ILSVOR navigation station flight verification processing method under broadband large noise condition

Abstract

The invention relates to the field of aviation navigation systems, and discloses an ILSVOR navigation station flight verification processing method under a broadband large noise condition, and the method comprises the steps: constructing a multi-height-layer flight path of an aircraft, and calculating a coverage coefficient of the multi-height-layer flight path to a verification region corresponding to an ILSVOR navigation station; a high-precision receiver is used for collecting emission signals of the ILSVOR navigation station, a noise separation model is used for carrying out noise separation on the emission signals, and navigation signals are obtained; reconstructing the navigation signal to obtain a reconstructed navigation signal; filtering parameters of the reconstructed navigation signal are analyzed, the reconstructed navigation signal is filtered to obtain a filtered navigation signal, and the filtered navigation signal and inertial navigation system data collected in advance are fused to obtain a high-precision navigation signal; and calculating a signal error of the high-precision navigation signal, and verifying the high-precision navigation signal to obtain a target navigation signal. According to the invention, the accuracy of the navigation information of the ILSVOR navigation station can be improved.

Description

Technical Field

[0001] The invention relates to an ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions, and belongs to the field of aviation navigation systems. Background Art

[0002] ILSVOR navigation station flight verification refers to a series of data processing and analysis work for the flight verification of the instrument landing system (ILS) and very high frequency omnidirectional range (VOR) navigation stations. The purpose is to verify whether the signal of the navigation station meets the requirements of the International Civil Aviation Organization (ICAO) and related standards, and ensure that it can provide accurate and reliable navigation services for aircraft.

[0003] The flight verification of the ILSVOR navigation station usually relies on an aircraft equipped with specific instruments (such as an ILS receiver) to actually fly along a predetermined flight trajectory to directly measure the accuracy and coverage of the navigation signal. This method often lacks in-depth analysis of signal processing in a wide-band and high-noise environment, and is unable to effectively separate and filter out noise, resulting in large signal errors, making the flight verification of the ILSVOR navigation station inaccurate. Summary of the invention

[0004] The invention provides an ILSVO navigation station flight verification processing method under wide-band and high-noise conditions, the main purpose of which is to improve the accuracy of navigation information of the ILSVO navigation station.

[0005] To achieve the above object, the present invention provides an ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions, comprising: Determine an aircraft of an ILSVOR navigation station, analyze a sensitivity value of a high-precision receiver corresponding to the aircraft, construct a multi-altitude flight trajectory of the aircraft based on the sensitivity value, and calculate a coverage factor of the multi-altitude flight trajectory for a verification area corresponding to the ILSVOR navigation station; According to the coverage factor, using the high-precision receiver to collect the transmission signal of the ILSVOR navigation station, identifying the broadband noise characteristics of the transmission signal, and using the broadband noise characteristics and a pre-trained noise separation model to perform noise separation on the transmission signal to obtain a navigation signal; constructing an observation matrix of the navigation signal, and reconstructing the navigation signal based on the observation matrix to obtain a reconstructed navigation signal; Analyzing the filtering parameters of the reconstructed navigation signal using a preset intelligent optimization algorithm, filtering the reconstructed navigation signal using the filtering parameters to obtain a filtered navigation signal, and fusing the filtered navigation signal with pre-collected inertial navigation system data to obtain a high-precision navigation signal; A signal error of the high-precision navigation signal is calculated, and based on the signal error, the high-precision navigation signal is verified to obtain a target navigation signal.

[0006] Optionally, analyzing the sensitivity value of the high-precision receiver corresponding to the aircraft includes: Constructing an interference-free environment for the high-precision receiver; Determine the signal source of the ILSVOR navigation station corresponding to the high-precision receiver; defining a test intensity gradient of the signal source; analyzing the intensity demodulation coefficient of the test intensity gradient; The sensitivity value of the high-precision receiver is determined according to the strength demodulation coefficient.

[0007] Optionally, determining the sensitivity value of the high-precision receiver according to the strength demodulation coefficient includes: Determining a demodulation threshold of the high-precision receiver; analyzing a minimum detectable signal of the high-precision receiver according to the strength demodulation coefficient; According to the demodulation threshold and the minimum detectable signal, the sensitivity value of the high-precision receiver is calculated using the following formula:

[0008] in, Represents the sensitivity value of the high-precision receiver, represents the bandwidth of the high-precision receiver, represents the noise generated by the bandwidth of the high-precision receiver, represents the noise factor, represents the demodulation threshold, represents the noise floor of a high-precision receiver, Indicates the minimum detectable signal.

[0009] Optionally, constructing a multi-altitude flight trajectory of the aircraft includes: Obtaining a flight area map of the aircraft; marking obstacles and danger areas in the map of the flight area; defining test requirements for the aircraft; Analyzing multiple altitude layers of the aircraft according to the test requirements; Determining flight parameters of the aircraft based on the obstacles, the dangerous area, and the multiple altitude layers, wherein the flight parameters include a take-off point, a turning point, a multiple altitude layer transition point, and a multiple altitude layer landing point; The multi-altitude flight trajectory of the aircraft is determined by the flight parameters.

[0010] Optionally, the calculating the coverage coefficient of the multi-altitude flight trajectory to the verification area corresponding to the ILSVOR navigation station includes: Determining the navigation station parameters of the ILSVOR navigation station; determining flight trajectory parameters of the multi-level flight trajectory; constructing a radio propagation model for the multi-level flight trajectory; Analyzing the effective coverage area of ​​the multi-layer flight trajectory using the radio propagation model based on the navigation station parameters and the flight trajectory parameters; Based on the effective coverage area, the coverage factor of the multi-level flight trajectory on the corresponding verification area of ​​the ILSVOR navigation station is analyzed.

[0011] Optionally, the using a pre-trained noise separation model to perform noise separation on the transmission signal to obtain a navigation signal includes: constructing a time-frequency diagram of the transmitted signal; Normalizing the time-frequency graph to obtain a normalized time-frequency graph; Outputting a noise probability map and a signal probability map of the normalized time-frequency map using the noise separation model; The noise probability map and the signal probability map are used to separate the transmitted signal from noise to obtain a navigation signal.

[0012] Optionally, constructing the observation matrix of the navigation signal includes: Analyzing observation matrix indicators of the navigation signal; Determining a sparse basis of the navigation signal according to the observation matrix indicator; Analyzing the sparsity of the navigation signal by using the sparse basis; Based on the sparsity, an observation matrix of the navigation signal is constructed.

[0013] Optionally, analyzing the sparsity of the navigation signal by using the sparse basis includes: Convert the navigation signal according to the sparse basis to obtain a sparse navigation signal; identifying a signal length of the sparse navigation signal; defining an indicator function of the sparse navigation signal; The number of non-zero elements of the sparse navigation signal is calculated based on the signal length and the indicator function:

[0014] in, represents the number of non-zero elements, Represents the sparse navigation signal elements, represents the signal length of the sparse navigation signal, represents the indicator function; The sparsity of the navigation signal is determined according to the number of non-zero elements.

[0015] Optionally, the analyzing the filtering parameters of the reconstructed navigation signal by using a preset intelligent optimization algorithm includes: Determining a filtering target and a filter type for the reconstructed navigation signal; identifying initial filter parameters for the filter type; Constructing a filtering parameter group of the initial filtering parameters; According to the filtering target, analyzing the filtering performance of the filtering parameter group using the intelligent optimization algorithm; Based on the filtering performance, filtering parameters of the reconstructed navigation signal are determined.

[0016] Optionally, calculating the signal error of the high-precision navigation signal includes: Analyzing the position PVT solution of the high-precision navigation signal; Defining a reference benchmark for the high-precision navigation signal; Based on the reference datum, analyzing and calculating the position error of the position PVT solution; A signal error of the high-precision navigation signal is determined based on the position error.

[0017] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned ILSVOR navigation station flight verification processing method under wide-band and high-noise conditions.

[0018] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned ILSVOR navigation station flight verification processing method under wide-band and high-noise conditions.

[0019] Compared with the problems described in the background technology, firstly, by analyzing the sensitivity value of the high-precision receiver corresponding to the aircraft and constructing a multi-altitude flight trajectory, it can ensure that the flight verification covers all important levels of the verification area corresponding to the navigation station, thereby improving the comprehensiveness and accuracy of the verification. The calculation of the coverage coefficient makes the planning of the flight trajectory more scientific and reasonable, ensuring the uniformity and effectiveness of signal acquisition. Secondly, by using a high-precision receiver to collect the transmitted signal and identify the broadband noise characteristics, combined with a pre-trained noise separation model, it can effectively separate the noise from the transmitted signal, thereby improving the quality of the navigation signal. This method is particularly effective in broadband and high-noise environments. The invention is effective and significantly improves the credibility of the signal. Furthermore, by constructing an observation matrix to reconstruct the navigation signal and combining the intelligent optimization algorithm to analyze the filtering parameters, the accurate filtering of the reconstructed navigation signal can be realized. This method not only improves the signal processing efficiency, but also reduces the signal error and enhances the stability of the navigation system. Finally, the filtered navigation signal is fused with the inertial navigation system data to obtain a high-precision navigation signal, and the signal error is calculated for verification to finally obtain the target navigation signal. This process greatly improves the navigation accuracy of the navigation system, provides more reliable and accurate navigation information for the aircraft, and ensures flight safety. Therefore, the invention can improve the accuracy of the navigation information of the ILSVOR navigation station. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic flow chart of an ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions provided by an embodiment of the present invention; The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0022] The embodiment of the present application provides an ILSVR navigation station flight verification processing method under wide-band and high-noise conditions. The execution subject of the ILSVR navigation station flight verification processing method under wide-band and high-noise conditions includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the ILSVR navigation station flight verification processing method under wide-band and high-noise conditions can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. Example

[0023] Reference Figure 1FIG. 2 is a flow chart of a method for flight verification of an ILSVR navigation station under wide-band and high-noise conditions provided by an embodiment of the present invention. In this embodiment, the method for flight verification of an ILSVR navigation station under wide-band and high-noise conditions includes: S1. Determine an aircraft of an ILSVOR navigation station, analyze the sensitivity value of a high-precision receiver corresponding to the aircraft, construct a multi-altitude flight trajectory of the aircraft based on the sensitivity value, and calculate the coverage factor of the multi-altitude flight trajectory for a verification area corresponding to the ILSVOR navigation station.

[0024] It should be explained that the ILSVOR navigation station refers to an aviation navigation facility that provides precision approach guidance. It guides the aircraft to align with the runway centerline and the correct glide path during the final approach phase by emitting vertical and horizontal navigation signals (i.e., glide path and localizer signals). The aircraft refers to a flying tool for conducting ILSVOR navigation station navigation tests, such as a drone, fixed-wing aircraft or helicopter. The high-precision receiver refers to a receiver used to receive signals emitted by the ILSVOR navigation station and capable of interpreting these signals with extremely high accuracy.

[0025] The present invention analyzes the sensitivity value of the aircraft corresponding to the high-precision receiver to improve the reliability of collected data.

[0026] In detail, the analyzing the sensitivity value of the high-precision receiver corresponding to the aircraft includes: Constructing an interference-free environment for the high-precision receiver; Determine the signal source of the ILSVOR navigation station corresponding to the high-precision receiver; defining a test intensity gradient of the signal source; analyzing the intensity demodulation coefficient of the test intensity gradient; The sensitivity value of the high-precision receiver is determined according to the strength demodulation coefficient.

[0027] Among them, the interference-free environment refers to an electromagnetic environment in which there is no or only negligible electromagnetic interference, so as to ensure that the test results are only affected by the performance of the receiver and the signal source itself; the signal source refers to a controllable transmitter used to simulate the signal transmitted by the ILSVOR navigation station; the test intensity gradient refers to a series of predefined signal strength levels used to test the sensitivity of the receiver; the intensity demodulation coefficient refers to the relationship between the signal strength and the demodulation performance when the receiver demodulates the signal; and the sensitivity value refers to the minimum signal strength required for the receiver to correctly demodulate the signal.

[0028] Further, determining the sensitivity value of the high-precision receiver according to the strength demodulation coefficient includes: Determining a demodulation threshold of the high-precision receiver; analyzing a minimum detectable signal of the high-precision receiver according to the strength demodulation coefficient; According to the demodulation threshold and the minimum detectable signal, the sensitivity value of the high-precision receiver is calculated using the following formula:

[0029] in, Represents the sensitivity value of the high-precision receiver, represents the bandwidth of the high-precision receiver, represents the noise generated by the bandwidth of the high-precision receiver, represents the noise factor, represents the demodulation threshold, represents the noise floor of a high-precision receiver, Indicates the minimum detectable signal.

[0030] Among them, the demodulation threshold refers to the minimum signal-to-noise ratio at which the demodulator of the high-precision receiver can work, the minimum detectable signal refers to the minimum signal power that the high-precision receiver can detect, the bandwidth, the noise generated by the bandwidth refers to the noise power caused by the bandwidth of the receiver, the noise figure refers to the amount of additional noise introduced by the receiver when amplifying the signal, and the noise floor refers to the inherent noise level of the high-precision receiver.

[0031] It should be noted that, in the present application, the sensitivity value of the high-precision receiver is calculated by the above formula to determine the signal strength limit of the ILSVOR navigation station, thereby improving the reliability of navigation by the ILSVOR navigation station. In order for the high-precision receiver to correctly demodulate the signal, the input signal power must be greater than or equal to the minimum detectable signal (MDS) plus the demodulation threshold. The demodulation threshold is the additional signal power that the high-precision receiver needs to add on the basis of the MDS in order to overcome the loss and noise generated during the internal processing process.

[0032] The invention constructs the multi-altitude flight trajectory of the aircraft and can effectively test the verification area of ​​the ILSVOR navigation station.

[0033] In detail, constructing the multi-altitude flight trajectory of the aircraft includes: Obtaining a flight area map of the aircraft; marking obstacles and danger areas in the map of the flight area; defining test requirements for the aircraft; Analyzing multiple altitude layers of the aircraft according to the test requirements; Determining flight parameters of the aircraft based on the obstacles, the dangerous area, and the multiple altitude layers, wherein the flight parameters include a take-off point, a turning point, a multiple altitude layer transition point, and a multiple altitude layer landing point; The multi-altitude flight trajectory of the aircraft is determined by the flight parameters.

[0034] The flight area map refers to a geographic information map showing the area where the aircraft is to fly, the obstacle refers to any object in the flight area that may affect the safe flight of the aircraft, such as buildings, towers, trees, etc., the dangerous area refers to an area in the flight area that may pose a threat to the aircraft, such as a high electromagnetic interference area, a military restricted area, and a restricted airspace around an airport, etc. The test requirements refer to the specific objectives and technical requirements of the flight mission, including the performance test standards of the receiver, the required data collection type, the flight altitude, the flight speed, the flight time and other requirements, the multiple altitude layers refer to the different altitudes that the aircraft needs to fly when performing the mission, the take-off point refers to the place where the aircraft starts to fly, the turning point refers to the predetermined point in the flight trajectory where the aircraft changes direction, the multi-altitude layer transition point refers to the predetermined point where the aircraft transitions from one altitude layer to another altitude layer, the multi-altitude layer landing point refers to the place where the aircraft lands after completing all the predetermined altitude layer flights, and the multi-altitude layer flight trajectory refers to the flight path predetermined by the aircraft in the entire mission, including the paths of all stages such as take-off, flight at different altitude layers, turning, transition and landing.

[0035] Optionally, the obstacles and dangerous areas in the flight area map may be marked on the map with different symbols and colors, and annotations may be added to the marked obstacles and dangerous areas to explain their nature, height, radius and other information.

[0036] The present invention calculates the coverage factor of the multi-altitude flight trajectory to the corresponding verification area of ​​the ILSVOR navigation station to ensure the reliability of the test data.

[0037] In detail, the calculation of the coverage factor of the multi-altitude flight trajectory to the verification area corresponding to the ILSVOR navigation station includes: Determining the navigation station parameters of the ILSVOR navigation station; determining flight trajectory parameters of the multi-level flight trajectory; constructing a radio propagation model for the multi-level flight trajectory; Analyzing the effective coverage area of ​​the multi-layer flight trajectory using the radio propagation model based on the navigation station parameters and the flight trajectory parameters; Based on the effective coverage area, the coverage coefficient of the multi-altitude flight trajectory to the verification area corresponding to the ILSVOR navigation station is analyzed.

[0038] Among them, the navigation station parameters refer to the parameters of technical specifications related to the performance of the ILSVOR navigation station, such as frequency, transmission power and other parameters; the flight trajectory parameters refer to data related to the flight path of the aircraft; the radio propagation model refers to a model used to predict the propagation characteristics and coverage range of radio waves in space; the effective coverage area refers to an area where radio signals can provide sufficient strength to support navigation services under specific conditions; the verification area refers to an area set to ensure the normal operation of the navigation station; and the coverage coefficient refers to a parameter used to represent the degree of overlap between the effective coverage area of ​​the flight trajectory and the verification area of ​​the ILSVOR navigation station.

[0039] Optionally, the radio propagation model for constructing the multi-altitude flight trajectory can be trained by a free space propagation model using a large amount of historical flight trajectory parameter data.

[0040] S2. According to the coverage factor, the transmission signal of the ILSVOR navigation station is collected by using the high-precision receiver, and the broadband noise characteristics of the transmission signal are identified. Based on the broadband noise characteristics, a pre-trained noise separation model is used to perform noise separation on the transmission signal to obtain a navigation signal.

[0041] It should be explained that the transmission signal refers to the radio signal emitted by the ILSVOR navigation station, which is used to provide navigation information, and the wide-band noise characteristics refer to the noise characteristics within the broadband frequency range in the ILSVOR navigation station transmission signal collected by the receiver, except for the expected navigation signal, such as noise power, noise spectrum and other characteristics.

[0042] The present invention uses the broadband noise feature and a pre-trained noise separation model to perform noise separation on the transmission signal to obtain a navigation signal, thereby improving the quality of the navigation signal.

[0043] In detail, the using a pre-trained noise separation model to perform noise separation on the transmission signal to obtain a navigation signal includes: constructing a time-frequency diagram of the transmitted signal; Normalizing the time-frequency graph to obtain a normalized time-frequency graph; Outputting a noise probability map and a signal probability map of the normalized time-frequency map using the noise separation model; The noise probability map and the signal probability map are used to separate the transmitted signal from noise to obtain a navigation signal.

[0044] Among them, the time-frequency diagram refers to the conversion of a one-dimensional time domain signal into a two-dimensional time-frequency domain representation through time-frequency analysis (such as STFT, wavelet transform), the normalized time-frequency diagram refers to the time-frequency diagram after the original time-frequency diagram is standardized, the noise probability diagram refers to the two-dimensional matrix of the probability that the time-frequency unit in the normalized time-frequency diagram belongs to the noise, the signal probability diagram refers to the two-dimensional matrix of the probability that the time-frequency unit in the normalized time-frequency diagram belongs to the navigation signal, and the navigation signal refers to the pure signal after time-frequency mask processing.

[0045] Optionally, the constructing of the time-frequency diagram of the transmission signal may be converted by short-time Fourier transform.

[0046] S3. Constructing an observation matrix of the navigation signal, and reconstructing the navigation signal based on the observation matrix to obtain a reconstructed navigation signal.

[0047] The present invention constructs the observation matrix of the navigation signal to provide a data basis for the subsequent reconstruction of the navigation signal.

[0048] In detail, constructing the observation matrix of the navigation signal includes: Analyzing observation matrix indicators of the navigation signal; Determining a sparse basis of the navigation signal according to the observation matrix indicator; Analyzing the sparsity of the navigation signal by using the sparse basis; Based on the sparsity, an observation matrix of the navigation signal is constructed.

[0049] Among them, the observation matrix indicators refer to some metrics used to evaluate the performance of the observation matrix, the sparse basis refers to a set of basis functions that can represent the signal as a small number of non-zero coefficients (sparse representation), the sparsity refers to the number of non-zero coefficients when the signal is represented under the sparse basis, and the observation matrix refers to a matrix that maps a high-dimensional sparse signal or a compressible signal to a low-dimensional space.

[0050] Further, analyzing the sparsity of the navigation signal through the sparse basis includes: Convert the navigation signal according to the sparse basis to obtain a sparse navigation signal; identifying a signal length of the sparse navigation signal; defining an indicator function of the sparse navigation signal; The number of non-zero elements of the sparse navigation signal is calculated based on the signal length and the indicator function:

[0051] in, represents the number of non-zero elements, Represents the sparse navigation signal elements, represents the signal length of the sparse navigation signal, represents the indicator function; The sparsity of the navigation signal is determined according to the number of non-zero elements.

[0052] Among them, the sparse navigation signal refers to the navigation signal after sparse basis conversion, the signal length refers to the total number of elements in the sparse navigation signal, the indicator function refers to the function used to identify non-zero elements in the sparse navigation signal, the number of non-zero elements refers to the total number of non-zero elements in the sparse navigation signal, and the sparsity refers to the ratio of the number of non-zero elements to the signal length.

[0053] It should be noted that, in the present application, the quality and integrity of the signal can be evaluated by calculating the number of non-zero elements of the sparse navigation signal using the above formula.

[0054] The present invention reconstructs the navigation signal based on the observation matrix to obtain a reconstructed navigation signal, which can further improve the signal quality of the navigation signal, thereby improving the accuracy of the later ILSVOR navigation station flight verification. The reconstructed navigation signal refers to the original navigation signal recovered from the compressed or undersampled observation data by a mathematical algorithm. In detail, the compressed sampling matching pursuit (CoSaMP) of the navigation signal reconstructs the signal by iteratively selecting and updating the columns of the observation matrix.

[0055] S4. Analyze the filtering parameters of the reconstructed navigation signal using a preset intelligent optimization algorithm, filter the reconstructed navigation signal using the filtering parameters to obtain a filtered navigation signal, and fuse the filtered navigation signal with pre-collected inertial navigation system data to obtain a high-precision navigation signal.

[0056] The present invention utilizes a preset intelligent optimization algorithm to analyze the filtering parameters of the reconstructed navigation signal to improve the processing quality of the navigation signal and the overall performance of the system.

[0057] In detail, the analyzing the filtering parameters of the reconstructed navigation signal by using a preset intelligent optimization algorithm includes: Determining a filtering target and a filter type for the reconstructed navigation signal; identifying initial filter parameters for the filter type; Constructing a filtering parameter group of the initial filtering parameters; According to the filtering target, analyzing the filtering performance of the filtering parameter group using the intelligent optimization algorithm; Based on the filtering performance, filtering parameters of the reconstructed navigation signal are determined.

[0058] Among them, the filtering target refers to the specific purpose that is hoped to be achieved through the filtering process, such as reducing noise, eliminating multipath effects, improving signal quality, etc. The filter type refers to the mathematical model used to process the signal, such as FIR (finite impulse response) filter, IIR (infinite impulse response), the initial filtering parameters refer to a set of preset parameter values ​​of the filter before starting the optimization process, the filtering parameter group refers to a set of parameters used to configure the filter, the filtering performance refers to the effect of the filter in achieving the filtering target, the filtering parameters refer to a set of parameters that are finally determined, and the filtering parameters include cutoff frequency, filter order and filter coefficient.

[0059] Optionally, the analyzing the filtering performance of the filtering parameter group by using the intelligent optimization algorithm may be implemented by a particle swarm optimization (PSO) algorithm.

[0060] It should be explained that the filtered navigation signal refers to a signal obtained by filtering the reconstructed navigation signal using a filtering parameter.

[0061] The present invention fuses the filtered navigation signal with the pre-collected inertial navigation system data to obtain a high-precision navigation signal that can provide more accurate and reliable navigation data. The inertial navigation system data is a series of information collected by the inertial navigation system, such as acceleration data, angular velocity data, attitude data and other data, and the high-precision navigation signal refers to the navigation information obtained by fusing data from different navigation systems (such as GPS, GLONASS, Beidou, etc.). In detail, the fusion of the filtered navigation signal and the pre-collected inertial navigation system data to obtain a high-precision navigation signal can be fused by an extended Kalman filter fusion algorithm.

[0062] S5. Calculate a signal error of the high-precision navigation signal, and verify the high-precision navigation signal based on the signal error to obtain a target navigation signal.

[0063] The signal error of the high-precision navigation signal calculated by the present invention can be used as a data basis for subsequent signal verification, thereby improving the signal quality of the high-precision navigation signal.

[0064] In detail, the calculating the signal error of the high-precision navigation signal includes: Analyzing the position PVT solution of the high-precision navigation signal; Defining a reference benchmark for the high-precision navigation signal; Based on the reference datum, analyzing and calculating the position error of the position PVT solution; A signal error of the high-precision navigation signal is determined based on the position error.

[0065] Among them, the position PVT solution refers to the carrier position solution result obtained by navigation signal processing, usually including three coordinate values ​​of latitude, longitude and altitude; the reference benchmark refers to a known and precise position standard used to compare and evaluate the navigation signal solution results; the position error refers to the difference between the carrier position obtained by navigation signal processing and the reference benchmark position; the signal error refers to a comprehensive indicator used to evaluate the overall accuracy and reliability of the navigation signal.

[0066] Finally, the present invention verifies the high-precision navigation signal based on the signal error, and obtains the target navigation signal, which can effectively verify the high-precision navigation signal, improve its accuracy and reliability, and finally obtain the navigation signal for operation. Among them, the target navigation signal refers to a navigation signal that meets the predetermined accuracy and reliability requirements after a series of error analysis and verification processes. In detail, the verification of the high-precision navigation signal based on the signal error can be verified by a sequence estimation verification method.

[0067] First, by analyzing the sensitivity value of the high-precision receiver corresponding to the aircraft and constructing a multi-altitude flight trajectory, it can be ensured that the flight verification covers all important aspects of the verification area corresponding to the navigation station, improving the comprehensiveness and accuracy of the verification. The calculation of the coverage coefficient makes the planning of the flight trajectory more scientific and reasonable, ensuring the uniformity and effectiveness of signal acquisition. Secondly, by using a high-precision receiver to collect the transmitted signal and identify the broadband noise characteristics, combined with a pre-trained noise separation model, it can effectively separate the noise from the transmitted signal and improve the quality of the navigation signal. This method is particularly effective in a broadband and high-noise environment and significantly improves the credibility of the signal. Furthermore, by constructing an observation matrix to reconstruct the navigation signal and combining the intelligent optimization algorithm to analyze the filtering parameters, it can achieve accurate filtering of the reconstructed navigation signal. This method not only improves the signal processing efficiency, but also reduces the signal error and enhances the stability of the navigation system. Finally, the filtered navigation signal is fused with the inertial navigation system data to obtain a high-precision navigation signal, which is verified by calculating the signal error to finally obtain the target navigation signal. This process greatly improves the navigation accuracy of the navigation system, provides the aircraft with more reliable and accurate navigation information, and ensures flight safety. Therefore, the present invention can improve the accuracy of the navigation information of the ILSVOR navigation station.

Claims

1. A method for processing flight calibration of an ILSVOR navigation station under wide-band and high-noise conditions, characterized in that: The method comprises: Determine an aircraft of an ILSVOR navigation station, analyze a sensitivity value of a high-precision receiver corresponding to the aircraft, construct a multi-altitude flight trajectory of the aircraft based on the sensitivity value, and calculate a coverage factor of the multi-altitude flight trajectory for a verification area corresponding to the ILSVOR navigation station; According to the coverage factor, using the high-precision receiver to collect the transmission signal of the ILSVOR navigation station, identifying the broadband noise characteristics of the transmission signal, and using the broadband noise characteristics and a pre-trained noise separation model to perform noise separation on the transmission signal to obtain a navigation signal; constructing an observation matrix of the navigation signal, and reconstructing the navigation signal based on the observation matrix to obtain a reconstructed navigation signal; Analyzing the filtering parameters of the reconstructed navigation signal using a preset intelligent optimization algorithm, filtering the reconstructed navigation signal using the filtering parameters to obtain a filtered navigation signal, and fusing the filtered navigation signal with pre-collected inertial navigation system data to obtain a high-precision navigation signal; A signal error of the high-precision navigation signal is calculated, and based on the signal error, the high-precision navigation signal is verified to obtain a target navigation signal.

2. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 1, characterized in that: The analyzing the sensitivity value of the high-precision receiver corresponding to the aircraft includes: Constructing an interference-free environment for the high-precision receiver; Determine the signal source of the ILSVOR navigation station corresponding to the high-precision receiver; defining a test intensity gradient of the signal source; analyzing the intensity demodulation coefficient of the test intensity gradient; The sensitivity value of the high-precision receiver is determined according to the strength demodulation coefficient.

3. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 2, characterized in that: Determining the sensitivity value of the high-precision receiver according to the strength demodulation coefficient includes: Determining a demodulation threshold of the high-precision receiver; analyzing a minimum detectable signal of the high-precision receiver according to the strength demodulation coefficient; According to the demodulation threshold and the minimum detectable signal, the sensitivity value of the high-precision receiver is calculated using the following formula: in, Represents the sensitivity value of the high-precision receiver, represents the bandwidth of the high-precision receiver, represents the noise generated by the bandwidth of the high-precision receiver, represents the noise factor, represents the demodulation threshold, represents the noise floor of a high-precision receiver, Indicates the minimum detectable signal.

4. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 3, characterized in that: The step of constructing a multi-altitude flight trajectory of the aircraft includes: Obtaining a flight area map of the aircraft; marking obstacles and danger areas in the map of the flight area; defining test requirements for the aircraft; Analyzing multiple altitude layers of the aircraft according to the test requirements; Determining flight parameters of the aircraft based on the obstacles, the dangerous area, and the multiple altitude layers, wherein the flight parameters include a take-off point, a turning point, a multiple altitude layer transition point, and a multiple altitude layer landing point; The multi-altitude flight trajectory of the aircraft is determined by the flight parameters.

5. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 4, characterized in that: The calculating of the coverage coefficient of the multi-altitude flight trajectory to the verification area corresponding to the ILSVOR navigation station includes: Determining the navigation station parameters of the ILSVOR navigation station; determining flight trajectory parameters of the multi-layer flight trajectory; constructing a radio propagation model for the multi-level flight trajectory; Analyzing the effective coverage area of ​​the multi-layer flight trajectory using the radio propagation model based on the navigation station parameters and the flight trajectory parameters; Based on the effective coverage area, the coverage coefficient of the multi-altitude flight trajectory to the verification area corresponding to the ILSVOR navigation station is analyzed.

6. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 5, characterized in that: The using a pre-trained noise separation model to perform noise separation on the transmission signal to obtain a navigation signal includes: constructing a time-frequency diagram of the transmitted signal; Normalizing the time-frequency graph to obtain a normalized time-frequency graph; Outputting a noise probability map and a signal probability map of the normalized time-frequency map using the noise separation model; The noise probability map and the signal probability map are used to separate the transmitted signal from noise to obtain a navigation signal.

7. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 6, characterized in that: The constructing the observation matrix of the navigation signal comprises: Analyzing observation matrix indicators of the navigation signal; Determining a sparse basis of the navigation signal according to the observation matrix indicator; Analyzing the sparsity of the navigation signal by using the sparse basis; Based on the sparsity, an observation matrix of the navigation signal is constructed.

8. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 7, characterized in that: The analyzing the sparsity of the navigation signal by using the sparse basis includes: Convert the navigation signal according to the sparse basis to obtain a sparse navigation signal; identifying a signal length of the sparse navigation signal; defining an indicator function of the sparse navigation signal; The number of non-zero elements of the sparse navigation signal is calculated based on the signal length and the indicator function: in, represents the number of non-zero elements, Represents the sparse navigation signal elements, represents the signal length of the sparse navigation signal, represents the indicator function; The sparsity of the navigation signal is determined according to the number of non-zero elements.

9. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 8, characterized in that: The analyzing the filtering parameters of the reconstructed navigation signal by using a preset intelligent optimization algorithm includes: Determining a filtering target and a filter type for the reconstructed navigation signal; identifying initial filter parameters for the filter type; Constructing a filtering parameter group of the initial filtering parameters; According to the filtering target, analyzing the filtering performance of the filtering parameter group using the intelligent optimization algorithm; Based on the filtering performance, filtering parameters of the reconstructed navigation signal are determined.

10. The ILSVOR navigation station flight calibration processing method under wide-band and high-noise conditions as claimed in claim 9, characterized in that: The calculating the signal error of the high-precision navigation signal comprises: Analyzing the position PVT solution of the high-precision navigation signal; Defining a reference benchmark for the high-precision navigation signal; Based on the reference datum, analyzing and calculating the position error of the position PVT solution; A signal error of the high-precision navigation signal is determined based on the position error.

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