A pulse electromagnetic signal detection device real-time control and acquisition management system

Abstract

The application discloses a kind of pulse electromagnetic signal detection device real-time control and acquisition management system, it is related to electromagnetic signal detection technical field, the component of this system includes: signal acquisition module, time-frequency domain joint processing module, real-time control module, data storage and management module, the dynamic signal processing of time-frequency domain joint is utilized in the present application, the time domain and frequency domain characteristics of pulse electromagnetic signal can be analyzed in real time, accurately, by adaptively adjusting time-frequency resolution, system can accurately capture the transient change of signal, more accurately detect the reflection signal of target, reduce the misjudgment or the situation of missing judgment caused by inaccurate signal detection, to greatly improve the detection accuracy and reliability of radar system, and, for the communication signal detection under complex electromagnetic environment, useful signal and interference signal can also be effectively distinguished, ensure the stability of communication and the accuracy of data transmission, provide strong guarantee for communication quality.

Description

TECHNICAL FIELD

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

[0002] In today's era of rapid technological development, electromagnetic signal detection technology plays a crucial role in many fields, such as radar detection, communication systems, electronic countermeasures, and electromagnetic detection in biomedicine. With the continuous progress of these fields, there are increasingly high requirements for the precision, speed, and reliability of pulse electromagnetic signal detection.

[0003] Traditional pulse electromagnetic signal detection methods usually separate time domain and frequency domain analysis. In the face of complex electromagnetic environments and diverse pulse signals, there are obvious limitations. In time domain analysis, fixed sampling rate and resolution are difficult to adapt to the rapid changes and weak features of signals. In frequency domain analysis, static spectrum analysis methods cannot timely track the dynamic changes of signal frequency components, and when the signal is partially missing or disturbed, traditional techniques lack effective reconstruction means, leading to signal loss or misjudgment, seriously affecting the accuracy and integrity of detection, and cannot meet the demand of modern applications for high-precision and high-reliability pulse electromagnetic signal detection.

[0004] In summary, traditional pulse electromagnetic signal detection methods have obvious shortcomings in the face of complex electromagnetic environments and high-speed changing signal characteristics. Therefore, developing a new type of pulse electromagnetic signal detection device that can realize dynamic signal capture and reconstruction in time-frequency domain is of great significance to improve the accuracy of signal detection and system stability. SUMMARY

[0005] The purpose of the present application is to overcome the shortcomings of the prior art and provide a real-time control and acquisition management system of a pulse electromagnetic signal detection device, which can simultaneously analyze the time domain and frequency domain characteristics of pulse electromagnetic signals in the detection process, accurately capture the transient changes of signals by adaptively adjusting the time-frequency resolution, and reconstruct the original signal with high fidelity using the redundant information in time-frequency domain in the case of signal partial loss and interference, thereby improving the detection and restoration ability of complex modulated pulse signals and signals in multipath fading environment.

[0006] To solve the above technical problems, the present application provides the following technical solution: a real-time control and acquisition management system of a pulse electromagnetic signal detection device, the components of the system include: a signal acquisition module, a time-frequency domain joint processing module, a real-time control module, a data storage and management module;

[0007] The signal acquisition module uses a pulse electromagnetic signal detection device to collect pulse electromagnetic signals according to an initial sampling rate fs It continuously collects pulsed electromagnetic signals and converts the collected pulsed electromagnetic signals into digital signals, which are then transmitted 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 both the time and frequency domains, and to analyze the signal.

[0009] By segmenting the signal into frames and applying FFT and STFT transforms to each frame length N, the time-frequency domain representation of the signal is obtained. Simultaneously, the characteristic parameters of the signal's energy distribution E(n), time-domain rate of change Δt(n), and frequency-domain rate of change Δf(n) are monitored in real time. Based on the changes in these characteristic parameters, the time-frequency resolution is adaptively adjusted, as shown in the formula: Where k1 and k2 are adjustment constants and 0 <k1,k2<2,E th and Δf th These are the thresholds for energy distribution and frequency domain rate of change, 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 based on the feedback information from 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 acquired 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 sensor array is arranged 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 determined according to the objective function. Optimize, where s ijk Let (i,j,k) be the signal strength actually acquired at the (i,j,k) cube cell position. The ideal signal strength at this location is predicted by the pulse electromagnetic signal detection device;

[0014] Meanwhile, 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 cell, the ideal signal strength is... Where s0 is the signal strength of the transmitting source, d ijk R is the distance from the emission source to the cubic unit. ijk S represents the number of reflections along this path. 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 per frame eff as: where denotes rounding down. Starting from the signal start point, 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 and STFT transforms on the frame signal, as well as calculate the energy distribution E(n) and the frequency change rate Δf(n).

[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 the time-frequency domain joint processing module calculates the frequency change rate Δf(n), it first performs a frequency domain transform on the n-th frame signal. That is, for the time signal x[n], n = 0, 1, …, N - 1, after performing the frequency domain transform, it becomes where X n [k] represents the k-th frequency component of the n-th frame signal in the frequency domain. Find the peak position k in the frequency domain data X[k] peak 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 partial signal loss and interference, 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 recover 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 and 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 ensure that 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 based on the time-frequency domain characteristics of the signal, specifically as follows:

[0021] For each frame of signal, calculate the standard deviation σ of its frequency domain energy distribution. f (n) and average frequency μ f (n), the average frequency μ f The formula for calculating (n) is: The standard deviation σ of the frequency domain energy distribution f The formula for calculating (n) is: When satisfied Where σ th P is the threshold value for the standard deviation of energy in the frequency domain. th If the frequency domain energy ratio threshold is used, it is determined that the pulse electromagnetic signal has obvious frequency components. At this time, the discrete cosine transform basis is used as a sparse basis. The discrete cosine transform basis is an orthogonal transform basis that transforms the discrete signal from the time domain to the frequency domain. For a discrete signal x(n) of length N, its forward DCT transform is: Where k = 0, 1, ..., N-1, when k = 0, ... When k≠0 The forward DCT transform concentrates the signal energy on the low-frequency coefficients, making the frequency components of the signal 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, adjusting it to... k6 is the proportional coefficient. In addition, the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula are used to achieve dynamic optimization and precise control of the entire detection process.

[0023] Compared with existing technologies, this real-time control and acquisition management system for pulse electromagnetic signal detection devices has the following advantages:

[0024] I. This invention utilizes dynamic signal processing combining time and frequency domains to analyze the time and frequency domain characteristics of pulsed electromagnetic signals in real time and with high precision. By adaptively adjusting the time and frequency resolution, the system can accurately capture transient changes in the signal, more accurately detect the reflected signal of the target, and reduce the misjudgment or missed detection of the target due to inaccurate signal detection. This greatly improves the detection accuracy and reliability of the radar system. Furthermore, it can effectively distinguish between useful signals and interference signals in the detection of communication signals in complex electromagnetic environments, ensuring the stability of communication and the accuracy of data transmission, and providing strong support for communication quality.

[0025] Second, when the present invention detects that a part of the signal is missing or interfered with, the system uses a signal reconstruction program to restore the waveform and characteristic parameters of the original signal with high fidelity, thereby restoring the accurate original signal, thus 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 invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0028] Figure 1 This is a flowchart illustrating the operation steps of a real-time control and acquisition management system for a pulse electromagnetic signal detection device.

[0029] Figure 2 This is a block diagram of a real-time control and acquisition management system for a pulse electromagnetic signal detection device. Detailed Implementation

[0030] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0031] Example 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 technologies such as time-frequency domain joint processing and adaptive adjustment, it realizes high-precision detection and reconstruction of pulsed electromagnetic signals and improves the system performance.

[0033] The signal acquisition module sets an initial sampling rate f based on a preliminary analysis of the detection target and environment. s During the acquisition process, after the sensor array receives the pulsed electromagnetic signal, it samples at intervals 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, thus achieving the discretization of the amplitude. The quantized level values are 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 time-frequency domain joint dynamic signal processing algorithm. 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 for 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 n. Such a frame segmentation method helps to better analyze the time-domain change 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. For each frame of signal x. n [i] (i = 0, 1,..., N - 1), the FFT transform is applied, and the formula is X. n [k] represents the k-th frequency component of the n-th frame 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], the time-frequency component distribution of the signal can be clearly observed through FFT transformation, so as to more comprehensively analyze the signal's variation characteristics 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 within each frame. By monitoring changes in E(n), the intensity fluctuations of the signal and the presence of abnormal energy peaks can be determined. Based on the time-frequency domain representation of X... n [k], finding the peak position k in the frequency domain data. peak Determine the main frequency The rate of change of frequency in Given the time length of each frame, the frequency change rate Δf(n) reflects how quickly the signal frequency changes over time, playing a crucial role in detecting frequency-modulated signals or frequency drift during signal propagation. Based on 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 as follows: Where k1 and k2 are adjustment constants 0 <k1,k2<2,E th and Δf th These are the thresholds for energy distribution and frequency domain rate of change, respectively. When the energy distribution E(n) of the signal approaches or exceeds E... th When the signal exhibits strong characteristics or changes, adjusting k1 and related parameters alters the time-domain resolution Δt(n) to capture more precise changes in the signal's time domain. Similarly, when the frequency change rate Δf(n) approaches or exceeds Δf... th At the same time, the parameters of k2 are adjusted to change the frequency domain resolution Δf(n), ensuring accurate tracking of the dynamic changes in signal frequency. This adaptive adjustment mechanism allows the system to flexibly optimize the time-frequency resolution according to the actual characteristics of the signal, improving the accuracy of signal analysis. When partial signal loss or interference is detected, the signal reconstruction program is initiated, setting the measurement matrix to Φ, with its elements Φ ij satisfy Where m is the number of measurements, p is the probability parameter (representing the probability of signal loss and interference occurring 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 signal, the standard deviation σ of its frequency domain energy distribution is calculated. f (n) and 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) thP is the threshold value for the standard deviation of energy in the frequency domain. th When the frequency domain energy proportion threshold is used, the pulse signal is determined to have a significant frequency component. Using the Discrete Cosine Transform (DCT) basis as a sparse basis, its forward DCT transform is... When k = 0 When k≠0 Using known signal segments and time-frequency domain redundancy information, the reconstruction formula is used. Where y is the measurement vector, x is the coefficient vector of the original signal under the sparse basis, e is the noise vector, and λ is the regularization parameter used to balance... and By calculating the weights of the two terms, we can obtain an estimate of the original signal. Then through Obtain the reconstructed signal Achieve high-fidelity recovery of missing or interfered signals.

[0035] The real-time control module continuously receives signal characteristic parameters from the time-frequency domain joint processing module and dynamically adjusts the frame length N according to the signal's time-frequency resolution requirements. The adjustment formula is as follows: k6 is a scaling factor. For example, when the detected signal frequency changes are complex and higher frequency domain resolution is required, adjusting k6 appropriately increases the frame length N to analyze the signal more finely in the frequency domain. Simultaneously, it controls the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula, optimizing the adjustment strategy based on the actual signal energy distribution and frequency change rate. This ensures the system is always in optimal detection mode, achieving dynamic optimization and precise control of the entire detection process. Furthermore, the real-time control module is responsible for communicating with external devices, transmitting the acquired signal data, processed feature information, and system status parameters. During communication, it ensures the accuracy and integrity of data transmission. It also receives control commands or configuration information from external devices, adjusting and operating the system accordingly to achieve effective interaction between the system and the external environment.

[0036] The data storage and management module receives signal data and processed feature information from the time-frequency domain joint processing module. It employs an efficient data storage format and indexing mechanism to classify and store the data. Regular backups are performed to prevent data loss, ensure continuous and stable system operation, and guarantee data integrity and security.

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

[0038] System initialization phase: The real-time control system starts up and initializes the signal acquisition module, time-frequency domain joint processing unit, and data storage and management module, 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 phase: The signal acquisition module continuously acquires pulse electromagnetic signals according to the preset sampling rate and parameter settings, and converts the acquired analog signals into digital signals, which are then transmitted 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 signal quality. Then, it analyzes the signal using a time-frequency domain joint dynamic signal processing algorithm. By segmenting the signal into frames and applying FFT and STFT transforms to each frame, the time-frequency domain representation of the signal is obtained. Simultaneously, it monitors the signal's energy distribution, frequency change rate, and other characteristic parameters in real time, and adaptively adjusts the time-frequency resolution based on changes in these parameters. When partial signal loss or interference is detected, a signal reconstruction program is initiated. Based on the signal's time-frequency domain characteristics, a suitable reconstruction algorithm and basis function are selected. Using known signal segments and time-frequency domain redundancy information, the waveform and characteristic parameters of the original signal are gradually restored.

[0041] Real-time control and feedback phase: The time-frequency domain joint processing unit feeds back the processing results and signal characteristic parameters to the real-time control system. Based on this feedback information, the real-time control system determines whether the system is operating normally and adjusts the parameters of the signal acquisition module and the time-frequency domain joint processing unit according to preset rules. For example, if the signal strength is found to be outside the normal range, the real-time control system will automatically adjust the gain of the signal acquisition module to avoid signal saturation distortion; if a change in the signal modulation method is detected, 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 phase: The processed signal data and feature information are transmitted to the data storage and management module. This module categorizes and stores the data according to a preset storage format and indexing mechanism, and records relevant metadata such as data acquisition time and signal source information. Simultaneously, it periodically backs up the stored data and provides data query and export functions for subsequent data analysis and application development.

[0043] In summary, this embodiment details the implementation process of the real-time control and acquisition management system for the pulse electromagnetic signal detection device. Through a series of operations, including signal acquisition and conversion by the signal acquisition module, signal analysis and reconstruction by the time-frequency domain joint processing module, dynamic adjustment and communication by the real-time control module, and data management by the data storage and management module, the system can effectively detect and process pulse electromagnetic signals, achieving dynamic signal capture and reconstruction in the time-frequency domain, and improving the detection and reconstruction capabilities for complex pulse electromagnetic signals.

[0044] Example 2

[0045] This embodiment details the application process of the real-time control and acquisition management system for pulse electromagnetic signal detection devices in radar detection scenarios. Through the coordinated work of various modules, it effectively addresses the characteristics of radar signals and complex environments, achieving 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 devices, illegal signal jammers, and electromagnetic noise in the natural environment. These interference signals can seriously affect communication quality, leading to problems such as signal interruption, data transmission errors, or reduced speed. Therefore, a pulse electromagnetic signal detection device real-time control and acquisition management system is needed to detect, analyze, and process these interference signals in a timely manner to ensure the stable operation of communication base stations.

[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 environment surrounding the base station is taken into account, such as the impact of building obstruction and reflection, and terrain undulations on signal propagation. The objective function is then used to... Optimization is performed when calculating the ideal signal strength. Simultaneously, the signal attenuation factor α, reflection coefficient β, and scattering coefficient γ are accurately measured. By continuously adjusting the position and number of sensors, the objective function value is minimized, ensuring accurate acquisition of interference signals within the base station coverage area and improving the reliability and integrity of signal acquisition. The sensor array acquires pulsed electromagnetic signals, converts the received analog signals into digital signals, and transmits them in real time to the time-frequency domain joint processing module.

[0048] Time-frequency domain joint processing module: Frame segmentation and feature parameter calculation: Calculate the number of effective data points per frame based on the total signal length L and frame overlap rate r. Starting from the signal's origin, data segments of length N are sequentially extracted as a frame, with adjacent frames overlapping by N. eff There are 10 data points, and each frame is numbered n, and each frame signal x is 10 data points. n [i] Apply the STFT transform to obtain the frequency domain representation X.n [k] and time-frequency domain representations are used to calculate the energy distribution. This parameter can intuitively reflect the intensity changes of the interference signal. For example, when a strong interference source appears, the value of E(n) will increase significantly; when the interference signal is intermittent, E(n) will exhibit periodic fluctuations. The frequency change rate Δf(n) is calculated by first performing a frequency domain transformation on the nth frame signal to obtain X. n [k], finding the peak position k peak Determine the main frequency in accordance with The calculation is used to monitor the frequency modulation or drift of interference signals. For example, an illegal signal jammer may continuously change the frequency of the interference signal, and this change can be detected in time by using Δf(n). Time-frequency resolution adaptive adjustment: Based on the calculated E(n) and Δf(n), dynamic adjustment is performed using the time-frequency resolution adjustment formula. In communication base station interference detection, when a sudden increase in the energy distribution E(n) of a certain frequency band and an abnormal frequency change rate Δf(n) are detected, it indicates the possible presence of a strong interference signal. At this time, if the energy distribution E(n) exceeds the energy distribution threshold E... th The rate of change of frequency Δf(n) is close to or exceeds the frequency domain rate of change threshold Δf th The system automatically adjusts the regulation constants k1 and k2 to more precisely capture the rapid time-domain changes of the interference signal, thereby more accurately analyzing the frequency components of the interference signal and determining 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 initiated. A measurement matrix Φ is constructed, and based on the statistical laws and historical records of communication base station interference, the number of measurements m and the probability parameter p are determined. For example, in areas with frequent interference, the standard deviation σ of the frequency domain energy distribution of each frame of signal is calculated for the selection of the sparse basis Ψ. f (n) and average frequency μ f (n), due to the certain frequency specifications and bandwidth limitations of communication signals, if σ is satisfied... f (n)<σ th and The signal is determined to have a distinct frequency component. A discrete cosine transform basis is used as the sparse basis. Utilizing known signal segments and time-frequency domain redundancy information, a reconstruction formula is employed. The estimated value of the original signal is obtained by solving the problem. Thus, the reconstructed signal is obtained. To restore interfered or missing signal information and ensure the continuity and stability of communication.

[0049] Real-time control module: Based on the signal characteristic parameters fed back by the time-frequency domain joint processing module, dynamically adjusts the frame length N and the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula. When complex frequency changes and long durations of interference signals are detected, the module adjusts the frame length N and the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula. Adjusting the frame length ensures the system can track the dynamic changes of interference signals in real time, providing accurate signal analysis results for interference source location and suppression; communicating with external devices: real-time transmission of collected interference signal data, processed feature information, and system status parameters; simultaneously receiving operation instructions from the monitoring center and configuring and controlling the system accordingly, achieving efficient interaction between the system and external devices, and ensuring the normal operation of the communication base station.

[0050] Data storage and management module: Receives and stores collected interference signal data and processed feature information, classifying and storing them according to attributes such as time, frequency, and intensity of the interference signals. It periodically backs up the stored data to multiple independent storage devices, providing reliable data support for subsequent interference signal analysis and communication base station performance optimization.

[0051] In summary, the pulse electromagnetic signal detection device real-time control and acquisition management system provided in this embodiment effectively copes with complex electromagnetic interference environments through the coordinated work of various modules. From the optimized layout of signal acquisition to the precise analysis and reconstruction of time-frequency domain joint processing, and then 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 operational stability of communication base stations, and provides strong technical support for the reliable operation of communication networks.

[0052] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope 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 system comprises: a signal acquisition module, a time-frequency domain joint processing module, a real-time control module, and a data storage and management module; The signal acquisition module utilizes a pulse electromagnetic signal detection device at an initial sampling rate f. s It continuously collects pulsed electromagnetic signals and converts the collected pulsed electromagnetic signals into digital signals, which are then transmitted 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 both the time and frequency domains, and to analyze the signal. By segmenting the signal into frames and applying FFT and STFT transforms to the signal x[n] of length N in each frame, the time-frequency domain representation X of the signal is obtained. n [k], simultaneously, the characteristic parameters of the energy distribution E(n), time-domain rate of change Δt(n), and frequency-domain rate of change Δf(n) of the signal are monitored in real time. Based on the changes in these characteristic parameters, the time-frequency resolution is adaptively adjusted, i.e., the time-frequency resolution adjustment formula is: Where k1 and k2 are adjustment constants and 0 <k1,k2<2,E th and Δf th These are the thresholds for energy distribution and frequency domain rate of change, 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 based on the feedback information from 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 acquired signal data and processed feature information.

2. The real-time control and acquisition management system for a 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 sensor array is arranged 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 determined according to the objective function. Optimize, where s ijk Let (i,j,k) be the actual signal strength acquired at the (i,j,k) cube cell position. The ideal signal strength at this location is predicted by the pulse electromagnetic signal detection device; Meanwhile, 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 cell, the ideal signal strength is... Where s0 is the signal strength of the transmitting source, d ijk R is the distance from the emission source to the cubic unit. ijk S represents the number of reflections along this path. ijk To determine the intensity of the scattered signal, 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. The real-time control and acquisition management system for a pulse electromagnetic signal detection device according to claim 1, characterized in that, The frame processing process in the joint time-frequency domain processing module is as follows: Assume the total length of the signal is L. First, calculate the number of effective data points N per frame according to the initial sampling rate f s and the frame overlap rate r, where 0 < r < 1 eff as follows: where denotes 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 and STFT transforms on the frame signal, as well as calculate the energy distribution E(n) and the frequency change rate Δf(n).

4. The real-time control and acquisition management system for a 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: Where, x n (i) represents the data of the i-th sampling point in the n-th frame signal.

5. The real-time control and acquisition management system for a 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 a frequency domain transformation on the nth frame signal, i.e., the time signal x[n], n=0,1,…,N-1, after the frequency domain transformation, becomes... in k = 0, 1, ..., N-1, X n [k] represents the k-th frequency component of the n-th frame signal in the frequency domain. The goal is to find the peak position k in the frequency domain data X[k]. peak Determine the main frequency Then the rate of change of frequency Δf(n) is: in The duration of each frame.

6. The real-time control and acquisition management system for a pulse electromagnetic signal detection device according to claim 1, characterized in that, When the time-frequency domain joint processing module detects partial signal loss or interference, it initiates a signal reconstruction program. Based on the time-frequency domain characteristics of the signal, it sets the measurement matrix to Φ and the sparse basis to Ψ. Utilizing known signal segments and time-frequency domain redundancy information, it reconstructs and restores 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 under the sparse basis, e is the noise vector, and λ is the regularization parameter used to balance... and The weights of the two terms are used to obtain an estimate of the original signal. Then through Obtain the reconstructed signal 7. The real-time control and acquisition management system for a 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 ensure that the elements Φ in the matrix are... ij satisfy: Where m is the number of measurements, p is the probability parameter, and withprobabilityp means that signal loss and interference occur with probability p.

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

9. The real-time control and acquisition management system for a 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, adjusting it to... k6 is the proportional coefficient. In addition, the adjustment constants k1 and k2 in the time-frequency resolution adjustment formula are used to achieve dynamic optimization and precise control of the entire detection process.

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