A fast signal acquisition system for radio monitoring receivers

Abstract

The present invention relates to the field of radio monitoring technology and discloses a rapid signal acquisition system for a radio monitoring receiver. The system can accurately evaluate signal status and perform real-time signal amplification 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 data organization and preprocessing, the data calculation module and the data analysis module make signal enhancement decisions more accurate and intelligent, and the feedback module ensures rapid response of the system in a real-time environment. The coordinated operation of these modules not only improves the signal processing capability and response speed of the system, but also makes signal enhancement more intelligent and automated.

Description

Technical Field

[0001] The present 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, particularly those designed for rapid signal acquisition, often face challenges with insufficient signal strength and the inability to quickly adjust signal strength in dynamic environments. Many existing systems suffer from slow response times and limited signal processing capabilities in complex signal environments, making it difficult to optimize and adjust to signal changes in real time. This results in low signal amplification efficiency and compromises communication quality. Traditional signal processing methods often rely on fixed thresholds and simple processing logic, making them inflexible in response 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 in 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 solution: 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 to generate a first comparison result, and determine 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 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 bandwidth is recorded as D1, D2, D3, ..., Dn according to the timestamp;

[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 timestamp;

[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 by 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 by the following formulas respectively;

[0036]

[0037] Where: PA, PB, PC, PD, PE, PF, PG, PH and PI are the bit 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 respectively;

[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 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 as follows;

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

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

[0050] When QDJ < R×75%, it means that the current signal is in the third-level to-be-enhanced state and needs to increase the signal strength 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 signal status and amplify signals 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 organization 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 and make optimization and enhancement decisions in a timely and accurate manner. Through user-adjustable weight values ​​and window sizes, each calculation unit can adapt to different signal environments and needs. This flexibility provides the system with more adaptability. 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 clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts 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 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;

[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 to generate a first comparison result, and determine 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 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 configured 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, with its primary task being to collect signals in real time and generate multi-source datasets. By collaborating with multiple data acquisition units, this module can extract a variety of key parameters from different signal sources, such as signal-to-noise ratio, frequency, bandwidth, power spectral density, and latency, ensuring comprehensive signal collection. This collected data provides accurate and comprehensive raw data support for subsequent processing, calculation, and analysis modules. The effective operation of this module ensures the system's ability to cover multiple signal sources and achieve efficient data collection, providing the necessary data foundation for signal enhancement and optimization.

[0068] Data processing module 2 is responsible for preprocessing the multi-source data sets from data acquisition module 1 to ensure the uniformity and validity of the data format. During the preprocessing stage, this module performs operations such as dimensionless transformation to eliminate irrelevant noise in the data and improve data usability. 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, providing a more accurate basis for subsequent signal enhancement decisions. The presence of data processing module 2 improves the system's processing efficiency and data accuracy, making subsequent calculations more efficient.

[0069] Data Calculation Module 3 integrates various processed data sets into a data strength coefficient (QDX), a core metric for signal enhancement and amplification. Through complex mathematical calculations, this module transforms information from multiple data sets into a comprehensive signal strength coefficient, reflecting the current signal strength. The QDX calculation provides a scientific basis for subsequent signal optimization decisions, helping the system accurately assess signal strength requirements. The computational power of Data Calculation Module 3 directly impacts system response speed and signal optimization accuracy, and is crucial for the system's ability to rapidly adapt to dynamic electromagnetic environments.

[0070] The primary task of Data Analysis Module 4 is to determine whether the current signal requires enhancement by comparing it with a preset threshold. By comparing the data intensity coefficient QDX with a first threshold Y, the generated first comparison result determines whether the system should initiate signal amplification. If the signal requires enhancement, Data Analysis Module 4 further calculates the amplification magnitude coefficient QDJ and compares it with a second threshold R to generate a second comparison result. Through precise analysis and intelligent decision-making, Data Analysis Module 4 achieves precise control of signal amplification, avoiding the over- or under-enhancement issues that can occur with traditional methods, thereby ensuring that signal quality remains within the optimal range.

[0071] Feedback module 5 amplifies the signal based on the second comparison result and is the executor of the entire signal enhancement process. Once the signal amplification decision is made, feedback module 5 adjusts the amplification level based on the signal strength requirements 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 signal output to ensure the stability and reliability of communication quality. The presence of feedback module 5 makes signal enhancement not only automated but also able to adapt in real time to changing environments, avoiding the complexity and delay of traditional manual adjustments and greatly improving the real-time and flexibility of the system.

[0072] Traditional radio monitoring systems, when faced with complex signals and dynamic environments, often rely on simple fixed parameters and thresholds, making them unable to quickly adjust signal strength or process complex data. However, through sophisticated data acquisition, multidimensional data processing, comprehensive calculations, and intelligent analysis, this system can accurately assess signal status and amplify signals in real time in dynamically changing electromagnetic environments. Data acquisition module 1 provides comprehensive signal source data, data processing module 2 ensures efficient data organization and preprocessing, data calculation module 3 and data analysis module 4 enable more accurate and intelligent signal enhancement decisions, and feedback module 5 ensures rapid system response in real-time environments. The collaborative work of these modules not only improves the system's signal processing capabilities 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 collect bit rate, signal-to-noise ratio and frequency, the second data acquisition unit 12 is used to collect bandwidth, power spectrum density and link budget, and the third data acquisition unit 13 is used to collect 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, forming a more comprehensive and detailed multi-source data set.

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

[0078] By collecting a wider range of signal parameters, the system can comprehensively assess 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 assess signal stability and transmission efficiency. This multi-dimensional signal data enables Data Processing Module 2 to perform more precise data organization and analysis, providing a solid foundation for subsequent signal amplification and optimization decisions.

[0079] In complex electromagnetic environments or scenarios with poor signal quality, traditional single-source data acquisition methods often fail to detect problems or implement effective optimizations in a timely manner. By introducing multiple data acquisition units, the system can more flexibly respond to various environmental changes, ensuring real-time and accurate signal enhancement, thereby improving the system's adaptability and robustness.

[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 dimensionlessly transform the multi-source data set. 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.

[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 bandwidth is recorded as D1, D2, D3, ..., Dn according to the timestamp;

[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 timestamp;

[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 data preprocessing unit 21 and data collation unit 22, the system can more efficiently and accurately process signal data from multiple sources. This not only improves data standardization and dimensionless processing, but also enhances the ability to track signal changes through time series. This multi-level, multi-dimensional data management approach enables the system to more accurately capture changes in signal characteristics and optimize signal enhancement decisions in complex and changing radio environments, ultimately improving the flexibility, accuracy, and reliability of signal processing.

[0095] The data preprocessing unit 21 preprocesses and dimensionlessly transforms the collected multi-source data sets, eliminating redundancy and noise. This makes the data more standardized and scalable, facilitating subsequent processing and calculations. This approach ensures seamless integration of data from different sources and eliminates the impact of differences between signal sources, improving data validity and accuracy. 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, ensuring system consistency and stability under different signal conditions.

[0096] By recording each data item with a timestamp, the data collation unit 22 can correlate the changes in each data point with time, forming a precise 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. It can accurately capture fluctuations in signal strength, enabling more precise signal enhancement decisions.

[0097] The data organization unit 22 divides the preprocessed data into a first dataset, a second dataset, and a third dataset. Each dataset includes different signal characteristics. For example, the first dataset includes bit error rate, signal-to-noise ratio, and frequency, while the second dataset includes bandwidth, power spectral density, and link budget. This structured organization method effectively improves the efficiency of subsequent analysis and calculation, allowing each dataset to be processed independently based on 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, improving the accuracy of the overall signal enhancement process.

[0098] By organizing precise time series data and multi-dimensional signal characteristics, the system can more flexibly adapt to different signal requirements in dynamically changing radio environments. For example, in complex radio spectrum environments, signal characteristics such as delay and harmonic distortion can affect signal quality. By organizing timestamps and multiple data sets, the system can understand these changes in real time and respond promptly, effectively improving signal reliability and stability.

[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 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;

[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] Where: PA, PB, PC, PD, PE, PF, PG, PH and PI are the bit 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 respectively;

[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 and obtains the data intensity coefficient QDX by the following formula:

[0110] QDX=d1×S1+d2×S2+d3×S3;

[0111] Wherein: 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 introduces a data calculation module 3, which includes a first calculation unit 31, a second calculation unit 32, and a third calculation unit 33, to achieve multi-dimensional, dynamic calculation and evaluation of signal quality. This design improvement not only improves the accuracy of signal analysis but also enables adaptive adjustments based on actual signal changes, significantly enhancing the system's response speed and processing capabilities.

[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 spectral density, link budget, delay, harmonic distortion rate, and phase error, significantly improving the ability to analyze signal characteristics in a fine-grained manner. Compared with traditional signal calculation methods, window value calculation can capture the dynamic changes of the signal, allowing the system to 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 the signal. This calculation method effectively avoids the impact of long-term data lag and enhances the system's responsiveness.

[0114] The second calculation unit 32 introduces adaptive reference coefficients S1, S2, and S3 calculations based on signal differences. This formula compares the current signal state with the calculated window value to derive the reference coefficients. 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 optimize in real time based on different signal changes, avoiding the limitations of fixed thresholds and standardized parameters, enabling 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 features, 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, 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, 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] Embodiment 5: 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待增强 state and needs to increase the signal intensity by 5%;

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

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

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

[0126]

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

[0128] In this embodiment: This system combines the first data analysis unit 41 and the second data analysis unit 42 in the data analysis module 4 with the precise calculation of the data intensity coefficient QDX and the amplification magnitude coefficient QDJ, making the signal enhancement decision more intelligent and flexible, and can be dynamically optimized 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 Y to generate a first comparison result. If the signal needs to be enhanced, the system further compares the amplification magnitude coefficient QDJ with the preset second threshold 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 based on the difference in signal quality, thereby avoiding over-enhancement or under-enhancement, improving the efficiency of signal amplification and the rationality of resource utilization.

[0130] The amplification factor, QDJ, is dynamically adjusted based on the data strength factor, QDX, and the first threshold, Y. This formula accurately calculates the required boost level based on the difference between the real-time calculated signal strength and the preset threshold. This calculation method provides greater flexibility and accuracy, enabling timely adjustments to the boost strategy based on changes in signal strength.

[0131] The system monitors and optimizes signal strength in real time, avoiding the lag, misjudgment, or over-enhancement issues found in traditional methods, significantly improving the response speed and performance efficiency of radio monitoring systems. This intelligent, dynamic decision-making approach offers significant advantages over traditional methods in practical applications, particularly in complex and rapidly changing signal environments, enabling more efficient management and optimization of signal quality.

[0132] The contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[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 scope of protection of the present invention.

Claims

1. A fast signal acquisition system for a radio monitoring receiver, characterized in that: It includes 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 multi-source data sets; 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 the data intensity coefficient QDX; The data calculation module (3) includes 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 strength coefficient QDX; 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; 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 spectrum density, link budget, delay, harmonic distortion rate, and phase error of the kth data point in the data sequence, respectively; 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 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 for performing signal amplification according to the second comparison result.

2. The rapid 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 rapid signal acquisition system for a radio monitoring receiver according to claim 2, characterized in that: The data processing module (2) includes 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. 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 bandwidth is recorded as D1, D2, D3, ..., Dn according to the timestamp; 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 timestamp; 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 rapid signal acquisition system for a radio monitoring receiver according to claim 3, 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; Where: PA, PB, PC, PD, PE, PF, PG, PH and PI are the bit 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 respectively; 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.

5. The rapid signal acquisition system for a radio monitoring receiver according to claim 4, 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; Wherein: 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.

6. The rapid signal acquisition system for a radio monitoring receiver according to claim 5, characterized in that: The data analysis module (4) comprises a first data analysis unit (41) and a second data analysis unit (42), wherein 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.

7. The rapid signal acquisition system for a radio monitoring receiver according to claim 6, characterized in that: The specific first comparison result is as follows; When QDX < Y, it represents that the current signal needs to be enhanced; When QDX ≥ Y, it represents that the current signal does not need to be enhanced; The specific second comparison result is as follows; When QDJ ≥ R, it represents that the current signal is in the first-level to-be-enhanced state and the signal strength needs to be increased by 5%; When R × 75% ≤ QDJ < R, it represents that the current signal is in the second-level to-be-enhanced state and the signal strength needs to be increased by 15%; When QDJ < R × 75%, it represents that the current signal is in the third-level to-be-enhanced state and the signal strength needs to be increased by 35%.

8. The rapid signal acquisition system for a radio monitoring receiver according to claim 7, characterized in that: The amplification level coefficient QDJ is obtained through the following formula; In the formula: QDX is the data strength coefficient, and Y is the first threshold value.

Images