electromagnetic signal detection device. DETAILED DESCRIPTION

[0030] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0031] Embodiment 1

[0032] This embodiment details the working process of a real-time control and acquisition management system for a pulsed electromagnetic signal detection device. The system consists of a signal acquisition module, a time-frequency domain joint processing module, a real-time control module, and a data storage and management module, aiming to solve the limitations of traditional pulsed electromagnetic signal detection methods in complex electromagnetic environments. Through techniques such as time-frequency domain joint processing and adaptive adjustment, high-precision detection and reconstruction of pulsed electromagnetic signals are achieved, improving the system performance.

[0033] The signal acquisition module sets the initial sampling rate f based on the preliminary analysis of the detection target and environment. s During the acquisition process, after the sensor array receives the pulsed electromagnetic signal, it performs interval sampling according to the established f. s The continuous time signal is accurately discretized into a series of sample values at time points, and then enters the quantization link. In the quantization process, the actual amplitude of each sampling point is divided into multiple discrete levels, and the closest level value is taken as the quantization result of this sampling point, thereby realizing the discretization of the amplitude. The quantized level value is converted into a digital signal sequence, which is the digital signal representation form after conversion of this sampling point. The converted digital signal will be transmitted to the time-frequency domain joint processing module in real time and continuously, ensuring the timeliness and coherence of signal processing.

[0034] After receiving the digital signal, the time-frequency domain joint processing module performs preliminary preprocessing to improve the signal quality. It analyzes the signal using the dynamic signal processing algorithm of the time-frequency domain joint. By performing frame segmentation on the signal and applying FFT and STFT transforms to each frame, the time-frequency domain representation of the signal is obtained. For example, if the total length of the received signal is L, according to the initial sampling rate f. s and the preset frame overlap rate r (0 < r < 1), the number of valid data points N in each frame is calculated. eff The formula is The setting of the frame overlap rate r is to reduce the loss of signal information caused by frame segmentation while ensuring a certain processing efficiency. For example, if r = 0.2 is selected, it means that there is a 20% overlapping part between adjacent frames. Starting from the signal start point, data segments with a length of N are sequentially intercepted as one frame, and the adjacent frames overlap by N - N. eff data points, and each frame is numbered. Such a frame segmentation method helps to better analyze the time-domain variation characteristics of the signal in subsequent processing, and at the same time uses the inter-frame overlap information to improve the accuracy of signal feature extraction. Apply the FFT transform to each frame of signal x n [i] (i = 0, 1,..., N - 1), and the formula is k=0,1,…,N-1, X[k] represents the kth frequency component of the signal in the frequency domain. The signal is converted from the time domain to the frequency domain to obtain the time-frequency domain representation X n [k], through FFT transformation, we can clearly observe the distribution of the time-frequency components of the signal, so as to more comprehensively analyze the changing characteristics of the signal at different times and frequencies, and calculate the energy distribution E(n), the formula is The energy distribution E(n) reflects the energy concentration of the signal in each frame. By monitoring the changes in E(n), we can determine the intensity fluctuation of the signal and whether there is an abnormal energy peak. n [k], find the peak position k in the frequency domain data peak Determine the main frequency The frequency change rate in is the time length of each frame, and the frequency change rate Δf(n) can reflect the speed of signal frequency change over time, which plays a key role in detecting frequency modulated signals or frequency drift of signals during propagation. According to the calculated energy distribution E(n), time domain change rate Δt(n) and frequency domain change rate Δf(n), the time-frequency resolution is adaptively adjusted. The time-frequency resolution adjustment formula is: Among them, k1 and k2 are adjustment constants 0 <k1,k2<2),E th and Δf th are the thresholds of energy distribution and frequency domain change rate, respectively. When the energy distribution E(n) of the signal approaches or exceeds E th When the signal may have strong characteristics or changes, the time domain resolution Δt(n) can be changed accordingly by adjusting k1 and related parameters, so as to more finely capture the detailed changes of the signal in the time domain. Similarly, when the frequency change rate Δf(n) approaches or exceeds Δf th When the signal is partially missing or interfered, the signal reconstruction program is started, and the measurement matrix is ​​set to Φ, whose element Φ ij satisfy Where m is the number of measurements, p is the probability parameter (indicating that signal loss and interference occur with probability p), and a suitable sparse basis Ψ is selected, which is determined based on the time-frequency domain characteristics of the signal, that is, for each frame of the signal, the standard deviation σ of its frequency domain energy distribution is calculated f (n) and the average frequency μ f (n), the average frequency Standard deviation of frequency domain energy distribution When σ is satisfied f (n)<σ th and (where σ t h is the frequency domain energy standard deviation threshold, P t h is the frequency domain energy ratio threshold), the pulse signal is judged to have obvious frequency components, and the discrete cosine transform (DCT) basis is used as the sparse basis, and its forward DCT transform is When k = 0, When k≠0, Using known signal segments and redundant information in the time and frequency domains, the reconstruction formula Where y is the measurement vector, x is the coefficient vector of the original signal in a sparse basis, e is the noise vector, and λ is the regularization parameter used to balance The weights of the two terms are solved to obtain the estimated value of the original signal And then through Get the reconstructed signal Achieve high-fidelity restoration of missing or interfered signals.

[0035] The real-time control module continuously receives the signal characteristic parameters fed back by the time-frequency domain joint processing module, and dynamically adjusts the frame length N according to the time-frequency resolution requirements of the signal. The adjustment formula is: k6 is a proportional coefficient. For example, when the detected signal frequency changes are more complex and a higher frequency domain resolution is required, k6 is adjusted to appropriately increase the sub-frame length N so as to analyze the signal more finely in the frequency domain. At the same time, the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula are controlled. According to the actual situation of the signal energy distribution and the frequency change rate, the adjustment strategy of the time-frequency resolution is optimized to ensure that the system is always in the best detection state and realize dynamic optimization and precise control of the entire detection process. In addition, the real-time control module is also responsible for communicating with external devices, transmitting the collected signal data, processed feature information and system status parameters to external devices, ensuring the accuracy and integrity of data transmission during the communication process, and receiving control instructions or configuration information from external devices. According to this information, the system is adjusted and operated accordingly to realize effective interaction between the system and the external environment.

[0036] The data storage and management module receives the signal data and processed feature information from the time-frequency domain joint processing module, and uses an efficient data storage format and indexing mechanism to classify and store the data. The stored data is backed up regularly to prevent data loss, ensure the continuous and stable operation of the system, and ensure the integrity and security of the data.

[0037] like Figure 1As shown, the specific operation process of a real-time control and acquisition management system for a pulse electromagnetic signal detection device of this embodiment is as follows:

[0038] System initialization phase: The real-time control system is started, and the signal acquisition module, time-frequency domain joint processing unit, and data storage and management module are initialized, including setting the default sampling rate, gain, algorithm parameters, etc., and checking the working status of each module to ensure that the system is ready.

[0039] Signal acquisition stage: The signal acquisition module continuously collects pulsed electromagnetic signals according to the preset sampling rate and parameter settings, converts the collected analog signals into digital signals, and transmits them to the time-frequency domain joint processing module in real time.

[0040] Time-frequency domain joint processing stage: After receiving the digital signal, the time-frequency domain joint processing module first performs preliminary preprocessing to improve the quality of the signal. Then, the signal is analyzed using the dynamic signal processing algorithm of the time-frequency domain joint. The signal is framed and FFT and STFT transforms are applied to each frame to obtain the time-frequency domain representation of the signal. At the same time, the characteristic parameters of the signal such as energy distribution and frequency change rate are monitored in real time, and the time-frequency resolution is adaptively adjusted according to the changes in these parameters. When it is detected that the signal is partially missing or interfered, the signal reconstruction program is started, and the appropriate reconstruction algorithm and basis function are selected according to the time-frequency domain characteristics of the signal. The waveform and characteristic parameters of the original signal are gradually restored using the known signal fragments and redundant information in the time-frequency domain.

[0041] Real-time control and feedback stage: The time-frequency domain joint processing unit feeds back the processing results and signal characteristic parameters to the real-time control system. The real-time control system determines whether the system is working normally based on the feedback information, and adjusts the parameters of the signal acquisition module and the time-frequency domain joint processing unit according to the preset rules. For example, if the signal strength is found to be beyond the normal range, the real-time control system will automatically adjust the gain of the signal acquisition module to avoid signal saturation distortion; if the signal modulation mode is detected to have changed, the real-time control system will update the algorithm parameters of the time-frequency domain joint processing unit to adapt to the new signal characteristics.

[0042] Data storage and management stage: The processed signal data and characteristic information are transmitted to the data storage and management module, which stores the data in categories according to the preset storage format and index mechanism, and records the data acquisition time, signal source information and other related metadata. At the same time, the stored data is backed up regularly, and data query and export functions are provided for subsequent data analysis and application development.

[0043] In summary, this embodiment elaborates on the implementation process of the real-time control and acquisition management system of the pulse electromagnetic signal detection device. Through a series of operations such as signal acquisition and conversion of the signal acquisition module, signal analysis and reconstruction of the time-frequency domain joint processing module, dynamic adjustment and communication of the real-time control module, and data management of the data storage and management module, the system can effectively detect and process pulse electromagnetic signals, realize dynamic signal capture and reconstruction of the time-frequency domain joint, and improve the detection and restoration capabilities of complex pulse electromagnetic signals.

[0044] Embodiment 2

[0045] This embodiment describes in detail the application process of the real-time control and acquisition management system of the pulse electromagnetic signal detection device in the radar detection scenario. Through the collaborative work of various modules, it effectively responds to the characteristics of radar signals and complex environments, and achieves high-precision target detection and tracking.

[0046] During the operation of communication base stations, they are often affected by various interference sources, such as electromagnetic leakage from other surrounding electronic equipment, illegal signal jammers, and electromagnetic noise in the natural environment. These interference signals will seriously affect the communication quality, leading to signal interruption, data transmission errors or reduced rate, etc. Therefore, a pulse electromagnetic signal detection device real-time control and acquisition management system is needed to timely detect, analyze and process these interference signals to ensure the stable operation of the communication base station.

[0047] Signal acquisition module: Set the initial sampling rate f s , the detection area is divided into I×J×K cubic units. When optimizing the sensor array layout, the complexity of the surrounding environment of the base station is taken into account, such as the influence of factors such as building occlusion and reflection, terrain undulation, etc. on signal propagation. Through the objective function Optimize and calculate the ideal signal strength When the signal is detected, the attenuation factor α, reflection coefficient β and scattering coefficient γ of the signal are accurately measured. By continuously adjusting the position and number of sensors, the objective function value is minimized to ensure that the interference signal can be accurately collected within the coverage of the base station, thereby improving the reliability and integrity of signal collection. The sensor array collects pulsed electromagnetic signals, converts the received analog signals into digital signals, and transmits them to the time-frequency domain joint processing module in real time.

[0048] Time-frequency domain joint processing module: frame processing and characteristic parameter calculation: according to the total signal length L and frame overlap rate r, calculate the number of valid data points in each frame Starting from the start point of the signal, data segments of length N are sequentially intercepted as a frame, and adjacent frames overlap NN eff data points, and number each frame n, for each frame signal x n [i] Apply STFT transform to get the frequency domain representation Xn [k] and time-frequency domain representation, calculate energy distribution This parameter can directly reflect the intensity change of the interference signal. For example, when a strong interference source appears, the E(n) value will increase significantly; when the interference signal is intermittent, E(n) will show periodic fluctuations. Calculate the frequency change rate Δf(n): First, perform frequency domain transformation on the nth frame signal to obtain X n [k], find the peak position k peak Determine the main frequency in accordance with The calculation is used to monitor the frequency modulation or drift of the interference signal. For example, an illegal signal jammer may continuously change the frequency of the interference signal, and this change can be detected in time through Δf(n); Adaptive adjustment of time-frequency resolution: According to the calculated E(n) and Δf(n), the time-frequency resolution adjustment formula is used for dynamic adjustment. In the interference detection of communication base stations, when it is detected that the energy distribution E(n) of a certain frequency band suddenly increases and the frequency change rate Δf(n) is abnormal, it indicates that there may be a strong interference signal. At this time, if the energy distribution E(n) exceeds the energy distribution threshold E th , the frequency change rate Δf(n) approaches or exceeds the frequency domain change rate threshold Δf th , the system automatically adjusts the constants k1 and k2 to more precisely capture the fast-changing characteristics of the interference signal in the time domain, so as to more accurately analyze the frequency components of the interference signal and determine the type and characteristics of the interference source; Signal reconstruction: When the communication signal is severely interfered with, resulting in partial signal loss or distortion, the signal reconstruction program is started. Construct the measurement matrix Φ, and determine the number of measurements m and the probability parameter p according to the statistical laws and historical records of the interference of the communication base station. For example, in areas where interference is more frequent, for the selection of the sparse basis Ψ, the standard deviation σ of the frequency domain energy distribution of each frame signal is calculated f (n) and the average frequency μ f (n), since the communication signal has certain frequency specifications and bandwidth limitations, if it satisfies The signal is judged to have obvious frequency components, and the discrete cosine transform basis is used as the sparse basis. By using the known signal fragments and redundant information in the time and frequency domains, the reconstruction formula is y=Φx+e Solve to get the estimated value of the original signal Then we get the reconstructed signal Restore interfered or missing signal information to ensure the continuity and stability of communications.

[0049] Real-time control module: According to the signal characteristic parameters fed back by the time-frequency domain joint processing module, dynamically adjust the frame length N and the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula. When the frequency change of the interference signal is detected to be complex and the duration is long, according to the formula Adjust the frame length to ensure that the system can track the dynamic changes of interference signals in real time and provide accurate signal analysis results for locating and suppressing interference sources; communicate with external devices: collect interference signal data, processed feature information and system status parameters in real time. At the same time, receive operation instructions from the monitoring center, and configure and control the system accordingly according to the instructions, so as to achieve efficient interaction between the system and external devices and ensure the normal operation of communication base stations.

[0050] Data storage and management module: Receive and store the collected interference signal data and processed feature information, and classify and store them according to the time, frequency, intensity and other attributes of the interference signal. Back up the stored data regularly and back up the data to multiple independent storage devices to provide reliable data support for subsequent interference signal analysis and communication base station performance optimization.

[0051] To sum up, the real-time control and acquisition management system of the pulse electromagnetic signal detection device provided in this embodiment effectively copes with the complex electromagnetic interference environment through the collaborative work of various modules, from the optimized layout of signal acquisition to the precise analysis and reconstruction of the joint processing in the time and frequency domains, to the dynamic adjustment of real-time control and the efficient guarantee of data storage and management. It realizes the accurate detection, analysis and processing of interference signals of communication base stations, significantly improves the anti-interference capability and operation stability of communication base stations, and provides strong technical support for the reliable operation of communication networks.

[0052] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A real-time control and acquisition management system for a pulse electromagnetic signal detection device, characterized in that: The components of the system include: signal acquisition module, time-frequency domain joint processing module, real-time control module, data storage and management module; The signal acquisition module uses a pulse electromagnetic signal detection device to detect the initial sampling rate f s , continuously collect pulse electromagnetic signals, convert the collected pulse electromagnetic signals into digital signals, and transmit them to the time-frequency domain joint processing module in real time; The time-frequency domain joint processing module is used to perform dynamic signal processing on the digital signal in the time domain and frequency domain to analyze the signal; By dividing the signal into frames and applying FFT and STFT transforms on the signal x[n] with each frame length N, the time-frequency domain representation X of the signal is obtained. n [k], at the same time, the characteristic parameters of the energy distribution E(n), the time domain change rate Δt(n) and the frequency domain change rate Δf(n) of the signal are monitored in real time, and the time-frequency resolution is adaptively adjusted according to the changes of the characteristic parameters, that is, the time-frequency resolution adjustment formula is: Among them, k1 and k2 are adjustment constants and 0 <k1,k2<2,E th and Δf th are the thresholds of energy distribution and frequency domain change rate, respectively; The real-time control module dynamically adjusts the sampling rate of the signal acquisition module and the characteristic parameters of the time-frequency domain joint processing module according to the feedback information of the time-frequency domain joint processing module. At the same time, the real-time control module is also responsible for communicating with external devices to realize data transmission and interaction; The data storage and management module is used to store and manage the collected signal data and processed feature information.

2. A real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 1, characterized in that: The pulse electromagnetic signal detection device in the signal acquisition module includes a sensor array, and the layout of the sensor array is as follows: The detection area is divided into a three-dimensional space of I×J×K cubic units. At the center of each cubic unit, the number and position distribution of sensors are based on the objective function Optimize, where s ijk is the signal strength actually collected at the (i,j,k) cube unit position, is the ideal signal strength at the location predicted by the pulse electromagnetic signal detection device; At the same time, considering the signal attenuation factor α, reflection coefficient β and scattering coefficient γ, for the signal propagation path from the emission source to the (i, j, k) cube unit, its ideal signal strength is Among them, s0 is the signal strength of the transmitting source, d ijk is the distance from the source to the cube unit, R ijk is the number of reflections on the path, S ijk In order to scatter the signal intensity, the position and number of sensors are continuously adjusted to minimize the objective function value, thereby determining the optimal layout of the sensor array for signal acquisition.

3. A real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 1, characterized in that: In the time-frequency domain joint processing module, the frame division process is as follows: Assume the total length of the signal is L. First, according to the initial sampling rate f s and the frame overlap rate r, where 0 < r < 1, calculate the number of valid data points N eff per frame as follows: where represents rounding down. Starting from the beginning of the signal, successively intercept data segments of length N as one frame. There is an overlap of N - N eff data points between adjacent frames. For each intercepted frame, assign it a number and perform FFT, STFT transforms, and calculations of the energy distribution E(n) and the frequency change rate Δf(n) for this frame of the signal.

4. A real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 3, characterized in that: The energy distribution E(n) in the time-frequency domain joint processing module is: Among them, x n (i) is the i-th sampling point data in the n-th frame signal.

5. The real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 3, characterized in that: When calculating the frequency change rate Δf(n), the time-frequency domain joint processing module first performs frequency domain transformation on the n-th frame signal, that is, the time signal x[n], n=0, 1, ..., N-1, after frequency domain transformation, is in X[k] represents the kth frequency component of the signal in the frequency domain. Find the peak position k in the frequency domain data X[k] peak Determine the main frequency Then the frequency change rate Δf(n) is: in The duration of each frame.

6. The real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 1, characterized in that: When the time-frequency domain joint processing module detects that the signal is partially missing or interfered, it starts the signal reconstruction program, sets the measurement matrix to Φ and the sparse basis to Ψ according to the time-frequency domain characteristics of the signal, and uses the known signal fragments and redundant information in the time-frequency domain to restore the waveform s(t) and characteristic parameters of the original signal through reconstruction: Among them, y is the measurement vector, x is the coefficient vector of the original signal in the sparse basis, e is the noise vector, and λ is the regularization parameter used to balance and The weights of the two items give an estimate of the original signal And then through Get the reconstructed signal 7. A real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 6, characterized in that: When constructing the measurement matrix Φ, the time-frequency domain joint processing module should make the elements Φ in the matrix ij satisfy: Where m is the number of measurements, p is the probability parameter, and with probability p means that signal loss and interference occur with probability p.

8. The real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 6, characterized in that: The selection of the sparse basis Ψ is determined according to the time-frequency domain characteristics of the signal, specifically: For each frame of signal, calculate the standard deviation σ of its frequency domain energy distribution f (n) and the average frequency μ f (n), the average frequency μ f The calculation formula for (n) is: The standard deviation σ of the frequency domain energy distribution f The calculation formula for (n) is: When σ is satisfied f (n)<σ th and where σ th is the frequency domain energy standard deviation threshold, P th is the frequency domain energy ratio threshold, then it is determined that the pulse signal has obvious frequency components. At this time, the discrete cosine transform basis is used as the sparse basis. The discrete cosine transform basis converts the discrete signal from the time domain to the orthogonal transform basis of the frequency domain. For a discrete signal x(n) with a length of N, its forward DCT transform is; Where k = 0, 1, ..., N-1, when k = 0, When k≠0, The forward DCT transform concentrates the energy of the signal on the low-frequency coefficients, making the signal of the frequency component appear sparse in the DCT domain.

9. The real-time control and acquisition management system for pulse electromagnetic signal detection device according to claim 1, characterized in that: The real-time control module dynamically adjusts the frame length N according to the time-frequency resolution requirements of the signal, and adjusts it to k6 is the proportional coefficient. In addition, the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula are controlled to achieve dynamic optimization and precise control of the entire detection process.

Images