Radio station threshold debugging method of portable radio, electronic equipment and storage medium

Abstract

The invention provides a radio station threshold value debugging method of a portable radio, electronic equipment and a storage medium, and relates to the technical field of radio station threshold value debugging, and the method specifically comprises the steps: obtaining initial signal feature data, carrying out the average processing of the obtained initial signal feature data, carrying out the frequency disturbance based on the initial signal feature data obtained in S100, and obtaining a radio station threshold value debugging result; s200, performing change rate calculation on the basis of the response change data obtained in the S200, performing analysis on the basis of a change rate calculation result, obtaining initial signal characteristic data in a receiving range of the portable radio, and applying tiny frequency disturbance to the signal, so as to obtain the characteristic data of the portable radio. According to the method, deep analysis of signal response change characteristics is realized, the sensitivity of the signal to frequency disturbance can be identified by acquiring response data of the signal under different disturbance frequencies and calculating the change rate, and the method has a dimensionality of judging the authenticity of the signal, so that the accuracy of signal identification is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of true and false radio station threshold debugging, and in particular to a radio station threshold debugging method, electronic equipment and storage medium of a portable radio. Background Art

[0002] As a common wireless receiving device, portable radio is widely used in various environments due to its portability and ease of use. Usually, portable radio achieves audio playback by receiving radio station signals in a specified frequency band. However, in a complex signal environment, especially in areas with more electromagnetic interference, the radio may receive false signals, interference signals or non-radio signals, making it difficult for users to effectively distinguish between real radio station signals and false radio station signals, seriously affecting the user's normal usage experience.

[0003] Existing methods for identifying true and false radio station signals mainly rely on the frequency and intensity characteristics of the signal and judge the authenticity of the signal through static thresholds. However, these methods have great limitations in complex environments and are easily interfered by environmental noise, resulting in a high misjudgment rate. Especially when the electromagnetic environment changes frequently, the static threshold is difficult to effectively adapt to different signal conditions, resulting in poor recognition effect.

[0004] In addition, although some technologies attempt to use dynamically adjusted thresholds, due to the lack of in-depth analysis of the changing characteristics of signal response, it is still difficult to achieve high-precision false signal filtering, and the recognition accuracy and environmental adaptability need to be improved.

[0005] Therefore, it is urgent to propose a radio station threshold debugging method for a portable radio. Summary of the invention

[0006] The present invention provides a radio threshold debugging method, electronic device and storage medium of a portable radio, aiming to utilize frequency disturbance analysis and change rate calculation, combined with dynamic threshold setting and user feedback mechanism, to effectively improve the accuracy and adaptability of pseudo signal recognition, by dynamically analyzing the response change of the signal under a small frequency disturbance, setting the frequency disturbance dynamic threshold and the abnormal response number threshold, and combining user feedback adjustment to ensure that the radio can automatically optimize the pseudo signal recognition standard in a complex environment, compared with the traditional method, the false judgment rate is reduced, and the signal reception stability of the portable radio in a changeable environment is enhanced.

[0007] To achieve the above object, the present invention provides a first aspect of a radio station threshold debugging method for a portable radio, comprising the following steps:

[0008] S100, acquiring initial signal characteristic data, and performing average processing on the initial signal characteristic data;

[0009] S200, performing frequency disturbance on the initial signal characteristic data, and obtaining response change data under the disturbance frequency;

[0010] S300, calculating the change rate of the response change data, and performing analysis based on the change rate calculation result;

[0011] S400, setting a frequency disturbance dynamic threshold based on the data obtained after the analysis in S300, and performing analysis based on the data obtained after the frequency disturbance dynamic threshold is adjusted;

[0012] S500, based on the analysis result of the frequency disturbance dynamic threshold adjustment obtained in S400, setting and determining the abnormal response number threshold;

[0013] S600: Adjust the frequency disturbance dynamic threshold based on user tag feedback.

[0014] Preferably, the obtaining of initial signal characteristic data and averaging the obtained initial signal characteristic data specifically includes:

[0015] Step S100.1: When the portable radio is started for the first time in a new environment, the predetermined frequency band range is scanned in sequence, and receivable signals in each frequency band are detected step by step.

[0016] The frequency band scans a predetermined range of 88 MHz to 108 MHz.

[0017] The frequency increment of each scan is 0.1MHz, ensuring full coverage of the entire frequency band.

[0018] Step S100.1.1, based on scanning the acceptable signals in each frequency band, including: signal frequency, strength and spectrum characteristics, obtain initial signal characteristic data.

[0019] Among them, frequency is used to identify the basic position of the signal, intensity is used to reflect the relative strength of signal reception, and spectrum characteristics are used to provide more signal information for subsequent judgment.

[0020] Step S100.1.2, performing sampling value averaging processing based on the acquired initial signal characteristic data;

[0021] The averaging process is to collect the frequency, intensity and spectrum characteristics of each frequency band signal for 3 to 5 times respectively, add the sampled values ​​and divide them by the number of sampling times to obtain the average value of the initial signal characteristic data.

[0022] It should be noted that, since sampling value averaging processing is an existing technology well known to those skilled in the art, it will not be described in detail here.

[0023] Preferably, the frequency disturbance is performed on the initial signal characteristic data, and the response change data under the disturbance frequency is obtained, and the specific steps are:

[0024] Step S200.1: Perform frequency perturbation based on the acquired initial signal characteristic data.

[0025] Step S200.1.1: Based on the initial frequency of the initial signal characteristic data, set the small frequency disturbance range to 0.1 MHz.

[0026] The disturbance range is around the initial frequency of the target signal, and is increased or decreased in small increments of 0.01 MHZ to generate different micro-disturbance frequencies.

[0027] The disturbance range shall not exceed 0.02MHz to avoid interfering with signal reception in adjacent frequency bands.

[0028] Step S200.2: Based on the disturbance range of the initial frequency, apply a small frequency disturbance range in small increments.

[0029] Among them, the range of small frequency disturbance is to increase the frequency by 0.01MHz and then decrease it by 0.01MHz, and record the changes in signal strength and stability at each disturbance frequency.

[0030] Step S200.2.1, perform repeated detection based on the disturbance frequency, and record the signal response at each disturbance frequency.

[0031] Step S200.2.2: Generate response change data of the initial signal characteristic data under various disturbance frequencies by cyclically applying different micro-disturbances.

[0032] Preferably, the change rate is calculated based on the response change data obtained in step S200, and analysis is performed based on the change rate calculation result, specifically:

[0033] Step S300.1: Record response change data based on initial signal characteristic data at each disturbance frequency.

[0034] Step S300.1.1: The intensity change and stability fluctuation caused by each disturbance frequency are recorded as frequency disturbance response change rate data, and multiple groups of signal response data sets under disturbance frequencies are formed.

[0035] Step S300.2: Calculate the rate of change based on the signal response data set under each set of disturbance frequencies.

[0036] The change rate calculation is the relative change rate calculation between the original values ​​of the signal strength and stability at each disturbance frequency in the initial signal characteristic data, specifically:

[0037]

[0038] In the formula: the signal value under the disturbance frequency refers to the signal strength or stability value measured after applying a specific disturbance frequency, the initial signal value refers to the signal strength in the initial signal characteristic data recorded in step S100, which is used as the reference value of the initial signal characteristic data, and the rate of change refers to the relative change of the signal value relative to the initial signal value after applying the disturbance frequency, which is specifically reflected in the degree of response change of the signal strength or stability under different disturbance frequencies, wherein the larger the value of the rate of change, the more sensitive the signal response to the disturbance frequency.

[0039] Step S300.3: After calculating the change rates of all disturbance frequencies based on the change rate, further analyze the frequency disturbance response change rate data.

[0040] Among them, analysis means that if the rate of change at multiple disturbance frequencies obviously deviates from the normal fluctuation range of the initial signal characteristic data, it indicates that the initial signal characteristic data is abnormally sensitive to tiny frequency disturbances and is a suspected false signal.

[0041] Preferably, the frequency disturbance dynamic threshold is set based on the data obtained after the analysis in step S300, and the analysis is performed based on the data obtained after the frequency disturbance dynamic threshold is adjusted, specifically:

[0042] Step S400.1: Based on the analyzed frequency disturbance response change rate data, a reference range is calculated by statistically analyzing the mean and standard deviation of the change rate data, and the obtained reference range represents the change rate range of a normal signal.

[0043] Step S400.1.1: Set a frequency disturbance dynamic threshold based on a reference range as a benchmark for identifying abnormal signal responses.

[0044] The frequency disturbance dynamic threshold is defined as the mean of the rate of change data plus a certain multiple of the standard deviation to determine whether the rate of change of the normal signal is lower than the frequency disturbance dynamic threshold, specifically:

[0045] Frequency disturbance dynamic threshold = μ + k·σ

[0046] Wherein: The frequency disturbance dynamic threshold is used to determine whether the signal is an abnormal response. When the rate of change data exceeds the frequency disturbance dynamic threshold, the signal will be marked as abnormal and then identified as a suspected false signal.

[0047] Among them, μ is the mean of the rate of change data, which represents the average value of the signal response change rate under all disturbance frequencies. The mean μ is used to reflect the typical changes of normal signals under different disturbance frequency conditions, specifically:

[0048]

[0049] Where: N is the total number of rate of change data, that is, the number of rate of change data points recorded under different disturbance frequency conditions, R i It is the rate of change data at each disturbance frequency, indicating the response change rate of the signal at a specific disturbance frequency.

[0050] Among them, σ is the standard deviation of the rate of change data, which is used to describe the degree of dispersion of the rate of change data relative to the mean μ. The larger the standard deviation σ, the greater the volatility of the signal response change under different disturbance frequency conditions, specifically:

[0051]

[0052] Where: (R i -μ) 2 It is the square difference between the rate of change data and the mean, indicating the degree of deviation of each rate of change data point from the mean. All deviation values ​​are squared and summed.

[0053] Among them, k is the adjustment coefficient, which is used to control the sensitivity of the frequency disturbance dynamic threshold. The value of the adjustment coefficient k is between 1 and 3. When k=2, the frequency disturbance dynamic threshold will cover the range of the mean plus two standard deviations, and the change rate of most normal signals will be controlled below the threshold. The change rate exceeding this range will be identified as an abnormal response.

[0054] In the above formula, the mean μ reflects the central value of the normal signal change, the standard deviation σ reflects the fluctuation range of the signal change, and the frequency disturbance dynamic threshold is set to μ+k·σ, which can effectively cover the variation range of the normal signal. The flexible adjustment coefficient k allows the threshold to adapt to the signal fluctuation in different environments, ensuring accurate identification of abnormal change rates.

[0055] Step S400.2, compare the change rate data under the disturbance frequency after adjustment based on the frequency disturbance dynamic threshold one by one, and check whether it exceeds the frequency disturbance dynamic threshold. If the change rate under the frequency disturbance exceeds the threshold, it indicates that the response of the initial signal characteristic data under this disturbance frequency exceeds the normal range and has abnormal sensitivity.

[0056] Step S400.3: Based on the comparison result, all change rates exceeding the frequency disturbance dynamic threshold are marked as abnormal responses.

[0057] Among them, if the change rates of multiple disturbance frequencies are all marked as abnormal responses, it is considered that the response of the initial signal characteristic data is significantly abnormal and is identified as a false signal.

[0058] Preferably, based on the analysis result after the frequency disturbance dynamic threshold adjustment obtained in step S400, the abnormal response number threshold is set and determined, specifically including:

[0059] Step S500.1: Based on the comparison result, count the number of abnormal responses of each initial signal characteristic data, including the distribution at different disturbance frequencies.

[0060] Among them, the abnormal response number threshold is set to 3.

[0061] When the number of abnormal responses of the initial signal characteristic data at different disturbance frequencies reaches or exceeds 3 times, it is judged as a false signal.

[0062] Step S500.2: Based on the abnormal response statistics, further compare the overall response characteristics of the initial signal feature data.

[0063] Among them, if a signal shows abnormal response under multiple disturbance frequencies, it can be regarded as unstable under the condition of small frequency disturbance, that is, it has possible pseudo signal characteristics.

[0064] Step S500.3: Based on the comparison and analysis results, if the number of abnormal responses of a certain signal at different disturbance frequencies reaches or exceeds the abnormal response number threshold, it is further determined to be a false signal.

[0065] Preferably, adjusting the frequency disturbance dynamic threshold based on user tag feedback specifically includes:

[0066] Step S600.1: Based on the initial signal feature data received daily, the user can manually mark it as a false signal or a misjudged signal. The feedback based on the manual marking will be recorded and used as the basis for adjusting the frequency disturbance dynamic threshold and updating the false signal feature data set.

[0067] Step S600.2: Based on the user's manual note feedback, regularly perform environmental signal analysis on the new initial signal feature data set and monitor signal fluctuations in the environment.

[0068] Among them, environmental signal analysis and environmental signal fluctuations, including the intensity changes and stability distribution of different frequency bands, are used to determine whether there are many signal fluctuations in the current environment. When frequent interference or fluctuations are detected, the frequency disturbance dynamic threshold is appropriately adjusted. It is specifically divided into general receiving environment, high noise receiving environment and high stability receiving environment.

[0069] Among them, based on the general receiving environment, the threshold calculation method of the change rate mean plus twice the standard deviation is adopted, that is, k=2 is set, specifically:

[0070] Frequency disturbance dynamic threshold = μ + 2·σ

[0071] Among them, based on the high noise receiving environment and frequent interference signals, the frequency disturbance dynamic threshold is appropriately relaxed and k=3 is set, specifically:

[0072] Frequency disturbance dynamic threshold = μ + 3·σ

[0073] In the case of a high-stability receiving environment, the tolerance of the dynamic threshold of the frequency disturbance is reduced, and k=1 is set as follows:

[0074] Frequency disturbance dynamic threshold = μ + 3·σ

[0075] It should be noted that since the meaning of the formula has been explained in step S400, it will not be repeated here.

[0076] Step S600.3: recalculate the frequency disturbance dynamic threshold based on user feedback and environmental signal analysis results.

[0077] Among them, if there is misjudgment or missed false signal in the user feedback, the adjustment coefficient k is appropriately increased or decreased to flexibly adjust the sensitivity of the frequency disturbance dynamic threshold. When the signal interference increases in the environment, the k value can be increased to reduce misjudgment, and in the environment with high stability requirements, the k value can be reduced to improve the recognition sensitivity of false signals.

[0078] A second aspect of the present application provides an electronic device, including:

[0079] Processor; and

[0080] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the method as described above.

[0081] A third aspect of the present application provides a storage medium having executable code stored thereon. When the executable code is executed by a processor of a control system, the processor is caused to execute the method described above.

[0082] In the present application, the initial signal characteristic data within the receiving range of the portable radio is obtained, and the frequency disturbance is applied based on the initial signal characteristic data, the response change data of the signal under the disturbance frequency condition is collected, the change rate analysis is performed on the response change data under different disturbance frequencies, and the frequency disturbance dynamic threshold is set by statistically analyzing the mean and standard deviation of the change rate data to determine the normal fluctuation range of the signal response, and the abnormal response number threshold is set based on the dynamic threshold analysis result, and the suspected false signal is identified and marked by comparing the abnormal response number, and the frequency disturbance dynamic threshold is dynamically adjusted in combination with the user's manual feedback and the fluctuation analysis of the environmental signal to ensure the recognition process It can adapt to different changes in signal environments, and effectively improves the accuracy and reliability of identifying true and false radio stations through frequency disturbance analysis, dynamic threshold setting and user feedback optimization mechanism. Compared with the prior art, the present invention not only identifies the frequency and intensity characteristics of radio signals, but also comprehensively considers the signal response changes under frequency disturbances, and can adapt to changeable signal reception environments. In addition, the present invention can more accurately identify and eliminate false signals through automated dynamic threshold adjustment and user feedback mechanism, thereby improving the signal quality and user experience of portable radios in complex radio reception environments, and effectively solving the problems of misidentification and insufficient adaptability in the prior art.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] 1. The present invention obtains the initial signal characteristic data within the receiving range of the portable radio and applies a small frequency disturbance to the signal, thereby achieving an in-depth analysis of the signal response change characteristics. By collecting the response data of the signal at different disturbance frequencies and calculating the rate of change, the sensitivity of the signal to the frequency disturbance can be identified. This method effectively improves the accuracy of signal recognition by judging the authenticity of the signal.

[0085] 2. The present invention calculates the dynamic threshold of frequency disturbance based on the mean and standard deviation of the change rate data through the setting of dynamic threshold, which can adapt to complex signal environments. The dynamic threshold ensures that normal signals are stably received within the fluctuation range, and abnormal responses exceeding the threshold are marked and identified. Combined with the setting of the threshold of the number of abnormal responses, false signals of frequently occurring abnormal responses can be effectively filtered out, greatly reducing the misjudgment rate. At the same time, the flexible adjustment mechanism of the dynamic threshold can adapt to different noise levels and environmental changes, further enhancing the environmental adaptability of signal recognition.

[0086] 3. The present invention further optimizes the pseudo-signal determination process through a user feedback mechanism, ensuring that the portable radio can automatically update the frequency disturbance dynamic threshold and pseudo-signal feature data set according to the user's manual marking, and automatically adapt to different signal reception conditions by combining user feedback and environmental signal analysis, thereby effectively identifying and eliminating pseudo-signals in a changing signal environment. In addition, it not only improves the accuracy of signal recognition, but also enhances the ability to adapt to complex environments, greatly improving the user's listening experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] The above and other objects, features and advantages of the present application will become more apparent through a more detailed description of exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0088] Figure 1 A flowchart of a radio station threshold debugging method for a portable radio provided in an embodiment of the present application;

[0089] Figure 2 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0090] The following will combine 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 them. 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.

[0091] See also Figure 1 , Figure 1 A flowchart of a method for debugging a radio station threshold of a portable radio is provided for an embodiment of the present application.

[0092] In this embodiment, a method for debugging a radio station threshold of a portable radio may include steps S100, S200, S300, S400, S500 and S600.

[0093] Step S100: Acquire initial signal characteristic data, and perform averaging processing on the acquired initial signal characteristic data.

[0094] Specifically, they include:

[0095] Step S100.1: When the portable radio is started for the first time in a new environment, the predetermined frequency band range is scanned in sequence, and receivable signals in each frequency band are detected step by step.

[0096] The frequency band scans a predetermined range of 88 MHz to 108 MHz.

[0097] The frequency increment of each scan is 0.1MHz, ensuring full coverage of the entire frequency band.

[0098] Step S100.1.1, based on scanning the acceptable signals in each frequency band, including: signal frequency, strength and spectrum characteristics, obtain initial signal characteristic data.

[0099] Among them, frequency is used to identify the basic position of the signal, intensity is used to reflect the relative strength of signal reception, and spectrum characteristics are used to provide more signal information for subsequent judgment.

[0100] Step S100.1.2, performing sampling value averaging processing based on the acquired initial signal characteristic data;

[0101] The averaging process is to collect the frequency, intensity and spectrum characteristics of each frequency band signal for 3 to 5 times respectively, add the sampled values ​​and divide them by the number of sampling times to obtain the average value of the initial signal characteristic data.

[0102] It should be noted that, since sampling value averaging processing is an existing technology well known to those skilled in the art, it will not be described in detail here.

[0103] Step S200: Perform frequency disturbance based on the initial signal characteristic data obtained in step S100, and obtain response change data under the disturbance frequency.

[0104] Specifically, they include:

[0105] Step S200.1: Perform frequency perturbation based on the acquired initial signal characteristic data.

[0106] Step S200.1.1: Based on the initial frequency of the initial signal characteristic data, set the small frequency disturbance range to 0.1 MHz.

[0107] The disturbance range is around the initial frequency of the target signal, and is increased or decreased in small increments of 0.01 MHZ to generate different micro-disturbance frequencies.

[0108] The disturbance range shall not exceed 0.02MHz to avoid interfering with signal reception in adjacent frequency bands.

[0109] Step S200.2: Based on the disturbance range of the initial frequency, apply a small frequency disturbance range in small increments.

[0110] Among them, the range of small frequency disturbance is to increase the frequency by 0.01MHz and then decrease it by 0.01MHz, and record the changes in signal strength and stability at each disturbance frequency.

[0111] Step S200.2.1, perform repeated detection based on the disturbance frequency, and record the signal response at each disturbance frequency.

[0112] Step S200.2.2: Generate response change data of the initial signal characteristic data under various disturbance frequencies by cyclically applying different micro-disturbances.

[0113] Step S300: Calculate the change rate based on the response change data obtained in step S200, and perform analysis based on the change rate calculation result.

[0114] Specifically, they include:

[0115] Step S300.1: Record response change data based on initial signal characteristic data at each disturbance frequency.

[0116] Step S300.1.1: The intensity change and stability fluctuation caused by each disturbance frequency are recorded as frequency disturbance response change rate data, and multiple groups of signal response data sets under disturbance frequencies are formed.

[0117] Step S300.2: Calculate the rate of change based on the signal response data set under each set of disturbance frequencies.

[0118] The change rate calculation is the relative change rate calculation between the original values ​​of the signal strength and stability at each disturbance frequency in the initial signal characteristic data, specifically:

[0119]

[0120] In the formula: the signal value under the disturbance frequency refers to the signal strength or stability value measured after applying a specific disturbance frequency, the initial signal value refers to the signal strength in the initial signal characteristic data recorded in step S100, which is used as the reference value of the initial signal characteristic data, and the rate of change refers to the relative change of the signal value relative to the initial signal value after applying the disturbance frequency, which is specifically reflected in the degree of response change of the signal strength or stability under different disturbance frequencies, wherein the larger the value of the rate of change, the more sensitive the signal response to the disturbance frequency.

[0121] Step S300.3: After calculating the change rates of all disturbance frequencies based on the change rate, further analyze the frequency disturbance response change rate data.

[0122] Among them, analysis means that if the rate of change at multiple disturbance frequencies obviously deviates from the normal fluctuation range of the initial signal characteristic data, it indicates that the initial signal characteristic data is abnormally sensitive to tiny frequency disturbances and is a suspected false signal.

[0123] Step S400, setting the frequency disturbance dynamic threshold based on the data obtained after the analysis in step S300, and performing analysis based on the data obtained after the frequency disturbance dynamic threshold is adjusted.

[0124] Specifically, they include:

[0125] Step S400.1: Based on the analyzed frequency disturbance response change rate data, a reference range is calculated by statistically analyzing the mean and standard deviation of the change rate data, and the obtained reference range represents the change rate range of a normal signal.

[0126] Step S400.1.1: Set a frequency disturbance dynamic threshold based on a reference range as a benchmark for identifying abnormal signal responses.

[0127] The frequency disturbance dynamic threshold is defined as the mean of the rate of change data plus a certain multiple of the standard deviation to determine whether the rate of change of the normal signal is lower than the frequency disturbance dynamic threshold, specifically:

[0128] Frequency disturbance dynamic threshold = μ + k·σ

[0129] Wherein: The frequency disturbance dynamic threshold is used to determine whether the signal is an abnormal response. When the rate of change data exceeds the frequency disturbance dynamic threshold, the signal will be marked as abnormal and then identified as a suspected false signal.

[0130] Among them, μ is the mean of the rate of change data, which represents the average value of the signal response change rate under all disturbance frequencies. The mean μ is used to reflect the typical changes of normal signals under different disturbance frequency conditions, specifically:

[0131]

[0132] Where: N is the total number of rate of change data, that is, the number of rate of change data points recorded under different disturbance frequency conditions, R i It is the rate of change data at each disturbance frequency, indicating the response change rate of the signal at a specific disturbance frequency.

[0133] Among them, σ is the standard deviation of the rate of change data, which is used to describe the degree of dispersion of the rate of change data relative to the mean μ. The larger the standard deviation σ, the greater the volatility of the signal response change under different disturbance frequency conditions, specifically:

[0134]

[0135] Where: (R i -μ) 2 It is the square difference between the rate of change data and the mean, indicating the degree of deviation of each rate of change data point from the mean. All deviation values ​​are squared and summed.

[0136] Among them, k is the adjustment coefficient, which is used to control the sensitivity of the frequency disturbance dynamic threshold. The value of the adjustment coefficient k is between 1 and 3. When k=2, the frequency disturbance dynamic threshold will cover the range of the mean plus two standard deviations, and the change rate of most normal signals will be controlled below the threshold. The change rate exceeding this range will be identified as an abnormal response.

[0137] In the above formula, the mean μ reflects the central value of the normal signal change, the standard deviation σ reflects the fluctuation range of the signal change, and the frequency disturbance dynamic threshold is set to μ+k·σ, which can effectively cover the variation range of the normal signal. The flexible adjustment coefficient k allows the threshold to adapt to the signal fluctuation in different environments, ensuring accurate identification of abnormal change rates.

[0138] Step S400.2, compare the change rate data under the disturbance frequency after adjustment based on the frequency disturbance dynamic threshold one by one, and check whether it exceeds the frequency disturbance dynamic threshold. If the change rate under the frequency disturbance exceeds the threshold, it indicates that the response of the initial signal characteristic data under this disturbance frequency exceeds the normal range and has abnormal sensitivity.

[0139] Step S400.3: Based on the comparison result, all change rates exceeding the frequency disturbance dynamic threshold are marked as abnormal responses.

[0140] Among them, if the change rates of multiple disturbance frequencies are all marked as abnormal responses, it is considered that the response of the initial signal characteristic data is significantly abnormal and is identified as a false signal.

[0141] Step S500: Based on the analysis result of the frequency disturbance dynamic threshold adjustment obtained in step S400, the abnormal response number threshold is set and determined.

[0142] Specifically, they include:

[0143] Step S500.1: Based on the comparison result, count the number of abnormal responses of each initial signal characteristic data, including the distribution at different disturbance frequencies.

[0144] Among them, the abnormal response number threshold is set to 3.

[0145] When the number of abnormal responses of the initial signal characteristic data at different disturbance frequencies reaches or exceeds 3 times, it is judged as a false signal.

[0146] Step S500.2: Based on the abnormal response statistics, further compare the overall response characteristics of the initial signal feature data.

[0147] Among them, if a signal shows abnormal response under multiple disturbance frequencies, it can be regarded as unstable under the condition of small frequency disturbance, that is, it has possible pseudo signal characteristics.

[0148] Step S500.3: Based on the comparison and analysis results, if the number of abnormal responses of a certain signal at different disturbance frequencies reaches or exceeds the abnormal response number threshold, it is further determined to be a false signal.

[0149] Step S600: adjusting the frequency disturbance dynamic threshold based on user tag feedback.

[0150] Specifically, they include:

[0151] Step S600.1: Based on the initial signal feature data received daily, the user can manually mark it as a false signal or a misjudged signal. The feedback based on the manual marking will be recorded and used as the basis for adjusting the frequency disturbance dynamic threshold and updating the false signal feature data set.

[0152] Step S600.2: Based on the user's manual note feedback, regularly perform environmental signal analysis on the new initial signal feature data set and monitor signal fluctuations in the environment.

[0153] Among them, environmental signal analysis and environmental signal fluctuations, including the intensity changes and stability distribution of different frequency bands, are used to determine whether there are many signal fluctuations in the current environment. When frequent interference or fluctuations are detected, the frequency disturbance dynamic threshold is appropriately adjusted. It is specifically divided into general receiving environment, high noise receiving environment and high stability receiving environment.

[0154] Among them, based on the general receiving environment, the threshold calculation method of the change rate mean plus twice the standard deviation is adopted, that is, k=2 is set, specifically:

[0155] Frequency disturbance dynamic threshold = μ + 2·σ

[0156] Among them, based on the high noise receiving environment and frequent interference signals, the frequency disturbance dynamic threshold is appropriately relaxed and k=3 is set, specifically:

[0157] Frequency disturbance dynamic threshold = μ + 3·σ

[0158] In the case of a high-stability receiving environment, the tolerance of the dynamic threshold of the frequency disturbance is reduced, and k=1 is set as follows:

[0159] Frequency disturbance dynamic threshold = μ + 3·σ

[0160] It should be noted that since the meaning of the formula has been explained in step S400, it will not be repeated here.

[0161] Step S600.3: recalculate the frequency disturbance dynamic threshold based on user feedback and environmental signal analysis results.

[0162] Among them, if there is misjudgment or missed false signal in the user feedback, the adjustment coefficient k is appropriately increased or decreased to flexibly adjust the sensitivity of the frequency disturbance dynamic threshold. When the signal interference increases in the environment, the k value can be increased to reduce misjudgment, and in the environment with high stability requirements, the k value can be reduced to improve the recognition sensitivity of false signals.

[0163] In the above content, in actual application, first, when the portable radio is started for the first time or enters a new environment, the initial signal characteristic data within the receiving range is obtained, including the frequency, strength and spectral characteristics of the signal, as the benchmark data for signal judgment. The specific operation is to scan all signals within the preset frequency band one by one, and record the basic information such as the frequency, strength and spectral characteristics of each signal in turn for subsequent analysis. This step samples each signal feature 3-5 times and takes the average value to ensure the stability and accuracy of the collected data.

[0164] Secondly, after obtaining the initial signal characteristic data, a series of small frequency disturbances are applied to the specific signal, and its response data under each disturbance condition is collected. The range of frequency disturbance is set between 0.01MHz and 0.02MHz to trigger the slight fluctuation of signal response. By recording the intensity and stability changes under each disturbance frequency, a complete frequency disturbance response data set is formed. These response data reflect the changing characteristics of the signal under disturbance conditions and provide a basis for judging pseudo signals. The purpose of applying the disturbance frequency and recording the response is to observe whether the signal shows sensitivity or instability under small-range disturbances based on the initial signal characteristic data, which is a common feature of pseudo signals.

[0165] Secondly, the change rate of the frequency disturbance response data is calculated, and the frequency disturbance dynamic threshold is set based on the change rate data to determine whether the signal has an abnormal response. The calculation formula is:

[0166] Frequency disturbance dynamic threshold = μ + k·σ

[0167] Specifically in the formula: μ is the mean of the rate of change data, σ is the standard deviation, k is the adjustment coefficient, and its value is between 1 and 3. The mean value μ of the rate of change represents the response center value of the normal signal, and the standard deviation σ represents the volatility of the signal response. The adjustment coefficient k is flexibly set according to the environmental noise conditions. The purpose of the dynamic threshold is to ensure that it can automatically adapt to different signal environments. By setting a reasonable rate of change range, signals with large abnormal responses can be screened out, thereby identifying possible false signals.

[0168] Secondly, in order to further improve the recognition accuracy, a threshold of abnormal response times is set to count the frequency of abnormal responses of the signal under different disturbance frequency conditions. The threshold of abnormal response times is generally set to 3, that is, if a signal has abnormal responses for 3 or more times under multiple disturbance frequency conditions, the signal is judged to be a false signal. The basis for setting this threshold is that normal signals may occasionally have abnormal responses, but signals with frequent abnormal responses are often unstable, which is a common feature of false signals. The threshold can be flexibly adjusted according to the complexity of the signal environment to ensure the accuracy of false signal recognition.

[0169] Secondly, in order to further adapt to different usage environments, a user feedback mechanism is set up to dynamically adjust the frequency disturbance dynamic threshold by collecting feedback on pseudo signals manually marked by users. The role of the user feedback mechanism is that if the user reports a misjudged or missed signal in a specific environment, the characteristic data of the signal will be included in the feedback data set to readjust the sensitivity of the dynamic threshold, including increasing the value of the adjustment coefficient k in a high interference environment, appropriately widening the dynamic threshold range, and reducing misjudgments. In a relatively stable signal environment, the k value can be reduced to improve the recognition sensitivity of pseudo signals.

[0170] Secondly, in order to further improve the adaptability of pseudo-signal recognition, a pseudo-signal feature data set update mechanism is proposed to automatically adapt to the changing signal reception environment. This mechanism regularly updates the pseudo-signal feature data set according to the dynamic changes of the signal environment. When new pseudo-signal feature data is detected in different environments, the pseudo-signal feature will be added and the data confirmed as normal signals will be removed to prevent the recognition data set from being outdated. By automatically updating the pseudo-signal feature data set, the portable radio can more quickly and accurately identify and exclude pseudo-signals in new signal environments, effectively ensuring the quality of signal reception.

[0171] See also Figure 2 , the electronic device 1000 includes a memory 1010 and a processor 1020.

[0172] The processor 1020 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0173] The memory 1010 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. Among them, ROM can store static data or instructions required by the processor 1020 or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory 1010 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 1010 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0174] The memory 1010 stores executable codes, and when the executable codes are processed by the processor 1020 , the processor 1020 can execute part or all of the methods described above.

[0175] The scheme of the present application has been described in detail above with reference to the accompanying drawings. In the above embodiments, the description of each embodiment has its own emphasis. For the part that is not described in detail in a certain embodiment, refer to the relevant description of other embodiments. Those skilled in the art should also know that the actions and modules involved in the description are not necessarily required for the present application. In addition, it can be understood that the steps in the method of the embodiment of the present application can be adjusted in order, merged and deleted according to actual needs, and the modules in the device of the embodiment of the present application can be merged, divided and deleted according to actual needs.

[0176] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0177] Alternatively, the present application can also be implemented as a storage medium (or computer-readable storage medium, or machine-readable storage medium) on which executable code (or computer program, or computer instruction code) is stored. When the executable code (or computer program, or computer instruction code) is executed by a processor of a control system (or control system, server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0178] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the application herein may be implemented as electronic hardware, computer software, or a combination of both.

[0179] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for debugging a radio station threshold of a portable radio, characterized in that: The steps include: S100, acquiring initial signal characteristic data, and performing average processing on the initial signal characteristic data; S200, performing frequency disturbance on the initial signal characteristic data, and obtaining response change data under the disturbance frequency; S300, calculating the change rate of the response change data, and performing analysis based on the change rate calculation result; S400, setting a frequency disturbance dynamic threshold based on the data obtained after the analysis in S300, and performing analysis based on the data obtained after the frequency disturbance dynamic threshold is adjusted; S500, based on the analysis result of the frequency disturbance dynamic threshold adjustment obtained in S400, setting and determining the abnormal response number threshold; S600: Adjust the frequency disturbance dynamic threshold based on user tag feedback.

2. The method for debugging a radio station threshold of a portable radio according to claim 1, characterized in that: The obtaining of the initial signal characteristic data and averaging the obtained initial signal characteristic data specifically includes: S100.

1. based on the first start-up of the portable radio in a new environment, sequentially scanning the predetermined frequency band range and gradually detecting the receivable signals in each frequency band; Among them, the predetermined range of the frequency band scanning is greater than 0MHz; S100.1.

1. Scan the acceptable signals in each frequency band including: signal frequency, strength and spectrum characteristics, and obtain initial signal characteristic data; S100.1.

2. Perform sampling value averaging processing on the initial signal characteristic data.

3. The method for debugging a radio station threshold of a portable radio according to claim 1, characterized in that: The frequency disturbance is performed on the initial signal characteristic data, and the response change data under the disturbance frequency is obtained, and the specific steps are as follows: S200.

1. Perform frequency perturbation based on the acquired initial signal characteristic data; S200.1.

1. Based on the initial frequency of the initial signal characteristic data, set the small frequency disturbance range to be greater than 0 MHz; The perturbation range is around the initial frequency of the target signal, and is increased or decreased by a small increment greater than 0 MHz to generate different micro-perturbation frequencies; S200.2, based on the disturbance range of the initial frequency, apply a small frequency disturbance range in small increments; S200.2.

1. Repeated testing is performed at the disturbance frequency, and the signal response is recorded at each disturbance frequency; S200.2.

2. Generate response change data of initial signal characteristic data at various disturbance frequencies by cyclically applying different micro-disturbances.

4. The method for debugging a radio station threshold of a portable radio according to claim 1, characterized in that: The calculation of the change rate of the response change data and the analysis based on the change rate calculation result are specifically as follows: S300.

1. recording response change data based on initial signal characteristic data at each disturbance frequency; S300.1.

1. The intensity change and stability fluctuation caused by each disturbance frequency will be recorded as frequency disturbance response change rate data, and multiple groups of signal response data sets under disturbance frequencies will be formed; S300.2, calculating the rate of change based on the signal response data set at each set of disturbance frequencies; The change rate calculation is the relative change rate calculation between the original values ​​of the signal strength and stability at each disturbance frequency in the initial signal characteristic data, specifically: Wherein: the signal value under the disturbance frequency refers to the signal strength or stability value measured after applying a specific disturbance frequency, the initial signal value refers to the signal strength in the initial signal characteristic data recorded in step S100, which is used as the reference value of the initial signal characteristic data, and the rate of change refers to the relative change of the signal value relative to the initial signal value after the disturbance frequency is applied, which is specifically reflected in the degree of response change of the signal strength or stability under different disturbance frequencies, wherein the larger the value of the rate of change, the more sensitive the signal is to the disturbance frequency; S300.3, after calculating the change rates of all disturbance frequencies based on the change rates, further analyzing the frequency disturbance response change rate data; Among them, analysis means that if the rate of change at multiple disturbance frequencies obviously deviates from the normal fluctuation range of the initial signal characteristic data, it indicates that the initial signal characteristic data is abnormally sensitive to tiny frequency disturbances and is a suspected false signal.

5. The method for debugging the radio station threshold of a portable radio according to claim 1, characterized in that: The frequency disturbance dynamic threshold is set based on the data obtained after the analysis in S300, and the analysis is performed based on the data obtained after the frequency disturbance dynamic threshold is adjusted, specifically: S400.

1. Based on the analyzed frequency disturbance response change rate data, a reference range is calculated by statistically analyzing the mean and standard deviation of the change rate data, and the change rate range of a normal signal is represented based on the obtained reference range; S400.1.

1. Setting a frequency disturbance dynamic threshold based on a reference range as a benchmark for identifying abnormal signal responses; The frequency disturbance dynamic threshold is defined as the mean of the rate of change data plus a certain multiple of the standard deviation to determine whether the rate of change of the normal signal is lower than the frequency disturbance dynamic threshold, specifically: Frequency disturbance dynamic threshold = μ + k·σ Where: The frequency disturbance dynamic threshold is used to determine whether the signal is an abnormal response. When the change rate data exceeds the frequency disturbance dynamic threshold, the signal will be marked as abnormal and then identified as a suspected false signal; Among them, μ is the mean of the rate of change data, which represents the average value of the signal response change rate under all disturbance frequencies; σ is the standard deviation of the rate of change data, which is used to describe the degree of dispersion of the rate of change data relative to the mean μ; k is the adjustment coefficient, which is used to control the sensitivity of the dynamic threshold of frequency disturbance; S400.

2. Compare the change rate data under the disturbance frequency adjusted based on the frequency disturbance dynamic threshold one by one, and check whether it exceeds the frequency disturbance dynamic threshold. If the change rate under the frequency disturbance exceeds the threshold, it indicates that the response of the initial signal characteristic data under this disturbance frequency exceeds the normal range and has abnormal sensitivity; S400.

3. Based on the comparison result, mark all change rates exceeding the frequency disturbance dynamic threshold as abnormal responses.

6. The method for debugging the radio station threshold of a portable radio according to claim 1, characterized in that: The abnormal response number threshold setting and determination based on the analysis result of the frequency disturbance dynamic threshold adjustment obtained in S400 specifically include: S500.

1. Based on the comparison results, count the number of abnormal responses of each initial signal characteristic data, including the distribution at different disturbance frequencies; Among them, the abnormal response number threshold is set to be greater than 0; S500.

2. Based on the abnormal response statistics, further compare the overall response characteristics of the initial signal characteristic data; Among them, if a signal shows abnormal response under multiple disturbance frequencies, it can be regarded as unstable under the condition of small frequency disturbance, that is, it has possible pseudo signal characteristics; S500.

3. Based on the comparison analysis results, if the number of abnormal responses of a certain signal at different disturbance frequencies reaches or exceeds the abnormal response number threshold, it is further determined to be a false signal.

7. The method for debugging a radio station threshold of a portable radio according to claim 1, characterized in that: In S600, adjusting the frequency disturbance dynamic threshold based on user tag feedback specifically includes: S600.

1. Based on the initial signal feature data received daily, the user can manually mark it as a false signal or a misjudged signal. The feedback based on the manual marking will be recorded and used as the basis for adjusting the frequency disturbance dynamic threshold and updating the false signal feature data set; S600.

2. Based on the user's manual note feedback, regularly perform environmental signal analysis on the new initial signal feature data set and monitor the signal fluctuations in the environment; Among them, environmental signal analysis and environmental signal fluctuations, including the intensity changes and stability distribution of different frequency bands, determine whether there are many signal fluctuations in the current environment. When frequent interference or fluctuations are detected, the frequency disturbance dynamic threshold is appropriately adjusted. It is specifically divided into general receiving environment, high noise receiving environment and high stability receiving environment; Among them, based on the general receiving environment, the threshold calculation method of the change rate mean plus twice the standard deviation is adopted, that is, k=2 is set; Among them, based on the high noise receiving environment and frequent interference signals, the frequency disturbance dynamic threshold is appropriately relaxed and k=3 is set; Among them, in a high-stability receiving environment, the tolerance of the frequency disturbance dynamic threshold is reduced, and k=1 is set; S600.

3. Recalculate the frequency disturbance dynamic threshold based on user feedback and environmental signal analysis results.

8. An electronic device comprising: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method according to any one of claims 1 to 7.

9. A storage medium having executable codes stored thereon, which, when executed by a processor of a control system, causes the processor to execute the method according to any one of claims 1 to 7.

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