Civil aviation radio parameter intelligent testing and tracing method and system

Abstract

The invention relates to the technical field of data intelligent testing and traceability, and provides a civil aviation radio parameter intelligent testing and traceability method and system, and the method comprises the steps: obtaining target spectrum feature data obtained by scanning a target frequency band through a phased-array antenna array in a dynamic spectrum interference environment, and adjusting the phased-array antenna array; and converting a civil aviation radio receiving signal in the target spectrum data after anti-interference optimization into time-frequency domain data, generating a signal spectrum, generating a modulation parameter characteristic and a frequency deviation parameter characteristic, and generating a civil aviation radio parameter traceability result containing an equipment identity identifier and a parameter deviation value. According to the invention, through optimization adjustment and signal feature analysis of the phased-array antenna in a dynamic spectrum interference environment, the problem of unstable anti-interference effect in the prior art is solved; the intelligent level and the practicability of the whole system are not high, and intelligent testing and accurate traceability of civil aviation radio parameters are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of data intelligent testing and traceability, and particularly to an intelligent testing and traceability method and system for civil aviation radio parameters. Background Art

[0002] Civil aviation radio communication faces increasingly complex electromagnetic environment challenges. Especially in the areas around airports and dense airway regions, various radio signals are intertwined and superimposed, resulting in serious interference to the civil aviation ground-air communication link. To ensure flight safety and communication reliability, it is urgent to conduct real-time intelligent testing on the parameters of civil aviation radio receiving signals and realize the identity traceability of interference sources or transmitting devices to support rapid positioning and interference suppression.

[0003] In response to the above technical requirements, the current mainstream technical solution is an automated signal recognition method based on the combination of multi-antenna joint processing and time-frequency analysis. This technical solution deploys a multi-channel receiving array to perform synchronous signal acquisition within the target frequency band, and combines beamforming technology to perform spatial filtering processing on interference signals; by comparing with the existing signal feature database, the signal source and its communication protocol type are initially judged. There are some inherent defects in the existing technical solutions. For example, in the case where the azimuth of the interference signal is constantly changing, the fixed beamforming strategy is difficult to continuously optimize the receiving direction pattern, resulting in unstable anti-interference effects and affecting the accuracy of subsequent parameter extraction; the signal feature extraction and device recognition processes are processed in isolation, and the multi-dimensional parameter information fails to be effectively integrated, restricting the intelligent level and practicality of the overall system. Summary of the Invention

[0004] The present invention provides an intelligent testing and traceability method and system for civil aviation radio parameters to solve the problems of unstable anti-interference effects and low intelligent level and practicality of the overall system in the prior art.

[0005] In a first aspect, the present invention provides an intelligent testing and traceability method for civil aviation radio parameters, including: Obtaining spectrum feature data scanned by a phased array antenna array in a dynamic spectrum interference environment for a target frequency band; Adjusting the phases of each antenna unit in the phased array antenna array based on the azimuth information of the interference signal in the spectrum feature data to generate target spectrum data optimized for anti-interference; Converting the civil aviation radio receiving signal in the target spectrum data into time-frequency domain data to generate a signal map; Identifying the time-frequency feature pattern of civil aviation radio parameters from the signal map, and analyzing the time-frequency feature pattern to obtain modulation parameter features and frequency offset parameter features matching a preset civil aviation communication protocol; Combine the modulation parameter features and the frequency offset parameter features to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio; Based on the mapping relationship library, the modulation parameter features, and the frequency offset parameter features, generate a civil aviation radio parameter traceability result including device identity identification and parameter deviation values.

[0006] Optionally, identify the time-frequency feature pattern of the civil aviation radio parameters from the signal spectrum, and analyze the time-frequency feature pattern to generate modulation parameter features and frequency offset parameter features that match the preset civil aviation communication protocol, including: Perform time-frequency decomposition on the signal spectrum to generate the time-frequency feature pattern of the civil aviation radio parameters, and the time-frequency feature pattern is determined by the low-frequency component and the high-frequency component; Analyze the amplitude envelope of the low-frequency component to determine the phase jump point and the modulation symbol type; Locate the carrier phase mutation point synchronized with the phase jump point in the high-frequency component; According to the instantaneous frequency value corresponding to the carrier phase mutation point, calculate the frequency offset of the carrier frequency of the civil aviation radio received signal relative to the nominal value, and determine the stable frequency offset component according to the frequency offset; Match the modulation symbol type with the modulation type in the preset civil aviation communication protocol to select multiple candidate modulation types that meet the preset conditions; Calculate the symbol rate variance value of each candidate modulation type according to the time stamp interval between adjacent phase jump points, and use the candidate modulation type with the smallest symbol rate variance value as the modulation parameter feature; Based on the symbol rate in the modulation parameter features and the stable frequency offset component, generate a mean sequence, and perform filtering processing on the mean sequence to generate frequency offset parameter features.

[0007] Optionally, perform time-frequency decomposition on the signal spectrum to generate the time-frequency feature pattern of the civil aviation radio parameters, and the time-frequency feature pattern is determined by the low-frequency component and the high-frequency component, including: Decompose the signal spectrum to generate multiple frequency band components; Calculate the amplitude change rate of each frequency band component; Use the frequency band component with an amplitude change rate lower than the first threshold as the high-frequency component, and use the frequency band component with an amplitude change rate higher than the second threshold as the high-frequency component; Superpose and fuse the amplitude data of the low-frequency component and the amplitude data of the high-frequency component to generate a time-frequency feature pattern.

[0008] Optionally, parse the amplitude envelope of the low-frequency component to determine phase jump points and modulation symbol types, including: Perform extreme point detection on the amplitude envelope of the low-frequency component according to the theoretical period length corresponding to the preset symbol rate to generate a sequence of maximum points; Generate a candidate period set according to the time intervals between adjacent maximum points in the sequence of maximum points, and screen out a target period from the candidate period set whose difference from the theoretical period length is less than a preset threshold; Segment the waveform of the amplitude envelope according to the target period to generate a sequence of symbol period segments; Calculate the absolute value of the derivative of the amplitude envelope within each symbol period segment in the sequence of symbol period segments, identify target time domain points where the absolute value of the derivative exceeds a preset mutation threshold and there is a phase continuity interruption, and use the target time domain points as phase jump points; Count the number and distribution positions of adjacent phase jump points within each symbol period segment to obtain a statistical result; Match the statistical result with the modulation type symbol jump rule defined in the preset civil aviation communication protocol to determine the modulation symbol type.

[0009] Optionally, generate a mean value sequence based on the symbol rate and the stable frequency offset component in the modulation parameter features, and perform filtering processing on the mean value sequence to generate frequency offset parameter features, including: Arrange the stable frequency offset components in chronological order to generate a stable frequency offset component sequence; Segment the stable frequency offset component sequence according to the symbol period corresponding to the symbol rate in the modulation parameter features to generate a symbol synchronization segmentation sequence; Calculate the mean value of the stable frequency offset components within each symbol synchronization segment in the symbol synchronization segmentation sequence to generate a mean value sequence; Perform filtering processing on the mean value sequence according to the cut-off frequency parameter corresponding to the symbol rate to generate a filtered stable frequency offset component; Calculate the arithmetic mean value of the filtered stable frequency offset components, and use the arithmetic mean value as the frequency offset parameter feature.

[0010] In a second aspect, the present invention provides a civil aviation radio parameter intelligent testing and traceability system, including: An acquisition module, configured to acquire spectrum feature data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment; An adjustment module, configured to adjust the phases of the antenna elements in the phased array antenna based on the azimuth information of the interference signal in the spectrum feature data, so as to generate target spectrum data optimized for anti-interference; A conversion module, configured to convert the civil aviation radio receiving signal in the target spectrum data into time-frequency domain data to generate a signal spectrogram; An analysis module, configured to identify the time-frequency feature pattern of the civil aviation radio parameters from the signal spectrogram, and analyze the time-frequency feature pattern to obtain the modulation parameter feature and the frequency offset parameter feature that match the preset civil aviation communication protocol; A combination module, configured to combine the modulation parameter feature and the frequency offset parameter feature to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio; A generation module, configured to generate a civil aviation radio parameter traceability result including the device identity identifier and the parameter deviation value based on the mapping relationship library, the modulation parameter feature, and the frequency offset parameter feature.

[0011] In a third aspect, the present invention provides a computing device, including a processor and a memory, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the methods for intelligent testing and traceability of civil aviation radio parameters in the first aspect.

[0012] In a fourth aspect, the present invention provides a computer storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the methods for intelligent testing and traceability of civil aviation radio parameters in any one of the first aspect are implemented.

[0013] In the present invention, spectral feature data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment is acquired; based on the azimuth information of interference signals in the spectral feature data, the phases of each antenna element in the phased array antenna array are adjusted to generate target spectral data after anti-interference optimization; the civil aviation radio receiving signals in the target spectral data are converted into time-frequency domain data to generate a signal spectrogram; a time-frequency feature pattern of civil aviation radio parameters is identified from the signal spectrogram, and the time-frequency feature pattern is analyzed to obtain modulation parameter features and frequency offset parameter features matching a preset civil aviation communication protocol; the modulation parameter features and the frequency offset parameter features are combined to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio; based on the mapping relationship library, the modulation parameter features, and the frequency offset parameter features, a civil aviation radio parameter traceability result including a device identity identifier and a parameter deviation value is generated. The technical solution provided by the present invention actively scans the target frequency band in a dynamic spectrum interference environment, captures the original spectral features of civil aviation radio signals in real time, and overcomes the data lag problem of traditional static spectrum monitoring in a dynamic interference scenario; dynamically adjusts the antenna phase distribution using the azimuth information of interference signals, suppresses the radiation gain in the interference direction at the physical layer, and improves the anti-interference ability of target signals; enhances the capture ability of instantaneous frequency offset and modulation mutation by characterizing the dynamic characteristics of signals through time-frequency joint distribution; separates the modulation parameter and frequency offset features by analyzing the time-frequency feature pattern based on the constraints of the civil aviation communication protocol; constructs a dynamic mapping relationship between device parameters and measured features, realizes the correlation modeling of parameter features and device identity, and solves the defects of the traditional method relying on the update lag and insufficient coverage of the manually calibrated database; synchronously completes the parameter compliance test and device source traceability by intelligently matching and outputting the device identity and parameter deviation, and breaks through the efficiency bottleneck caused by the step-by-step operation of testing and traceability in the prior art. Among them, by step-by-step analyzing the low-frequency modulation feature and the high-frequency carrier feature, and combining protocol constraint screening and symbol rate variance optimization, the accuracy of modulation type recognition in a complex interference environment is improved; the carrier phase mutation is synchronously located using the phase jump point, and the instantaneous noise and stable offset components are separated, solving the problem that the frequency offset measurement in the traditional method is easily affected by random interference.

[0014] These aspects or other aspects of the present invention will be more clearly understood in the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a flowchart of an intelligent test and traceability method for civil aviation radio parameters provided by an embodiment of the present invention; Figure 2 It is a schematic structural diagram of an intelligent test and traceability system for civil aviation radio parameters provided by an embodiment of the present invention; Figure 3 It is a schematic structural diagram of a computing device provided by an embodiment of the present invention. Detailed implementation manners

[0017] In order to enable those skilled in the art of the present technology to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention.

[0018] In some processes described in the specification, claims and the above-mentioned accompanying drawings of the present invention, there are multiple operations that appear in a specific order. However, it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The operation numbers such as 101, 102, etc. are only used to distinguish different operations, and the numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, nor do they limit that "first" and "second" are of different types.

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0020] Figure 1 An embodiment of the present invention provides a flowchart of an intelligent test and traceability method for civil aviation radio parameters, as Figure 1 shown, the method includes: For the technical problems of real-time detection and traceability of civil aviation radio signal parameters in a dynamic spectrum interference environment, there are three major bottlenecks in the existing technologies: First, traditional fixed-beam antennas are difficult to dynamically suppress time-varying interference, resulting in insufficient signal acquisition signal-to-noise ratio; second, conventional spectrum analysis cannot effectively separate the time-frequency characteristics of civil aviation signals from interference components, causing misjudgment of modulation parameters; third, the testing of equipment parameters and source tracing rely on manual correlation, and it is difficult to balance real-time performance and accuracy. To address these problems, the present invention combines phased array beamforming and time-frequency domain analysis, realizes spatial domain interference suppression by dynamically sensing the interference direction, combines signal spectrum analysis to analyze the modulation and frequency offset characteristics of civil aviation radio receiving signals, constructs a mapping relationship library between the parameters of the transmitting source equipment and the measured parameters, and finally synchronously outputs the parameter deviation value and the equipment identity identifier in the interference environment. Based on this, the present invention provides an intelligent testing and tracing method for civil aviation radio parameters, such as Figure 1 , including: Step 101: Obtain the spectrum feature data obtained by scanning the target frequency band by a phased array antenna array in a dynamic spectrum interference environment.

[0021] In this step, the phased array antenna array refers to an array composed of multiple antenna elements arranged in a specific geometric structure, which realizes electronic scanning and shaping of the beam direction by controlling the phase difference of each element, and is used for directional reception of signals in a dynamic environment; the dynamic spectrum interference environment refers to an electromagnetic environment with time-varying interference signals (such as burst noise, co-channel interference), and the intensity, frequency and direction of its interference signals change rapidly with time; the target frequency band refers to the specific frequency range used by the civil aviation radio communication system, including the very high frequency communication band (118 - 137 MHz) and the ADS-B signal band (1090 MHz); the spectrum feature data refers to the set of signal parameters obtained by spectrum analysis, including signal intensity, frequency distribution, phase information and the spatial direction information of interference signals.

[0022] In an embodiment of the present invention, the phased array antenna array continuously samples the signals in the target frequency band through electronic scanning, generates spectrum feature data including signal intensity, frequency distribution and phase information. During the scanning process, the beam direction of the antenna array is dynamically adjusted according to a preset scanning path to ensure coverage of all potential signal sources in the target frequency band.

[0023] Step 102: Based on the interference signal direction information of the spectrum feature data, adjust the phases of the antenna elements in the phased array antenna array to generate target spectrum data optimized for anti-interference.

[0024] In this step, the azimuth information of the interference signal refers to the incident direction of the interference signal calculated by the direction-of-arrival estimation algorithm, including the horizontal azimuth angle and the elevation angle; the phase of each antenna element refers to the RF signal phase value of each antenna element in the phased array antenna array, and the beam direction is controlled by adjusting the phase difference; the adjustment operation refers to dynamically calculating and setting the phase compensation value of the antenna element according to the azimuth of the interference signal to suppress the signal reception in the interference direction; the target spectrum data refers to the civil aviation radio signal spectrum data retained after interference suppression processing, and its interference components are attenuated.

[0025] In the embodiment of the present invention, by calculating the angle between the incident direction of the interference signal and the normal direction of the antenna array, the phase compensation value of each antenna element is determined, so that the synthetic beam of the antenna array forms a radiation gain zero point in the direction of the interference signal, thereby generating the target spectrum data optimized for anti-interference. During the phase adjustment process, a closed-loop feedback control algorithm is used to update the phase compensation value in real time to ensure that the interference suppression effect is synchronized with the dynamic interference environment.

[0026] Step 103: Convert the civil aviation radio received signal in the target spectrum data into time-frequency domain data to generate a signal spectrogram.

[0027] In this step, the time-frequency domain data refers to the signal representation form that simultaneously contains time and frequency dimension information, and the time-domain signal is converted into time-frequency joint distribution data through the time-frequency analysis algorithm; the signal spectrogram refers to the time-frequency domain data presented in the form of a two-dimensional image, with the horizontal axis being time, the vertical axis being frequency, and the color depth representing the signal intensity.

[0028] In the embodiment of the present invention, the short-time Fourier transform algorithm is used to perform time-frequency decomposition on the signal, calculate the spectrum distribution of the signal in units of time windows, and finally generate a two-dimensional time-frequency feature spectrogram with time as the horizontal axis, frequency as the vertical axis, and signal intensity as the color depth.

[0029] Step 104: Identify the time-frequency feature patterns of the civil aviation radio parameters from the signal spectrogram, and analyze the time-frequency feature patterns to generate modulation parameter features and frequency offset parameter features that match the preset civil aviation communication protocol.

[0030] In this step, the time-frequency feature pattern refers to the time-frequency distribution law that characterizes the civil aviation radio parameter characteristics in the signal spectrogram, including the time-frequency ridge line of the modulation symbol and the offset trajectory of the carrier frequency; the analysis operation refers to the technical process of separating and extracting the modulation parameter features and the frequency offset parameter features from the time-frequency feature pattern, including time-frequency ridge line tracking and feature quantization; the modulation parameter features refer to the parameter set that describes the signal modulation method, including modulation type, symbol rate, and phase jump point distribution; the frequency offset parameter features refer to the parameter set that describes the deviation of the carrier frequency from the nominal value, including instantaneous offset, stable offset component, and offset fluctuation variance.

[0031] In the embodiment of the present invention, a time-frequency ridge line in a signal spectrogram is extracted through an edge detection algorithm to separate the modulation feature components and frequency offset components of a civil aviation signal; according to the modulation types and frequency tolerance ranges defined in a preset civil aviation communication protocol, the separated feature components are matched and verified, and finally, modulation parameter features (such as modulation symbol rate, modulation type) and frequency offset parameter features (such as carrier frequency deviation value, stable offset component) that match the protocol are output.

[0032] Step 105: Combine the modulation parameter features and the frequency offset parameter features to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio.

[0033] In this step, the combination operation refers to the process of combining the modulation parameter features and the frequency offset parameter features into a multi-dimensional feature vector, which is used to construct the device parameter mapping relationship; the transmission source device parameters refer to the factory nominal parameters of the civil aviation radio transmission device, including the device model, nominal value of the modulation type, and frequency tolerance range; the measured parameters refer to the modulation parameter features and frequency offset parameter features actually extracted from the received signal through this method; the mapping relationship library refers to a database storing the correlation relationship between the transmission source device parameters and the measured parameter features, which is used for the matching query of device identity and parameter traceability.

[0034] In the embodiment of the present invention, the modulation parameter features (such as symbol rate) and the frequency offset parameter features (such as stable offset) are combined into a multi-dimensional feature vector through the feature vector splicing technology, and a one-to-one mapping relationship is established with the pre-stored transmission source device parameters (such as device model, factory nominal value) to form a dynamically updated parameter correlation database.

[0035] Step 106: Based on the mapping relationship library, the modulation parameter features, and the frequency offset parameter features, generate a civil aviation radio parameter traceability result including the device identity identifier and the parameter deviation value.

[0036] In this step, the device identity identifier refers to the coding information that uniquely identifies the civil aviation radio transmission device, including the device serial number, registration number, and affiliated institution code; the parameter deviation value refers to the difference quantization value between the measured parameter features and the nominal parameters of the civil aviation radio transmission device, which is used to evaluate the compliance of the device performance.

[0037] In the embodiment of the present invention, the device parameter combination closest to the current parameter features is retrieved in the mapping relationship library through a feature similarity matching algorithm (such as cosine similarity calculation), and the corresponding device identity identifier (such as device serial number) and parameter deviation value (such as the difference between the measured frequency offset and the nominal value) are output to complete the closed-loop operation of parameter testing and device traceability.

[0038] For example, in the radio monitoring scenario of an airport tower, a phased array antenna array scans the VHF communication band (125 MHz), and detects a co-frequency interference signal from 30° in the southeast direction; based on the interference azimuth information, the phase of the antenna unit is adjusted to form a radiation gain suppression of -30 dB in the interference direction; the signal after interference suppression is converted into time-frequency domain data to generate a two-dimensional map containing the time-frequency ridge line of the ACARS signal; the modulation symbol rate of 1200 bps and the stable frequency offset are parsed from the map; the parameter features are matched and combined with the pre-stored airborne radio parameter library to construct a device parameter mapping relationship; finally, the device identity identifier (such as the radio of Flight B-1234) and the frequency deviation value are output to complete the parameter compliance detection and device traceability.

[0039] In the embodiment of the present invention, the signal acquisition signal-to-noise ratio is improved by spatial domain interference suppression, and the problem of parameter measurement distortion of traditional methods in a dynamic interference environment is solved; based on the time-frequency feature pattern analysis and protocol matching mechanism, the accuracy of modulation type recognition and frequency offset measurement is improved; through the parameter feature mapping library, the intelligent linkage of testing and traceability is realized, breaking through the limitations of low efficiency and easy error of manual correlation operations, and realizing high-precision testing of civil aviation radio parameters and device source tracing in a dynamic spectrum interference environment.

[0040] The present invention provides a specific embodiment. In step 104, the time-frequency feature pattern of civil aviation radio parameters is identified from the signal map, and the time-frequency feature pattern is analyzed to generate modulation parameter features and frequency offset parameter features that match the preset civil aviation communication protocol, which specifically includes the following steps: Step 401: Perform time-frequency decomposition on the signal map to generate the time-frequency feature pattern of civil aviation radio parameters, and the time-frequency feature pattern is determined by the low-frequency component and the high-frequency component.

[0041] In this step, time-frequency decomposition refers to the process of separating the time-frequency domain signal into different frequency components, including a low-frequency component (reflecting modulation information) and a high-frequency component (reflecting carrier characteristics), which is realized by wavelet transform or filter bank; the low-frequency component refers to the component in the signal with a frequency lower than the carrier frequency, containing the phase and amplitude change information of the modulation symbol; the high-frequency component refers to the component in the signal with a frequency close to the carrier frequency, reflecting the offset and phase fluctuation of the carrier frequency.

[0042] In the embodiments of the present invention, the wavelet transform algorithm is used to decompose the signal spectrum into a low-frequency component and a high-frequency component, where the low-frequency component corresponds to the modulation information of the signal (such as symbol rate, phase jump), and the high-frequency component corresponds to the frequency offset characteristic of the carrier. The time-frequency feature pattern is jointly determined by the time-frequency energy distributions of the low-frequency component and the high-frequency component. The time-frequency ridge line of the low-frequency component reflects the change of modulation symbols, and the time-frequency fluctuation of the high-frequency component reflects the carrier frequency offset.

[0043] Step 402: Analyze the amplitude envelope of the low-frequency component to determine the phase jump points and the modulation symbol types.

[0044] In this step, the amplitude envelope refers to the contour curve of the signal amplitude changing with time, which is extracted by the Hilbert transform and used to detect the modulation symbol jump; the phase jump point refers to the position of the sudden change of the signal phase caused by the switching of the modulation symbol, corresponding to the symbol boundary of the modulation type; the modulation symbol type refers to the types of symbols used in the modulation method, such as the 0° and 180° phase states in binary phase shift keying.

[0045] In the embodiments of the present invention, the amplitude envelope curve of the low-frequency component is extracted by the Hilbert transform, and the mutation points of the envelope curve are detected as the phase jump points; based on the amplitude change pattern between the phase jump points (such as the 180° jump in binary phase shift keying), combined with the preset modulation symbol mapping table, the corresponding modulation symbol types are determined.

[0046] Step 403: Locate the carrier phase mutation points synchronized with the phase jump points in the high-frequency component.

[0047] In this step, the carrier phase mutation point refers to the moment when the phase of the carrier signal undergoes a sudden change, which is synchronized with the modulation symbol jump and is used for frequency offset calculation.

[0048] In the embodiments of the present invention, the time stamps of the phase jump points of the low-frequency component are mapped to the high-frequency component through the time domain alignment algorithm, and the phase mutation positions that are time-aligned with the phase jump points are searched in the instantaneous phase sequence of the high-frequency component as the carrier phase mutation points.

[0049] Step 404: Calculate the frequency offset of the carrier frequency of the civil aviation radio receiving signal relative to the nominal value according to the instantaneous frequency value corresponding to the carrier phase mutation point, and determine the stable frequency offset component according to the frequency offset.

[0050] In this step, the instantaneous frequency value refers to the instantaneous frequency of the signal at a certain moment, which is calculated by the phase change rate, and the formula is instantaneous frequency = phase derivative / ; The nominal value refers to the theoretical carrier frequency value calibrated when the civil aviation radio equipment leaves the factory, such as the nominal frequency of 125 MHz for VHF communication; the frequency offset refers to the difference between the measured carrier frequency and the nominal frequency, including instantaneous offset and stable offset components; the stable frequency offset component refers to the average value of the frequency offset after removing random noise, reflecting the systematic deviation of the carrier frequency.

[0051] In the embodiment of the present invention, the instantaneous frequency calculation formula (the instantaneous frequency is equal to the phase change rate divided by ) is used to calculate the instantaneous frequency value of each carrier phase mutation point, and the instantaneous frequency offset is obtained by subtracting the instantaneous frequency value from the nominal frequency; the instantaneous frequency offsets of multiple phase mutation points are subjected to a moving average process to obtain the stable frequency offset component after removing random noise interference.

[0052] Step 405: Match the modulation symbol type with the modulation types in the preset civil aviation communication protocol to select multiple candidate modulation types that meet the preset conditions.

[0053] In this step, the modulation type refers to the modulation method adopted by the signal, such as amplitude shift keying, frequency shift keying (FSK), etc., which is specified by the communication protocol; the matching operation refers to the process of comparing and screening the measured modulation symbol type with the modulation types allowed by the protocol; the preset conditions refer to the modulation type constraint conditions specified in the protocol, such as the ACARS protocol only allows the use of specific modulation methods; the candidate modulation types refer to the set of possible modulation methods retained after protocol matching and screening.

[0054] In the embodiment of the present invention, according to the modulation type constraint conditions defined by the protocol (such as the ACARS protocol only allows the use of amplitude shift keying modulation), a set of candidate modulation types that match the current modulation symbol type (such as detecting amplitude shift keying characteristics) is screened out.

[0055] Step 406: Calculate the symbol rate variance value of each candidate modulation type according to the time stamp interval between adjacent phase jump points, and use the candidate modulation type with the smallest symbol rate variance value as the modulation parameter feature.

[0056] In this step, the time stamp interval refers to the time difference between adjacent phase jump points, which is used to calculate the actual symbol rate; the symbol rate variance value refers to the mean square of the deviation between the actual symbol period and the theoretical symbol period, which is used to evaluate the modulation type matching degree.

[0057] In the embodiment of the present invention, the time interval sequence of adjacent phase jump points is statistically analyzed, and the variance value between the theoretical symbol period of each candidate modulation type and the actual interval sequence is calculated (such as the theoretical symbol period is and the mean value of the actual interval sequence is and the variance is ; Select the candidate modulation type with the smallest variance (such as the amplitude keying type with the smallest variance) as the final modulation parameter feature.

[0058] Step 407: Generate a mean sequence based on the symbol rate in the modulation parameter feature and the stable frequency offset component, and perform filtering processing on the mean sequence to generate a frequency offset parameter feature.

[0059] In this step, the symbol rate refers to the number of modulation symbols transmitted per unit time, with the unit of symbols per second (Baud); the mean sequence refers to the sequence of the average values of the symbol rate and the stable frequency offset arranged in chronological order; the filtering processing refers to a technique for suppressing noise in the mean sequence, such as Kalman filtering or moving average filtering, which is used to extract stable parameter features.

[0060] In the embodiment of the present invention, the reciprocal of the period corresponding to the symbol rate and the stable frequency offset component are arranged in chronological order as a mean sequence, and the Kalman filtering algorithm is used to smooth the mean sequence to generate a frequency offset parameter feature (such as the stable offset mean fluctuation range).

[0061] The embodiment of the present invention improves the measurement accuracy of civil aviation radio parameters in a dynamic interference environment through time-frequency decomposition and carrier-modulation joint analysis; accurately identifies the modulation type under complex interference through low-frequency component analysis and protocol matching mechanism; effectively suppresses the influence of instantaneous noise on frequency offset measurement based on carrier phase mutation point synchronous positioning and stable offset component extraction; enhances the robustness of parameter features through symbol rate variance optimization and filtering processing, and solves the problem of unstable modulation recognition caused by symbol rate jitter in traditional methods.

[0062] The present invention provides a specific embodiment. In step 401, perform time-frequency decomposition on the signal spectrum to generate a time-frequency feature pattern of civil aviation radio parameters. The time-frequency feature pattern is determined by low-frequency components and high-frequency components, and specifically includes the following steps: Step 411: Decompose the signal spectrum to generate a plurality of frequency band components.

[0063] In this step, the decomposition operation refers to the process of dividing the time-frequency domain signal into multiple sub-signals according to the frequency range, which is realized by a filter bank or wavelet transform and is used to separate the signal components of different frequency bands; the frequency band component refers to the sub-band signal data obtained after the decomposition operation, and each component covers a specific frequency interval (such as a 10 kHz bandwidth) and contains the amplitude, phase, and time-frequency distribution information of that frequency band.

[0064] In an embodiment of the present invention, a filter bank algorithm is used to perform multi-channel filtering on the time-frequency domain data of a signal spectrogram, dividing the original signal into multiple sub-band components according to the frequency range. Each band component covers a specific frequency interval (such as every 10 kHz as a sub-band), which is used to separate the modulation information and carrier information of different frequency components.

[0065] Step 412: Calculate the amplitude change rate of each band component.

[0066] In this step, the amplitude change rate refers to the rate at which the signal amplitude changes with time, which is calculated by dividing the absolute value of the amplitude difference between adjacent time points by the time interval, and is used to quantify the dynamic characteristics of the signal.

[0067] In an embodiment of the present invention, differential calculation is performed on the amplitude data of each band component along the time axis. The amplitude change rate is equal to the absolute value of the amplitude difference between adjacent time points divided by the time interval, which is used to quantify the dynamic characteristics of signals in different frequency bands. For example, the amplitude change rate of the high-frequency component is calculated as / , where A(t) is the amplitude value at time t.

[0068] Step 413: Use the band components with an amplitude change rate lower than the first threshold as low-frequency components, and use the band components with an amplitude change rate higher than the second threshold as high-frequency components.

[0069] In this step, the first threshold refers to the amplitude change rate threshold value for distinguishing low-frequency components, which is set based on the statistical mean of the amplitude change rates of all band components (such as 50% of the mean). Bands with a change rate lower than this value are regarded as low-frequency components; the second threshold refers to the amplitude change rate threshold value for distinguishing high-frequency components, which is set based on the statistical mean (such as 150% of the mean). Bands with a change rate higher than this value are regarded as high-frequency components.

[0070] In an embodiment of the present invention, the first threshold is set to 50% of the average value of the amplitude change rates of all band components, and the second threshold is set to 150% of the average value; the low-frequency components correspond to the slowly changing modulated baseband signal, and the high-frequency components correspond to the rapidly fluctuating carrier noise and interference components.

[0071] Step 414: Superpose and fuse the amplitude data of the low-frequency components and the amplitude data of the high-frequency components to generate a time-frequency feature pattern.

[0072] In this step, the amplitude data refers to the set of amplitude values of each frequency component of the signal in the time-frequency domain, which is stored in matrix form, with rows representing time points and columns representing frequency points; superposition and fusion refer to the process of adding the amplitude data of different band components according to weight coefficients, which is used to synthesize the low-frequency modulation information and high-frequency carrier characteristics to generate an enhanced time-frequency feature.

[0073] In the embodiment of the present invention, the weighted sum of the amplitude data of the low-frequency component (weight coefficient is 0.7) and the weighted sum of the amplitude data of the high-frequency component (weight coefficient is 0.3) are calculated to generate a fused time-frequency energy distribution map, which serves as the time-frequency feature pattern characterizing the civil aviation radio parameter features.

[0074] In the embodiment of the present invention, through frequency band decomposition and dynamic amplitude feature fusion, the recognition accuracy of civil aviation radio parameters in complex interference environments is improved; based on the amplitude change rate threshold, the low-frequency and high-frequency components are divided to effectively separate the modulated baseband signal and the carrier interference component; by weighted superposition fusion, the key parameter features are enhanced to solve the misjudgment of modulation types caused by the fuzzy time-frequency energy distribution in traditional methods; the adaptive frequency band division mechanism adapts to the parameter characteristics of different communication protocols, breaking through the limitations of the fixed frequency band decomposition mode.

[0075] The present invention provides a specific embodiment. In step 402, the amplitude envelope of the low-frequency component is analyzed to determine the phase jump points and the modulation symbol types, which specifically includes the following steps: Step 421: According to the theoretical period length corresponding to the preset symbol rate, perform extreme point detection on the amplitude envelope of the low-frequency component to generate a sequence of maximum points.

[0076] In this step, the preset symbol rate refers to the theoretical symbol transmission rate specified in the civil aviation communication protocol (such as 1200 symbols / second), which is used as the reference value for determining the symbol period length; the theoretical period length refers to the reciprocal of the preset symbol rate (such as 1 / 1200 second = 0.833 ms), which represents the duration of a single symbol in the ideal case; extreme point detection refers to the technique of identifying the positions of local maximum or minimum values in the signal amplitude envelope, which is used to locate the symbol period boundary; the sequence of maximum points refers to the set of local maximum positions of the amplitude envelope arranged in chronological order obtained through extreme point detection.

[0077] In the embodiment of the present invention, the sliding window extreme value detection algorithm is adopted to search for local maximum points (i.e., positions where the amplitude value is greater than the adjacent points before and after) on the amplitude envelope curve, and a sequence of maximum points arranged in chronological order is generated as the candidate markers for the symbol period boundary.

[0078] Step 422: According to the time intervals between adjacent maximum points in the sequence of maximum points, generate a set of candidate periods, and select the target period from the set of candidate periods whose difference from the theoretical period length is less than the preset threshold.

[0079] In this step, the time interval refers to the time difference between adjacent maximum points, which is used to calculate the actual symbol period length; the set of candidate periods refers to the set of candidate period lengths obtained by screening the time intervals whose differences from the theoretical period are less than the threshold; the preset threshold refers to the maximum deviation value allowed between the actual period and the theoretical period (such as (ms) for screening valid symbol periods.

[0080] In an embodiment of the present invention, calculate the time intervals between all adjacent maximum points (such as the time stamp of the nth maximum point minus the time stamp of the (n - 1)th maximum point), and retain the time intervals whose absolute difference from the theoretical period length (0.833 ms) is less than a preset threshold (such as ms) to form a set of target periods.

[0081] Step 423: Segment the waveform of the amplitude envelope according to the target period to generate a symbol period segment sequence.

[0082] In this step, the waveform refers to the curve form of the amplitude envelope changing with time, reflecting the amplitude characteristics of the modulation symbols; the segmentation process refers to the operation of cutting the waveform into equal-length time periods according to the symbol period length for symbol-level analysis; the symbol period segment sequence refers to the set of symbol period data segments arranged in chronological order generated after the segmentation process.

[0083] In an embodiment of the present invention, taking the maximum points as demarcation points, divide the amplitude envelope waveform into multiple equal-length time periods according to the target period length (such as 0.833 ms), and each time period corresponds to a symbol period segment to form a symbol period segment sequence.

[0084] Step 424: Calculate the absolute value of the derivative of the amplitude envelope within each symbol period segment in the symbol period segment sequence, identify the target time domain points where the absolute value of the derivative exceeds the preset mutation threshold and there is a phase continuity interruption, and use the target time domain points as phase jump points.

[0085] In this step, the absolute value of the derivative refers to the absolute value of the slope of the amplitude envelope curve at a certain point, calculated by first-order difference (such as ), for detecting amplitude mutations; the preset mutation threshold refers to the derivative absolute value threshold for determining phase jumps (such as 30% of the amplitude maximum value), and exceeding this value is regarded as an effective jump; the phase continuity interruption refers to a mutation of the signal phase exceeding a preset angle (such as 90°) before and after the jump point, indicating a modulation symbol switch.

[0086] In an embodiment of the present invention, take the first derivative of the amplitude envelope of each symbol period segment and calculate the absolute value of the derivative; when the absolute value of the derivative exceeds the preset mutation threshold (such as 30% of the amplitude maximum value) and the phase difference before and after this point exceeds 90°, it is determined as a phase jump point.

[0087] Step 425: Count the number and distribution positions of adjacent phase jump points within each symbol period segment to obtain a statistical result.

[0088] In this step, the statistical result refers to the number and position distribution data of phase jump points within the symbol period segment, used for modulation type matching.

[0089] In the embodiment of the present invention, the number of phase transition points within each symbol period segment is counted (such as 0 or 1 transition point), and the relative positions of the transition points within the period are recorded (such as the first 20% or the last 30% position of the period), forming the statistical results of the number distribution and position distribution of the transition points.

[0090] Step 426: Match the statistical results with the modulation type symbol transition rules defined in the preset civil aviation communication protocol to determine the modulation symbol type.

[0091] In this step, the modulation type symbol transition rule refers to the modulation symbol transition characteristics defined by the protocol (such as 1 180° transition per symbol for BPSK), which is used as the basis for matching; the matching operation refers to the process of logically comparing the statistical results with the protocol rules to screen out the modulation types that meet the conditions.

[0092] In the embodiment of the present invention, according to the protocol rules (such as the FSK modulation requires at most 1 phase transition within each symbol period and the transition position is in the middle), the modulation types whose statistical results meet the rules are screened (such as the candidate types with the number of transition points ≤ 1 and the position deviation < 10%), and the final modulation symbol type is output.

[0093] The embodiment of the present invention improves the reliability and anti-noise ability of modulation type recognition through the symbol period division and transition point statistical matching mechanism; based on the dynamic matching of the theoretical period and the measured period, it solves the period division error caused by the fuzzy symbol boundary; through the statistical matching of the phase transition points and the protocol rules, it effectively distinguishes similar modulation types; combined with derivative mutation detection and phase continuity analysis, it enhances the anti-interference ability of transition point recognition.

[0094] The present invention provides a specific embodiment. In step 407, based on the symbol rate and the stable frequency offset component in the modulation parameter characteristics, a mean sequence is generated, and the mean sequence is filtered to generate the frequency offset parameter characteristics, which specifically includes the following steps: Step 471: Arrange the stable frequency offset components in chronological order to generate a stable frequency offset component sequence.

[0095] In this step, the stable frequency offset component sequence refers to a set of stable frequency offset values arranged in chronological order, which is composed of the frequency offset data after removing the instantaneous noise and is used to characterize the systematic deviation of the carrier frequency.

[0096] In the embodiment of the present invention, the stable frequency offset values corresponding to multiple time points (such as -2.3 kHz, -2.2 kHz, -2.4 kHz) are arranged in chronological order of the time stamps to form a time series data, forming a stable frequency offset component sequence for subsequent symbol synchronization processing.

[0097] Step 472: Segment the stable frequency offset component sequence according to the symbol period corresponding to the symbol rate in the modulation parameter characteristics to generate a symbol synchronization segmented sequence.

[0098] In this step, the symbol period refers to the duration of a single modulation symbol, which is calculated from the reciprocal of the symbol rate (e.g., 1200 symbols / second corresponds to 0.833 ms) and is used for signal segmentation synchronization; the symbol synchronization segmented sequence refers to a set of multiple consecutive time periods generated by time-dividing the stable frequency offset component sequence according to the symbol period length, and each segment corresponds to a symbol period.

[0099] In the embodiment of the present invention, with the symbol period as the time window length, the stable frequency offset component sequence is divided into multiple consecutive time periods (e.g., each time period contains all offset values within 0.833 ms) to form a symbol synchronization segmented sequence.

[0100] Step 473: Calculate the mean value of the stable frequency offset components within each symbol synchronization segment in the symbol synchronization segmented sequence to generate a mean value sequence.

[0101] In this step, the symbol synchronization segment refers to a single time period in the symbol synchronization segmented sequence, which contains all the stable frequency offset component data within a symbol period; the mean value calculation refers to the operation of summing the stable frequency offset components within the symbol synchronization segment and dividing by the number of components, which is used to extract the segmented average offset value; the mean value sequence refers to a set of symbol synchronization segmented average offset values arranged in chronological order, reflecting the phased statistical characteristics of the carrier frequency offset.

[0102] In the embodiment of the present invention, after summing all the stable frequency offset components within each symbol synchronization segment and dividing by the number of components (e.g., if there are 5 offset values within the segment, the mean value is offset value / 5), the average offset value of each segment is obtained and arranged in chronological order as the mean value sequence.

[0103] Step 474: Filter the mean value sequence according to the cut-off frequency parameter corresponding to the symbol rate to generate a filtered stable frequency offset component.

[0104] In this step, the cut-off frequency parameter refers to the upper frequency limit value of the low-pass filter, which is set according to the symbol rate (e.g., 1 / 2 of the symbol rate) and is used to filter out high-frequency noise; the filtered stable frequency offset component refers to the mean value sequence data after low-pass filtering, which retains the low-frequency stable offset component and suppresses high-frequency fluctuations.

[0105] In an embodiment of the present invention, a low-pass filter is used to smooth the mean sequence, filtering out high-frequency noise components above the cut-off frequency (such as filtering out fluctuations above 600 Hz), and retaining the low-frequency stable offset component.

[0106] Step 475: Calculate the arithmetic mean of the filtered stable frequency offset components, and use the arithmetic mean as the frequency offset parameter feature.

[0107] In this step, the arithmetic mean refers to the calculation result of dividing the sum of the filtered stable frequency offset components by the number of components, representing the global average offset of the carrier frequency.

[0108] In an embodiment of the present invention, all the filtered stable frequency offset components are added and then divided by the total number of components (such as the sum of 10 components divided by 10) to obtain the global average offset value, which is used as the final frequency offset parameter feature (such as -2.3 kHz).

[0109] The embodiment of the present invention improves the measurement accuracy and stability of the frequency offset parameter through symbol synchronization segmentation and double filtering processing; eliminates the influence of inter-symbol interference on offset statistics through symbol synchronization segmentation; combines segmented mean calculation and low-pass filtering for double noise reduction to effectively suppress random fluctuations; and finally outputs the global arithmetic mean to solve the defect that traditional single-point measurement is easily interfered by instantaneous outliers.

[0110] The present invention provides a specific embodiment. Step 102: Based on the azimuth information of the interference signal in the spectral feature data, adjust the phases of the antenna elements in the phased array antenna array to generate target spectral data after anti-interference optimization, which specifically includes the following steps: Step 201: Extract multiple interference direction angle sets of the interference signals in the dynamic spectral interference environment from the azimuth information of the interference signals in the spectral feature data.

[0111] In this step, the interference direction angle set refers to the angle set of the incident directions of multiple interference signals extracted from the spectral data through the direction-of-arrival estimation technology, including the horizontal azimuth angle and the elevation angle.

[0112] In an embodiment of the present invention, spatial spectrum analysis is performed on the spectral feature data through the direction-of-arrival estimation algorithm to identify the incident direction angles (such as the horizontal azimuth angle and the elevation angle) of multiple interference signals, forming an interference direction angle set (such as 30°, 45°, 60°) for subsequent phase adjustment.

[0113] Step 202: According to the interference direction angle set, calculate the phase adjustment weight values of each antenna element in the phased array antenna array for each interference direction to generate a direction weight value set.

[0114] In this step, an antenna element refers to a single radiating element that independently controls the phase and amplitude in a phased array antenna array, and is used to receive or transmit radio frequency signals; the phase adjustment weight value refers to the phase compensation amount of the antenna element calculated to suppress a specific interference direction, usually in the form of a complex number (such as the amplitude and phase adjustment amount); the set of direction weight values refers to the phase adjustment weight matrix arranged according to the interference direction and the antenna element index, and is used for the joint control of multi-direction interference suppression.

[0115] In an embodiment of the present invention, the minimum variance distortionless response beamforming algorithm is adopted. With the goal of suppressing the signal energy in the interference direction, the phase compensation weight value of each antenna element in a specific interference direction is calculated to form a direction weight value matrix arranged according to the interference direction and the antenna element index.

[0116] Step 203: Superimpose the phase adjustment weight value of each antenna element in the set of direction weight values on the original phase data received by the corresponding antenna element to generate an adjusted phase value corresponding to each antenna element.

[0117] In this step, the original phase data refers to the initial phase information of the signal received by the antenna element without adjustment, which reflects the natural phase difference of the signal in space propagation; the superimposing operation refers to the process of algebraically adding the phase adjustment weight value and the original phase data to achieve the optimization of the phase distribution; the adjusted phase value refers to the final phase setting value of the antenna element obtained after the superimposing operation and is used for beamforming synthesis.

[0118] In an embodiment of the present invention, the original phase data of each antenna element (such as the initial phase value of the radio frequency signal) and the phase adjustment weight value (such as a +15° compensation amount) are algebraically added to obtain an adjusted phase value (such as the original phase 120° + the adjustment weight 15° = 135°) to achieve the optimization of the phase distribution.

[0119] Step 204: According to the adjusted phase value, perform beamforming synthesis on the phased array antenna array to suppress the interference energy component corresponding to the interference direction angle and generate an initial synthesized signal.

[0120] In this step, beamforming synthesis refers to the technology of vectorially superimposing the signals of multiple antenna elements according to the adjusted phase value to form a directional beam; the interference energy component refers to the radiation energy of the interference signal in the direction of the synthesized beam, and a gain null is formed in the interference direction through beamforming to suppress this component; the initial synthesized signal refers to the signal output after the first beamforming, which may still contain residual interference components that have not been completely suppressed.

[0121] In the embodiment of the present invention, the adjusted signals of all antenna elements are coherently combined through a vector superposition algorithm to form a radiation gain null point (such as -30 dB suppression) in the interference direction, while enhancing the gain in the direction of the target signal, and an initial combined signal is output.

[0122] Step 205: Perform interference residue detection on the initial combined signal. If the angle deviation between the interference direction angle of the detected residual interference signal and the angle of any interference direction in the interference direction angle set is less than a preset tolerance threshold, iteratively adjust the phase adjustment weight value until the interference direction angle of the residual interference signal exceeds the preset tolerance threshold, and generate a target phase adjustment weight set.

[0123] In this step, interference residue detection refers to performing a secondary direction estimation on the initial combined signal to detect the direction of the interference signal that has not been completely suppressed; the preset tolerance threshold refers to the maximum angle deviation allowed between the residual interference direction and the original interference direction (such as ), and exceeding this value is regarded as a new interference source; iterative adjustment refers to the process of cyclically optimizing the phase adjustment weight value according to the residual detection result until the interference suppression requirement is met; the target phase adjustment weight set refers to the final phase adjustment weight matrix obtained after iterative optimization, which realizes effective suppression of multiple interference directions.

[0124] In the embodiment of the present invention, the residual interference angle is detected through a secondary direction of arrival estimation. If there is residual interference (such as detecting a 32° interference, with a deviation of 2° from the original 30° interference), the direction weight value is updated and steps 202-204 are repeated until the residual interference angle exceeds the threshold (such as 35°).

[0125] Step 206: Perform phase adjustment on the phased array antenna array according to the target phase adjustment weight set to generate target spectrum data optimized for anti-interference.

[0126] In this step, phase adjustment refers to applying the target phase adjustment weight set to the antenna element controller to adjust the array phase distribution in real time; anti-interference optimization refers to the effect of improving the signal quality after interference suppression through phase adjustment and beamforming.

[0127] In the embodiment of the present invention, the finally optimized phase adjustment weight value is solidified to the antenna element controller to adjust the array phase distribution in real time, continuously suppress the signals in the interference direction, and output high-quality spectrum data containing only civil aviation radio target signals.

[0128] In the embodiments of the present invention, through multi-directional interference detection and iterative beamforming optimization, the anti-interference performance in a dynamic spectrum interference environment is improved; based on the joint optimization of phase weights in multiple interference directions, multi-directional synchronous suppression is achieved; through residual interference detection and iterative adjustment mechanisms, the suppression blind area of traditional single-shot beamforming is solved; finally, high-purity target spectrum data is output, providing a reliable data basis for subsequent parameter testing and traceability.

[0129] The present invention provides a specific embodiment. In step 105, the modulation parameter features and the frequency offset parameter features are combined to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of civil aviation radio, which specifically includes the following steps: Step 501: Combine the modulation parameter features and the frequency offset parameter features to generate a device parameter combination sequence.

[0130] In this step, the device parameter combination sequence refers to a set of modulation parameter features and frequency offset parameter features arranged in chronological order, and each element is combined data containing multiple parameters.

[0131] In the embodiments of the present invention, using the feature vector splicing technology, the modulation symbol type is encoded as a digital identifier (such as QPSK is encoded as 1), the symbol rate (such as 1200 symbols / second) and the stable frequency offset mean value (such as -2.3 kHz) are combined into a multi-dimensional vector, and arranged in chronological order to form a device parameter combination sequence.

[0132] Step 502: Add the target parameter combinations in the device parameter combination sequence whose modulation symbol type satisfies the device parameter constraint range in the preset civil aviation communication protocol and the fluctuation range of the stable frequency offset is within the offset tolerance interval to the candidate device parameter combination set.

[0133] In this step, the device parameter constraint range refers to the value range of parameters such as modulation type and symbol rate allowed in the civil aviation communication protocol. For example, VHF communication limits the modulation type to AM / FM; the stable frequency offset refers to the filtered frequency offset mean value, which reflects the systematic deviation of the carrier frequency, such as -2.3 kHz 0.1 kHz; the candidate device parameter combination set refers to the set of qualified parameter combinations retained after screening by the protocol constraint conditions, which is used for further matching and verification.

[0134] In the embodiments of the present invention, according to the device parameter constraint range defined by the protocol (such as VHF communication requires the modulation type to be AM or FM) and the offset tolerance interval (such as frequency offset ≤ ), filter out the parameter combinations whose modulation symbol type is within the allowable range and the fluctuation range of the stable frequency offset (such as ) is within the tolerance interval to form a candidate device parameter combination set.

[0135] Step 503: Calculate the matching degree between the timestamps of the phase jump points in the set of candidate device parameter combinations and the standard time template in the preset civil aviation communication protocol, retain the candidate device parameter combinations with a matching degree higher than the preset threshold, and generate a set of target device parameter combinations.

[0136] In this step, the timestamp refers to the absolute time mark when the phase jump point occurs, accurate to the microsecond level, and is used to align with the protocol template; the standard time template refers to the symbol period alignment rule specified by the protocol. For example, the ACARS protocol requires that the starting time error of each symbol period ≤ 5 μs; the matching degree refers to the quantization value of the time alignment accuracy between the measured timestamp sequence and the protocol template, which is obtained through time difference statistics; the set of target device parameter combinations refers to the set of parameter combinations with a matching degree higher than the threshold, representing the device parameters that meet the protocol time synchronization requirements.

[0137] In the embodiment of the present invention, the measured phase jump point timestamp sequence is time-aligned with the protocol template (such as the symbol period alignment rule specified by the ACARS protocol), the matching degree (such as the sum of the squares of the timestamp differences) is calculated, and the combinations with a matching degree higher than the preset threshold (such as the matching degree ≥ 85%) are retained to generate a set of target device parameter combinations.

[0138] Step 504: Based on the mean value of the stable frequency offsets in the set of target device parameter combinations and the nominal frequency offset of the preset device type, determine the device type label of each target device parameter combination in the set of target device parameter combinations.

[0139] In this step, the nominal frequency offset refers to the theoretical frequency offset value calibrated when the device leaves the factory. For example, a certain type of radio has a nominal offset of -2.0 kHz; the device type label refers to the code that uniquely identifies the device model, such as "VHF-COM-001", which is determined through parameter matching.

[0140] In the embodiment of the present invention, calculate the absolute difference between the measured stable frequency offset mean value (such as -2.3 kHz) and the nominal offsets of each device type (such as device A with a nominal -2.0 kHz and device B with a nominal -2.5 kHz), and use the device type with the smallest difference (such as device B, with a difference of 0.2 kHz) as the device type label of the current parameter combination.

[0141] Step 505: Correlate the device type label, modulation symbol type, and the mean value of the stable frequency offset in the set of target device parameter combinations to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio.

[0142] In this step, the association operation refers to the operation of establishing a logical link between the device type tag and the parameter characteristics to form a structured database entry; the transmitting source device parameters refer to the set of nominal parameters of the device when leaving the factory, including the device model, the nominal value of the modulation type, the nominal frequency offset, etc.; the measured parameters refer to the set of parameters actually measured by this method, including the modulation symbol type, the average value of the stable frequency offset, etc.; the mapping relationship library refers to the database that stores the association relationship between the transmitting source device parameters and the measured parameters, and supports the intelligent matching query of the device identity and parameters.

[0143] In the embodiment of the present invention, the key-value pair database technology is adopted, with the device type tag as the primary key, and the modulation symbol type, the average value of the stable frequency offset (such as -2.3 kHz) and the measured timestamp are associated and stored to form a dynamic mapping relationship library of the civil aviation radio transmitting source device parameters and the measured parameters.

[0144] The embodiment of the present invention realizes the construction of a high-precision device parameter mapping relationship; based on the dual screening mechanism of protocol constraint and time template matching, it improves the compliance and accuracy of parameter combinations; by dynamically comparing the measured offset average value with the nominal value, it solves the defect of the traditional method relying on the update lag of the static device database; constructs an extensible mapping relationship library to support the intelligent association and rapid traceability of multi-device type parameters.

[0145] Figure 2 The following is a schematic structural diagram of a civil aviation radio parameter intelligent testing and traceability system provided by an embodiment of the present invention, as Figure 2 shown, the system includes: An acquisition module 21, configured to acquire the spectrum feature data obtained by scanning the target frequency band by the phased array antenna array in the dynamic spectrum interference environment; An adjustment module 22, configured to adjust the phases of the antenna units in the phased array antenna array based on the interference signal azimuth information of the spectrum feature data to generate target spectrum data after anti-interference optimization; A conversion module 23, configured to convert the civil aviation radio receiving signal in the target spectrum data into time-frequency domain data to generate a signal spectrogram; An analysis module 24, configured to identify the time-frequency feature pattern of the civil aviation radio parameters from the signal spectrogram, and analyze the time-frequency feature pattern to obtain the modulation parameter feature and the frequency offset parameter feature that match the preset civil aviation communication protocol; A combination module 25, configured to combine the modulation parameter feature and the frequency offset parameter feature to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio; A generation module 26, configured to generate a civil aviation radio parameter traceability result including the device identity identifier and the parameter deviation value based on the mapping relationship library, the modulation parameter feature, and the frequency offset parameter feature.

[0146] Figure 2 The described intelligent test and traceability system for civil aviation radio parameters can execute Figure 1 For the intelligent test and traceability method of civil aviation radio parameters described in the illustrated embodiment, its implementation principle and technical effects will not be elaborated further. For the intelligent test and traceability system for civil aviation radio parameters in the above embodiment, the specific ways in which each module and unit perform operations have been described in detail in the embodiment related to this method, and will not be elaborated here.

[0147] In a possible design, Figure 2 The intelligent test and traceability system for civil aviation radio parameters in the illustrated embodiment can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32.

[0148] The processing component 32 is used to: obtain the spectral feature data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment; based on the azimuth information of the interference signal in the spectral feature data, adjust the phases of the antenna elements in the phased array antenna array to generate target spectral data after anti-interference optimization; convert the civil aviation radio reception signal in the target spectral data into time-frequency domain data to generate a signal map; identify the time-frequency feature pattern of the civil aviation radio parameters from the signal map, and analyze the time-frequency feature pattern to generate modulation parameter features and frequency offset parameter features that match a preset civil aviation communication protocol; combine the modulation parameter features and the frequency offset parameter features to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio; based on the mapping relationship library, the modulation parameter features, and the frequency offset parameter features, generate a civil aviation radio parameter traceability result including device identity identification and parameter deviation values.

[0149] Among them, the processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for executing the above method.

[0150] The storage component 31 is configured to store various types of data to support the operation of the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0151] Of course, the computing device may necessarily further include other components, such as input / output interfaces, display components, communication components, etc.

[0152] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above-mentioned peripheral interface module can be an output device, an input device, etc.

[0153] The communication component is configured to facilitate communication between the computing device and other devices in a wired or wireless manner, etc.

[0154] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. At this time, the computing device can refer to a cloud server, and the above-mentioned processing component, storage component, etc. can be basic server resources leased or purchased from a cloud computing platform.

[0155] The embodiment of the present invention also provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it can implement the above Figure 1 intelligent test and traceability method for civil aviation radio parameters shown in the embodiment.

[0156] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0157] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement without creative efforts.

[0158] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent testing and traceability method for civil aviation radio parameters, characterized in that, Including: Obtain the spectral feature data obtained by scanning the target frequency band by the phased array antenna array in a dynamic spectrum interference environment; Based on the azimuth information of the interference signal in the spectral feature data, adjust the phases of the antenna elements in the phased array antenna array to generate target spectral data after anti-interference optimization; Convert the civil aviation radio receiving signal in the target spectral data into time-frequency domain data to generate a signal spectrogram; Identify the time-frequency feature pattern of the civil aviation radio parameters from the signal spectrogram, and analyze the time-frequency feature pattern to generate modulation parameter features and frequency offset parameter features that match the preset civil aviation communication protocol; Combine the modulation parameter features and the frequency offset parameter features to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio; Based on the mapping relationship library, the modulation parameter features, and the frequency offset parameter features, generate a civil aviation radio parameter traceability result including device identity identification and parameter deviation values.

2. The method according to claim 1, characterized in that, Identify the time-frequency feature pattern of the civil aviation radio parameters from the signal spectrogram, and analyze the time-frequency feature pattern to generate modulation parameter features and frequency offset parameter features that match the preset civil aviation communication protocol, including: Perform time-frequency decomposition on the signal spectrogram to generate a time-frequency feature pattern of the civil aviation radio parameters, and the time-frequency feature pattern is determined by a low-frequency component and a high-frequency component; Analyze the amplitude envelope of the low-frequency component to determine the phase jump point and the modulation symbol type; Locate the carrier phase mutation point synchronized with the phase jump point in the high-frequency component; According to the instantaneous frequency value corresponding to the carrier phase mutation point, calculate the frequency offset of the carrier frequency of the civil aviation radio receiving signal relative to the nominal value, and determine the stable frequency offset component according to the frequency offset; Match the modulation symbol type with the modulation types in the preset civil aviation communication protocol to select multiple candidate modulation types that meet the preset conditions; Calculate the symbol rate variance value of each candidate modulation type according to the time stamp interval between adjacent phase jump points, and use the candidate modulation type with the smallest symbol rate variance value as the modulation parameter feature; Based on the symbol rate in the modulation parameter feature and the stable frequency offset component, generate a mean sequence, and perform filtering processing on the mean sequence to generate a frequency offset parameter feature.

3. The method according to claim 2, wherein Perform time-frequency decomposition on the signal spectrogram to generate a time-frequency feature pattern of the civil aviation radio parameters, and the time-frequency feature pattern is determined by a low-frequency component and a high-frequency component, including: Decompose the signal spectrogram to generate multiple frequency band components; Calculate the amplitude change rate of each frequency band component; Use the frequency band components with an amplitude change rate lower than the first threshold as high-frequency components, and use the frequency band components with an amplitude change rate higher than the second threshold as high-frequency components; Superpose and fuse the amplitude data of the low-frequency component and the amplitude data of the high-frequency component to generate a time-frequency feature pattern.

4. The method according to claim 2, wherein Analyze the amplitude envelope of the low-frequency component to determine the phase jump point and the modulation symbol type, including: Detect the extreme points of the amplitude envelope of the low-frequency component according to the theoretical period length corresponding to the preset symbol rate, so as to generate a sequence of maximum points; Generate a candidate period set according to the time intervals between adjacent maximum points in the sequence of maximum points, and screen out the target period from the candidate period set, the difference between which and the theoretical period length is less than a preset threshold; Segment the waveform of the amplitude envelope according to the target period to generate a sequence of symbol period segments; Calculate the absolute value of the derivative of the amplitude envelope within each symbol period segment in the sequence of symbol period segments, identify the target time domain points where the absolute value of the derivative exceeds the preset mutation threshold and there is a phase continuity interruption, and take the target time domain points as phase jump points; Count the number and distribution positions of adjacent phase jump points within each symbol period segment to obtain a statistical result; Match the statistical result with the symbol jump rule of the modulation type defined in the preset civil aviation communication protocol to determine the modulation symbol type.

5. The method according to claim 2, wherein Based on the symbol rate and the stable frequency offset component in the modulation parameter feature, generate a mean value sequence, and perform filtering processing on the mean value sequence to generate a frequency offset parameter feature, including: Arrange the stable frequency offset components in chronological order to generate a sequence of stable frequency offset components; Segment the sequence of stable frequency offset components according to the symbol period corresponding to the symbol rate in the modulation parameter feature to generate a symbol synchronization segmented sequence; Calculate the mean value of the stable frequency offset components within each symbol synchronization segment in the symbol synchronization segmented sequence to generate a mean value sequence; Perform filtering processing on the mean value sequence according to the cut-off frequency parameter corresponding to the symbol rate to generate a filtered stable frequency offset component; Calculate the arithmetic mean value of the filtered stable frequency offset components, and take the arithmetic mean value as the frequency offset parameter feature.

6. The method according to claim 1, characterized in that Based on the interference signal azimuth information of the spectrum feature data, adjust the phases of the antenna elements in the phased array antenna array to generate target spectrum data after anti-interference optimization, including: Extract multiple interference direction angle sets of the interference signals in the dynamic spectrum interference environment from the interference signal azimuth information of the spectrum feature data; Calculate the phase adjustment weight values of each antenna element in the phased array antenna array for each interference direction according to the interference direction angle set to generate a set of direction weight values; Superimpose the phase adjustment weight value of each antenna element in the set of direction weight values on the original phase data received by the corresponding antenna element to generate an adjusted phase value corresponding to each antenna element; Perform beamforming synthesis on the phased array antenna array according to the adjusted phase value to suppress the interference energy component corresponding to the interference direction angle and generate an initial synthesized signal; Perform interference residue detection on the initial synthesized signal. If the angular deviation between the interference direction angle of the detected residue interference signal and the angle of any interference direction in the interference direction angle set is less than the preset tolerance threshold, iteratively adjust the phase adjustment weight value until the interference direction angle of the residue interference signal exceeds the preset tolerance threshold, and generate a target phase adjustment weight set; Perform phase adjustment on the phased array antenna array according to the target phase adjustment weight set to generate target spectrum data after anti-interference optimization.

7. The method according to claim 1, characterized in that, Combine the modulation parameter features and the frequency offset parameter features to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio, including: Combine the modulation parameter features and the frequency offset parameter features to generate a device parameter combination sequence; Add the target parameter combinations in the device parameter combination sequence whose modulation symbol types satisfy the device parameter constraint range in the preset civil aviation communication protocol and the fluctuation range of the stable frequency offset is within the offset tolerance interval to the candidate device parameter combination set; Calculate the matching degree between the timestamps of the phase jump points in the candidate device parameter combination set and the standard time template in the preset civil aviation communication protocol, and retain the candidate device parameter combinations with a matching degree higher than the preset threshold to generate a target device parameter combination set; Based on the mean value of the stable frequency offset in the target device parameter combination set and the nominal frequency offset of the preset device type, determine the device type label of each target device parameter combination in the target device parameter combination set; Associate the device type label, modulation symbol type, and mean value of the stable frequency offset in the target device parameter combination set to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio.

8. An intelligent test and traceability system for civil aviation radio parameters, characterized in that, Including: An acquisition module for acquiring spectrum feature data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment; An adjustment module for adjusting the phases of the antenna elements in the phased array antenna array based on the azimuth information of the interference signal in the spectrum feature data to generate target spectrum data after anti-interference optimization; A conversion module for converting the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal map; An analysis module for identifying the time-frequency feature pattern of the civil aviation radio parameters from the signal map and analyzing the time-frequency feature pattern to obtain modulation parameter features and frequency offset parameter features that match the preset civil aviation communication protocol; A combination module for combining the modulation parameter features and the frequency offset parameter features to generate a mapping relationship library between the transmitting source device parameters and the measured parameters of the civil aviation radio; A generation module for generating a civil aviation radio parameter traceability result including a device identity identifier and a parameter deviation value based on the mapping relationship library, the modulation parameter features, and the frequency offset parameter features.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement an intelligent test and traceability method for civil aviation radio parameters as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, A computer program is stored, and when the computer program is executed by a computer, it implements an intelligent test and traceability method for civil aviation radio parameters as described in any one of claims 1 to 7.

Images