Frequency detection system and method of airport navigational light control system

Abstract

The invention discloses a frequency detection system and method for an airport navigation-aid light control system, and belongs to the technical field of frequency detection. Comprising the following modules: a band-pass filtering module, a sampling rate conversion module, a total energy estimation module, a frequency energy estimation module, an energy ratio estimation module, an energy ratio frequency distribution estimation module, an optimal detection threshold estimation module and a detection module. According to the frequency detection system and method, the energy ratio of the i frequencies to be detected in the input signals to be detected is detected to judge whether the frequencies to be detected exist or not, a lamp state control signal is output, and then the runway lamp is controlled; the effects of high data transmission reliability, high data processing response speed and low cost and design complexity are achieved; the mode of analyzing the frequency through the energy ratio provided by the invention has good adaptability to signal attenuation, is suitable for a scene in which the signal intensity is changed due to transmission distance or attenuation, and has strong anti-noise capability.

Description

Technical Field

[0001] The invention belongs to the technical field of frequency detection, and in particular relates to a frequency detection system and method for an airport navigation light control system. Background Art

[0002] With the rapid development of the global aviation transportation industry, the importance of airport navigation lighting control systems has become increasingly prominent. As an important facility to ensure the safe taxiing, takeoff and landing of aircraft, the demand for the intelligence and high reliability of airport navigation lighting control systems has continued to increase. In recent years, with the development of communication technology and control technology, airport navigation lighting control systems have gradually evolved from traditional wired switch control to centralized and digital management using power line carrier technology. At the same time, as an important branch of the signal processing field, signal frequency detection technology has been rapidly developed in recent years with the rapid development of communication technology and digital processing technology. Its application scope has been continuously expanded, covering wireless communication, industrial automation, environmental monitoring and intelligent transportation. In the airport navigation lighting control system, signal frequency detection technology is particularly important, which is directly related to the system's accurate judgment and control of the lighting status. The uniqueness of the airport navigation lighting control system lies in the fact that its operating environment has high noise and high interference characteristics, and at the same time, it has extremely high requirements for the real-time and accuracy of signal detection. In this scenario, traditional amplitude detection or data frame parsing methods are difficult to meet the needs, and frequency detection technology has gradually become a key technology in the airport navigation lighting control system with its advantages of strong anti-interference and flexible implementation.

[0003] In the prior art, the Chinese patent with publication number CN109506896A relates to an airport runway lighting detection system, which is mainly composed of a single-chip control system, a camera, a Bluetooth sending module, a Bluetooth receiving module and a computer terminal, and remotely detects the runway lighting through photos taken by the camera; this patent has the following disadvantages: long processing time, low efficiency; and the need to consume manpower and material resources for detection. In addition, the Chinese patent with publication number CN110749601A relates to an airport runway lighting detection system and method based on images, including an image acquisition device for acquiring all images containing lighting areas in the runway area, and sending the images containing the lighting areas to a processor; a processor for real-time detection of whether there is an image area with damaged lighting in the image set containing the lighting area; and a result output device for outputting the detection results. This patent has the following disadvantages: high implementation cost, requiring high-resolution cameras and image processing hardware, etc.; image detection may lead to misjudgment due to dirt, light, bad weather or interference; image acquisition, transmission and processing require a long time, and the calculation burden is heavy. Summary of the invention

[0004] The present invention aims at the above-mentioned problems, makes up for the deficiencies of the prior art, and provides a frequency detection system and method for an airport navigation lighting control system.

[0005] To achieve the above purpose, the present invention adopts the following technical solution.

[0006] The present invention provides a frequency detection system for an airport navigation lighting control system, comprising the following modules: Bandpass filter module: used for filtering the input signal to be tested, including a high-pass filter and a low-pass filter connected in series, the cutoff frequency of the high-pass filter is set to filter out signal components below the frequency range to be tested, and the cutoff frequency of the low-pass filter is set to filter out signal components above the frequency range to be tested; Sampling rate conversion module: used to downsample the filtered signal by D times to generate a downsampled signal; Total energy estimation module: used to calculate the total energy of the signal based on the downsampled signal; Multiple frequency energy estimation modules: Each frequency energy estimation module uses the Goertzel algorithm to calculate the fundamental wave and second harmonic energy of the frequency to be measured, and uses the sum of the calculated fundamental wave and second harmonic energy as the total energy of the frequency to be measured; Energy proportion estimation module: used to calculate the energy proportion of each frequency to be measured according to the total signal energy obtained by the total energy estimation module and the total energy of each frequency to be measured obtained by the frequency energy estimation module; Energy proportion frequency distribution estimation module: Generates frequency distribution histogram of energy proportion based on historical data; Optimal detection threshold estimation module: applying Otsu algorithm to analyze the frequency distribution histogram to determine the optimal decision threshold; Detection module: used to compare the energy proportion of each frequency to be tested with the optimal decision threshold to determine whether these frequencies to be tested exist.

[0007] As a preferred solution of the present invention, the frequency range to be measured is 4 kHz to 9 kHz, the cut-off frequency of the high-pass filter is set to 3 kHz, and the cut-off frequency of the low-pass filter is set to 10 kHz.

[0008] As another preferred embodiment of the present invention, the differential equation of the high-pass filter is: (1), The difference equation of the low-pass filter is: (2); in, a is the filter coefficient of the high-pass filter, b is the filter coefficient of the low-pass filter, x 0(n ) is the input of the high-pass filter, that is, the signal to be tested that is input into the band-pass filter module. y 1( n ) is the output of the high-pass filter, x 1( n ) is the output of the low-pass filter, n =0, 1, …, N -1, N express x 0( n ), that is, x 0( n ) is N sampling points, the sampling rate f s .

[0009] As another preferred solution of the present invention, the total energy estimation module is provided by the formula: (3), Calculate the total energy of the signal; in the formula: D Indicates the downsampling multiple in the sampling rate conversion module. N / D for D times the length of the downsampled signal, x 2 ( n ) is the output signal of the sampling rate conversion module, the output signal x 2 ( n )= x 1( nD ), n =0, 1, …, N / D- 1.

[0010] As another preferred solution of the present invention, in the frequency energy estimation module, the Goertzel algorithm is used to calculate the fundamental wave energy. e i，1 The calculation steps are as follows: , (4), (5), (6); in, q 1 ( n ) is the intermediate variable of the Goertzel algorithm; Calculate the second harmonic energy using the Goertzel algorithm e i，2 The calculation steps are as follows: (7), (8), (9), (10); in, fi, 1 means the i The fundamental frequency of the frequency to be measured; fi, 2 means the i The second harmonic frequency of the frequency to be measured, that is, twice the fundamental frequency; q 2 ( n ) is the intermediate variable of the Goertzel algorithm; the output of the frequency energy estimation module e i for: e i = e i，1＋ e i，2 (11).

[0011] As another preferred embodiment of the present invention, in the optimal detection threshold estimation module, the optimal decision threshold is determined by applying the Otsu algorithm to calculate the maximum value of the inter-class variance, which specifically includes: normalizing the histogram probability; calculating the cumulative probability and the cumulative mean; traversing all thresholds and selecting the value that maximizes the inter-class variance as the optimal decision threshold.

[0012] As another preferred solution of the present invention, in the detection module, if the energy proportion of each frequency to be tested exceeds the optimal decision threshold, it is determined that these frequencies to be tested exist, and a lamp state control signal is output.

[0013] The present invention provides a frequency detection method for an airport navigation lighting control system, which is implemented using the frequency detection system of the airport navigation lighting control system, and includes the following steps: First, the input signal to be tested x 0( n ) Through the bandpass filter module, the signal is obtained after filtering out some high-frequency and low-frequency components x 1( n ), and then the signal is obtained through the sampling rate conversion module x 2 ( n ); Then, the signal x 2 ( n ) respectively through i A frequency energy estimation module and a total energy estimation module, i Represents the number of frequencies to be measured; the output of each frequency energy estimation module e iand the output of the total energy estimation module e total As input, enter i An energy proportion estimation module calculates the energy proportion corresponding to each frequency to be tested d i ; Finally, for each energy proportion corresponding to the frequency to be measured, the optimal decision threshold is obtained through the energy proportion frequency distribution estimation module and the optimal detection threshold estimation module. Th i , the energy proportion corresponding to each frequency to be tested is calculated through the detection module d i and the optimal decision threshold Th i The detection results are obtained by comparison to determine whether these frequencies to be tested exist.

[0014] Furthermore, in the test results, if the energy proportion corresponding to each frequency to be tested is d i Exceeding the optimal decision threshold Th i , it is determined that these frequencies to be tested exist and the lamp status control signal is output.

[0015] Beneficial effects of the present invention: The present invention provides a frequency detection system and method for an airport navigation lighting control system. By using the frequency detection system and method of the present invention, the frequency of the input signal to be tested is detected. i The energy proportion of the frequencies to be tested is used to determine whether these frequencies to be tested exist among these frequencies to be tested, and then the runway lights are controlled; and through the above technical solution, the present invention achieves the effects of strong data transmission reliability, fast data processing response speed, and low cost and design complexity. In addition, the frequency detection system and method proposed by the present invention are low in cost and easy to implement; they have good stability and high accuracy under harsh noise environment conditions such as airports; the amount of calculation in the system is small, the detection efficiency is high, and it is convenient for subsequent operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a signal trend processing flow chart of a frequency detection system of an airport navigation light control system.

[0017] Figure 2 The present invention is a flow chart of signal trend processing of a bandpass filter module of a frequency detection system of an airport navigation light control system.

[0018] Figure 3 It is the time domain waveform of the signal to be tested transmitted back by the lamp.

[0019] Figure 4It is the spectrum diagram of the signal to be tested sent back by the lamp.

[0020] Figure 5 It is the frequency distribution histogram of the energy proportion of the candidate frequencies. DETAILED DESCRIPTION

[0021] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be understood that the specific implementation methods described herein are only used to explain the present invention and are not used to limit the present invention.

[0022] Combination Figure 1 and Figure 2 As shown, a frequency detection system for an airport navigation lighting control system provided by an embodiment of the present invention includes the following modules: Bandpass filter module: used for filtering the input signal to be tested, including a high-pass filter and a low-pass filter connected in series, the cutoff frequency of the high-pass filter is set to filter out signal components below the frequency range to be tested, and the cutoff frequency of the low-pass filter is set to filter out signal components above the frequency range to be tested; Sampling rate conversion module: used to downsample the filtered signal by D times to generate a downsampled signal; Total energy estimation module: used to calculate the total energy of the signal based on the downsampled signal; Multiple frequency energy estimation modules: Each frequency energy estimation module uses the Goertzel algorithm to calculate the fundamental wave and second harmonic energy of the frequency to be measured, and uses the sum of the calculated fundamental wave and second harmonic energy as the total energy of the frequency to be measured; Energy proportion estimation module: used to calculate the energy proportion of each frequency to be measured according to the total signal energy obtained by the total energy estimation module and the total energy of each frequency to be measured obtained by the frequency energy estimation module; Energy proportion frequency distribution estimation module: Generates frequency distribution histogram of energy proportion based on historical data; Optimal detection threshold estimation module: applying Otsu algorithm to analyze the frequency distribution histogram to determine the optimal decision threshold; Detection module: used to compare the energy proportion of each frequency to be tested with the optimal decision threshold to determine whether these frequencies to be tested exist.

[0023] Specifically, in the application scenario of the present invention, the frequency range to be measured is concentrated between 4kHz and 9kHz, the basic alternating current of the power supply line is a periodic sine wave with a frequency of 50Hz, and the signal used to transmit the lamp status information is superimposed on the low-frequency 50Hz sine wave; in addition, due to the complex electromagnetic environment of the airport, there will be irrelevant frequency components that interfere with subsequent frequency detection; preliminary filtering is performed through the bandpass filter module, and the signal processed by the bandpass filter module filters out irrelevant frequency components of high and low frequencies, which can improve the reliability of subsequent frequency detection. Therefore, the cutoff frequency of the high-pass filter is set to 3kHz, and the cutoff frequency of the low-pass filter is set to 10kHz; the differential equation of the high-pass filter is: (1), The difference equation of the low-pass filter is: (2); in, a is the filter coefficient of the high-pass filter, b is the filter coefficient of the low-pass filter, x 0( n ) is the input of the high-pass filter, that is, the signal to be tested that is input into the band-pass filter module. y 1( n ) is the output of the high-pass filter, x 1( n ) is the output of the low-pass filter, n =0, 1, …, N -1, N express x 0( n ), that is, x 0( n ) is N sampling points, the sampling rate f s .

[0024] Specifically, the total energy estimation module uses the formula: (3), Calculate the total energy of the signal; in the formula: D Indicates the downsampling multiple in the sampling rate conversion module. N / D for D times the length of the downsampled signal, x 2 ( n ) is the output signal of the sampling rate conversion module, x 1( n ) After the sampling rate conversion module D After downsampling, the output signal is x 2 (n )= x 1( nD ), n =0, 1, …, N / D- 1.

[0025] Specifically, in the frequency energy estimation module, the Goertzel algorithm is used to calculate the signal energy on the specific frequency component to be measured in the signal to be measured. The Goertzel algorithm is an efficient digital signal processing algorithm for detecting specific frequency components in the signal. The present invention significantly reduces the computational complexity and resource consumption by using the Goertzel algorithm. In order to improve the accuracy of detection, the present invention calculates the energy of the fundamental wave and the second harmonic (i.e., the double frequency of the fundamental wave) on the specific frequency component to be measured in the signal to be measured, and uses them together to analyze the existence of the specific frequency to be measured; x 2 ( n ) Frequency f i The output of the energy estimation module is the energy e i , i= 1. … N－ 1. Fundamental wave energy in the present invention e i，1 The calculation steps are as follows: , (4), (5), (6); in, q 1 ( n ) is the intermediate variable of the Goertzel algorithm; Calculate the second harmonic energy using the Goertzel algorithm e i，2 Steps and calculation of fundamental wave energy e i，1 The steps are the same, but the frequency used for calculation needs to be replaced by twice the frequency, that is: (7), (8), (9), (10); in, fi, 1 means the i The fundamental frequency of the frequency to be measured; fi, 2 means the iThe second harmonic frequency of the frequency to be measured, that is, twice the fundamental frequency; q 2 ( n ) is the intermediate variable of the Goertzel algorithm; the output of the frequency energy estimation module e i for: e i = e i，1＋ e i，2 (11).

[0026] Specifically, the equations (3) and (11) are respectively e total and e i , the energy proportion corresponding to each frequency to be measured can be calculated d i , the calculation formula is: (12).

[0027] When determining whether there is a specific frequency component to be tested in the carrier signal sent back by the lamp, an optimal decision threshold is set. If the energy ratio of the candidate frequency exceeds the optimal decision threshold, it is considered that the specific frequency component to be tested exists in the carrier signal, which can be used to determine the state of the lamp. In order to calculate the optimal decision threshold, it is necessary to first use the existing historical R The energy proportion frequency distribution estimation module calculates the latest R Frequency in data f i The energy proportion d i The frequency distribution histogram of is shown as follows: hist i [ m ], m =0, 1, ..., 99 (13); The frequency distribution histogram is counted according to the energy percentage of the candidate frequencies. The frequency distribution histogram consists of 100 columns from 0 to 99, where m The energy percentage calculated by equation (12) is rounded down to an integer, ranging from 0 to 99. hist i [ m ] represents the energy proportion of the candidate frequency m The frequency of occurrence in the test data. Calculate the energy ratio d iThe method for the frequency distribution histogram is as follows: First initialize, histi[m]=0 (14); Then, R The first data k In the data d i The corresponding frequency of occurrence is accumulated, that is, every time the same energy proportion d i When it appears once, the corresponding frequency distribution histogram value is increased by 1, and the energy proportion can be obtained. d i Frequency distribution histogram of .

[0028] In the optimal detection threshold estimation module, the optimal decision threshold is determined by applying the Otsu algorithm to calculate the maximum value of the inter-class variance, which specifically includes: normalizing the histogram probability; calculating the cumulative probability and the cumulative mean; traversing all thresholds and selecting the value that maximizes the inter-class variance as the optimal decision threshold.

[0029] In the optimal detection threshold estimation module, the above R The energy proportion obtained by the data detection is used to find the threshold value as the optimal decision threshold in the Otsu algorithm using the Otsu algorithm. Among them, the Otsu algorithm is a method for automatically determining the image binarization threshold. By calculating the grayscale histogram of the image, a grayscale value is selected as the threshold value to divide the image pixels into two parts: foreground and background. The Otsu algorithm is used in the present invention to find a suitable energy proportion threshold value through the frequency distribution histogram of the energy proportion to divide the presence or absence of a specific frequency to be tested, so as to serve as the optimal decision threshold for detecting a specific frequency to be tested; the detailed calculation steps of the Otsu algorithm are as follows: Calculate the normalized histogram probability as follows: (15); in, p ( i ) indicates the i The probability of occurrence of an energy proportion.

[0030] Calculate the cumulative probability and cumulative mean as follows: (weight of the frequency absent class) (16), (Weight of frequency-presence class) (17), (mean of the frequency-free class) (18), (mean of frequency presence class) (19); The between-class variance is calculated as follows: (20); Iterate through all possible thresholds t , find The largest t This is the optimal decision threshold.

[0031] In addition, an embodiment of the present invention provides a frequency detection method for an airport navigation lighting control system, comprising the following steps: First, the input signal to be tested x 0( n ) Through the bandpass filter module, the signal is obtained after filtering out some high-frequency and low-frequency components x 1( n ), and then the signal is obtained through the sampling rate conversion module x 2 ( n ); Then, the signal x 2 ( n ) respectively through i A frequency energy estimation module and a total energy estimation module, i Represents the number of frequencies to be measured; the output of each frequency energy estimation module e i and the output of the total energy estimation module e total As input, enter i An energy proportion estimation module calculates the energy proportion corresponding to each frequency to be tested d i ; Finally, for each frequency to be tested, the energy proportion corresponding to the optimal decision threshold is obtained through the energy proportion frequency distribution estimation module and the optimal detection threshold estimation module. Th i , the energy proportion corresponding to each frequency to be tested is calculated through the detection module d i and the optimal decision threshold Th i The detection results are compared to determine whether these frequencies to be tested exist; in the detection results, if the energy proportion corresponding to each frequency to be tested d i Exceeding the optimal decision threshold Th i , it is determined that these frequencies to be tested exist and the lamp status control signal is output.

[0032] Airport navigation light detection technology is an important part of the airport navigation light control system, which determines whether the airport tower can accurately know the status of the lights on the airport runway and perform further control. The frequency detection system and method of the airport navigation light control system proposed in the present invention can mainly solve the following problems in the airport navigation light control system: (1) The problem of low data transmission reliability in the existing technology: The existing airport navigation light detection technology is easily affected by the external environment such as bad weather, dust and light changes on image acquisition in the airport environment, resulting in misjudgment of the status of the lights on the airport runway; (2) The problem of poor real-time performance and slow response speed in the existing technology: The existing airport navigation light detection technology needs to judge the status of the lights through the pictures sent back from the site, and cannot perform real-time processing, and the response speed is slow; (3) The problem of high cost and design complexity of the existing technology: The existing airport navigation light detection technology requires high hardware cost, and the image processing system requires a large amount of computing resources and complex image processing algorithms, which has high cost and design complexity.

[0033] In summary, the present invention accurately determines the state of the lamp by analyzing certain specific frequency components in the carrier signal sent back by the lamp. The carrier signal sent back by the lamp is an electrical signal. The present invention allows the user to provide i The frequency to be tested is detected by using the frequency detection system and method of the present invention. i The energy proportion of the frequencies to be tested is used to determine whether these frequencies to be tested exist, and then the runway lights are controlled; and through the above-mentioned technical solution, the present invention achieves the effects of strong data transmission reliability, fast data processing response speed, and low cost and design complexity. The method of parsing frequency by energy proportion proposed in the present invention has good adaptability to signal attenuation, is suitable for scenarios where signal strength changes due to transmission distance or attenuation, and has strong anti-noise ability; in the frequency energy estimation module of the present invention, the Goertzel algorithm is used to calculate the energy of specific frequency components to be tested in the signal to be tested, which has high efficiency and reliability; in the optimal detection threshold estimation module of the present invention, the Otsu algorithm is applied to the field of signal processing, and the accuracy of the optimal decision threshold calculated by the Otsu algorithm is higher when making decisions. In the present invention, the Goertzel algorithm is combined with the Otsu algorithm to further improve the reliability and real-time performance of the airport navigation lighting control system in complex electromagnetic environments.

[0034] In order to verify the effectiveness of the frequency detection system and method of the present invention, the frequency detection system and method are implemented on a development board based on the STM32F446RE microcontroller and tested; STM32F446RE is a microcontroller based on the ARMCortex-M4 core, with rich peripheral interfaces and powerful processing capabilities, and is widely used in industrial control, consumer electronics, communications and other fields.

[0035] Furthermore, we selected data collected from the airport site for testing. There are about 130 signals sent back from the lamps collected from the site. The waveform of a typical signal is as follows: Figure 3 As shown in the figure, the window length of the effective signal is about 3~4ms. It is known that the transmission frequency of this signal is 4.3kHz. Due to the complex electromagnetic environment at the airport and the interference of components, the main peak of the signal spectrum may be partially offset. Check the spectrum diagram of the signal, as shown in Figure 4 The test is performed under Keil uversion5 environment, and the number of frequencies to be tested is i There are 3 options, namely f 1=4.3kHz, f 2 = 5.2kHz, f 3=6.6kHz, the test results are shown in Table 1 below.

[0036] Table 1 Test results for a signal to be tested

[0037] As can be seen from Table 1, the energy proportion results obtained by detecting the three candidate frequencies respectively show that the energy proportion corresponding to the 4.3kHz frequency is the highest, about 0.21948, and it can be preliminarily determined that the frequency component exists in the signal to be tested. At the same time, for a signal to be tested with a length of about 3-4ms, the detection time of the frequency detection system and method of the present invention is only about 1ms, which can achieve efficient real-time detection and control.

[0038] Subsequently, in order to obtain the best decision threshold, 100 pieces of data collected on site were used for batch detection, and the frequency distribution histogram of the energy proportion of the candidate frequencies was statistically calculated, as shown in Figure 5 As shown; the frequency distribution histogram of the candidate frequency energy ratio is applied to the Otsu algorithm described in the present invention to calculate the classification threshold, and the optimal threshold is 0.16 as the optimal decision threshold. Another 30 data collected at the same scene are tested, and the test results are shown in Table 2 below.

[0039] Table 2 Test results of another 30 data from the same site

[0040] From the data in Table 2, it can be seen that with 0.16 as the optimal decision threshold, all the frequency information carried in the 30 data can be analyzed, and the analysis accuracy can reach 100% under the condition of limited data in this environment.

[0041] It can be understood that the above specific description of the present invention is only used to illustrate the present invention and is not limited to the technical solutions described in the embodiments of the present invention. Those skilled in the art should understand that the present invention can still be modified or replaced by equivalents to achieve the same technical effects; as long as the use requirements are met, they are within the protection scope of the present invention.

Claims

1. A frequency detection system for an airport navigation lighting control system, characterized in that: Includes the following modules; Bandpass filter module: used for filtering the input signal to be tested, including a high-pass filter and a low-pass filter connected in series, the cutoff frequency of the high-pass filter is set to filter out signal components below the frequency range to be tested, and the cutoff frequency of the low-pass filter is set to filter out signal components above the frequency range to be tested; Sampling rate conversion module: used to downsample the filtered signal by D times to generate a downsampled signal; Total energy estimation module: used to calculate the total energy of the signal based on the downsampled signal; Multiple frequency energy estimation modules: Each frequency energy estimation module uses the Goertzel algorithm to calculate the fundamental wave and second harmonic energy of the frequency to be measured, and uses the sum of the calculated fundamental wave and second harmonic energy as the total energy of the frequency to be measured; Energy proportion estimation module: used to calculate the energy proportion of each frequency to be measured according to the total signal energy obtained by the total energy estimation module and the total energy of each frequency to be measured obtained by the frequency energy estimation module; Energy proportion frequency distribution estimation module: Generates frequency distribution histogram of energy proportion based on historical data; Optimal detection threshold estimation module: applying Otsu algorithm to analyze the frequency distribution histogram to determine the optimal decision threshold; Detection module: used to compare the energy proportion of each frequency to be tested with the optimal decision threshold to determine whether these frequencies to be tested exist.

2. The frequency detection system of the airport navigation lighting control system according to claim 1, characterized in that: The frequency range to be measured is 4 kHz to 9 kHz, the cutoff frequency of the high-pass filter is set to 3 kHz, and the cutoff frequency of the low-pass filter is set to 10 kHz.

3. The frequency detection system of the airport navigation lighting control system according to claim 1, characterized in that: The difference equation of the high-pass filter is: （1）， The difference equation of the low-pass filter is: （2）； in, a is the filter coefficient of the high-pass filter, b is the filter coefficient of the low-pass filter, x 0( n ) is the input of the high-pass filter, that is, the signal to be tested that is input into the band-pass filter module. y 1( n ) is the output of the high-pass filter, x 1( n ) is the output of the low-pass filter, n =0, 1, …, N -1, N express x 0( n ), that is, x 0( n ) is N sampling points, the sampling rate f s .

4. A frequency detection system for an airport navigation lighting control system according to claim 1, wherein The characteristic is that the total energy estimation module is through the formula: （3）， Calculate the total energy of the signal; in the formula: D Indicates the downsampling multiple in the sampling rate conversion module. N / D for D times the length of the downsampled signal, x 2 ( n ) is the output signal of the sampling rate conversion module, the output signal x 2 ( n )= x 1( nD ), n =0, 1, …, N / D- 1.

5. The frequency detection system of the airport navigation lighting control system according to claim 1, characterized in that: In the frequency energy estimation module, the Goertzel algorithm is used to calculate the fundamental wave energy. e i，1 The calculation steps are as follows: ， （4）， （5）， （6）； in, q 1 ( n ) is the intermediate variable of the Goertzel algorithm; Calculate the second harmonic energy using the Goertzel algorithm e i，2 The calculation steps are as follows: （7）， （8）， （9）， （10）； in, fi, 1 means the i The fundamental frequency of the frequency to be measured; fi, 2 means the i The second harmonic frequency of the frequency to be measured, that is, twice the fundamental frequency; q 2 ( n ) is the intermediate variable of the Goertzel algorithm; the output of the frequency energy estimation module e i for: e i = e i，1＋ e i，2 （11）。 6. The frequency detection system of the airport navigation lighting control system according to claim 1, characterized in that: In the optimal detection threshold estimation module, the optimal decision threshold is determined by applying the Otsu algorithm to calculate the maximum value of the inter-class variance, which specifically includes: normalizing the histogram probability; calculating the cumulative probability and the cumulative mean; traversing all thresholds and selecting the value that maximizes the inter-class variance as the optimal decision threshold.

7. The frequency detection system of the airport navigation lighting control system according to claim 1, characterized in that: In the detection module, if the energy proportion of each frequency to be tested exceeds the optimal decision threshold, it is determined that these frequencies to be tested exist, and a lamp state control signal is output.

8. A frequency detection method for an airport navigation lighting control system, characterized in that: The frequency detection system of the airport navigation lighting control system according to any one of claims 1 to 7 is used for implementation, comprising the following steps: First, the input signal to be tested x 0( n ) Through the bandpass filter module, the signal is obtained after filtering out some high-frequency and low-frequency components x 1( n ), and then the signal is obtained through the sampling rate conversion module x 2 ( n ); Then, the signal x 2 ( n ) respectively through i A frequency energy estimation module and a total energy estimation module, i Represents the number of frequencies to be measured; the output of each frequency energy estimation module e i and the output of the total energy estimation module e total As input, enter i An energy proportion estimation module calculates the energy proportion corresponding to each frequency to be tested d i ; Finally, for each energy proportion corresponding to the frequency to be measured, the optimal decision threshold is obtained through the energy proportion frequency distribution estimation module and the optimal detection threshold estimation module. Th i , the energy proportion corresponding to each frequency to be tested is calculated through the detection module d i and the optimal decision threshold Th i The detection results are compared to determine whether a specific target frequency exists.

9. The frequency detection method of an airport navigation light control system according to claim 8, characterized in that: In the test results, if the energy proportion corresponding to each frequency to be tested is d i Exceeding the optimal decision threshold Th i , it is determined that these frequencies to be tested exist and the lamp status control signal is output.

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