Rapid signal acquisition system for radio monitoring receiver

Abstract

The invention relates to the technical field of radio monitoring, and discloses a rapid signal acquisition system for a radio monitoring receiver, which can accurately evaluate a signal state and amplify a signal in real time in a dynamically changing electromagnetic environment through refined data acquisition, multi-dimensional data processing, comprehensive calculation and intelligent analysis. The data acquisition module provides comprehensive signal source data, the data processing module ensures efficient arrangement and preprocessing of the data, the data calculation module and the data analysis module enable a signal enhancement decision to be more accurate and intelligent, the feedback module ensures quick response of the system in a real-time environment, and through cooperative work of the modules, the real-time performance of the system is improved. The signal processing capability and the response speed of the system are improved, and the signal enhancement is more intelligent and automatic.

Description

Technical Field

[0001] The invention relates to the technical field of radio monitoring, in particular to a fast signal acquisition system for a radio monitoring receiver. Background Art

[0002] Radio monitoring receivers are one of the core devices in modern communication technology and are widely used in wireless communications, satellite communications, military radars, navigation systems and other fields.

[0003] Current radio monitoring receivers, especially those used for rapid signal acquisition, often face the problem of insufficient signal strength and the inability to quickly adjust signal strength in dynamic environments. Many existing systems have slow response speeds and limited signal processing capabilities when facing complex signal environments, making it difficult to optimize and adjust according to signal changes in real time, resulting in low signal amplification efficiency and affecting communication quality. Traditional signal processing methods often rely on fixed thresholds and simple processing logic, and cannot flexibly respond to changes in multi-source data.

[0004] Therefore, we propose a fast signal acquisition system for radio monitoring receivers to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a fast signal acquisition system for a radio monitoring receiver to solve the problems raised by the above background technology, such as slow response speed, limited signal processing capability, difficulty in real-time optimization and adjustment according to signal changes, low signal amplification efficiency and poor communication quality when facing a complex signal environment.

[0006] To achieve the above object, the present invention provides the following technical solutions: A fast signal acquisition system for a radio monitoring receiver, comprising a data acquisition module, a data processing module, a data calculation module, a data analysis module and a feedback module;

[0007] The data acquisition module is used to collect signals and generate multi-source data sets;

[0008] The data processing module is used to pre-process the multi-source data set and reorganize the processed multi-source data set into a first data set, a second data set and a third data set;

[0009] The data calculation module is used to integrate the first data set, the second data set and the third data set to calculate the data intensity coefficient QDX;

[0010] The data analysis module is used to compare the data intensity coefficient QDX with a preset first threshold value Y, thereby generating a first comparison result, and judging whether the current signal needs to be amplified according to the first comparison result;

[0011] If the first comparison result indicates that signal amplification is required, the data intensity coefficient QDX is integrated and calculated with the first threshold value Y to generate an amplification magnitude coefficient QDJ, and the amplification magnitude coefficient QDJ is compared with a preset second threshold value R to generate a second comparison result;

[0012] The feedback module is used to amplify the signal according to the second comparison result.

[0013] Preferably, the data acquisition module includes a first data acquisition unit, a second data acquisition unit and a third data acquisition unit;

[0014] The first data acquisition unit is used to acquire bit rate, signal-to-noise ratio and frequency, the second data acquisition unit is used to acquire bandwidth, power spectrum density and link budget, and the third data acquisition unit is used to acquire delay, harmonic distortion rate and phase error;

[0015] The bit rate, signal-to-noise ratio, frequency, bandwidth, power spectrum density, link budget, delay, harmonic distortion rate and phase error constitute a multi-source data set.

[0016] Preferably, the data processing module includes a data preprocessing unit and a data sorting unit, wherein the data preprocessing unit is used to preprocess and dimensionlessly transform the multi-source data set, and the data sorting unit is used to sort the processed multi-source data set into a first data set, a second data set, and a third data set respectively;

[0017] The first data set includes bit error rate, signal-to-noise ratio, and frequency;

[0018] The bit error rates are recorded as A1, A2, A3, ..., An according to the timestamps;

[0019] The signal-to-noise ratios are recorded as B1, B2, B3, ..., Bn according to the timestamps;

[0020] The frequencies are recorded as C1, C2, C3, ..., Cn according to the timestamps;

[0021] The second data set includes bandwidth, power spectral density, and link budget;

[0022] The bandwidths are recorded as D1, D2, D3, ..., Dn according to the timestamps;

[0023] The power spectrum density is recorded as E1, E2, E3, ..., En according to the timestamp;

[0024] The link budgets are recorded as F1, F2, F3, ..., Fn according to the timestamps;

[0025] The third data set includes time delay, harmonic distortion, and phase error;

[0026] The delays are recorded as G1, G2, G3, ..., Gn according to the timestamps;

[0027] The harmonic distortion rates are recorded as H1, H2, H3, ..., Hn according to the timestamps;

[0028] The phase errors are recorded as I1, I2, I3, ..., In according to the timestamps.

[0029] Preferably, the data calculation module includes a first calculation unit, a second calculation unit and a third calculation unit, the first calculation unit is used to calculate the bit rate window value PA, the signal-to-noise ratio window value PB, the frequency window value PC, the bandwidth window value PD, the power spectrum density window value PE, the link budget window value PF, the delay window value PG, the harmonic distortion rate window value PH and the phase error window value PI, the second calculation unit is used to calculate the first reference coefficient S1, the second reference coefficient S2 and the third reference coefficient S3, and the third calculation unit is used to calculate the data strength coefficient QDX.

[0030] Preferably, the first calculation unit calculates and obtains the bit rate window value PA, the signal-to-noise ratio window value PB, the frequency window value PC, the bandwidth window value PD, the power spectrum density window value PE, the link budget window value PF, the delay window value PG, the harmonic distortion rate window value PH and the phase error window value PI respectively through the following formulas;

[0031]

[0032]

[0033] Where: m is the window size, indicating that there are m data points in each window, and k is the starting position of the window;

[0034] Ak, Bk, Ck, Dk, Ek, Fk, Gk, Hk and Ik are the code rate, signal-to-noise ratio, frequency, bandwidth, power spectral density, link budget, delay, harmonic distortion rate and phase error of the kth data point in the data sequence respectively.

[0035] Preferably, the second calculation unit calculates and obtains the first reference coefficient S1, the second reference coefficient S2 and the third reference coefficient S3 respectively by the following formulas;

[0036]

[0037] Wherein: PA, PB, PC, PD, PE, PF, PG, PH and PI are respectively the code rate window value, signal-to-noise ratio window value, frequency window value, bandwidth window value, power spectrum density window value, link budget window value, delay window value, harmonic distortion rate window value and phase error window value;

[0038] An, Bn, Cn, Dn, En, Fn, Gn, Hn, and In are the bit rate, signal-to-noise ratio, frequency, bandwidth, power spectral density, link budget, delay, harmonic distortion rate, and phase error of the nth data point in the data sequence, respectively;

[0039] a1, a2, a3, b1, b2, b3, c1, c2, and c3 are weight values, and the values of A1, a2, a3, b1, b2, b3, c1, c2, and c3 are adjusted and set by the user.

[0040] Preferably, the third calculation unit calculates and obtains the data intensity coefficient QDX through the following formula;

[0041] QDX = d1 × S1 + d2 × S2 + d3 × S3;

[0042] In the formula: d1, d2, and d3 are weight values, and the values of d1, d2, and d3 are adjusted and set by the user, S1 is the first reference coefficient, S2 is the second reference coefficient, and S3 is the third reference coefficient.

[0043] Preferably, the data analysis module includes a first data analysis unit and a second data analysis unit. The first data analysis unit is used to generate a first comparison result, and the second data analysis unit is used to generate a second comparison result.

[0044] Preferably, the first comparison result is specifically as follows;

[0045] When QDX < Y, it means that the current signal needs to be enhanced;

[0046] When QDX ≥ Y, it means that the current signal does not need to be enhanced;

[0047] The second comparison result is specifically as follows;

[0048] When QDJ ≥ R, it means that the current signal is in the first-level to-be-enhanced state and the signal intensity needs to be increased by 5%;

[0049] When R × 75% ≤ QDJ < R, it means that the current signal is in the second-level to-be-enhanced state and the signal intensity needs to be increased by 15%;

[0050] When QDJ < R × 75%, it means that the current signal is in the third-level to-be-enhanced state and the signal intensity needs to be increased by 35%.

[0051] Preferably, the amplification level coefficient QDJ is calculated and obtained through the following formula;

[0052]

[0053] In the formula: QDX is the data intensity coefficient, and Y is the first threshold.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. Through refined data acquisition, multi-dimensional data processing, comprehensive calculation and intelligent analysis, this system can accurately evaluate the signal status and amplify the signal in real time in a dynamically changing electromagnetic environment. The data acquisition module provides comprehensive signal source data, the data processing module ensures efficient data sorting and preprocessing, the data calculation module and the data analysis module make signal enhancement decisions more accurate and intelligent, and the feedback module ensures that the system responds quickly in a real-time environment. The collaborative work of these modules not only improves the system's signal processing capability and response speed, but also makes signal enhancement more intelligent and automated.

[0056] 2. This system can conduct in-depth analysis of signals from multiple dimensions. Through refined window value calculation, dynamic reference coefficient adjustment and weighted strength coefficient calculation, the system can evaluate the quality of the signal from different aspects and determine whether it needs to be enhanced. Traditional radio monitoring systems can often only make signal assessments based on limited features, which may be at risk of misjudgment and slow response. The calculation module of this system can comprehensively evaluate the dynamic changes of the signal, make optimization and enhancement decisions in a timely and accurate manner, and enable each calculation unit to adapt to different signal environments and requirements through user-adjustable weight values ​​and window sizes. This flexibility provides the system with more adaptability, and users can make adjustments based on actual usage to further optimize system performance and ensure that the system can achieve the best signal enhancement effect in different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a system flow chart of the present invention.

[0058] In the figure: 1. Data acquisition module; 11. First data acquisition unit; 12. Second data acquisition unit; 13. Third data acquisition unit; 2. Data processing module; 21. Data preprocessing unit; 22. Data sorting unit; 3. Data calculation module; 31. First calculation unit; 32. Second calculation unit; 33. Third calculation unit; 4. Data analysis module; 41. First data analysis unit; 42. Second data analysis unit; 5. Feedback module. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Example 1: Please refer to Figure 1 , a fast signal acquisition system for a radio monitoring receiver, comprising a data acquisition module 1, a data processing module 2, a data calculation module 3, a data analysis module 4 and a feedback module 5;

[0061] The data acquisition module 1 is used to collect signals and generate multi-source data sets;

[0062] The data processing module 2 is used to preprocess the multi-source data set and reorganize the processed multi-source data set into a first data set, a second data set and a third data set;

[0063] The data calculation module 3 is used to integrate the first data set, the second data set and the third data set to calculate the data intensity coefficient QDX;

[0064] The data analysis module 4 is used to compare the data intensity coefficient QDX with a preset first threshold value Y, thereby generating a first comparison result, and judging whether the current signal needs to be amplified according to the first comparison result;

[0065] If the first comparison result indicates that signal amplification is required, the data intensity coefficient QDX is integrated and calculated with the first threshold value Y to generate an amplification magnitude coefficient QDJ, and the amplification magnitude coefficient QDJ is compared with a preset second threshold value R to generate a second comparison result;

[0066] The feedback module 5 is used to amplify the signal according to the second comparison result.

[0067] In this embodiment: Data acquisition module 1 is the core component of the radio monitoring receiver, and its main task is to collect signals in real time and generate multi-source data sets. Through the collaboration of multiple data acquisition units, this module can extract multiple key parameters from different signal sources, such as signal-to-noise ratio, frequency, bandwidth, power spectrum density, delay, etc., to ensure comprehensive collection of signals. Through these collected data, accurate and comprehensive raw data support can be provided for subsequent processing, calculation and analysis modules. The effective operation of this module ensures that the system can cover multiple signal sources and achieve efficient data collection, providing the necessary data basis for signal enhancement and optimization.

[0068] The data processing module 2 is responsible for preprocessing the multi-source data sets from the data acquisition module 1 to ensure the uniformity and validity of the data format. In the preprocessing stage, the module performs operations such as dimensionless transformation to eliminate irrelevant noise in the data and improve the availability of the data. The processed data is further organized into three specific data sets: the first data set, the second data set, and the third data set. This refined processing method ensures that each type of data can be analyzed and calculated separately, thereby providing a more accurate basis for subsequent signal enhancement decisions. The existence of the data processing module 2 improves the processing efficiency of the system and the accuracy of the data, making subsequent calculations more efficient.

[0069] The role of data calculation module 3 in the system is to integrate and calculate various processed data sets into the data strength coefficient QDX, which is the core calculation indicator for signal enhancement and amplification. Through complex mathematical calculations, this module converts the information in multiple data sets into a comprehensive signal strength coefficient to reflect the current signal strength status. The calculation of QDX provides a scientific basis for subsequent signal optimization decisions and helps the system accurately evaluate the signal strength requirements. The computing power of data calculation module 3 directly affects the system response speed and the accuracy of signal optimization, and is an important guarantee for the system to quickly adapt to the dynamic electromagnetic environment.

[0070] The main task of the data analysis module 4 is to determine whether the current signal needs to be enhanced by comparing and analyzing it with a preset threshold. By comparing the data intensity coefficient QDX with the first threshold Y, the first comparison result generated determines whether the system needs to start signal amplification. If the signal needs to be enhanced, the data analysis module 4 will further calculate the amplification magnitude coefficient QDJ and compare it with the second threshold R to generate a second comparison result. Through precise analysis and intelligent decision-making, the data analysis module 4 can achieve precise control of signal amplification, avoiding the problems of over-enhancement or under-enhancement that may occur in traditional methods, thereby ensuring that the quality of the signal is within the optimal range.

[0071] The feedback module 5 is the executor of the entire signal enhancement process by amplifying the signal according to the second comparison result. When the signal amplification decision is made, the feedback module 5 will adjust the amplification level according to the signal strength requirement to ensure that the signal reaches the required strength level. Through this feedback mechanism, the system can respond to changes in the electromagnetic environment in real time and dynamically adjust the signal output to ensure the stability and reliability of communication quality. The existence of the feedback module 5 makes the signal enhancement not only automated, but also able to adapt in real time in a changing environment, avoiding the complexity and delay of traditional manual adjustment, and greatly improving the real-time and flexibility of the system.

[0072] Traditional radio monitoring systems often rely on simple fixed parameters and thresholds when facing complex signals and dynamic environments, and are unable to quickly adjust signal strength or process complex data. However, this system can accurately evaluate signal status and amplify signals in real time in a dynamically changing electromagnetic environment through refined data acquisition, multi-dimensional data processing, comprehensive calculation and intelligent analysis. Data acquisition module 1 provides comprehensive signal source data, data processing module 2 ensures efficient data collation and preprocessing, data calculation module 3 and data analysis module 4 make signal enhancement decisions more accurate and intelligent, and feedback module 5 ensures that the system responds quickly in a real-time environment. The collaborative work of these modules not only improves the system's signal processing capability and response speed, but also makes signal enhancement more intelligent and automated.

[0073] Example 2: Please refer to Figure 1 , the data acquisition module 1 includes a first data acquisition unit 11, a second data acquisition unit 12 and a third data acquisition unit 13;

[0074] The first data acquisition unit 11 is used to acquire bit rate, signal-to-noise ratio and frequency, the second data acquisition unit 12 is used to acquire bandwidth, power spectrum density and link budget, and the third data acquisition unit 13 is used to acquire delay, harmonic distortion rate and phase error;

[0075] The bit rate, signal-to-noise ratio, frequency, bandwidth, power spectral density, link budget, delay, harmonic distortion rate and phase error constitute the multi-source data set.

[0076] In this embodiment: the data acquisition module 1 introduces multiple data acquisition units. The first data acquisition unit 11 collects bit rate, signal-to-noise ratio, and frequency; the second data acquisition unit 12 collects bandwidth, power spectrum density, and link budget; and the third data acquisition unit 13 collects delay, harmonic distortion rate, and phase error, thereby forming a more comprehensive and detailed multi-source data set.

[0077] Multiple acquisition units can collect signal features from different angles and provide comprehensive signal analysis data. This enables the system to accurately capture the various dimensional changes of complex signals, especially for the monitoring of high-order features such as delay and harmonic distortion, which can better reflect the true state of radio signals.

[0078] By collecting more diverse signal parameters, the system can comprehensively evaluate signal quality and perform more accurate processing and calculations. For example, the impact of signal-to-noise ratio and frequency on signal strength can be analyzed separately, while bandwidth and link budget help evaluate signal stability and transmission efficiency. Multi-dimensional signal data enables data processing module 2 to organize and analyze data more accurately, providing a solid basis for subsequent signal amplification and optimization decisions.

[0079] In scenarios with complex electromagnetic environments or poor signal quality, traditional single data acquisition methods often fail to detect problems in a timely manner or make effective optimizations. By introducing multiple data acquisition units, the system can more flexibly respond to various environmental changes, ensure the real-time and accuracy of signal enhancement, and thus improve the adaptability and robustness of the system.

[0080] The acquisition of multi-source data sets not only provides richer data input for the data processing module 2, but also provides more complete and comprehensive signal parameters for the subsequent data calculation module 3 and data analysis module 4, thereby improving the decision-making efficiency and processing capabilities of the entire system.

[0081] Example 3: Please refer to Figure 1 The data processing module 2 includes a data preprocessing unit 21 and a data sorting unit 22. The data preprocessing unit 21 is used to preprocess and dimensionless the multi-source data set, and the data sorting unit 22 is used to sort the processed multi-source data set into a first data set, a second data set, and a third data set respectively;

[0082] The first data set includes bit error rate, signal-to-noise ratio, and frequency;

[0083] The bit error rates are recorded as A1, A2, A3, ..., An according to the timestamps;

[0084] The signal-to-noise ratios are recorded as B1, B2, B3, ..., Bn according to the timestamps;

[0085] The frequencies are recorded as C1, C2, C3, ..., Cn according to the timestamps;

[0086] The second data set includes bandwidth, power spectral density, and link budget;

[0087] The bandwidths are recorded as D1, D2, D3, ..., Dn according to the timestamps;

[0088] The power spectrum density is recorded as E1, E2, E3, ..., En according to the timestamp;

[0089] The link budgets are recorded as F1, F2, F3, ..., Fn according to the timestamps;

[0090] The third data set includes time delay, harmonic distortion, and phase error;

[0091] The delays are recorded as G1, G2, G3, ..., Gn according to the timestamps;

[0092] The harmonic distortion rates are recorded as H1, H2, H3, ..., Hn according to the timestamps;

[0093] The phase errors are recorded as I1, I2, I3, ..., In according to the timestamps.

[0094] In this embodiment: by introducing the data preprocessing unit 21 and the data sorting unit 22, the system can process signal data from multiple sources more efficiently and accurately, not only improving the standardization and dimensionless processing of data, but also enhancing the ability of time series to track signal changes. This multi-level and multi-dimensional data management method enables the system to more accurately capture signal feature changes and optimize signal enhancement decisions when facing complex and changeable radio environments, ultimately improving the flexibility, accuracy and reliability of signal processing.

[0095] The data preprocessing unit 21 preprocesses and dimensionlessly converts the collected multi-source data sets, thereby eliminating redundancy and noise in the data, making the data more normalized and standardized, and facilitating subsequent processing and calculation. This processing method ensures that data from different sources can be seamlessly integrated, eliminates the impact of differences in various signal sources, and improves the validity and accuracy of the data. For example, when processing parameters such as bit error rate, signal-to-noise ratio, and frequency, preprocessing helps reduce calculation errors caused by dimensional differences and ensures the consistency and stability of the system under different signal conditions.

[0096] By introducing a timestamp to record each data item, the data sorting unit 22 can associate the change of each data point with time to form an accurate time series. This timestamp mechanism not only enhances the system's ability to monitor signal changes over time, but also clearly reflects the dynamic performance of the signal at different time points. This is crucial for real-time tracking of signal quality and future trend prediction, especially in high-speed, dynamically changing radio environments, where fluctuations in signal strength can be accurately captured, thereby achieving more accurate signal enhancement decisions.

[0097] The data sorting unit 22 divides the pre-processed data into a first data set, a second data set and a third data set, each of which includes different signal characteristics. For example, the first data set includes bit error rate, signal-to-noise ratio and frequency, and the second data set includes bandwidth, power spectrum density and link budget. This structured sorting method effectively improves the efficiency of subsequent analysis and calculation, so that each data set can be processed independently according to its specific properties, thereby avoiding the complexity caused by the mixing of different signal parameters. This refined management helps the system better understand and optimize different signal characteristics and improves the accuracy of the overall signal enhancement process.

[0098] Through accurate time series data and multi-dimensional signal feature collation, the system can more flexibly adapt to different signal requirements in a dynamically changing radio environment. For example, in a complex radio spectrum environment, signal characteristics such as delay and harmonic distortion rate will affect the quality of the signal. Through the collation of timestamps and multiple data sets, the system can understand these changes in real time and respond in a timely manner, thereby effectively improving the reliability and stability of the signal.

[0099] Example 4: Please refer to Figure 1 The data calculation module 3 includes a first calculation unit 31, a second calculation unit 32 and a third calculation unit 33. The first calculation unit 31 is used to calculate the bit rate window value PA, the signal-to-noise ratio window value PB, the frequency window value PC, the bandwidth window value PD, the power spectrum density window value PE, the link budget window value PF, the delay window value PG, the harmonic distortion rate window value PH and the phase error window value PI. The second calculation unit 32 is used to calculate the first reference coefficient S1, the second reference coefficient S2 and the third reference coefficient S3. The third calculation unit 33 is used to calculate the data strength coefficient QDX.

[0100] The first calculation unit 31 calculates and obtains the code rate window value PA, the signal-to-noise ratio window value PB, the frequency window value PC, the bandwidth window value PD, the power spectrum density window value PE, the link budget window value PF, the delay window value PG, the harmonic distortion rate window value PH and the phase error window value PI respectively through the following formulas;

[0101]

[0102] Where: m is the window size, indicating that there are m data points in each window, and k is the starting position of the window;

[0103] Ak, Bk, Ck, Dk, Ek, Fk, Gk, Hk and Ik are the code rate, signal-to-noise ratio, frequency, bandwidth, power spectral density, link budget, delay, harmonic distortion rate and phase error of the kth data point in the data sequence respectively.

[0104] The second calculation unit 32 calculates and obtains the first reference coefficient S1, the second reference coefficient S2 and the third reference coefficient S3 by the following formulas respectively;

[0105]

[0106] Wherein: PA, PB, PC, PD, PE, PF, PG, PH and PI are respectively the code rate window value, signal-to-noise ratio window value, frequency window value, bandwidth window value, power spectrum density window value, link budget window value, delay window value, harmonic distortion rate window value and phase error window value;

[0107] An, Bn, Cn, Dn, En, Fn, Gn, Hn and In are the code rate, signal-to-noise ratio, frequency, bandwidth, power spectrum density, link budget, delay, harmonic distortion rate and phase error of the nth data point in the data sequence respectively;

[0108] a1, a2, a3, b1, b2, b3, c1, c2 and c3 are weight values, and the values ​​of A1, a2, a3, b1, b2, b3, c1, c2 and c3 are adjusted and set by the user.

[0109] The third calculation unit 33 calculates the acquisition data intensity coefficient QDX by the following formula:

[0110] QDX = d1 × S1 + d2 × S2 + d3 × S3;

[0111] In the formula: d1, d2 and d3 are weight values, and the values ​​of d1, d2 and d3 are adjusted and set by the user, S1 is the first reference coefficient, S2 is the second reference coefficient, and S3 is the third reference coefficient.

[0112] In this embodiment: the system realizes multi-dimensional and dynamic calculation and evaluation of signal quality by introducing data calculation module 3 and setting first calculation unit 31, second calculation unit 32 and third calculation unit 33 therein. Such design improvement not only improves the accuracy of signal analysis, but also can make adaptive adjustments according to actual signal changes, thereby significantly improving the response speed and processing capacity of the system.

[0113] The first calculation unit 31 uses a sliding window method to calculate the window values ​​of bit rate, signal-to-noise ratio, frequency, bandwidth, power spectrum density, link budget, delay, harmonic distortion rate and phase error, which significantly improves the fine-grained analysis capability of signal features. Compared with traditional signal calculation methods, window value calculation can capture the dynamic changes of signals, so that the system can make decisions based on data changes in a short period of time rather than a single data point, thereby achieving real-time tracking and analysis of signals. This calculation method effectively avoids the impact of long-term lagging data and enhances the responsiveness of the system.

[0114] The second calculation unit 32 introduces adaptive reference coefficients S1, S2, and S3 calculations based on signal differences, and compares the current signal state with the calculated window value through a formula to obtain the reference coefficient. This design enables the system to flexibly adjust parameters to adapt to different environments and signal conditions. The adaptability of the reference coefficient calculation means that the system can be optimized in real time according to different signal changes, avoiding the limitations of fixed thresholds and standardized parameters, and enabling the system to achieve more accurate signal quality assessment and processing in complex radio environments.

[0115] The third calculation unit 33 calculates the data intensity coefficient QDX through weighted calculation based on the first reference coefficient S1, the second reference coefficient S2, and the third reference coefficient S3. This weighted comprehensive calculation method can effectively synthesize the importance of different signal characteristics, providing a comprehensive signal intensity evaluation index for the system. By dynamically adjusting the weighting coefficients d1, d2, and d3, the system can flexibly adjust the degree of emphasis on various signal characteristics according to changes in the signal environment, making the signal intensity evaluation more accurate and enabling timely optimization decisions when the signal quality fluctuates.

[0116] The system can perform in-depth analysis of signals from multiple dimensions. Through refined window value calculation, dynamic reference coefficient adjustment, and weighted intensity coefficient calculation, the system can evaluate the signal quality from different aspects and determine whether it needs to be enhanced. Traditional radio monitoring systems often make signal evaluations based on limited characteristics, which may carry the risks of misjudgment and slow response. In contrast, the calculation module of this system can comprehensively evaluate the dynamic changes of signals and make optimization and enhancement decisions promptly and accurately. By means of user-adjustable weight values and window sizes, each calculation unit can adapt to different signal environments and requirements. This flexibility provides the system with more adaptability, allowing users to adjust according to actual usage conditions to further optimize system performance and ensure that the system can achieve the best signal enhancement effect in different scenarios.

[0117] Example Five: Please refer to Figure 1 , the data analysis module 4 includes a first data analysis unit 41 and a second data analysis unit 42. The first data analysis unit 41 is used to generate a first comparison result, and the second data analysis unit 42 is used to generate a second comparison result.

[0118] The specific content of the first comparison result is as follows;

[0119] When QDX < Y, it means that the current signal needs to be enhanced;

[0120] When QDX ≥ Y, it means that the current signal does not need to be enhanced;

[0121] The specific content of the second comparison result is as follows;

[0122] When QDJ ≥ R, it means that the current signal is in the first-level state to be enhanced and the signal intensity needs to be increased by 5%;

[0123] When R × 75% ≤ QDJ < R, it means that the current signal is in the second-level state to be enhanced and the signal intensity needs to be increased by 15%;

[0124] When QDJ < R × 75%, it means that the current signal is in the third-level state to be enhanced and the signal intensity needs to be increased by 35%.

[0125] The amplification magnitude coefficient QDJ is calculated by the following formula:

[0126]

[0127] Where: QDX is the data intensity coefficient, Y is the first threshold.

[0128] In this embodiment: This system combines the precise calculation of the data intensity coefficient QDX and the amplification magnitude coefficient QDJ through the first data analysis unit 41 and the second data analysis unit 42 in the data analysis module 4, making the signal enhancement decision more intelligent and flexible, and being able to perform dynamic optimization according to the real-time changes of the signal, thereby significantly improving the accuracy and efficiency of signal enhancement.

[0129] The first data analysis unit 41 and the second data analysis unit 42 jointly complete the signal enhancement decision. First, the first data analysis unit 41 compares the calculated data strength coefficient QDX with the preset first threshold value Y to generate a first comparison result. When the signal needs to be enhanced, the system further compares the amplification magnitude coefficient QDJ with the preset second threshold value R through the second data analysis unit 42 to generate a secondary decision result. This hierarchical enhancement decision can more accurately adjust the enhancement amount according to the difference in signal quality, thereby avoiding over-enhancement or under-enhancement, and improving the efficiency of signal amplification and the rationality of resource use.

[0130] The amplification magnitude coefficient QDJ can be dynamically adjusted according to the data strength coefficient QDX and the first threshold Y. The formula accurately calculates the magnitude that needs to be enhanced based on the difference between the real-time calculated signal strength and the preset threshold. This calculation method provides higher flexibility and accuracy, and can adjust the enhancement strategy in time according to changes in signal strength.

[0131] The system can monitor and optimize signal strength in real time, avoiding the lag, misjudgment or over-enhancement problems in traditional methods, thus significantly improving the response speed and performance efficiency of the radio monitoring system. This intelligent and dynamic decision-making method has obvious advantages over traditional methods in practical applications, especially in complex and rapidly changing signal environments, and can more efficiently manage and optimize signal quality.

[0132] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0133] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A fast signal acquisition system for a radio monitoring receiver, characterized in that: It comprises a data acquisition module (1), a data processing module (2), a data calculation module (3), a data analysis module (4) and a feedback module (5); The data acquisition module (1) is used to collect signals and generate a multi-source data set; The data processing module (2) is used to pre-process the multi-source data set and reorganize the processed multi-source data set into a first data set, a second data set and a third data set; The data calculation module (3) is used to integrate the first data set, the second data set and the third data set to calculate a data intensity coefficient QDX; The data analysis module (4) is used to compare the data intensity coefficient QDX with a preset first threshold value Y, thereby generating a first comparison result, and judging whether the current signal needs to be amplified according to the first comparison result; If the first comparison result indicates that signal amplification is required, the data intensity coefficient QDX is integrated and calculated with the first threshold value Y to generate an amplification magnitude coefficient QDJ, and the amplification magnitude coefficient QDJ is compared with a preset second threshold value R to generate a second comparison result; The feedback module (5) is used to amplify the signal according to the second comparison result.

2. The fast signal acquisition system for a radio monitoring receiver according to claim 1, characterized in that: The data acquisition module (1) comprises a first data acquisition unit (11), a second data acquisition unit (12) and a third data acquisition unit (13); The first data acquisition unit (11) is used to acquire bit rate, signal-to-noise ratio and frequency, the second data acquisition unit (12) is used to acquire bandwidth, power spectrum density and link budget, and the third data acquisition unit (13) is used to acquire delay, harmonic distortion rate and phase error; The bit rate, signal-to-noise ratio, frequency, bandwidth, power spectrum density, link budget, delay, harmonic distortion rate and phase error constitute a multi-source data set.

3. The fast signal acquisition system for a radio monitoring receiver according to claim 2, characterized in that: The data processing module (2) comprises a data preprocessing unit (21) and a data sorting unit (22), wherein the data preprocessing unit (21) is used to preprocess and dimensionlessly transform the multi-source data set, and the data sorting unit (22) is used to sort the processed multi-source data set into a first data set, a second data set, and a third data set respectively; The first data set includes bit error rate, signal-to-noise ratio, and frequency; The bit error rates are recorded as A1, A2, A3, ..., An according to the timestamps; The signal-to-noise ratios are recorded as B1, B2, B3, ..., Bn according to the timestamps; The frequencies are recorded as C1, C2, C3, ..., Cn according to the timestamps; The second data set includes bandwidth, power spectral density, and link budget; The bandwidths are recorded as D1, D2, D3, ..., Dn according to the timestamps; The power spectrum density is recorded as E1, E2, E3, ..., En according to the timestamp; The link budgets are recorded as F1, F2, F3, ..., Fn according to the timestamps; The third data set includes time delay, harmonic distortion, and phase error; The delays are recorded as G1, G2, G3, ..., Gn according to the timestamps; The harmonic distortion rates are recorded as H1, H2, H3, ..., Hn according to the timestamps; The phase errors are recorded as I1, I2, I3, ..., In according to the timestamps.

4. The fast signal acquisition system for a radio monitoring receiver according to claim 3, characterized in that: The data calculation module (3) comprises a first calculation unit (31), a second calculation unit (32) and a third calculation unit (33), wherein the first calculation unit (31) is used to calculate a code rate window value PA, a signal-to-noise ratio window value PB, a frequency window value PC, a bandwidth window value PD, a power spectrum density window value PE, a link budget window value PF, a delay window value PG, a harmonic distortion rate window value PH and a phase error window value PI, the second calculation unit (32) is used to calculate a first reference coefficient S1, a second reference coefficient S2 and a third reference coefficient S3, and the third calculation unit (33) is used to calculate a data intensity coefficient QDX.

5. The rapid signal acquisition system for a radio monitoring receiver according to claim 4, characterized in that: The first calculation unit (31) calculates and obtains a code rate window value PA, a signal-to-noise ratio window value PB, a frequency window value PC, a bandwidth window value PD, a power spectrum density window value PE, a link budget window value PF, a delay window value PG, a harmonic distortion rate window value PH, and a phase error window value PI respectively through the following formulas; Where: m is the window size, indicating that there are m data points in each window, and k is the starting position of the window; Ak, Bk, Ck, Dk, Ek, Fk, Gk, Hk and Ik are the code rate, signal-to-noise ratio, frequency, bandwidth, power spectral density, link budget, delay, harmonic distortion rate and phase error of the kth data point in the data sequence respectively.

6. The rapid signal acquisition system for a radio monitoring receiver according to claim 5, characterized in that: The second calculation unit (32) calculates and obtains the first reference coefficient S1, the second reference coefficient S2 and the third reference coefficient S3 respectively through the following formulas; Wherein: PA, PB, PC, PD, PE, PF, PG, PH and PI are respectively the code rate window value, signal-to-noise ratio window value, frequency window value, bandwidth window value, power spectrum density window value, link budget window value, delay window value, harmonic distortion rate window value and phase error window value; An, Bn, Cn, Dn, En, Fn, Gn, Hn and In are the code rate, signal-to-noise ratio, frequency, bandwidth, power spectrum density, link budget, delay, harmonic distortion rate and phase error of the nth data point in the data sequence respectively; a1, a2, a3, b1, b2, b3, c1, c2 and c3 are weight values, and the values ​​of A1, a2, a3, b1, b2, b3, c1, c2 and c3 are adjusted and set by the user.

7. The rapid signal acquisition system for a radio monitoring receiver according to claim 6, characterized in that: The third calculation unit (33) calculates and obtains the data intensity coefficient QDX by the following formula; QDX = d1 × S1 + d2 × S2 + d3 × S3; In the formula: d1, d2 and d3 are weight values, and the values ​​of d1, d2 and d3 are adjusted and set by the user, S1 is the first reference coefficient, S2 is the second reference coefficient, and S3 is the third reference coefficient.

8. The rapid signal acquisition system for a radio monitoring receiver according to claim 7, characterized in that: The data analysis module (4) comprises a first data analysis unit (41) and a second data analysis unit (42); the first data analysis unit (41) is used to generate a first comparison result, and the second data analysis unit (42) is used to generate a second comparison result.

9. The fast signal acquisition system for a radio monitoring receiver according to claim 8, characterized in that: The first comparison result is as follows: When QDX < Y, it means that the current signal needs to be enhanced; When QDX ≥ Y, it means that the current signal does not need to be enhanced; The specific second comparison result is as follows; When QDJ ≥ R, it means that the current signal is in the first-level state to be enhanced and the signal strength needs to be increased by 5%; When R × 75% ≤ QDJ < R, it means that the current signal is in the second-level state to be enhanced and the signal strength needs to be increased by 15%; When QDJ < R × 75%, it means that the current signal is in the third-level state to be enhanced and the signal strength needs to be increased by 35%.

10. The fast signal acquisition system for a radio monitoring receiver according to claim 9, characterized in that: The amplification level coefficient QDJ is obtained by calculating through the following formula; In the formula: QDX is the data strength coefficient, and Y is the first threshold.

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