CN115996103B - Adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication - Google Patents
Adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication Download PDFInfo
- Publication number
- CN115996103B CN115996103B CN202310029591.4A CN202310029591A CN115996103B CN 115996103 B CN115996103 B CN 115996103B CN 202310029591 A CN202310029591 A CN 202310029591A CN 115996103 B CN115996103 B CN 115996103B
- Authority
- CN
- China
- Prior art keywords
- interference
- signal
- unmanned aerial
- aerial vehicle
- optimal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004891 communication Methods 0.000 title claims abstract description 94
- 238000000034 method Methods 0.000 title claims abstract description 37
- 230000003044 adaptive effect Effects 0.000 title claims description 20
- 238000001514 detection method Methods 0.000 claims abstract description 20
- 238000004364 calculation method Methods 0.000 claims abstract description 17
- 230000002452 interceptive effect Effects 0.000 claims description 15
- 230000000694 effects Effects 0.000 claims description 14
- 230000003595 spectral effect Effects 0.000 claims description 14
- 230000005540 biological transmission Effects 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000004927 fusion Effects 0.000 claims description 4
- 238000007499 fusion processing Methods 0.000 claims description 3
- 238000004148 unit process Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 16
- 238000004088 simulation Methods 0.000 description 10
- 102100026758 Serine/threonine-protein kinase 16 Human genes 0.000 description 7
- 101710184778 Serine/threonine-protein kinase 16 Proteins 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 230000008569 process Effects 0.000 description 6
- 230000000903 blocking effect Effects 0.000 description 5
- 239000007787 solid Substances 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 108091081062 Repeated sequence (DNA) Proteins 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Mobile Radio Communication Systems (AREA)
Abstract
The invention provides a self-adaptive radio frequency interference system and a method for unmanned aerial vehicle frequency hopping communication, wherein the self-adaptive radio frequency interference system comprises the following steps: the radio frequency signal detection unit converts the received radio frequency signals of the uplink and downlink communication links of the unmanned aerial vehicle into digital signals and sends the digital signals to the digital signal processing unit; the digital signal processing unit processes and analyzes the received digital signal to obtain signal characteristic parameters and sends the signal characteristic parameters to the upper computer; the radar detects the position and distance information of the unmanned aerial vehicle and sends the position and distance information to the upper computer; the upper computer performs matching calculation to obtain the optimal narrow-band noise interference factor and the optimal signal-to-interference ratio, and sends the optimal narrow-band noise interference factor and the optimal signal-to-interference ratio to the FPGA interference digital signal source and the power amplifier; the FPGA interference digital signal source generates a narrow-band noise radio-frequency interference signal meeting the optimal frequency bandwidth and then sends the signal to the power amplifier; and the power amplifier amplifies the interference signal to a power multiple meeting the requirement of the optimal signal-to-interference ratio and then transmits the interference signal to the unmanned aerial vehicle to realize optimal interference.
Description
Technical Field
The invention relates to the technical field of communication interference, in particular to a self-adaptive radio frequency interference system, a method, electronic equipment and a storage medium for unmanned aerial vehicle frequency hopping communication.
Background
With the explosive growth of the global civil unmanned aerial vehicle industry, the 'low-speed' unmanned aerial vehicle is widely applied to various fields, and meanwhile, the 'black flight' of the unmanned aerial vehicle is increasingly threatening the public security of society, so that effective striking is required to be carried out on the 'black flight' unmanned aerial vehicle.
At present, the following three countering interference patterns are mainly adopted for unmanned aerial vehicle frequency hopping communication:
1. blocking interference: the interference power of the interference machine is distributed in all or most of the frequency range of the communication bandwidth of the unmanned aerial vehicle, the interference party does not need to acquire the hopping rule of the carrier frequency of the frequency hopping communication system, the characteristic parameters of the interference signal do not need to be similar to the characteristics of the frequency hopping communication signal, and the information transmission of the frequency hopping communication system can be effectively destroyed as long as the interference power is enough. The method has the advantages of less priori knowledge, simple realization and low cost, but has larger interference power, has poorer interference effect on the frequency hopping communication system with wider channel interval and wider frequency hopping bandwidth, and is easy to cause larger interference on other communication systems in the same frequency band.
2. Single or multiple frequency continuous wave interference: when the interference party obtains the frequency point distribution of the unmanned aerial vehicle frequency hopping system, but does not know the change rule of the frequency hopping frequency, single-frequency or multi-frequency continuous wave interference is generally used, and the interference mode is an interference mode which concentrates interference signals on part of specific frequencies of the frequency hopping channel. The method can accurately interfere the frequency hopping communication frequency band of the unmanned aerial vehicle, but for communication signals with a large number of frequency hopping points, if the number of frequency hopping points of the continuous wave interference signals is less than 1/3 of the number of frequency hopping points of the unmanned aerial vehicle, effective interference effect is difficult to achieve, and when a communication party changes the frequency hopping frequency, the interference effect is also reduced.
3. Tracking interference: on the basis of fast detection, interception and analysis of the frequency hopping communication signals of the unmanned aerial vehicle, the interference power of the jammer is guided to aim at the current communication channel of the frequency hopping system and narrow-band noise interference is implemented in the residence time of one frequency hopping frequency point. Tracking interference is generally considered one of the most effective interference means for frequency hopping communications. However, the existing unmanned aerial vehicle generally adopts a rapid frequency hopping communication system, the frequency hopping repeated sequence is long, the change rule of the frequency hopping pattern is difficult to analyze, the residence time of each frequency hopping is extremely short, the time proportion of effective interference implementation of the interference machine is small in the period of time, and the current hardware and software level is difficult to achieve the completion of tracking interference on the frequency hopping signal in such a short time.
The existing interference technology mainly adopts a noise interference mode with fixed bandwidth and fixed power to suppress interference with the unmanned aerial vehicle communication link, the interference efficiency is low, and precious power resources are wasted due to too large power.
The existing countermeasures for unmanned aerial vehicle frequency hopping communication have advantages and disadvantages, wherein the implementation mode of the blocking interference pattern is simpler and the interference effect is better, but the existing blocking interference pattern only carries out interference according to the fixed frequency bandwidth and the fixed interference power. If the bandwidth of the interference is wide, the power spectrum density distributed in the interference signal band will be reduced, and the interference effect will be reduced or will be ineffective. This has a problem of how to allocate between the interference power and the interference bandwidth to optimize the interference performance.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a self-adaptive radio frequency interference system and a self-adaptive radio frequency interference method for unmanned aerial vehicle frequency hopping communication.
In order to achieve the above object, the present invention provides an adaptive radio frequency interference system for frequency hopping communication of an unmanned aerial vehicle, comprising,
the system comprises a radio frequency signal detection unit, a digital signal processing unit and a control unit, wherein the radio frequency signal detection unit is used for converting received radio frequency signals of an uplink communication link and a downlink communication link of the unmanned aerial vehicle into digital signals and sending the generated digital signals to the digital signal processing unit;
the digital signal processing unit is used for carrying out signal processing and analysis on the received digital signals of the uplink and downlink communication links of the unmanned aerial vehicle to obtain signal characteristic parameters of the uplink and downlink communication links of the unmanned aerial vehicle, and sending the processed signal characteristic parameters of the uplink and downlink communication links of the unmanned aerial vehicle to the upper computer;
the upper computer is used for matching and calculating to obtain the average power of the uplink reaching the receiving end of the unmanned aerial vehicle, the optimal narrow-band noise interference factor and the optimal signal-to-interference ratio, and sending the calculation result to the FPGA interference digital signal source and the power amplifier to generate a required digital interference signal;
the FPGA interference digital signal source is used for generating a narrow-band noise radio frequency interference signal meeting the optimal frequency bandwidth and then sending the signal to the power amplifier;
the power amplifier is used for amplifying the narrowband noise radio frequency interference signal with the optimal frequency bandwidth to a power multiple meeting the requirement of the optimal signal-to-interference ratio and then sending the power multiple to the interference transmitting antenna;
the interference transmitting antenna is used for transmitting a narrowband noise radio frequency interference signal with the optimal frequency bandwidth meeting the power requirement to the unmanned aerial vehicle, so as to realize optimal interference.
Further, the unmanned aerial vehicle intelligent control system also comprises a radar which is used for detecting the azimuth, the pitching information and the distance of the unmanned aerial vehicle in real time and sending the information to the upper computer.
Further, the upper computer includes a fusion unit, configured to perform data fusion processing on the received signal characteristic parameter and the unmanned aerial vehicle position and distance information, so as to obtain average power Pr of the uplink to the unmanned aerial vehicle receiving end s 。
Further, the upper computer further comprises a calculation unit, which is used for calculating the optimal narrowband noise interference factor and the signal-to-interference ratio of the received signal characteristic parameters.
Further, the calculation unit sets the narrowband noise interference power of the unmanned aerial vehicle receiving end as J according to the received unmanned aerial vehicle frequency hopping bandwidth W, and the interference bandwidth is W J Defining the interference factor ρ as the ratio of the interference bandwidth to the frequency hopping bandwidth, i.e
Wherein,,when->When the noise is the full-band broadband noise interference;
obtaining equivalent single-side power spectral density of narrow-band interference noise signalThe method comprises the following steps:
wherein,,a power spectral density expressed as wideband interference noise;
the following relationship is obtained when the probability of the communication signal being within the interference band is ρ, the power spectral density of the noise is expressed asThe probability when the communication signal is outside the interference band is 1-p, the power density of the noise is +.>；
Bit error rate in case of narrowband noise interference of communication systemThe method comprises the following steps:
wherein,,bit error rate for communication systems of different modulation types, +.>For bit signal energy, +.>Is the white noise power spectral density, < >>Single-side power spectral density of the narrow-band interference signal;
when (when)When it is, can ignore +.>The following steps are:
。
further, the calculating unit is further configured to calculate an optimal narrowband noise interference factor and an optimal bit signal-to-interference ratio according to a bit error rate calculation formula of the modulation mode of the unmanned aerial vehicle.
Further, the calculating unit is configured to calculate an average power reaching the receiving end of the unmanned aerial vehicle according to the uplinkDefine the received signal power +.>The magnitude ratio to the noise interference power J is the signal-to-interference ratio +.>：
Wherein,,for the frequency hopping anti-interference processing gain, the detected unmanned aerial vehicle frequency hopping communication signal bandwidth W and symbol rate +.>Obtaining a ratio;
obtaining the optimal noise interference power of the unmanned aerial vehicle receiving terminal：
According to the formula of electromagnetic wave propagation in free space, calculating to obtain optimum interference transmitting powerIs that
Wherein the method comprises the steps ofFor optimal noise interference power, D is the distance of the interference system to the unmanned aerial vehicle, +.>For interfering signal wavelength, < >>For interfering with the transmit antenna gain +.>And receiving antenna gain for the unmanned aerial vehicle.
Further, the power amplifier is used for transmitting power according to the optimal interferenceDetermining the optimal magnification +.>Amplifying the interference signal +.>And the multiplied signals are sent to the interference transmitting antenna.
In order to achieve the above purpose, the present invention also provides an adaptive radio frequency interference method for unmanned aerial vehicle frequency hopping communication, comprising the following steps:
receiving radio frequency signals of an uplink communication link and a downlink communication link of the unmanned aerial vehicle, and converting the radio frequency signals into digital signals;
performing digital signal processing and analysis on the generated digital signals to obtain signal characteristic parameters of uplink and downlink communication links of the unmanned aerial vehicle;
according to the signal characteristic parameters and the radar detection, obtaining the position and distance information of the unmanned aerial vehicle, and calculating to obtain the average power of the uplink reaching the receiving end of the unmanned aerial vehicle, the optimal narrow-band noise interference factor and the optimal signal-to-interference ratio;
generating a narrow-band noise interference signal meeting the optimal frequency bandwidth according to the optimal narrow-band noise interference factor;
and amplifying the interference signal to the power multiple meeting the requirement of the optimal signal-to-interference ratio according to the optimal signal-to-interference ratio, and then sending the interference signal to the unmanned aerial vehicle to realize optimal interference.
In order to achieve the above object, the present invention further provides an electronic device, including a memory and a processor, where the memory stores a program running on the processor, and the processor executes the steps of the adaptive radio frequency interference method for frequency hopping communication of an unmanned aerial vehicle when running the program.
In order to achieve the above objective, the present invention further provides a computer readable storage medium having stored thereon computer instructions for executing the steps of the adaptive radio frequency interference method for unmanned aerial vehicle frequency hopping communication.
The self-adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication have the following beneficial effects:
the uplink and downlink communication link signals of the unmanned aerial vehicle are received in real time, the signal communication characteristic parameters are analyzed, and then specific interference signals are generated and sent, so that the interference effect is optimal, and the optimal interference effect can be achieved with the minimum interference power.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, and do not limit the invention. In the drawings:
fig. 1 is a schematic diagram of an adaptive radio frequency interference system for unmanned aerial vehicle frequency hopping communications according to the present invention;
FIG. 2 is a schematic diagram of a solid geometry relationship between a drone, a ground station, and an interfering system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of simulation of the relationship between bit error rate and interference factor ρ of a BFSK system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a derivative function of the MFSK system with the bit error rate biased against the interference factor ρ according to an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a simulation of the relationship between the maximum bit error rate and the optimal signal to interference ratio of an M-FSK system according to an embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating the simulation of the relationship between the bit error rate and the interference factor ρ of the MPSK system according to an embodiment of the present invention;
fig. 7 is a MPSK system according to an embodiment of the inventionDerivative function curve schematic diagram;
FIG. 8 is a schematic diagram illustrating a simulation of the relationship between the maximum bit error rate and the optimal signal to interference ratio of the MPSK system according to an embodiment of the invention;
FIG. 9 is a schematic diagram illustrating the simulation of the relationship between bit error rate and interference factor ρ of a 4QAM system according to an embodiment of the present invention;
FIG. 10 is a MQAM system according to an embodiment of the inventionDerivative function curve schematic diagram;
fig. 11 is a schematic diagram of a simulation of the relationship between the maximum bit error rate and the optimal signal to interference ratio of the MQAM system according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1
Fig. 1 is a schematic diagram of an adaptive radio frequency interference system for frequency hopping communication of an unmanned aerial vehicle according to the present invention, as shown in fig. 1, the adaptive radio frequency interference system for frequency hopping communication of an unmanned aerial vehicle of the present invention includes a radio frequency signal detecting unit 10, a digital signal processing unit 20, an upper computer 30, an FPGA interference digital signal source 40, a power amplifier 50, an interference transmitting antenna 60, and a radar 70, wherein,
the radio frequency signal detecting unit 10 is configured to convert, in real time, the received radio frequency signals of the uplink and downlink communication links of the unmanned aerial vehicle into digital signals, and send the generated digital signals to the real-time digital signal processing unit 20.
Specifically, a radar 70 is also included for being responsible for detecting in real time the azimuth, pitch information and distance of the drone.
Specifically, the wireless radio frequency signal detection device further comprises a detection receiving antenna, wherein the detection receiving antenna is used for being responsible for detecting and receiving wireless radio frequency signals of the unmanned aerial vehicle in the environment in real time, and when the unmanned aerial vehicle appears, the wireless radio frequency signals of an uplink communication link and a downlink communication link of the unmanned aerial vehicle can be received and sent to the radio frequency signal detection unit 10, and the wireless radio frequency signals are converted into digital signals through the radio frequency signal detection unit 10 and then sent to the digital signal processing unit.
The digital signal processing unit 20 is configured to process and analyze digital signals of the uplink and downlink communication links of the received unmanned aerial vehicle, obtain real-time signal parameters of the uplink and downlink communication links of the unmanned aerial vehicle, and send the processed characteristic parameters of the uplink and downlink communication signals of the unmanned aerial vehicle to the upper computer 30.
Specifically, the real-time signal parameters include characteristic parameters such as a signal modulation mode, a frequency hopping center frequency, a frequency hopping rate, a bandwidth, a symbol transmission rate, a signal average power, an azimuth angle and the like.
Specifically, the digital signal processing unit 20 sends the generated uplink and downlink signal characteristic parameters of the unmanned aerial vehicle and the unmanned aerial vehicle position and distance information detected by the radar 70 to the upper computer 30.
The upper computer 30 is configured to calculate the average power of the uplink to the receiving end of the unmanned aerial vehicle, the optimal narrowband noise interference factor, and the optimal signal-to-interference ratio. And sending the calculation result to the FPGA interference digital signal source 40 and the power amplifier 50 to generate a required digital interference signal.
Specifically, the upper computer 30 includes a fusion unit and a calculation unit, where the fusion unit is configured to perform data fusion processing on the received signal characteristic parameter and the position and distance information sent by the radar 70, so as to obtain average power of the uplink to reach the receiving end of the unmanned aerial vehicle。
In this embodiment, the average power of the signal detected by the rf signal detecting unit 10 to reach the interference system in the uplink of the frequency hopping communication of the unmanned aerial vehicle isThe information transmission rate is +.>The uplink frequency hopping center frequency F of the unmanned aerial vehicle, and the bandwidth of the frequency hopping signal is +.>The azimuth angle of the ground station from the interference system is beta; the rf signal detecting unit 10 detects that the average power of the signal reaching the interference system from the downlink of the frequency hopping communication of the unmanned aerial vehicle is +.>The information transmission rate is +.>Unmanned aerial vehicle downlink frequency hopping center frequency +.>The bandwidth of the frequency hopping signal is +.>The azimuth angle of the unmanned aerial vehicle from the interference system is alpha; because the data rate of the uplink is smaller, the data rate of the downlink is larger, i.e. the frequency hopping signal bandwidth of the uplink +.>And signal transmission rate->Are each smaller than the bandwidth of the down-link frequency hopping signal +.>And symbol transmission rate->There is->，<。
Reverse thrust is carried out according to an electromagnetic wave free space propagation formula to obtain the downlink transmitting power of the unmanned aerial vehicle，
Equation 1
In the formula 1 of the present invention,transmitting power (dBm) for the unmanned aerial vehicle;Transmit antenna gain (typically 3 dBi) for unmanned aerial vehicle, < >>Gain (in dBi) for the radio frequency detection device antenna;Receiving signal power (in dBm) of a downlink of the unmanned aerial vehicle for the radio frequency detection device;For unmanned aerial vehicle downlink frequency hopping centre frequency (unit is MHz), +.>Is the straight line distance (in km) of the drone to the interfering system.
In this embodiment, the downlink and uplink transmit powers of the civil unmanned aerial vehicle represented by Dajiang are the same, so we can obtain the uplink transmit power of the ground station，。
According to the electromagnetic wave free space propagation formula, the distance between the ground station and the interference system is obtained by back-pushing：
Equation 2
From equation 2:
equation 3
Wherein,,uplink transmit power (in dBm) for a ground station; f is the uplink frequency hopping center frequency (in MHz);Transmit antenna gain (typically 3 dBi) for ground stations;To detect the gain (in db) of the receiving antenna;Signal average power (in dBm) to reach the interfering system for the unmanned aerial vehicle uplink;Is the distance (in km) of the ground station from the interfering system.
Preferably, the distance between the unmanned aerial vehicle and the interference system detected by the radar 70 isPitch angle is +.>The height is h.
Preferably, there is a solid geometry relationship between the drone, the ground station and the interfering system as shown in fig. 2. Recording projection of unmanned aerial vehicle on ground as pointThe distance connecting line of the projection of the unmanned plane on the ground and the interference system is recorded as +.>. Taking an interference system as an origin, and detecting according to the radio frequency detection equipment to obtain an azimuth angle beta of the ground station; the azimuth angle alpha and the pitch angle of the unmanned aerial vehicle are detected according to the radar 70>Height->=h, distance os= =>。
The distance connection line of the projection of the unmanned aerial vehicle on the ground and the interference system can be obtained according to the solid geometry relation shown in fig. 2:。
an angle formed between the optical fiber and the OD->The method comprises the following steps:。
Based on the determined distance between the interference system and the ground stationTherefore there is->Thus, +.>The distance of (2) is:
equation 4
Further find the distance between ground station and unmanned aerial vehicle：
Equation 5
According to the electromagnetic wave free space propagation formula, the average power of the uplink to the receiving end of the unmanned aerial vehicle can be calculated(in dBm):
equation 6
Equation 7
Wherein,,uplink transmit power (in decibels dBm) for a ground station; f is the uplink frequency hopping center frequency (in MHz);Receiving antenna gain (generally 3 dBi) for the unmanned aerial vehicle;Is the distance (in km) between the ground station and the drone.
Specifically, the calculating unit is used for calculating the value of the optimal narrowband noise interference factor and the signal-to-interference ratio of the received signal characteristic parameter.
In the case of narrowband noise interference, it can be classified into two cases where the signal is within the bandwidth of the narrowband noise interference and the signal is outside the narrowband noise interference. The detection result shows that the frequency hopping bandwidth of the unmanned aerial vehicle is W, the narrow-band noise interference power of the unmanned aerial vehicle receiving end is J, and the interference bandwidth is W J The interference factor ρ can be defined as the ratio of the interference bandwidth to the frequency hopping bandwidth, i.e
When->And the full-band broadband noise interference is adopted.
We then obtain the equivalent single-sided power spectral density of the narrowband interference noise signalThe method comprises the following steps:
in the method, in the process of the invention,expressed as the power spectral density of the wideband interference noise.
The probability of the communication signal being within the interference band is ρ, and the power spectral density of the noise can be expressed asThe probability when the communication signal is outside the interference band is 1-p, the power density of the noise is +.>。
Bit error rate in case of narrowband noise interference of communication systemCan be expressed as:
in the method, in the process of the invention,bit error rate for communication systems of different modulation types, +.>For bit signal energy, +.>Is the white noise power spectral density, < >>Is the single-side power spectrum density of the narrow-band interference signal.
In general terms, the process is carried out,therefore, can ignore +.>The number of the steps is, if any,
equation 8
The bit error rate calculation formulas of various common unmanned aerial vehicle modulation modes are shown in the following table 1:
table 1 common unmanned aerial vehicle modulation bit error rate calculation formula
In this embodiment, substituting the bit error rate formula of each modulation scheme in table 1 into formula 8 can draw the system bit error rate of different modulation schemes under the condition of narrowband noise interferenceGraphs of interference factor p as a function of interference factor p are shown in fig. 3, 6, and 9.
As shown in fig. 3, 6 and 9, when the interference power is limited, there will always beSo that the bit error rate is +.>Maximum is reached, i.e. the best interference effect is produced. When signal to interference ratio->Timing, add->The expression of (c) can be obtained by biasing ρ by the above formula and the derivative is equal to zero.
For M-FSK systems, there are
The p is subjected to deflection derivation, so that the p is obtained,
the above may be further abbreviated as,
equation 9
In the method, in the process of the invention,
the derivative image can be plotted from equation 9 to yield a derivative graph of the MFSK system as shown in fig. 4.
By observingDerivative function images, which can be obtained as +.>The value increases continuously, the derivative value changes from positive to negative, and there is +.>。
It can be concluded that for M-FSK systems when the interference power is limitedThere will always be +.>Let->So that->Bit error Rate at this time->Maximum is reached, i.e. the best interference effect is produced.
Order theFrom equation 9
The above can be further abbreviated as:
equation 10
Due toWe can get the optimal interference factor +.>Sum signal to interference ratio->Is represented by the formula (i),
for MFSK systems, the k value can be solved from equation 10, as shown in table 2.
TABLE 2 k values for optimal interference effects for MFSK systems
Will be
The maximum bit error rate which can be achieved by the system under the condition of limited interference power is obtained by being brought into a bit error rate formula:
conversely, the present embodiment can give the lowest bit error rate acceptable by a communication system to obtain the optimal signal-to-interference ratio required at that timeAnd optimal interference factor->。
The best narrowband noise interference pattern parameter calculations for several commonly used MFSK are shown in table 3:
table 3 MFSK system optimum narrowband noise interference pattern parameters
As shown in FIG. 5, a simulation diagram of the relationship between the maximum bit error rate and the optimal signal-to-interference ratio of the MFSK system is shown.
Similarly, the present embodiment can analyze the BPSK/QPSK/O-QPSK/system, the effect of narrowband interference on the system bit error rate can be expressed by the following formula,
deviation of ρ to obtain
The above can be further simplified to a further,
the derivative image can be drawn from the above equation to yield the MPSK system derivative graph as shown in FIG. 7.
By observing the derivativeCan be obtained as a function of +.>The value increases continuously, the derivative value changes from positive to negative, and there is +.>。
It can be concluded that for M-FSK systems when the interference power is limitedThere will always be +.>Let->So that->Bit error Rate at this time->Maximum is reached, i.e. the best interference effect is produced.
Order theObtain->
The solution is carried out,
due to 0<ρ is less than or equal to 1 we can obtain the optimal interference factorSum signal to interference ratio->The expression of (2) is:
the maximum bit error rate which can be achieved by the system under the condition of limited interference power is obtained by being brought into a bit error rate formula:
conversely, the present embodiment can give the lowest bit error rate acceptable by a communication system to obtain the optimal signal-to-interference ratio required at that timeAnd optimal interference factor->。
The best narrowband noise interference pattern parameter calculations for several MPSK's in general are shown in table 4.
Table 4 MPSK system optimum narrowband noise interference pattern parameters
As shown in FIG. 8, a simulation diagram of the relationship between the maximum bit error rate and the optimal signal to interference ratio of the MPSK system is shown.
Similarly, an M-QAM system can be analyzed, the impact of narrowband interference on the bit error rate of the M-QAM system can be expressed by the following equation,
fig. 9 is a simulation diagram showing the relationship between the bit error rate and the interference factor ρ of the 4QAM system.
Deviation of ρ is conducted and letObtaining
As shown in fig. 10, is an MQAM systemDerivative function graph.
Will be
Substitution into the above equation yields the k value as shown in table 5.
TABLE 5 k-value for achieving optimal interference effects for MQAM systems
Thus, the optimal interference factorIt can be obtained by the following formula,
the maximum bit error rate which can be achieved by the system under the condition of limited interference power is obtained by being brought into a bit error rate formula:
the optimal signal-to-interference ratio can be found by the above equation given the lowest bit error rate acceptable to a communication systemAnd optimal interference factor->。
The best narrowband interference pattern parameter calculations for several MQAM systems in common use are shown in table 6.
Table 6 MQAM system optimal narrowband noise interference pattern parameters
As shown in FIG. 11, a simulation diagram of the relationship between the maximum bit error rate and the optimal signal-to-interference ratio of the MQAM system is shown.
Through the analysis, the upper computer 30 can calculate the optimal narrow-band noise interference factor by giving the lowest bit error rate Pb of the communication system through the obtained unmanned aerial vehicle frequency hopping communication characteristic parameters such as the signal modulation mode, the signal bandwidth and the likeAnd optimal bit signal to interference ratio->。
The upper computer 30 calculates the optimum bandwidth of the narrow-band noise interference signalTo the FPGA interfering digital signal source 40./>
In this embodiment, the average power of the uplink signal reaching the receiving end of the unmanned aerial vehicle is definedAnd noiseThe interference power J has a size ratio of signal to interference ratio +.>：
In the method, in the process of the invention,for the frequency hopping anti-interference processing gain, the bandwidth W and the symbol rate of the frequency hopping communication signal of the unmanned aerial vehicle can be obtained by radio frequency detection>And (5) obtaining a ratio.
Obtaining the optimal noise interference power of the unmanned aerial vehicle receiving terminal：
According to the formula of electromagnetic wave propagation in free space, the optimal interference transmitting power can be calculatedIs that
In the middle ofIs the optimal noise interference power; d is the distance of the interfering system from the drone, provided by radar 70;For interfering signal wavelength, < >>For interfering with the transmit antenna gain +.>The antenna gain (typically 3 dB) is received for the drone.
According to the optimal interference transmission powerDetermining the optimal magnification +.>。
In this embodiment, the upper computer 30 sends the calculation result to the FPGA interference digital signal source 40 and the power amplifier 50.
The FPGA interference digital signal source 40 generates a frequency band width ofThe narrowband noise with center frequency F interferes with the digital signal and is sent to the power amplifier 50.
The power amplifier 50 is used for amplifying the digital interference signal to a power multiple that meets the requirement of the optimal signal-to-interference ratio.
In this embodiment, the power amplifier 50 amplifies the interference signalAnd then transmitted to the interfering transmitting antenna 60.
The interfering transmitting antenna 60 will power asThe optimal narrow-band noise interference radio frequency signal is sent to the unmanned aerial vehicle, so that optimal interference is realized.
In the adaptive optimal narrowband radio frequency interference system and method provided by the embodiment, during the interference implementation period, the radio frequency detection unit and the digital signal processing unit are used for carrying out real-time processing on the unmanned aerial vehicle frequency hopping communication signal to obtain the communication characteristic parameter of the interfered signal, the upper computer calculates and adjusts the optimal narrowband noise interference factor and the optimal interference transmitting power according to the real-time communication characteristic parameter and the real-time position information of the unmanned aerial vehicle, and the adaptive interference signal is generated through the FPGA interference signal source and the power amplifier.
The invention provides a self-adaptive optimal radio frequency interference method and a system for unmanned aerial vehicle frequency hopping communication, which can analyze signal characteristic parameters of a target unmanned aerial vehicle frequency hopping communication signal in real time to obtain an optimal solution between an interference frequency bandwidth and interference power under the condition of blocking interference, and send a blocking interference signal under the optimal solution to ensure that the interference performance is optimal.
The invention also provides an electronic device, which comprises a memory and a processor, wherein the memory stores a program running on the processor, and the processor executes the steps of the adaptive radio frequency interference method aiming at unmanned aerial vehicle frequency hopping communication when running the program.
The invention also provides a computer readable storage medium, on which computer instructions are stored, wherein the computer instructions execute the steps of the adaptive radio frequency interference method for the unmanned aerial vehicle frequency hopping communication when running, and the adaptive radio frequency interference method for the unmanned aerial vehicle frequency hopping communication is referred to the description of the previous parts and is not repeated.
Those of ordinary skill in the art will appreciate that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. An adaptive radio frequency interference system for unmanned aerial vehicle frequency hopping communications, comprising: the device comprises a radio frequency signal detection unit, a digital signal processing unit, an upper computer, an FPGA interference digital signal source, a power amplifier and an interference transmitting antenna, wherein:
the system comprises a radio frequency signal detection unit, a digital signal processing unit and a control unit, wherein the radio frequency signal detection unit is used for converting received radio frequency signals of an uplink communication link and a downlink communication link of the unmanned aerial vehicle into digital signals and sending the generated digital signals to the digital signal processing unit;
the digital signal processing unit is used for carrying out signal processing and analysis on received digital signals of the uplink and downlink communication links of the unmanned aerial vehicle to obtain signal characteristic parameters of the uplink and downlink communication links of the unmanned aerial vehicle, and sending the signal characteristic parameters of the uplink and downlink communication links of the unmanned aerial vehicle obtained by processing to an upper computer, wherein the signal characteristic parameters comprise a signal modulation mode, a frequency hopping center frequency, a frequency hopping rate, an unmanned aerial vehicle frequency hopping bandwidth W, a symbol transmission rate, signal average power and an azimuth angle;
the upper computer is used for matching and calculating to obtain the average power of the uplink communication link reaching the receiving end of the unmanned aerial vehicle, the optimal narrow-band noise interference factor and the optimal bit signal-to-interference ratio, and sending the calculation result to the FPGA interference digital signal source and the power amplifier to generate a required digital interference signal;
the FPGA interference digital signal source is used for generating a narrow-band noise radio frequency interference signal meeting the optimal frequency bandwidth and then sending the signal to the power amplifier;
the power amplifier is used for amplifying the narrowband noise radio frequency interference signal with the optimal frequency bandwidth to a power multiple meeting the requirement of the optimal bit signal-to-interference ratio and then sending the power multiple to the interference transmitting antenna;
the interference transmitting antenna is used for transmitting a narrowband noise radio frequency interference signal with the optimal frequency bandwidth, which meets the power multiple required by the optimal bit signal-to-interference ratio, to the unmanned aerial vehicle so as to realize optimal interference;
the radar is used for detecting the azimuth, pitching information and distance of the unmanned aerial vehicle in real time and sending the information to the upper computer;
the upper computer comprises a fusion unit which is used for carrying out data fusion processing on the received signal characteristic parameters, the azimuth, the pitching information and the distance of the unmanned aerial vehicle, and obtaining the average power Pr of the uplink communication link to the receiving end of the unmanned aerial vehicle s ；
The upper computer also comprises a calculation unit which is used for calculating the optimal narrowband noise interference factor and the bit signal-to-interference ratio according to the received signal characteristic parameters;
the calculation unit sets the narrow-band noise interference power of the unmanned aerial vehicle receiving end as J according to the received unmanned aerial vehicle frequency hopping bandwidth W, and the interference bandwidth is W J Defining the narrow-band noise interference factor ρ as the ratio of the interference bandwidth to the frequency hopping bandwidth, i.e
Wherein,,when->When the noise is the full-band broadband noise interference;
obtaining equivalent single-side power spectral density of narrow-band interference noise signalThe method comprises the following steps:
wherein,,a power spectral density expressed as wideband interference noise;
the following relationship is obtained that the probability when the communication signal is within the interference band is ρ and the power spectral density of the noise is taken asThe probability of the communication signal being out of the interference frequency band is 1-rho, and the power spectral density of the noise is the value；
Bit error rate in case of narrowband noise interference of communication systemThe method comprises the following steps:
wherein,,(. Cndot.) is the bit error rate of communication systems of different modulation types, < >>For bit signal energy, +.>White noise power spectral density;
when (when)When neglecting +.>The following steps are:
when the interference power is limited, there isSo that->Bit error Rate at this time->Maximum value is reached, i.e. the best interference effect is produced, the maximum bit error rate which can be reached by the system under the condition of limited interference power is obtained>By +.>To find the optimum bit signal to interference ratio +.>And optimal narrowband noise interference factor->。
2. The adaptive radio frequency interference system for unmanned aerial vehicle frequency hopping communications according to claim 1, wherein the calculation unit is configured to calculate an average power for reaching the unmanned aerial vehicle receiving end according to the uplinkDefine average power +.>The magnitude ratio to the noise interference power J is the signal-to-interference ratio +.>：
Wherein E is b In order to be a bit signal energy,for the purposes of frequency hopping anti-interference processing gain, the detected unmanned aerial vehicle frequency hopping communication signal bandwidth W and symbol transmission rate +.>Obtaining a ratio;
obtaining the optimal noise interference power of the unmanned aerial vehicle receiving terminal：
For the optimal bit signal-to-interference ratio, calculating to obtain the optimal interference transmitting power according to the formula of the electromagnetic wave propagation in the free space>Is that
Wherein D is the distance from the interference system to the unmanned aerial vehicle,for interfering signal wavelength, < >>For interfering with the transmit antenna gain +.>Receiving the sky for unmanned aerial vehicleLine gain, the power of the optimal narrow-band noise interference radio frequency signal transmitted to the unmanned aerial vehicle by the interference transmitting antenna is the optimal interference transmitting power +.>。
3. The adaptive radio frequency interference system for unmanned aerial vehicle frequency hopping communications of claim 2, wherein the power amplifier is configured to transmit power according to optimal interferenceDetermining the optimal magnification +.>Amplifying the interference signal +.>And the multiplied signals are sent to the interference transmitting antenna.
4. An adaptive radio frequency interference method for unmanned aerial vehicle frequency hopping communication, which is applied to the system as claimed in claim 1, and is characterized by comprising the following steps:
receiving radio frequency signals of an uplink communication link and a downlink communication link of the unmanned aerial vehicle and converting the radio frequency signals into digital signals;
performing digital signal processing and analysis on the generated digital signals to obtain signal characteristic parameters of uplink and downlink communication links of the unmanned aerial vehicle;
the method comprises the steps of obtaining unmanned aerial vehicle position and distance information by radar detection, and obtaining average power and optimal narrow-band noise interference factors and optimal bit signal-to-interference ratios of an uplink communication link to an unmanned aerial vehicle receiving end according to signal characteristic parameters and the unmanned aerial vehicle position and distance information;
generating a narrowband noise radio frequency interference signal meeting the optimal frequency bandwidth according to the optimal narrowband noise interference factor;
and amplifying the interference signal to the power multiple meeting the requirement of the optimal bit signal-to-interference ratio according to the optimal bit signal-to-interference ratio, and then sending the interference signal to the unmanned aerial vehicle to realize optimal interference.
5. An electronic device comprising a memory and a processor, the memory having stored thereon a program running on the processor, the processor executing the steps of the adaptive radio frequency interference method for unmanned aerial vehicle frequency hopping communications of claim 4 when the program is run.
6. A computer readable storage medium having stored thereon computer instructions, which when run perform the steps of the adaptive radio frequency interference method for unmanned aerial vehicle frequency hopping communications of claim 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310029591.4A CN115996103B (en) | 2023-01-09 | 2023-01-09 | Adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310029591.4A CN115996103B (en) | 2023-01-09 | 2023-01-09 | Adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115996103A CN115996103A (en) | 2023-04-21 |
| CN115996103B true CN115996103B (en) | 2023-07-21 |
Family
ID=85990027
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310029591.4A Active CN115996103B (en) | 2023-01-09 | 2023-01-09 | Adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115996103B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111865224B (en) * | 2020-07-15 | 2024-09-10 | 武汉博畅通信设备有限责任公司 | Digital broadband power amplifier filter device and control method thereof |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105099585A (en) * | 2015-08-03 | 2015-11-25 | 陈昊 | Unmanned aerial vehicle signal processing device and signal processing method |
| CN109004951A (en) * | 2018-08-10 | 2018-12-14 | 北京历正科技有限责任公司 | A kind of UAV Communication interference method and system |
| CN109379161A (en) * | 2018-12-13 | 2019-02-22 | 浙江天则通信技术有限公司 | A kind of adaptive jammer system for unmanned plane |
| CN112367142A (en) * | 2020-10-29 | 2021-02-12 | 黄凯 | Interference signal generating device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8599901B2 (en) * | 2010-04-05 | 2013-12-03 | The United States Of America As Represented By The Secretary Of The Army | Method and apparatus for tracking a frequency-hopped signal |
| US8903304B2 (en) * | 2011-06-23 | 2014-12-02 | Talpha Technologies, Inc. | Systems and methods for radio frequency hopping communications jamming utilizing software defined radio platforms |
-
2023
- 2023-01-09 CN CN202310029591.4A patent/CN115996103B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105099585A (en) * | 2015-08-03 | 2015-11-25 | 陈昊 | Unmanned aerial vehicle signal processing device and signal processing method |
| CN109004951A (en) * | 2018-08-10 | 2018-12-14 | 北京历正科技有限责任公司 | A kind of UAV Communication interference method and system |
| CN109379161A (en) * | 2018-12-13 | 2019-02-22 | 浙江天则通信技术有限公司 | A kind of adaptive jammer system for unmanned plane |
| CN112367142A (en) * | 2020-10-29 | 2021-02-12 | 黄凯 | Interference signal generating device |
Non-Patent Citations (1)
| Title |
|---|
| 非相干JTIDS抗干扰性能研究;谢佳轩 等;《计算机仿真》(第06期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115996103A (en) | 2023-04-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115996103B (en) | Adaptive radio frequency interference system and method for unmanned aerial vehicle frequency hopping communication | |
| CN107422312B (en) | Deception jamming signal transmitting power estimation method | |
| CN105099585A (en) | Unmanned aerial vehicle signal processing device and signal processing method | |
| CN112564735B (en) | Unmanned aerial vehicle detects and trails interference device based on frequency hopping signal | |
| CN106896351B (en) | A kind of radar network composite Poewr control method based on non-cooperative game | |
| KR20110071838A (en) | Apparatus and method of repeating in wireless communication systems | |
| CN107390186B (en) | Method for estimating emission power of suppressed interference signal | |
| CN114221726B (en) | Down link co-channel interference characterization method of ka band unmanned aerial vehicle communication system | |
| CN116366199A (en) | Multidirectional noise modulation method for digital phased array antenna | |
| Riihonen et al. | Full-duplex operation for electronic protection by detecting communication jamming at transmitter | |
| US10749611B2 (en) | Underwater radio communication system, transmitting unit, receiving unit, and underwater radio communication method | |
| CN115348577B (en) | Beam scanning method based on reinforcement learning in hidden communication system | |
| CN109669165B (en) | Multi-base radar transmitter and waveform joint selection optimization method based on radio frequency stealth | |
| CN109669167B (en) | Airborne radar emission waveform selection method based on radio frequency stealth | |
| Armeniakos et al. | Angular Distance-Based Performance Analysis of mmWave Cellular Networks | |
| Arif et al. | Clustered jamming and antenna beam-width fluctuations for UAV-assisted cellular networks | |
| CN109039484B (en) | Method for identifying operator to which base station antenna belongs based on energy detection | |
| CN116170111A (en) | Interference power threshold estimation method and system based on unmanned aerial vehicle frequency hopping communication | |
| CN113822534A (en) | Interference resource optimal allocation method for cooperation of multiple unmanned aerial vehicles | |
| Zhang et al. | Covert Communication in Hybrid Microwave/mmWave A2G Systems with Transmission Mode Selection | |
| CN113225825B (en) | Particle swarm optimization algorithm-based hybrid artificial noise-assisted safe transmission method and device | |
| McADAMS | RF Fundamentals for the Internet of Things | |
| CN115396009B (en) | Satellite anti-interference method based on beam switching and optimization | |
| CN113765617B (en) | Method for resisting same-frequency interference based on reflection amplification surface | |
| CN111679249B (en) | Radio frequency stealth-based frequency control array radar radiation power control method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |