A self-control method for the transmitting power of a monitoring interference system based on multi-parameter weighting

Abstract

The present invention discloses a method for automatic control of the transmitting power of a monitoring interference system based on multi-parameter weighting. First, the target signal of the monitoring unmanned aerial vehicle is acquired; the average signal amplitude, signal duty cycle, and signal bandwidth ratio are calculated respectively based on the target signal of the monitoring unmanned aerial vehicle, and the modulation type of the signal is discriminated; the average signal amplitude, signal duty cycle, signal bandwidth ratio, and signal modulation type are weighted respectively to obtain the corresponding weighted values; according to the weighted value of the average signal amplitude, the weighted value of the signal duty cycle, the weighted value of the signal bandwidth ratio, and the weighted value of the signal modulation type, a multi-parameter weighted value is obtained; the decibel value for controlling the transmitting power is calculated through the multi-parameter weighted value, and the obtained decibel value is converted into the control quantity of the gain control circuit of the interference system in the monitoring interference system to realize the automatic control of the transmitting power; the cost-effectiveness of the interference signal is significantly improved, the cost expenditure is reduced and the benefit is increased, and the pollution of the surrounding electromagnetic environment is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and particularly to a method for automatic control of the transmission power of a monitoring interference system based on multi-parameter weighting. Background Art

[0002] It is prohibited for unmanned aerial vehicles (UAVs) to fly in protected or restricted flight areas. If a UAV enters a restricted flight area, targeted control and blocking measures are taken. After detecting a UAV, in order to effectively control the UAV to terminate its intended flight, radio signal suppression means are considered to intercept it. When using a radio spectrum monitoring interference system to detect and counter UAVs flying illegally, the conventional method of emitting interference signals is to turn on the full-power transmission state of the system, that is, to interfere with the target at the maximum transmission power of the system, so that the UAV loses contact with the remote control end and cannot fly normally. This brings problems such as low interference cost-effectiveness and high risk of electromagnetic pollution. Some interference systems that adopt automatic power control technology also mostly control or adjust the power of the transmitted signal according to the guidance of one input parameter. Relatively speaking, the adaptability is not improved much. At the same time, the existing technology has disadvantages such as low interference cost-effectiveness, inability to reduce costs and improve efficiency, and uncontrollable pollution of the surrounding electromagnetic environment. Summary of the Invention

[0003] Object of the Invention: In order to overcome the deficiencies in the prior art, the present invention provides a method for automatic control of the transmission power of a monitoring interference system based on multi-parameter weighting, which can optimize the control technology of the transmission power, significantly improve the cost-effectiveness of the interference signal, reduce costs and improve efficiency, and effectively reduce the pollution of the surrounding electromagnetic environment.

[0004] Technical Solution: To achieve the above object, a method for automatic control of the transmission power of a monitoring interference system based on multi-parameter weighting of the present invention includes the following steps:

[0005] Step 1: Obtain the target signal of the monitored UAV.

[0006] Step 2: Calculate the signal average amplitude, signal duty cycle, and signal bandwidth ratio respectively based on the target signal of the monitored UAV, and determine the modulation type of the signal.

[0007] Step 3: Weight the signal average amplitude, signal duty cycle, signal bandwidth ratio, and signal modulation type respectively to obtain the corresponding weighted values.

[0008] Step 4: Obtain the multi-parameter weighted value according to the signal average amplitude weighted value, signal duty cycle weighted value, signal bandwidth ratio weighted value, and signal modulation type weighted value.

[0009] Step 5: Calculate the decibel value for transmit power control through multi-parameter weighted values, convert the obtained decibel value into the control quantity of the gain control circuit of the interference system in the monitoring interference system, and achieve automatic control of the transmit power.

[0010] Further, in the second step, for the calculation of the average signal amplitude, intercept the original signal numerical sequence S from the monitored target signal;

[0011] S = [x1, x2, x3......x n ......x N

[0012] In the formula, N is the number of elements in the sequence, and N≥4096;

[0013] Perform fast Fourier transform FFT on each element in the original signal numerical sequence to obtain the result sequence S FFT , and the calculation process is as follows:

[0014]

[0015] S FFT = [X1, X2, X3,......, X k ,......, X K

[0016] In the formula, k is the serial number of the k-th element in the result sequence, is the rotation factor, where j is the imaginary unit;

[0017] Obtain the amplitude of each complex element in the result sequence respectively to get the amplitude sequence A FFT ; Obtain the average amplitude Ab of all elements in the amplitude sequence, and add the average amplitude to the value of the channel automatic gain control of the current monitoring system to get the true average amplitude Aa of the target signal.

[0018] Further, in the second step, for the calculation of the signal duty cycle, intercept a time-domain sampling sequence that contains at least five complete signal cycles in the target signal, obtain the pulse width of each signal, and calculate the average pulse width τ of the time-domain sampling sequence; obtain the period of each signal, calculate the average period T of the time-domain sampling sequence, and divide the average pulse width τ by the average period T to get the signal duty cycle T P .

[0019] Further, in the second step, for the calculation of the signal bandwidth ratio, the amplitude sequence A FFT ​​Subtract the frequency point at which the rising edge of the intermediate frequency spectrum signal appears from the frequency point at which the falling edge of the spectrum signal appears, and take the absolute value to obtain the spectrum bandwidth Fs of the target signal; divide the spectrum bandwidth Fs of the interfered target signal by the spectrum bandwidth Fj of the interference signal to obtain the signal bandwidth ratio Fr.

[0020] Further, in step three, calculate the signal amplitude weighting value a A 、the signal duty cycle weighting value a T and the signal bandwidth ratio weighting value a F ;

[0021] a A = As / Aa

[0022]

[0023] a F = e -Fr / 2

[0024] Where As is the receiver sensitivity of the monitoring system and e is the natural number.

[0025] Further, in step four, the calculation process of the multi-parameter weighting value a is as follows:

[0026] a = a A * a T * a M * a F

[0027] Where a A is the signal amplitude weighting value, a T is the signal duty cycle weighting value, a F is the signal bandwidth ratio weighting value, and a M is the signal modulation type weighting value.

[0028] Further, the calculation process of the decibel value B of the transmit power control is as follows:

[0029] B = 10 * log 10 (a)

[0030] Where a is the multi-parameter weighting value.

[0031] Beneficial effects: For a method for automatic control of the transmission power of a monitoring and interference system based on multi-parameter weighting according to the present invention, first, the monitoring system in the interference system extracts multiple parameters after sampling the communication signal of an unknown black flying unmanned aerial vehicle, and then performs multi-parameter weighting. According to the weighted result, the transmission power of the monitoring and interference system is automatically controlled, improving the interference efficiency and resource utilization rate; optimizing the control technology of the transmission power significantly improves the cost-effectiveness ratio of the interference signal. The increase in the cost-effectiveness ratio reduces the cost expenditure and improves the efficiency, and effectively reduces the pollution of the surrounding electromagnetic environment. Description of the Drawings

[0032] Figure 1 It is a flowchart of a method for automatic control of the transmission power of a monitoring and interference system based on multi-parameter weighting. Detailed Embodiment

[0033] The present invention will be further described below with reference to the drawings.

[0034] As Figure 1 shown, a method for automatic control of the transmission power of a monitoring and interference system based on multi-parameter weighting includes the following steps:

[0035] Step 1: The monitoring system in the monitoring and interference system monitors the unmanned aerial vehicle to obtain the target signal of the monitored unmanned aerial vehicle;

[0036] Step 2: Calculate the signal average amplitude, signal duty cycle, and signal bandwidth ratio respectively based on the target signal, and determine the modulation type of the signal;

[0037] Step 3: Based on the signal average amplitude, signal duty cycle, signal bandwidth ratio, and signal modulation type, obtain the signal average amplitude weighting value, signal duty cycle weighting value, signal bandwidth ratio weighting value, and signal modulation type weighting value respectively;

[0038] Step 4: Obtain the multi-parameter weighting value through the signal average amplitude weighting value, signal duty cycle weighting value, signal bandwidth ratio weighting value, and signal modulation type weighting value;

[0039] Step 5: Calculate the decibel value for transmission power control through the multi-parameter weighting value, convert the obtained decibel value into the control quantity of the gain control circuit of the interference system in the monitoring and interference system, and the change in the control quantity of the gain control circuit of the interference system changes the magnitude of the transmission power, realizing the automatic control of the transmission power.

[0040] In the above step 2, there are many methods for calculating the signal average amplitude. The signal average amplitude is calculated by performing a fast Fourier transform (FFT) on the target signal; first, the original signal numerical sequence S with no less than 4096 points is intercepted from the monitored target signal, and the original signal numerical sequence S is a numerical sequence composed of no less than 4096 real numbers or complex numbers;

[0041] S[x1, x2, x3......x n ......x N

[0042] Where N is the number of elements in the sequence, and N ≥ 4096;

[0043] Perform a fast Fourier transform (FFT) on each element in the original signal value sequence to obtain the result sequence S FFT , and the result sequence is a complex number sequence. The calculation process is as follows:

[0044]

[0045] Where k is the sequence number of the k-th element in the result sequence, is the rotation factor;

[0046]

[0047] Where j is the imaginary unit;

[0048] S FFT = [X1, X2, X3,......, X k ,......, X K

[0049] Calculate the amplitude of each complex number element in the result sequence to obtain the amplitude sequence A FFT , and this sequence is a positive real number sequence; the amplitude calculation process of the complex number element X k is as follows:

[0050]

[0051] Where X k is any complex number element in the result sequence, is the real part of X k , is the imaginary part of X k ;

[0052] Calculate the average amplitude Ab of all elements in the calculated amplitude sequence, and add the average amplitude to the value AGC of the automatic gain control of the current monitoring system channel to obtain the true average amplitude Aa of the target signal; the AGC value is a real-time parameter of a radio frequency circuit, which is set by the radio frequency circuit itself and informed to this system by the communication circuit. The radio frequency circuit is not a part of this system. The calculation process is as follows:

[0053] A a = A b + AGC.

[0054] ​​In the second step, there are many methods to calculate the signal duty cycle. The signal duty cycle is calculated by calculating the ratio of the average pulse width of the signal to the average period of the signal. First, intercept a time-domain sampling sequence of the target signal that contains at least five complete signal cycles. By subtracting the time point when the falling edge of the signal appears from the time point when the rising edge of each signal appears and taking the absolute value, the pulse width of each signal is obtained, and the average pulse width τ of the time-domain sampling sequence is calculated. By subtracting the time point when the rising edge of the adjacent signal appears from the time point when the rising edge of each signal appears and taking the absolute value, the period of each signal is obtained, and the average period T of the time-domain sampling sequence is calculated. The average pulse width τ is divided by the average period T to obtain the signal duty cycle T P .

[0055] In the second step, the signal bandwidth ratio refers to the ratio of the spectral bandwidth of the interfered target signal to the spectral bandwidth of the interference signal. There are various methods to calculate the spectral bandwidth of the target signal. One of the methods is to calculate the effective width of the signal in the frequency domain through fast Fourier transform to calculate the signal bandwidth ratio. Since the amplitude sequence A FFT has been obtained, the frequency point when the rising edge of the spectral signal in the amplitude sequence A FFT appears is subtracted from the frequency point when the falling edge of the spectral signal appears, and the absolute value is taken to obtain the spectral bandwidth Fs of the target signal. The spectral bandwidth Fs of the interfered target signal is divided by the spectral bandwidth Fj of the interference signal to obtain the signal bandwidth ratio Fr;

[0056] F r = Fs / Fj.

[0057] In the second step, for the discrimination of the signal modulation type, the modulation type of the monitored target signal is discriminated. Common conventional modulation types include AM modulation, FM modulation, PM modulation, QAM modulation, etc. Spectrum analysis is to observe the characteristics of the signal in the frequency domain by performing spectrum analysis on the signal. Signals of different modulation types will have different characteristics in the spectrum, such as frequency distribution, bandwidth, etc. The process of using the spectrum analysis method to determine that the modulation type of the target signal is FM modulation is as follows. Since the obtained result sequence S FFT is a complex sequence; the phase Ang k of each element in the result sequence is obtained, and the frequency-domain phase sequence Ang composed of the phases of each obtained element is obtained;

[0058]

[0059] In the formula, atan is the arctangent trigonometric function, is the real part of X k , is the imaginary part of X k ;

[0060] Ang = [Ang1, Ang2, Ang3......Ang k ......Ang K ;

[0061] The phase difference DeltA1 is obtained by subtracting the first element from the second element in the frequency-domain phase sequence Ang, the phase difference DeltA2 is obtained by subtracting the second element from the third element, and the phase difference DeltA is obtained by successively subtracting the previous element from the next element k , until the phase difference DeltA is obtained by subtracting the penultimate element from the last element K-1 ; The phase difference sequence DeltA is obtained;

[0062] DeltA k = Ang k+1 - Ang k , 1 ≤ k < K

[0063] DeltA = [DeltA1, DeltA2, DeltA3,......, DeltA k ,......, DeltA K-1

[0064] The phase difference DeltF1 is obtained by subtracting the first element from the second element in the phase difference sequence DeltA, the phase difference DeltF2 is obtained by subtracting the second element from the third element, and the phase difference DeltF is obtained by successively subtracting the previous element from the next element k , until the phase difference DeltF is obtained by subtracting the penultimate element from the last element K-2 ; The frequency difference phase sequence DeltF is obtained;

[0065] DeltF k = DeltA k+1 - DeltA k , 1 ≤ k < K - 1

[0066] DeltF = [DeltF1, DeltF2, DeltF3,......, DeltF k ,......, DeltF K-2

[0067] The determination condition for determining that the target signal is an FM modulated signal is that the element values of the elements in the frequency difference phase sequence DeltF in the part where the signal appears are within an error less than or equal to 0.1 from a set threshold DeltF R , then it is determined that the target signal is FM modulated;

[0068] (DeltF k - DeltF R ​​) / DeltF R ≤0.1

[0069] In addition to using the spectrum analysis method to determine the modulation type of the signal, there are also the eye diagram analysis method, the symbol demodulation method, the autocorrelation function method, and the feature extraction and machine learning method. Eye diagram analysis: The eye diagram is a graphical representation method used to observe the quality of digital communication signals; signals of different modulation types will show different shapes on the eye diagram, and the modulation type of the signal can be preliminarily judged by observing the eye diagram. Symbol demodulation: Demodulate the signal and observe the waveform of the demodulated signal; signals of different modulation types will have different waveform characteristics after demodulation, and the modulation type can be judged based on these characteristics. Autocorrelation function: Calculate the autocorrelation function of the signal, and signals of different modulation types will have different performances on the autocorrelation function; the autocorrelation function can help distinguish the modulation type. Feature extraction and machine learning: Using machine learning algorithms, the features of the signal can be extracted and a model can be trained to identify signals of different modulation types; common machine learning algorithms include support vector machine (SVM), neural network, etc.

[0070] Weighted value a of signal modulation type M The determination of the weighted value a is achieved by forming a look-up table through experience or actual measurement. When actually used, the weighted values of five modulation types, namely AM modulation, FM modulation, QAM8 modulation, QAM16 modulation, and OFDM modulation, are obtained by looking up. The weighted value of AM modulation is 0.5, the weighted value of FM modulation is 0.7; the weighted value of QAM8 modulation is 0.9; the weighted value of QAM16 modulation is 1; the weighted value of OFDM modulation is 1.

[0071] In step three, calculate the weighted value α of the signal amplitude A The calculation formula is as follows:

[0072] a A = As / Aa

[0073] In the formula, As is the receiver sensitivity of the monitoring system, and Aa is the true average amplitude of the target signal;

[0074] Weighted value a of signal duty cycle T The calculation formula is as follows:

[0075]

[0076] In the formula, e is the natural number, and T P is the signal duty cycle;

[0077] And weighted value a of signal bandwidth ratio F The calculation formula is as follows:

[0078] a F = e -Fr / 2

[0079] In the formula, e is a natural number, and Fr is the signal bandwidth ratio;

[0080] In step 4, the multi-parameter weighting value a is obtained by multiplying the signal amplitude weighting value a A , the signal duty cycle weighting value a T , the signal bandwidth ratio weighting value a F and the signal modulation type weighting value a M ; the calculation process of the multi-parameter weighting value a is as follows:

[0081] a = a A * a T * a M * a F

[0082] In the formula, a A is the signal amplitude weighting value, a T is the signal duty cycle weighting value, a F is the signal bandwidth ratio weighting value, a M is the signal modulation type weighting value.

[0083] Take the logarithm of the multi-parameter weighting value a to the base 10 and then multiply by 10 to obtain the decibel value of the monitoring interference system's transmission power control; the calculation process of the decibel value B of the transmission power control is as follows:

[0084] B = 10 * log 10 (α)

[0085] In the formula, a is the multi-parameter weighting value.

[0086] Convert the decibel value B of the monitoring interference system's transmission power control into a control quantity on the interference system gain control circuit in the monitoring interference system, so as to realize the parameters extracted from the target signal of the currently monitored UAV, and then control the magnitude of the transmission power of the interference system to interfere with the UAV's signal, so that the UAV is disconnected from the remote control signal and the UAV cannot fly. According to the communication signal of the UAV monitored by the monitoring system, the interference system calculates the multi-parameter weighting value a corresponding to the target signal based on the monitored target signal, so as to realize the automatic control of the transmission power of the interference system, and there will be no situation where the transmission power is too large and affects the surrounding signals; and the transmission power is too small and the interference system cannot interfere with the UAV, resulting in the remote control end still being able to remotely control the UAV, and the effect of interfering with the UAV so that the UAV cannot fly cannot be achieved.

[0087] During actual use, extract the above parameters of the drone's signal in real time, calculate the weights corresponding to their respective parameters, and then obtain the real-time multi-parameter weighted value a through weighting, so as to realize the automatic control of the transmission power of the interference system; it can effectively improve the interference cost-effectiveness ratio of the interference system. When the target signal is more than 12 dB greater than the system sensitivity, the modulation method is ordinary AM, the signal duty cycle is 50%, and the signal spectrum ratio is 1:1, the transmission power that only needs to be 10 dB lower than the full-scale radiation can achieve the same interference effect; the pollution of the surrounding electromagnetic environment can be reduced to 10% of that at full-scale transmission.

[0088] Embodiment

[0089] Taking the signal of a certain unknown consumer drone as an example, to improve the interference cost-effectiveness ratio of the monitoring interference system and achieve the purpose of effective interference. Intercept the original signal sequence S of 8000 points for the target signal that has been monitored and identified, and then perform an 8000-point FFT on S to obtain the result sequence S FFT , and obtain the amplitude sequence A FFT , and then calculate the average value of all elements of this amplitude sequence to obtain the original average amplitude Ab of the signal. For convenience, it is uniformly expressed in decibels here, and Ab = 80 dBm is obtained; use the obtained original average amplitude Ab of the signal and add the value of the channel automatic gain control of the current monitoring system AGC = 17 dBm to obtain the true average amplitude Aa of the signal = Ab + AGC = 97 dBm;

[0090] Intercept a segment of the time-domain sampling sequence containing 5 complete signal cycles, collect and calculate to obtain the average pulse width τ of the signal = 1 ms; then calculate to obtain the average period T of the signal = 2 ms; divide τ by T to obtain the signal duty cycle TP = 1 ms / 2 ms = 0.5. Through the autocorrelation function method, the modulation type of this consumer drone is obtained as OFDM. At the frequency point where the rising edge of the A FFT spectrum signal appears, subtract the frequency point where the falling edge of the spectrum signal appears, and take the absolute value to obtain the spectrum bandwidth Fs of the target signal to be interfered = 10 MHz; the bandwidth Fj of the interference signal is manually or automatically set by the jammer. In this embodiment, Fj = 20 MHz, and the signal bandwidth ratio Fr = Fs / Fj = 0.5.

[0091] The determination process of the signal amplitude weighted value is as follows: the receiver sensitivity of the monitoring system is As = -100 dBm, then the signal amplitude weighted value a A = As / Aa = 97 dBm - 100 dBm = -3 dB = 0.5;

[0092] The calculation process of the signal duty cycle weighted value a T is as follows: first calculate 1 - TP, then take the exponential with the natural number e as the base, and finally take the reciprocal, that is, the signal duty cycle weighted value

[0093] Signal modulation type weighting value a M Obtained by means of lookup, so a M = 1;

[0094] Signal bandwidth ratio weighting value a F The calculation process is as follows: First, find Fr / 2, then take the exponent with the natural number e as the base, and finally take the reciprocal, that is, the signal bandwidth ratio weighting value a F = e -Fr / 2 ≈0.78.

[0095] The value of the multi-parameter weighting value a is obtained by multiplying the weighting values corresponding to the above several parameters, that is, a = a A *a T *a M *a F ≈0.234.

[0096] According to the multi-parameter weighting value a, calculate the decibel value B of the transmission power control of the interference system in the monitoring interference system, and get 10*log 10 (a) is approximately equal to 6 dB; the decibel value of 6 dB is converted into the control amount on the interference system gain control circuit in the monitoring interference system to realize the automatic control of the transmission power of the interference system in the monitoring interference system.

[0097] The above is only a description of the preferred embodiment of the present invention. Those of ordinary skill in the art can make several modifications and optimizations based on the above disclosure without departing from the basic principle content. These improvements and optimizations should be regarded as the protection scope understood by the present invention.

Claims

1. A method for automatically controlling the transmitting power of a monitoring interference system based on multi-parameter weighting, characterized in that: It includes the following steps: Step 1: Obtain the target signal of the monitoring UAV; Step 2: Calculate the signal average amplitude, signal duty cycle and signal bandwidth ratio respectively based on the target signal of the monitoring UAV, and determine the modulation type of the signal; Step 3: Weight the signal average amplitude, signal duty cycle, signal bandwidth ratio and signal modulation type respectively to obtain the corresponding weighted values; The determination of the weighted value of the signal modulation type is formed by a look-up table through experience or actual measurement, and is obtained by looking up when in use; Step 4: Obtain the multi-parameter weighted value according to the weighted value of the signal average amplitude, the weighted value of the signal duty cycle, the weighted value of the signal bandwidth ratio and the weighted value of the signal modulation type; Step 5: Calculate the decibel value of the transmit power control through the multi-parameter weighted value, and convert the obtained decibel value into the control quantity of the gain control circuit of the interference system in the monitoring interference system to realize the automatic control of the transmit power.

2. The self - control method for the transmitting power of a monitoring interference system based on multi - parameter weighting according to claim 1, wherein: In the said Step 2, calculating the signal average amplitude includes: intercepting the original signal numerical sequence S from the monitored target signal; S = [x1, x2, x3......x n ......x N} where N is the number of elements in the sequence, and N≥4096; Perform a fast Fourier transform (FFT) on each element of the original signal numerical sequence to obtain the result sequence S FFT , and the calculation process is as follows: S FFT = [X1, X2, X3,......, X k ,......, X K ​ where k is the sequence number of the k-th element of the result sequence, is a rotation factor, where j is the imaginary unit; For each complex element in the result sequence, calculate its amplitude to obtain the amplitude sequence A FFT ; Calculate the average amplitude Ab of all elements in the amplitude sequence, and add the average amplitude to the value of the automatic gain control of the current monitoring system channel to obtain the true average amplitude Aa of the target signal.

3. The self - control method for the transmission power of a monitoring interference system based on multi - parameter weighting according to claim 1, characterized in that: In the second step, calculating the signal duty cycle includes: intercepting a time-domain sampling sequence of a target signal that contains at least five complete signal cycles, obtaining the pulse width of each signal, and calculating the average pulse width τ of the time-domain sampling sequence; obtaining the period of each signal, calculating the average period T of the time-domain sampling sequence, and dividing the average pulse width τ by the average period T to obtain the signal duty cycle T P .

4. A method for automatic control of the transmission power of a monitoring interference system based on multi-parameter weighting according to claim 2, characterized in that: In the second step, calculating the signal bandwidth ratio includes: the amplitude sequence A FFT subtracts the frequency point at which the rising edge of the spectrum signal appears from the frequency point at which the falling edge of the spectrum signal appears in FFT , and takes the absolute value to obtain the spectrum bandwidth Fs of the target signal; the spectrum bandwidth Fs of the target signal being interfered is divided by the spectrum bandwidth Fj of the interference signal to obtain the signal bandwidth ratio Fr.

5. A self - control method for the transmitting power of a monitoring interference system based on multi - parameter weighting according to claim 1, characterized in that: In the third step, calculate the signal amplitude weighting value a A , the signal duty cycle weighting value a T and the signal bandwidth ratio weighting value a F ; a A = As / Aa a F = e -Fr / 2 where As is the receiver sensitivity of the monitoring system, and e is the natural constant.

6. A method for automatic control of the transmission power of a monitoring interference system based on multi-parameter weighting according to claim 1, characterized in that: In the said Step 4, the calculation process of the multi-parameter weighted value a is as follows: a = a A *a T *a M *a F Wherein, a A is the signal amplitude weighting value, a T is the signal duty cycle weighting value, a F is the signal bandwidth ratio weighting value, a M is the signal modulation type weighting value.

7. A method for automatic control of the transmission power of a monitoring interference system based on multi-parameter weighting according to claim 1, characterized in that: The calculation process of the decibel value B of the transmit power control is as follows: B = 10 * log 10 (a) where a is the multi-parameter weighted value.

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