A method and system for intelligent testing and tracing of civil aviation radio parameters

Abstract

The present invention relates to the technical field of intelligent data testing and traceability, and provides a method and system for intelligent testing and traceability of civil aviation radio parameters. The method adjusts the phased array antenna array by acquiring target spectrum characteristic data obtained by scanning the target frequency band by the phased array antenna array in a dynamic spectrum interference environment; converts the civil aviation radio receiving signal in the target spectrum data after anti-interference optimization into time-frequency domain data, generates a signal spectrum, generates modulation parameter characteristics and frequency offset parameter characteristics, and generates civil aviation radio parameter traceability results containing device identification and parameter deviation values. The present invention solves the problems of unstable anti-interference effect in the prior art and low intelligence level and practicality of the overall system through optimized adjustment and signal characteristic analysis of the phased array antenna in a dynamic spectrum interference environment, thereby realizing intelligent testing and precise traceability of civil aviation radio parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of data intelligent testing and tracing technology, and in particular to a method and system for intelligent testing and tracing of civil aviation radio parameters. Background Art

[0002] Civil aviation radio communications face increasingly complex electromagnetic environments, particularly around airports and in densely populated airways. The interweaving and overlapping of various radio signals can severely interfere with civil aviation ground-to-air communication links. To ensure flight safety and communication reliability, there is an urgent need for real-time intelligent testing of civil aviation radio receive signal parameters and the ability to trace the identity of interference sources or transmitting devices to support rapid location and interference mitigation.

[0003] To address these technical requirements, the current mainstream solution is an automated signal recognition method based on a combination of multi-antenna joint processing and time-frequency analysis. This solution deploys a multi-channel receiving array, implements synchronous signal acquisition within the target frequency band, and combines beamforming technology to perform spatial filtering on interference signals. This method then compares the signal with an existing signal feature database to preliminarily determine the signal source and its communication protocol type. Existing technical solutions have some inherent flaws. For example, when the direction of the interference signal is constantly changing, fixed beamforming strategies are unable to continuously optimize the receiving pattern, resulting in unstable anti-interference effects and affecting the accuracy of subsequent parameter extraction. The isolated signal feature extraction and device identification processes fail to effectively integrate multi-dimensional parameter information, limiting the overall system's intelligence and practicality. Summary of the Invention

[0004] The present invention provides a civil aviation radio parameter intelligent testing and tracing method and system, which are used to solve the problems in the prior art of unstable anti-interference effect and low intelligence level and practicality of the overall system.

[0005] In a first aspect, the present invention provides a method for intelligent testing and tracing of civil aviation radio parameters, comprising:

[0006] Acquire spectrum characteristic data obtained by scanning the target frequency band by the phased array antenna array in a dynamic spectrum interference environment;

[0007] Adjusting the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization;

[0008] Converting the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal spectrum;

[0009] Identifying a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, parsing the time-frequency characteristic pattern to obtain a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol;

[0010] Combining the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and measured parameters of the civil aviation radio;

[0011] Based on the mapping relationship library, the modulation parameter characteristics and the frequency offset parameter characteristics, a civil aviation radio parameter traceability result including a device identity and a parameter deviation value is generated.

[0012] Optionally, identifying a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, parsing the time-frequency characteristic pattern to generate a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol, including:

[0013] Performing time-frequency decomposition on the signal spectrum to generate a time-frequency characteristic pattern of civil aviation radio parameters, wherein the time-frequency characteristic pattern is determined by a low-frequency component and a high-frequency component;

[0014] Analyzing the amplitude envelope of the low-frequency component to determine a phase jump point and a modulation symbol type;

[0015] Locating a carrier phase mutation point synchronized with the phase jump point in the high-frequency component;

[0016] Calculating a frequency offset of the carrier frequency of the civil aviation radio reception signal relative to a nominal value based on an instantaneous frequency value corresponding to the carrier phase mutation point, and determining a stable frequency offset component based on the frequency offset;

[0017] Matching the modulation symbol type with the modulation type in the preset civil aviation communication protocol to select a plurality of candidate modulation types that meet preset conditions;

[0018] Calculate the symbol rate variance value of each candidate modulation type according to the timestamp interval of adjacent phase jump points, and use the candidate modulation type with the smallest symbol rate variance value as the modulation parameter feature;

[0019] Based on the symbol rate and the stable frequency offset component in the modulation parameter feature, a mean value sequence is generated, and filtering processing is performed on the mean value sequence to generate a frequency offset parameter feature.

[0020] Optionally, performing time-frequency decomposition on the signal spectrum to generate a time-frequency characteristic pattern of civil aviation radio parameters, wherein the time-frequency characteristic pattern is determined by a low-frequency component and a high-frequency component, including:

[0021] Decomposing the signal spectrum to generate multiple frequency band components;

[0022] Calculate the amplitude change rate of each frequency band component;

[0023] The frequency band component whose amplitude change rate is lower than the first threshold is regarded as the high frequency component, and the frequency band component whose amplitude change rate is higher than the second threshold is regarded as the high frequency component;

[0024] The amplitude data of the low-frequency component and the amplitude data of the high-frequency component are superimposed and fused to generate a time-frequency feature pattern.

[0025] Optionally, parsing the amplitude envelope of the low-frequency component to determine a phase jump point and a modulation symbol type includes:

[0026] According to the theoretical cycle length corresponding to the preset symbol rate, the amplitude envelope of the low-frequency component is subjected to extreme point detection to generate a maximum point sequence;

[0027] Generating a candidate period set according to the time intervals between adjacent maximum points in the maximum point sequence, and screening out a target period whose difference with the theoretical period length is less than a preset threshold from the candidate period set;

[0028] Segmenting the waveform of the amplitude envelope according to the target period to generate a symbol period segment sequence;

[0029] Calculating the absolute value of the derivative of the amplitude envelope in each symbol period in the symbol period sequence, identifying a target time domain point where the absolute value of the derivative exceeds a preset mutation threshold and there is a phase continuity interruption, and using the target time domain point as a phase jump point;

[0030] Counting the number and distribution positions of adjacent phase jump points in each symbol period to obtain statistical results;

[0031] The statistical result is matched with the modulation type symbol hopping rule defined in the preset civil aviation communication protocol to determine the modulation symbol type.

[0032] Optionally, generating a mean sequence based on the symbol rate and the stable frequency offset component in the modulation parameter feature, and filtering the mean sequence to generate a frequency offset parameter feature, includes:

[0033] Arranging the stable frequency offset components in time sequence to generate a stable frequency offset component sequence;

[0034] According to the symbol period corresponding to the symbol rate in the modulation parameter characteristics, the stable frequency offset component sequence is segmented to generate a symbol synchronization segment sequence;

[0035] Calculating the mean of a stable frequency offset component in each symbol synchronization segment in the symbol synchronization segment sequence to generate a mean sequence;

[0036] performing filtering processing on the mean value sequence according to a cutoff frequency parameter corresponding to the symbol rate to generate a filtered stable frequency offset component;

[0037] An arithmetic mean value of the filtered stable frequency offset component is calculated, and the arithmetic mean value is used as a frequency offset parameter feature.

[0038] In a second aspect, the present invention provides a civil aviation radio parameter intelligent testing and traceability system, comprising:

[0039] An acquisition module is used to obtain spectrum characteristic data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment;

[0040] An adjustment module is configured to adjust the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization;

[0041] a conversion module, configured to convert the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal spectrum;

[0042] an analysis module, configured to identify a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, analyze the time-frequency characteristic pattern, and obtain a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol;

[0043] a combining module, combining the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio;

[0044] A generation module generates a civil aviation radio parameter traceability result including a device identity and a parameter deviation value based on the mapping relationship library, the modulation parameter characteristics and the frequency offset parameter characteristics.

[0045] In a third aspect, the present invention provides a computing device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a civil aviation radio parameter intelligent testing and traceability method as described in any one of the first aspects.

[0046] In a fourth aspect, the present invention provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement a civil aviation radio parameter intelligent testing and traceability method as described in any one of the first aspects.

[0047] In the present invention, spectrum characteristic data obtained by scanning the target frequency band of the phased array antenna array in a dynamic spectrum interference environment is obtained; based on the interference signal azimuth information of the spectrum characteristic data, the phase of each antenna unit in the phased array antenna array is adjusted to generate target spectrum data after anti-interference optimization; the civil aviation radio receiving signal in the target spectrum data is converted into time-frequency domain data to generate a signal spectrum; the time-frequency characteristic pattern of the civil aviation radio parameters is identified from the signal spectrum, and the time-frequency characteristic pattern is analyzed to obtain modulation parameter characteristics and frequency offset parameter characteristics that match the preset civil aviation communication protocol; the modulation parameter characteristics and the frequency offset parameter characteristics are combined to generate a mapping relationship library between the transmission source equipment parameters of the civil aviation radio and the measured parameters; based on the mapping relationship library, the modulation parameter characteristics and the frequency offset parameter characteristics, a civil aviation radio parameter traceability result containing equipment identity and parameter deviation value is generated. The technical solution provided by the present invention captures the original spectrum characteristics of civil aviation radio signals in real time by actively scanning the target frequency band in a dynamic spectrum interference environment, thereby overcoming the data lag problem of traditional static spectrum monitoring in dynamic interference scenarios; dynamically adjusts the antenna phase distribution using the azimuth information of the interference signal, realizes radiation gain suppression in the interference direction at the physical layer, and improves the anti-interference ability of the target signal; characterizes the dynamic characteristics of the signal through the joint time-frequency distribution, and enhances the ability to capture instantaneous frequency offsets and modulation mutations; analyzes the time-frequency feature pattern based on the constraints of the civil aviation communication protocol, and separates the modulation parameters and frequency offset features; constructs a dynamic mapping relationship between equipment parameters and measured features, and realizes the association modeling of parameter features and equipment identity, solving the update lag and insufficient coverage defects of traditional methods that rely on manual calibration databases; outputs equipment identity and parameter deviations through intelligent matching, and simultaneously completes parameter compliance testing and equipment source tracing, breaking through the efficiency bottleneck caused by the step-by-step operation of testing and tracing in the existing technology. Among them, by analyzing the low-frequency modulation characteristics and high-frequency carrier characteristics step by step, combining protocol constraint screening and symbol rate variance optimization, the accuracy of modulation type identification in complex interference environments is improved; the phase jump point is used to synchronously locate the carrier phase mutation, separate the instantaneous noise and stable offset components, and solve the problem that frequency offset measurement in traditional methods is easily affected by random interference.

[0048] These and other aspects of the present invention will become more readily apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 A flowchart of a method for intelligent testing and tracing of civil aviation radio parameters provided by an embodiment of the present invention;

[0051] Figure 2 A schematic diagram of the structure of a civil aviation radio parameter intelligent testing and traceability system provided by an embodiment of the present invention;

[0052] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0054] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial 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 of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types.

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0056] Figure 1 The present invention provides a flow chart of a method for intelligent testing and tracing of civil aviation radio parameters, as shown in FIG. Figure 1 As shown, the method includes:

[0057] In response to the technical difficulties in real-time detection and tracing of civil aviation radio signal parameters in a dynamic spectrum interference environment, the existing technology has three major bottlenecks: first, it is difficult for traditional fixed-beam antennas to dynamically suppress time-varying interference, resulting in insufficient signal-to-noise ratio in signal acquisition; second, conventional spectrum analysis cannot effectively separate the time-frequency characteristics of civil aviation signals from interference components, resulting in misjudgment of modulation parameters; third, equipment parameter testing and source tracing rely on manual association, and it is difficult to balance real-time and accuracy. To address these problems, the present invention integrates phased array beamforming and time-frequency domain analysis, realizes spatial domain interference suppression by dynamically sensing the interference direction, combines signal spectrum to analyze the modulation and frequency deviation characteristics of civil aviation radio receiving signals, constructs a mapping relationship library between the transmission source equipment parameters and the measured parameters, and finally synchronously outputs the parameter deviation value and the equipment identity in the interference environment. Based on this, the present invention provides a method for intelligent testing and tracing of civil aviation radio parameters, such as Figure 1 ,include:

[0058] Step 101: Acquire spectrum characteristic data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment.

[0059] In this step, the phased array antenna array refers to an array composed of multiple antenna units arranged in a specific geometric structure, which realizes electronic scanning and shaping of the beam direction by controlling the phase difference of each unit, and is used for directional signal reception in a dynamic environment; the dynamic spectrum interference environment refers to an electromagnetic environment with time-varying interference signals (such as burst noise and co-channel interference), and the intensity, frequency and orientation of the interference signals change rapidly over time; the target frequency band refers to the specific frequency range used by civil aviation radio communication systems, including the very high frequency communication band (118-137MHz) and the ADS-B signal band (1090MHz); the spectrum characteristic data refers to the set of signal parameters obtained through spectrum analysis, including signal strength, frequency distribution, phase information and spatial orientation information of the interference signal.

[0060] In an embodiment of the present invention, the phased array antenna array continuously samples the signals within the target frequency band through electronic scanning to generate spectral characteristic data containing signal strength, frequency distribution and phase information. During the scanning process, the beam direction of the antenna array is dynamically adjusted according to the preset scanning path to ensure coverage of all potential signal sources within the target frequency band.

[0061] Step 102: Based on the interference signal azimuth information of the spectrum characteristic data, the phase of each antenna unit in the phased array antenna array is adjusted to generate target spectrum data after anti-interference optimization.

[0062] In this step, the interference signal azimuth information refers to the incident direction of the interference signal calculated by the wave direction estimation algorithm, including the horizontal azimuth angle and the pitch angle; the phase of each antenna unit refers to the RF signal phase value of each antenna unit in the phased array antenna array, and the beam direction control is achieved by adjusting the phase difference; the adjustment operation refers to the dynamic calculation and setting of the phase compensation value of the antenna unit according to the interference signal azimuth to suppress the signal reception in the interference direction; the target spectrum data refers to the civil aviation radio signal spectrum data retained after the interference suppression processing, and its interference component is attenuated.

[0063] In this embodiment of the present invention, the phase compensation value for each antenna element is determined by calculating the angle between the incident direction of the interference signal and the normal direction of the antenna array. This allows the antenna array's composite beam to form a radiation gain null in the direction of the interference signal, thereby generating target spectrum data optimized for interference rejection. During the phase adjustment process, a closed-loop feedback control algorithm is used to update the phase compensation value in real time, ensuring that the interference suppression effect is synchronized with the dynamic interference environment.

[0064] Step 103: Convert the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal spectrum.

[0065] In this step, time-frequency domain data refers to the signal representation form that contains both time and frequency dimension information. The time-domain signal is converted into time-frequency joint distribution data through the time-frequency analysis algorithm; the signal spectrum refers to the time-frequency domain data presented in the form of a two-dimensional image, with the horizontal axis being time and the vertical axis being frequency, and the color depth representing the signal strength.

[0066] In an embodiment of the present invention, a short-time Fourier transform algorithm is used to perform time-frequency decomposition of the signal, and the spectral distribution of the signal is calculated in units of time windows, ultimately generating a two-dimensional time-frequency feature map with time as the horizontal axis, frequency as the vertical axis, and signal intensity as the color depth.

[0067] Step 104: Identify the time-frequency characteristic pattern of the civil aviation radio parameters from the signal spectrum, and analyze the time-frequency characteristic pattern to generate modulation parameter characteristics and frequency offset parameter characteristics that match the preset civil aviation communication protocol.

[0068] In this step, the time-frequency characteristic pattern refers to the time-frequency distribution law that characterizes the characteristics of civil aviation radio parameters in the signal spectrum, including the time-frequency ridges of the modulation symbols and the offset trajectory of the carrier frequency; the analytical operation refers to the technical process of separating and extracting the modulation parameter characteristics and frequency offset parameter characteristics from the time-frequency characteristic pattern, including time-frequency ridge tracking and feature quantization; the modulation parameter characteristics refer to the parameter set that describes the signal modulation method, including the modulation type, symbol rate and phase jump point distribution; the frequency offset parameter characteristics refer to the parameter set that describes the deviation of the carrier frequency from the nominal value, including the instantaneous offset, the stable offset component and the offset fluctuation variance.

[0069] In an embodiment of the present invention, the time-frequency ridges in the signal spectrum are extracted through an edge detection algorithm to separate the modulation characteristic components and the frequency offset components of the civil aviation signal; according to the modulation type and frequency tolerance range defined in the preset civil aviation communication protocol, the separated characteristic components are matched and verified, and finally the modulation parameter characteristics (such as modulation symbol rate, modulation type) and frequency offset parameter characteristics (such as carrier frequency deviation value, stable offset component) that match the protocol are output.

[0070] Step 105: combining the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio.

[0071] In this step, the combination operation refers to the process of merging the modulation parameter characteristics and the frequency offset parameter characteristics into a multidimensional feature vector, which is used to construct a device parameter mapping relationship; the transmitting source device parameters refer to the factory nominal parameters of the civil aviation radio transmitting equipment, including the equipment model, modulation type nominal value and frequency tolerance range; the measured parameters refer to the modulation parameter characteristics and frequency offset parameter characteristics actually extracted from the received signal by this method; the mapping relationship library refers to a database that stores the association relationship between the transmitting source device parameters and the measured parameter characteristics, which is used for matching queries between device identity and parameter traceability.

[0072] In an embodiment of the present invention, the modulation parameter characteristics (such as symbol rate) and the frequency offset parameter characteristics (such as stable offset) are combined into a multi-dimensional feature vector through 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 association database.

[0073] Step 106: Based on the mapping relationship library, the modulation parameter characteristics, and the frequency offset parameter characteristics, a civil aviation radio parameter traceability result including a device identity and a parameter deviation value is generated.

[0074] In this step, the equipment identity refers to the coded information that uniquely identifies the civil aviation radio transmitting equipment, including the equipment serial number, registration number and agency code; the parameter deviation value refers to the quantitative value of the difference between the measured parameter characteristics and the nominal parameters of the civil aviation radio transmitting equipment, which is used to evaluate the equipment performance compliance.

[0075] In an embodiment of the present invention, a feature similarity matching algorithm (such as cosine similarity calculation) is used to retrieve the device parameter combination closest to the current parameter feature in the mapping relationship library, and the corresponding device identity (such as the 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.

[0076] For example, in an airport tower radio monitoring scenario, the phased array antenna array scans the VHF communication frequency band (125MHz) and detects a co-frequency interference signal from 30° in the southeast direction; adjusts the antenna unit phase based on the interference azimuth information to form a -30dB radiation gain suppression in the interference direction; converts the interference suppressed signal into time-frequency domain data to generate a two-dimensional spectrum containing the time-frequency ridges of the ACARS signal; and parses the modulation symbol rate of 1200bps and the Stable frequency offset; matching and combining the parameter characteristics with the pre-stored airborne radio parameter library to build a device parameter mapping relationship; finally outputting the device identity (such as the B-1234 flight radio) and frequency deviation value , complete parameter compliance testing and equipment traceability.

[0077] The embodiments of the present invention improve the signal-to-noise ratio of signal acquisition through spatial domain interference suppression, thereby solving the parameter measurement distortion problem of traditional methods in dynamic interference environments; based on 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, intelligent linkage of testing and traceability is realized, breaking through the limitations of low efficiency and easy errors of manual correlation operations, and realizing high-precision testing of civil aviation radio parameters and equipment source tracing in dynamic spectrum interference environments.

[0078] The present invention provides a specific embodiment, step 104, identifying a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, parsing the time-frequency characteristic pattern to generate a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol, specifically comprising the following steps:

[0079] Step 401: performing time-frequency decomposition on the signal spectrum to generate a time-frequency characteristic pattern of civil aviation radio parameters, wherein the time-frequency characteristic pattern is determined by a low-frequency component and a high-frequency component.

[0080] In this step, time-frequency decomposition refers to the process of separating the time-frequency domain signal into different frequency components, including low-frequency components (reflecting modulation information) and high-frequency components (reflecting carrier characteristics), which is achieved through wavelet transform or filter group; low-frequency components refer to components in the signal with frequencies lower than the carrier frequency, containing phase and amplitude change information of the modulation symbols; high-frequency components refer to components in the signal with frequencies close to the carrier frequency, reflecting the offset and phase fluctuation of the carrier frequency.

[0081] In this embodiment of the present invention, a wavelet transform algorithm is used to decompose the signal spectrum into low-frequency and high-frequency components. The low-frequency components correspond to the signal's modulation information (such as symbol rate and phase transitions), while the high-frequency components correspond to the carrier's frequency offset characteristics. The time-frequency characteristic pattern is determined by the time-frequency energy distribution of the low-frequency and high-frequency components. The time-frequency ridges of the low-frequency component reflect changes in the modulation symbols, while the time-frequency fluctuations of the high-frequency component reflect the carrier frequency offset.

[0082] Step 402: Analyze the amplitude envelope of the low-frequency component to determine the phase jump point and the modulation symbol type.

[0083] In this step, the amplitude envelope refers to the contour curve of the signal amplitude changing with time, which is extracted through Hilbert transform and used to detect modulation symbol jumps; the phase jump point refers to the position of the signal phase mutation caused by the modulation symbol switching, corresponding to the symbol boundary of the modulation type; the modulation symbol type refers to the type of symbol used in the modulation method, such as the 0° and 180° phase states in binary phase shift keying.

[0084] In an embodiment of the present invention, the amplitude envelope curve of the low-frequency component is extracted by Hilbert transform, and the mutation point of the envelope curve is detected as the phase jump point; 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 type is determined.

[0085] Step 403: Locate a carrier phase mutation point synchronized with the phase jump point in the high-frequency component.

[0086] In this step, the carrier phase mutation point refers to the moment when the carrier signal phase undergoes a mutation, which is synchronized with the modulation symbol jump and is used for frequency offset calculation.

[0087] In an embodiment of the present invention, the phase jump point timestamp of the low-frequency component is mapped to the high-frequency component through a time domain alignment algorithm, and the phase mutation position that is time-aligned with the phase jump point is searched in the instantaneous phase sequence of the high-frequency component as the carrier phase mutation point.

[0088] Step 404: Calculate the frequency offset of the carrier frequency of the civil aviation radio reception 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.

[0089] 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. The formula is instantaneous frequency = phase derivative / ; The nominal value refers to the theoretical carrier frequency value calibrated when civil aviation radio equipment leaves the factory, such as the 125MHz nominal frequency of 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 mean frequency offset after removing random noise, reflecting the systematic deviation of the carrier frequency.

[0090] In the embodiment of the present invention, the instantaneous frequency calculation formula (instantaneous frequency is equal to the phase change rate divided by ) Calculate the instantaneous frequency value of each carrier phase mutation point, subtract the instantaneous frequency value from the nominal frequency to obtain the instantaneous frequency offset; perform sliding average processing on the instantaneous frequency offsets of multiple phase mutation points, and obtain the stable frequency offset component after removing random noise interference.

[0091] Step 405: Match the modulation symbol type with the modulation type in the preset civil aviation communication protocol to select a plurality of candidate modulation types that meet preset conditions.

[0092] In this step, the modulation type refers to the modulation method used by the signal, such as amplitude 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 type allowed by the protocol; the preset condition refers to the modulation type constraint specified in the protocol, such as the ACARS protocol only allows the use of specific modulation methods; the candidate modulation type refers to the set of possible modulation methods retained after passing the protocol matching screening.

[0093] In an embodiment of the present invention, according to the modulation type constraints defined by the protocol (such as the ACARS protocol only allows the use of amplitude keying modulation), a set of candidate modulation types that match the current modulation symbol type (such as the amplitude keying feature is detected) is screened out.

[0094] Step 406: Calculate the symbol rate variance value of each candidate modulation type according to the time stamp interval of adjacent phase jump points, and use the candidate modulation type with the smallest symbol rate variance value as the modulation parameter feature.

[0095] In this step, the timestamp 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 square mean of the deviation between the actual symbol period and the theoretical symbol period, which is used to evaluate the modulation type matching degree.

[0096] In the embodiment of the present invention, the time interval sequence of adjacent phase jump points is counted, and the variance value of the theoretical symbol period and the actual interval sequence of each candidate modulation type is calculated (for example, the theoretical symbol period is , the actual interval series mean is , 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.

[0097] Step 407: Generate a mean sequence based on the symbol rate and the stable frequency offset component in the modulation parameter feature, and perform filtering on the mean sequence to generate a frequency offset parameter feature.

[0098] In this step, the symbol rate refers to the number of modulation symbols transmitted per unit time, measured in symbols per second (Baud); the mean sequence refers to the time-ordered sequence of the average values ​​of the symbol rate and the stable frequency offset; and filtering refers to the technique of suppressing noise on the mean sequence, such as Kalman filtering or moving average filtering, to extract stable parameter features.

[0099] In the embodiment of the present invention, the cycle inverse corresponding to the symbol rate and the stable frequency offset component are arranged in chronological order as a mean sequence, and the mean sequence is smoothed using the Kalman filter algorithm to eliminate the measurement noise and generate the frequency offset parameter feature (such as the stable offset mean). fluctuation range).

[0100] The embodiments of the present invention improve the measurement accuracy of civil aviation radio parameters in dynamic interference environments through time-frequency decomposition and carrier-modulation joint analysis; accurately identify the modulation type under complex interference through low-frequency component analysis and protocol matching mechanism; effectively suppress the influence of transient noise on frequency offset measurement based on synchronous positioning of carrier phase mutation points and extraction of stable offset components; enhance the robustness of parameter characteristics through symbol rate variance optimization and filtering processing, and solve the problem of modulation recognition instability caused by symbol rate jitter in traditional methods.

[0101] The present invention provides a specific embodiment, step 401, performing time-frequency decomposition on the signal spectrum to generate a time-frequency characteristic pattern of civil aviation radio parameters, wherein the time-frequency characteristic pattern is determined by a low-frequency component and a high-frequency component, specifically comprising the following steps:

[0102] Step 411: Decompose the signal spectrum to generate multiple frequency band components.

[0103] 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 achieved 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, each component covers a specific frequency range (such as 10kHz bandwidth) and contains the amplitude, phase and time-frequency distribution information of the frequency band.

[0104] 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 the signal spectrum, dividing the original signal into multiple sub-band components according to the frequency range. Each sub-band component covers a specific frequency interval (such as one sub-band per 10 kHz), which is used to separate the modulation information and carrier information of different frequency components.

[0105] Step 412: Calculate the amplitude change rate of each frequency band component.

[0106] In this step, the amplitude change rate refers to the rate at which the signal amplitude changes over time. It 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.

[0107] In the embodiment of the present invention, the amplitude data of each frequency band component is differentially calculated along the time axis, and 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.

[0108] Step 413: The frequency band component whose amplitude change rate is lower than the first threshold is regarded as the high-frequency component, and the frequency band component whose amplitude change rate is higher than the second threshold is regarded as the high-frequency component.

[0109] In this step, the first threshold refers to the amplitude change rate threshold for distinguishing low-frequency components, which is set based on the statistical mean of the amplitude change rates of all frequency band components (such as 50% of the mean), and the frequency band below this value is regarded as a low-frequency component; the second threshold refers to the amplitude change rate threshold for distinguishing high-frequency components, which is set based on the statistical mean (such as 150% of the mean), and the frequency band above this value is regarded as a high-frequency component.

[0110] In an embodiment of the present invention, the first threshold is set to 50% of the average value of the amplitude change rate of all frequency band components, and the second threshold is set to 150% of the average value; the low-frequency component corresponds to the slowly changing modulated baseband signal, and the high-frequency component corresponds to the rapidly fluctuating carrier noise and interference components.

[0111] Step 414: superimpose 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.

[0112] In this step, 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 fusion refers to the process of adding the amplitude data of different frequency band components according to weight coefficients, which is used to integrate low-frequency modulation information and high-frequency carrier characteristics to generate enhanced time-frequency features.

[0113] In an embodiment of the present invention, a weighted summation of the amplitude data of the low-frequency component (with a weight coefficient of 0.7) and a weighted summation of the amplitude data of the high-frequency component (with a weight coefficient of 0.3) are performed to generate a fused time-frequency energy distribution spectrum as a time-frequency feature pattern characterizing the characteristics of civil aviation radio parameters.

[0114] The embodiments of the present invention improve the recognition accuracy of civil aviation radio parameters in complex interference environments by integrating frequency band decomposition with dynamic amplitude characteristics; divide low-frequency and high-frequency components based on the amplitude change rate threshold to effectively separate the modulated baseband signal and carrier interference components; enhance key parameter characteristics through weighted superposition and fusion to solve the misjudgment of modulation type caused by the ambiguity of time-frequency energy distribution in traditional methods; and 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.

[0115] The present invention provides a specific embodiment, step 402, parsing the amplitude envelope of the low-frequency component to determine the phase jump point and the modulation symbol type, specifically including the following steps:

[0116] Step 421: According to the theoretical cycle length corresponding to the preset symbol rate, the amplitude envelope of the low-frequency component is subjected to extreme point detection to generate a maximum point sequence.

[0117] 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 to determine the benchmark value of the symbol period length; the theoretical period length refers to the reciprocal of the preset symbol rate (such as 1 / 1200 second = 0.833ms), which represents the duration of a single symbol under ideal conditions; extreme point detection refers to the technology of identifying the local maximum or minimum position in the signal amplitude envelope, which is used to locate the symbol period boundary; the maximum point sequence refers to the set of local maximum positions of the amplitude envelope arranged in time order obtained by extreme point detection.

[0118] In an embodiment of the present invention, a sliding window extreme value detection algorithm is used 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 candidate markers for the symbol period boundary.

[0119] Step 422: Generate a candidate cycle set based on the time intervals between adjacent maximum points in the maximum point sequence, and select a target cycle from the candidate cycle set whose difference with the theoretical cycle length is less than a preset threshold.

[0120] 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 candidate period set refers to the set of candidate period lengths whose difference between the time interval and the theoretical period is 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), used to filter the valid symbol period.

[0121] In the embodiment of the present invention, the time intervals of all adjacent maximum points are calculated (e.g., the timestamp of the nth maximum point minus the timestamp of the n-1th maximum point), and the absolute difference between the time intervals and the theoretical period length (0.833ms) is retained, which is less than a preset threshold (e.g., ms) to form a target period set.

[0122] Step 423: Segment the waveform of the amplitude envelope according to the target period to generate a symbol period segment sequence.

[0123] In this step, the waveform refers to the curve shape of the amplitude envelope changing with time, reflecting the amplitude characteristics of the modulation symbol; segmentation processing refers to the operation of cutting the waveform into equal-length time segments according to the length of the symbol period, which is used for symbol-level analysis; the symbol period segment sequence refers to the set of symbol period data segments arranged in time order generated after segmentation processing.

[0124] In an embodiment of the present invention, the amplitude envelope waveform is divided into multiple equal-length time periods according to the target cycle length (such as 0.833ms) with the maximum point as the dividing point. Each time period corresponds to a symbol period segment, forming a symbol period segment sequence.

[0125] Step 424: Calculate the absolute value of the derivative of the amplitude envelope in each symbol period in the symbol period sequence, identify the target time domain point 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 point as the phase jump point.

[0126] 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, which is calculated by the first-order difference (such as ), used to detect amplitude mutations; the preset mutation threshold refers to the derivative absolute value threshold for determining phase jumps (such as 30% of the maximum amplitude), and exceeding this value is considered a valid jump; 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.

[0127] In an embodiment of the present invention, the first-order derivative of the amplitude envelope of each symbol period is taken, and the absolute value of the derivative is calculated. When the absolute value of the derivative exceeds a preset mutation threshold (such as 30% of the maximum amplitude value) and the phase difference before and after the point exceeds 90°, it is determined to be a phase jump point.

[0128] Step 425: Count the number and distribution positions of adjacent phase transition points in each symbol period to obtain statistical results.

[0129] In this step, the statistical result refers to the number and position distribution data of phase jump points within the symbol period, which is used for modulation type matching.

[0130] In an embodiment of the present invention, the number of phase transition points within each symbol period is counted (e.g., 0 or 1 transition point), and the relative position of the transition point within the period is recorded (e.g., the first 20% or last 30% of the period), forming statistical results of the transition point quantity distribution and position distribution.

[0131] Step 426: Match the statistical result with the modulation type symbol hopping rule defined in the preset civil aviation communication protocol to determine the modulation symbol type.

[0132] In this step, the modulation type symbol hopping rule refers to the modulation symbol hopping characteristics defined by the protocol (such as 1 180° hopping per symbol of BPSK), which is used as the matching basis; the matching operation refers to the process of logically comparing the statistical results with the protocol rules to screen the modulation types that meet the conditions.

[0133] In an embodiment of the present invention, according to the protocol rules (such as FSK modulation requires at most one phase jump in each symbol period and the jump position is centered), the modulation types whose statistical results meet the rules (such as candidate types with the number of jump points ≤ 1 and position deviation < 10%) are screened, and the final modulation symbol type is output.

[0134] The embodiments of the present invention improve the reliability and noise resistance of modulation type identification through the symbol period division and jump point statistical matching mechanism; solve the period division error caused by symbol boundary ambiguity based on the dynamic matching of theoretical period and measured period; effectively distinguish similar modulation types by matching phase jump point statistics with protocol rules; and enhance the anti-interference ability of jump point identification by combining derivative mutation detection and phase continuity analysis.

[0135] The present invention provides a specific embodiment, step 407, generating a mean sequence based on the symbol rate and the stable frequency offset component in the modulation parameter feature, and filtering the mean sequence to generate a frequency offset parameter feature, specifically comprising the following steps:

[0136] Step 471: Arrange the stable frequency offset components in time sequence to generate a stable frequency offset component sequence.

[0137] 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 frequency offset data after removing instantaneous noise and is used to characterize the systematic deviation of the carrier frequency.

[0138] In an embodiment of the present invention, the stable frequency offset values ​​corresponding to multiple time points (such as -2.3kHz, -2.2kHz, and -2.4kHz) are arranged in time series data in the order of timestamps to form a stable frequency offset component sequence for subsequent symbol synchronization processing.

[0139] 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 segment sequence.

[0140] In this step, the symbol period refers to the duration of a single modulation symbol, which is calculated by the inverse of the symbol rate (for example, 1200 symbols / second corresponds to 0.833ms) and is used for signal segment synchronization; the symbol synchronization segment sequence refers to a set of multiple continuous time periods generated by time-dividing the stable frequency offset component sequence according to the length of the symbol period, and each segment corresponds to one symbol period.

[0141] In the embodiment of the present invention, the symbol period is used as the time window length, and the stable frequency offset component sequence is divided into multiple continuous time periods (eg, each time period includes all offset values ​​within 0.833 ms) to form a symbol synchronization segment sequence.

[0142] Step 473: Calculate the mean of the stable frequency offset component in each symbol synchronization segment in the symbol synchronization segment sequence to generate a mean sequence.

[0143] In this step, the symbol synchronization segment refers to a single time period in the symbol synchronization segment sequence, which contains all stable frequency offset component data within a symbol period; the mean calculation refers to the operation of summing the stable frequency offset components in the symbol synchronization segment and dividing it by the number of components, which is used to extract the segment average offset value; the mean sequence refers to a set of symbol synchronization segment average offset values ​​arranged in chronological order, which reflects the stage-by-stage statistical characteristics of the carrier frequency offset.

[0144] In the embodiment of the present invention, all stable frequency offset components in each symbol synchronization segment are summed and divided by the number of components (e.g., if there are 5 offset values ​​in the segment, the average is Offset value / 5), the average offset value of each segment is obtained and arranged in chronological order as a mean value sequence.

[0145] Step 474: Filter the mean value sequence according to the cutoff frequency parameter corresponding to the symbol rate to generate a filtered stable frequency offset component.

[0146] In this step, the cutoff frequency parameter refers to the upper frequency limit of the low-pass filter, which is set according to the symbol rate (such as 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 sequence data processed by low-pass filtering, which retains the low-frequency stable offset component and suppresses high-frequency fluctuations.

[0147] In the embodiment of the present invention, a low-pass filter is used to smooth the mean sequence, filter out high-frequency noise components above the cutoff frequency (eg, filter out fluctuations >600 Hz), and retain low-frequency stable offset components.

[0148] Step 475: Calculate the arithmetic mean of the filtered stable frequency offset component, and use the arithmetic mean as the frequency offset parameter feature.

[0149] 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, which represents the global average offset of the carrier frequency.

[0150] In an embodiment of the present invention, all filtered stable frequency offset components are added together and divided by the total number of components (e.g., the sum of 10 components divided by 10) to obtain a global average offset value as the final frequency offset parameter feature (e.g., -2.3 kHz).

[0151] The embodiments of the present invention improve the measurement accuracy and stability of frequency offset parameters through symbol synchronization segmentation and double filtering processing; eliminate the influence of inter-symbol interference on offset statistics through symbol synchronization segmentation; combine segmented mean calculation and low-pass filtering for double noise reduction to effectively suppress random fluctuations; and finally output the global arithmetic mean to solve the defect that traditional single-point measurement is easily interfered by instantaneous outliers.

[0152] The present invention provides a specific embodiment, step 102, based on the interference signal azimuth information of the spectrum characteristic data, adjusting the phase of each antenna unit in the phased array antenna array to generate target spectrum data after anti-interference optimization, specifically includes the following steps:

[0153] Step 201: extracting multiple interference direction angle sets of interference signals in the dynamic spectrum interference environment from the interference signal azimuth information of the spectrum feature data.

[0154] In this step, the interference direction angle set refers to an angle set of multiple interference signal incident directions extracted from spectrum data by using a direction of arrival estimation technique, including horizontal azimuth angles and elevation angles.

[0155] In an embodiment of the present invention, spatial spectrum analysis is performed on the spectral feature data using a direction of arrival estimation algorithm to identify the incident direction angles (such as horizontal azimuth and elevation angles) of multiple interference signals, forming a set of interference direction angles (such as 30°, 45°, and 60°) for subsequent phase adjustment.

[0156] Step 202: Calculate the phase adjustment weight value of each antenna unit in the phased array antenna array for each interference direction according to the interference direction angle set to generate a direction weight value set.

[0157] In this step, the antenna unit refers to a single radiating element in a phased array antenna array that independently controls phase and amplitude, and is used to receive or transmit radio frequency signals; the phase adjustment weight value refers to the phase compensation amount of the antenna unit calculated to suppress a specific interference direction, usually in complex form (such as amplitude and phase adjustment amounts); the directional weight value set refers to a phase adjustment weight matrix arranged according to interference direction and antenna unit index, and is used for joint control of multi-directional interference suppression.

[0158] In an embodiment of the present invention, a minimum variance distortionless response beamforming algorithm is adopted to suppress the signal energy in the interference direction, calculate the phase compensation weight value of each antenna unit in a specific interference direction, and form a directional weight value matrix arranged according to the interference direction and the antenna unit index.

[0159] Step 203: superimpose the phase adjustment weight value of each antenna unit in the directional weight value set with the original phase data received by the corresponding antenna unit to generate an adjusted phase value corresponding to each antenna unit.

[0160] In this step, the original phase data refers to the initial phase information of the signal received by the antenna unit without adjustment, reflecting the natural phase difference of the signal in spatial propagation; the superposition operation refers to the process of algebraically adding the phase adjustment weight value to the original phase data to achieve phase distribution optimization; the adjusted phase value refers to the final phase setting value of the antenna unit obtained after the superposition operation, which is used for beamforming synthesis.

[0161] In an embodiment of the present invention, the original phase data of each antenna unit (such as the initial phase value of the RF signal) and the phase adjustment weight value (such as the +15° compensation amount) are algebraically added to obtain the adjusted phase value (such as the original phase 120° + the adjustment weight 15° = 135°), thereby achieving phase distribution optimization.

[0162] Step 204: performing 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 synthesis signal.

[0163] In this step, beamforming synthesis refers to the technology of vectoring the signals of multiple antenna units according to the adjusted phase values ​​to form a directional beam; the interference energy component refers to the radiated energy of the interference signal in the direction of the synthesized beam, and beamforming is used to form a gain zero point in the interference direction 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 are not completely suppressed.

[0164] In an embodiment of the present invention, the adjusted signals of all antenna units are coherently synthesized through a vector superposition algorithm to form a radiation gain zero point (such as -30dB suppression) in the interference direction, while enhancing the gain in the target signal direction and outputting an initial synthesized signal.

[0165] Step 205: Perform interference residual detection on the initial synthetic signal. If the interference direction angle of the detected residual interference signal is less than the angle deviation of any interference direction in the interference direction angle set by less than the 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, thereby generating a target phase adjustment weight set.

[0166] In this step, interference residual detection refers to the secondary direction estimation of the initial synthetic signal to detect the direction of the interference signal that has not been completely suppressed; the preset tolerance threshold refers to the maximum angular deviation allowed between the residual interference direction and the original interference direction (such as ), any value exceeding this value is considered a new interference source; iterative adjustment refers to the process of cyclically optimizing the phase adjustment weight value based on the residual detection results until the interference suppression requirements are 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.

[0167] In this embodiment of the present invention, the residual interference angle is detected by secondary direction of arrival estimation. If residual interference exists (for example, 32° interference is detected, which deviates 2° from the original 30° interference), the direction weight value is updated and steps 202-204 are repeated until the residual interference angle exceeds a threshold value (for example, 35°).

[0168] Step 206: performing 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.

[0169] In this step, phase adjustment refers to applying the target phase adjustment weight set to the antenna unit controller to adjust the array phase distribution in real time; anti-interference optimization refers to the signal quality improvement effect after interference suppression achieved through phase adjustment and beamforming.

[0170] In an embodiment of the present invention, the final optimized phase adjustment weight value is fixed to the antenna unit controller, the array phase distribution is adjusted in real time, the interference direction signal is continuously suppressed, and high-quality spectrum data containing only civil aviation radio target signals is output.

[0171] The embodiments of the present invention improve the anti-interference performance in a dynamic spectrum interference environment through multi-directional interference detection and iterative beamforming optimization; realize multi-directional synchronous suppression based on the joint optimization of phase weights in multiple interference directions; solve the suppression blind spot of traditional single beamforming through residual interference detection and iterative adjustment mechanism; and finally output high-purity target spectrum data, providing a reliable data basis for subsequent parameter testing and traceability.

[0172] The present invention provides a specific embodiment, in step 105, combining the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio, specifically comprising the following steps:

[0173] Step 501: Combine the modulation parameter characteristics and the frequency offset parameter characteristics to generate a device parameter combination sequence.

[0174] In this step, the device parameter combination sequence refers to a set of modulation parameter features and frequency offset parameter features arranged in time sequence, and each element is combination data containing multiple parameters.

[0175] In an embodiment of the present invention, a feature vector splicing technique is used to encode the modulation symbol type as a digital identifier (e.g., QPSK is encoded as 1), and the symbol rate (e.g., 1200 symbols / second) and the stable frequency offset mean (e.g., -2.3kHz) are combined into a multidimensional vector, which is then arranged in chronological order to form a device parameter combination sequence.

[0176] Step 502: Add 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 whose stable frequency offset fluctuation range is within the offset tolerance interval to the candidate device parameter combination set.

[0177] In this step, the device parameter constraint range refers to the 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 average value of the frequency offset after filtering, reflecting the systematic deviation of the carrier frequency, such as -2.3kHz. 0.1kHz; the candidate device parameter combination set refers to the qualified parameter combination set retained after screening by the protocol constraints, which is used for further matching verification.

[0178] In the embodiment 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 modulation symbol types within the allowed range and stable frequency offset fluctuation range (such as ) parameter combinations that are within the tolerance interval to form a set of candidate device parameter combinations.

[0179] Step 503: 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, retain the candidate device parameter combinations with matching degrees higher than the preset threshold, and generate the target device parameter combination set.

[0180] In this step, the timestamp refers to the absolute time mark of the phase jump point, which is 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, such as the ACARS protocol requires that the start time error of each symbol period is ≤5μs; the matching degree refers to the quantified value of the time alignment accuracy between the measured timestamp sequence and the protocol template, which is obtained by statistical calculation of the time difference; the target device parameter combination set refers to the parameter combination set with a matching degree higher than the threshold, which represents the device parameters that meet the protocol time synchronization requirements.

[0181] In an 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 in the ACARS protocol), the matching degree (such as the sum of the squares of the timestamp differences) is calculated, and the combinations with matching degrees higher than a preset threshold (such as matching degree ≥85%) are retained to generate a target device parameter combination set.

[0182] Step 504: Determine a device type label for each target device parameter combination in the target device parameter combination set based on the average of the stable frequency offsets in the target device parameter combination set and the nominal frequency offset of a preset device type.

[0183] In this step, the nominal frequency offset refers to the theoretical frequency offset value calibrated when the device leaves the factory, such as the nominal offset of a certain model radio station is -2.0kHz; 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.

[0184] In this embodiment of the present invention, the absolute difference between the measured stable frequency offset mean (e.g., -2.3 kHz) and the nominal offset of each device type (e.g., -2.0 kHz for device A and -2.5 kHz for device B) is calculated, and the device type with the smallest difference (e.g., device B, with a difference of 0.2 kHz) is used as the device type label for the current parameter combination.

[0185] Step 505: Associating the device type label, modulation symbol type, and average 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.

[0186] In this step, the association operation refers to the operation of establishing a logical link between the device type label and the parameter characteristics to form a structured database entry; the transmitter device parameters refer to the set of factory nominal parameters of the device, including the device model, modulation type nominal value, nominal frequency offset, etc.; the measured parameters refer to the set of parameters actually measured by this method, including the modulation symbol type, stable frequency offset mean, etc.; the mapping relationship library refers to the database that stores the association relationship between the transmitter device parameters and the measured parameters, and supports intelligent matching query of device identity and parameters.

[0187] In an embodiment of the present invention, a key-value database technology is adopted, with the device type tag as the primary key, to associate and store the modulation symbol type, the stable frequency offset mean (such as -2.3kHz) and the measured timestamp, thereby forming a dynamic mapping relationship library between the civil aviation radio transmission source equipment parameters and the measured parameters.

[0188] The embodiments of the present invention realize the construction of high-precision device parameter mapping relationships; based on the dual screening mechanism of protocol constraints and time template matching, the compliance and accuracy of parameter combinations are improved; through the dynamic comparison of measured offset mean values ​​with nominal values, the update lag defect of traditional methods that rely on static device databases is solved; and an extensible mapping relationship library is constructed to support intelligent association and rapid traceability of parameters of multiple device types.

[0189] Figure 2 The present invention provides a structural diagram of a civil aviation radio parameter intelligent testing and traceability system. Figure 2 As shown, the system includes:

[0190] An acquisition module 21 is configured to acquire spectrum characteristic data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment;

[0191] An adjustment module 22 is configured to adjust the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization;

[0192] A conversion module 23, configured to convert the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal spectrum;

[0193] An analysis module 24 is configured to identify a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, analyze the time-frequency characteristic pattern, and obtain a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol;

[0194] a combining module 25, configured to combine the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio;

[0195] The generating module 26 is configured to generate a civil aviation radio parameter traceability result including a device identity and a parameter deviation value based on the mapping relationship library, the modulation parameter characteristics, and the frequency offset parameter characteristics.

[0196] Figure 2 The intelligent testing and tracing system for civil aviation radio parameters can be executed Figure 1 The implementation principle and technical effects of the intelligent testing and tracing method for civil aviation radio parameters described in the illustrated embodiment will not be elaborated on here. The specific manner in which each module and unit performs operations in the intelligent testing and tracing system for civil aviation radio parameters in the above embodiment has been described in detail in the embodiments of the method and will not be elaborated on here.

[0197] In one possible design, Figure 2 The civil aviation radio parameter intelligent testing and tracing system of the embodiment shown 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;

[0198] 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 .

[0199] The processing component 32 is used to: obtain spectrum characteristic data obtained by scanning the target frequency band of the phased array antenna array in a dynamic spectrum interference environment; adjust the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization; convert the civil aviation radio receiving signal in the target spectrum data into time-frequency domain data to generate a signal spectrum; identify the time-frequency characteristic pattern of the civil aviation radio parameters from the signal spectrum, and analyze the time-frequency characteristic pattern to generate modulation parameter characteristics and frequency offset parameter characteristics that match the preset civil aviation communication protocol; combine the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source equipment parameters and the measured parameters of the civil aviation radio; based on the mapping relationship library, the modulation parameter characteristics and the frequency offset parameter characteristics, generate a civil aviation radio parameter traceability result including equipment identity and parameter deviation value.

[0200] 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 as 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 to perform the above method.

[0201] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory 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.

[0202] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0203] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0204] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0205] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0206] The embodiment of the present invention further provides a computer storage medium storing a computer program, which can achieve the above-mentioned Figure 1 The embodiment shown is a method for intelligent testing and tracing of civil aviation radio parameters.

[0207] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0208] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0209] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion 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, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0210] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for intelligent testing and tracing of civil aviation radio parameters, characterized in that: include: Acquire spectrum characteristic data obtained by scanning the target frequency band by the phased array antenna array in a dynamic spectrum interference environment; Adjusting the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization; Converting the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal spectrum; Identifying a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, and parsing the time-frequency characteristic pattern to generate a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol; Combining the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and measured parameters of the civil aviation radio; Based on the mapping relationship library, the modulation parameter characteristics and the frequency offset parameter characteristics, a civil aviation radio parameter traceability result including a device identity and a parameter deviation value is generated.

2. The method according to claim 1, characterized in that Identifying a time-frequency characteristic pattern of a civil aviation radio parameter from the signal spectrum, and parsing the time-frequency characteristic pattern to generate a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol, including: Performing time-frequency decomposition on the signal spectrum to generate a time-frequency characteristic pattern of civil aviation radio parameters, wherein the time-frequency characteristic pattern is determined by a low-frequency component and a high-frequency component; Analyzing the amplitude envelope of the low-frequency component to determine a phase jump point and a modulation symbol type; Locating a carrier phase mutation point synchronized with the phase jump point in the high-frequency component; Calculating a frequency offset of the carrier frequency of the civil aviation radio reception signal relative to a nominal value based on an instantaneous frequency value corresponding to the carrier phase mutation point, and determining a stable frequency offset component based on the frequency offset; Matching the modulation symbol type with the modulation type in the preset civil aviation communication protocol to select a plurality of candidate modulation types that meet preset conditions; Calculate the symbol rate variance value of each candidate modulation type according to the timestamp interval of 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 and the stable frequency offset component in the modulation parameter feature, a mean value sequence is generated, and filtering processing is performed on the mean value sequence to generate a frequency offset parameter feature.

3. The method according to claim 2, characterized in that Performing time-frequency decomposition on the signal spectrum to generate a time-frequency characteristic pattern of civil aviation radio parameters, wherein the time-frequency characteristic pattern is determined by a low-frequency component and a high-frequency component, including: Decomposing the signal spectrum to generate multiple frequency band components; Calculate the amplitude change rate of each frequency band component; The frequency band component whose amplitude change rate is lower than the first threshold is regarded as the high frequency component, and the frequency band component whose amplitude change rate is higher than the second threshold is regarded as the high frequency component; The amplitude data of the low-frequency component and the amplitude data of the high-frequency component are superimposed and fused to generate a time-frequency feature pattern.

4. The method according to claim 2, characterized in that Analyzing the amplitude envelope of the low-frequency component to determine a phase jump point and a modulation symbol type, including: According to the theoretical cycle length corresponding to the preset symbol rate, the amplitude envelope of the low-frequency component is subjected to extreme point detection to generate a maximum point sequence; Generating a candidate period set according to the time intervals between adjacent maximum points in the maximum point sequence, and screening out a target period whose difference with the theoretical period length is less than a preset threshold from the candidate period set; Segmenting the waveform of the amplitude envelope according to the target period to generate a symbol period segment sequence; Calculating the absolute value of the derivative of the amplitude envelope in each symbol period in the symbol period sequence, identifying a target time domain point where the absolute value of the derivative exceeds a preset mutation threshold and there is a phase continuity interruption, and using the target time domain point as a phase jump point; Counting the number and distribution positions of adjacent phase jump points in each symbol period to obtain statistical results; The statistical result is matched with the modulation type symbol hopping rule defined in the preset civil aviation communication protocol to determine the modulation symbol type.

5. The method according to claim 2, characterized in that Generating a mean sequence based on the symbol rate and the stable frequency offset component in the modulation parameter feature, and filtering the mean sequence to generate a frequency offset parameter feature, including: Arranging the stable frequency offset components in time sequence to generate a stable frequency offset component sequence; According to the symbol period corresponding to the symbol rate in the modulation parameter characteristics, the stable frequency offset component sequence is segmented to generate a symbol synchronization segment sequence; Calculating the mean of a stable frequency offset component in each symbol synchronization segment in the symbol synchronization segment sequence to generate a mean sequence; performing filtering processing on the mean value sequence according to a cutoff frequency parameter corresponding to the symbol rate to generate a filtered stable frequency offset component; An arithmetic mean value of the filtered stable frequency offset component is calculated, and the arithmetic mean value is used as a frequency offset parameter feature.

6. The method according to claim 1, wherein Adjusting the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization includes: Extracting multiple interference direction angle sets of interference signals in the dynamic spectrum interference environment from the interference signal azimuth information of the spectrum feature data; Calculating, based on the interference direction angle set, a phase adjustment weight value of each antenna unit in the phased array antenna array for each interference direction to generate a direction weight value set; Superimposing the phase adjustment weight value of each antenna unit in the directional weight value set with the original phase data received by the corresponding antenna unit to generate an adjusted phase value corresponding to each antenna unit; Performing 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; Performing interference residual detection on the initial synthesized signal, and if it is detected that the interference direction angle of the residual interference signal and the angle deviation of any interference direction in the interference direction angle set are less than a preset tolerance threshold, iteratively adjusting the phase adjustment weight value until the interference direction angle of the residual interference signal exceeds the preset tolerance threshold, thereby generating a target phase adjustment weight set; The phase of the phased array antenna array is adjusted 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 Combining the modulation parameter feature and the frequency offset parameter feature to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio, including: Combining the modulation parameter characteristics and the frequency offset parameter characteristics to generate a device parameter combination sequence; Adding target parameter combinations whose modulation symbol types in the device parameter combination sequence satisfy the device parameter constraint range in the preset civil aviation communication protocol and whose fluctuation range of the stable frequency offset is within the offset tolerance interval to the candidate device parameter combination set; Calculating 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, retaining the candidate device parameter combinations with matching degrees higher than a preset threshold, and generating a target device parameter combination set; determining a device type label for each target device parameter combination in the target device parameter combination set based on an average of the stable frequency offsets in the target device parameter combination set and a nominal frequency offset of a preset device type; The device type label, modulation symbol type and average value of the stable frequency offset in the target device parameter combination set are associated to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio.

8. A civil aviation radio parameter intelligent testing and traceability system, characterized in that: include: An acquisition module is used to obtain spectrum characteristic data obtained by scanning a target frequency band by a phased array antenna array in a dynamic spectrum interference environment; An adjustment module is configured to adjust the phase of each antenna unit in the phased array antenna array based on the interference signal azimuth information of the spectrum characteristic data to generate target spectrum data after anti-interference optimization; a conversion module, configured to convert the civil aviation radio reception signal in the target spectrum data into time-frequency domain data to generate a signal spectrum; an analysis module, configured to identify a time-frequency characteristic pattern of civil aviation radio parameters from the signal spectrum, analyze the time-frequency characteristic pattern, and obtain a modulation parameter characteristic and a frequency offset parameter characteristic that match a preset civil aviation communication protocol; a combining module, configured to combine the modulation parameter characteristics and the frequency offset parameter characteristics to generate a mapping relationship library between the transmission source device parameters and the measured parameters of the civil aviation radio; A generation module is used to generate a civil aviation radio parameter traceability result including a device identity and a parameter deviation value based on the mapping relationship library, the modulation parameter characteristics and the frequency offset parameter characteristics.

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 a civil aviation radio parameter intelligent testing and traceability method 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, a civil aviation radio parameter intelligent testing and tracing method according to any one of claims 1 to 7 is implemented.

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