Unmanned platform-oriented interference detection communication multifunctional radio system

Abstract

In order to solve the problem of how to design and implement a multi-functional radio frequency system with electromagnetic spectrum compatibility, good stealth and the ability to perform multiple tasks on an unmanned platform, the present application discloses a multi-functional radio frequency system for interference detection and communication of unmanned platforms, which comprises an antenna array unit, a digital radio frequency / intermediate frequency exchange network, a signal processing unit, a data exchange network, a data processing and display unit; the antenna array unit comprises an antenna radiation unit, a digital T / R component and a power supply; the antenna radiation unit comprises a communication antenna array, a detection antenna array and an interference antenna array; the digital T / R component comprises a sending link, a receiving link and a transceiver switch; the signal processing unit is used for realizing the signal processing process of detection, communication and interference; and the data processing and display unit is used for classifying and displaying the signal processing result data. The present application provides a hardware implementation basis for the integration and intelligence of unmanned platforms, and promotes the development of unmanned platforms towards intelligence and stealth.

Description

Technical Field

[0001] This invention relates to the fields of radio technology and unmanned technology, and in particular to a multi-functional radio frequency system for interference detection and communication for unmanned platforms. Background Technology

[0002] In recent years, intelligent unmanned platforms have developed rapidly, with drones, unmanned surface vessels, and other unmanned motion platforms being widely used. Unmanned platforms typically carry multiple payloads depending on their usage requirements. For multi-functional radio frequency (RF) payloads, considering the space limitations of unmanned platforms, the simultaneous operation of different types of RF payloads will generate electromagnetic interference, which can severely affect the normal operation of each payload. Simultaneously, the antennas carried by each RF payload will also affect the overall structure, stealth, and navigation safety of the unmanned platform. How to design a multi-functional RF system on an unmanned platform that achieves electromagnetic spectrum compatibility, good stealth, and the ability to perform multiple tasks is a pressing issue that needs to be addressed. Furthermore, multi-functional RF systems typically share corresponding RF front-ends; how to efficiently allocate and utilize RF resources is also one of the core problems that multi-functional RF systems need to solve. Summary of the Invention

[0003] To address the challenges of designing and implementing a multifunctional radio frequency (RF) system on an unmanned platform that is electromagnetically compatible, stealthy, and capable of performing various tasks, as well as the efficient allocation and use of RF resources by various RF functional payloads, this invention discloses a multifunctional RF system for interference detection and communication on unmanned platforms. The system includes an antenna array unit, a digital RF / IF switching network, a signal processing unit, a data switching network, and a data processing and display unit.

[0004] The antenna array unit includes antenna radiating elements, digital T / R components, and power supply.

[0005] The antenna radiating unit is used to receive and transmit radio frequency signals, detect the spectrum environment, and obtain spectrum monitoring data. The antenna radiating unit includes a communication antenna array, a probe antenna array, and an interference antenna array. The digital T / R component is used to perform low-noise amplification, down-conversion, phase shifting, and intermediate frequency sampling operations on the signals received by the antenna radiating unit, or to perform waveform generation, phase shifting, up-conversion, and high-power amplification operations on the received signal parameters, or to perform up-conversion, phase shifting, and high-power amplification operations on the received signal waveform. The power supply is used to provide voltage and current to the digital T / R component.

[0006] The digital T / R module includes a transmit link, a receive link, and a transceiver switch. The digital T / R module is connected to the antenna radiating element via the transceiver switch; both the transmit and receive links are connected to the transceiver switch. The transmit link of the digital T / R module includes a signal generator, a phase shifter, an up-converter, and a high-power amplifier, connected sequentially. The receive link of the digital T / R module includes an intermediate frequency sampler, a phase shifter, a down-converter, and a low-noise amplifier, connected sequentially. Both the high-power amplifier and the low-noise amplifier are connected to the transceiver switch.

[0007] The digital radio frequency / intermediate frequency switching network is used to select the corresponding signal from the receiving link of the digital T / R component of the antenna array unit according to the signal selection command of the signal processing unit, and send it to the signal processing unit, or send the signal parameters and signal waveforms sent by the signal processing unit to the corresponding digital T / R component.

[0008] The signal processing unit is used to implement the signal processing processes for detection, communication, and interference, and obtain signal processing result data; according to the signal processing requirements, it sends signal selection instructions to the digital radio frequency / intermediate frequency switching network; according to the signal processing result data for detection, communication, and interference, it sends signal parameters and signal waveforms to the digital radio frequency / intermediate frequency switching network; and it sends the signal processing result data for detection, communication, and interference to the data switching network.

[0009] The signal processing unit includes a digital beamforming (DBF) processing subunit, a radar signal processing subunit, a signal reconnaissance processing subunit, a deception jamming processing subunit, a suppression jamming processing subunit, a smart jamming processing subunit, a modulation and demodulation processing subunit, a resource allocation subunit, a resource monitoring and management subunit, and a computing resource subunit.

[0010] The radar signal processing subunit, signal reconnaissance processing subunit, and modulation / demodulation processing subunit generate corresponding radar signal selection instructions, jamming signal selection instructions, and communication signal selection instructions according to their respective signal processing needs. They then use the corresponding signal selection instructions to obtain the signals received by the detection antenna array, the jamming antenna array, and the communication antenna array from the antenna array unit through the digital radio frequency / intermediate frequency switching network.

[0011] The digital beamforming processing subunit is used to perform receive beamforming processing on the output signal of the receive link of the digital T / R component of the antenna array unit, and to perform transmit beamforming processing on the input signal of the transmit link of the digital T / R component of the antenna array unit.

[0012] The digital beamforming processing subunit, resource allocation subunit, and spectrum management unit are all connected to the digital radio frequency / intermediate frequency switching network. The digital beamforming processing subunit is also connected to the radar signal processing subunit, signal reconnaissance processing subunit, deception jamming processing subunit, suppression jamming processing subunit, smart jamming processing subunit, and modulation and demodulation processing subunit.

[0013] The radar signal processing subunit is used to perform pulse compression, target detection, track filtering, distance measurement, and angle measurement processing on the signals received by the detection antenna array to obtain target motion parameters.

[0014] The signal reconnaissance and processing subunit is used to intercept, measure parameters, sort pulses and identify threats to the signals received by the jamming antenna array, obtain the signal reconnaissance and processing results, and send the signal reconnaissance and processing results to the deception jamming processing subunit, the suppression jamming processing subunit and the agile jamming processing subunit.

[0015] The deception interference processing subunit, the suppression interference processing subunit, and the agile interference processing subunit are used to generate deception interference signal waveforms or parameters, suppression interference signal waveforms or parameters, and agile interference signal waveforms or parameters, respectively, based on the signal reconnaissance and processing results.

[0016] The modulation and demodulation processing subunit is used to perform equalization, demodulation, decoding and detection processing of the signals received by the communication antenna array. It is used to receive the communication transmission data generated by the data processing and display unit, encode and modulate the communication transmission data to obtain the modulated waveform, and send the modulated waveform to the digital radio frequency / intermediate frequency switching network.

[0017] The resource allocation subunit is used to receive resource usage demand information from other subunits included in the signal processing unit and idle resource information sent by the resource monitoring and management subunit. It processes the resource usage demand information and idle resource information using a resource allocation model to generate a resource allocation scheme and allocates various resources to the corresponding subunits according to the resource allocation scheme.

[0018] The computing resource subunit is used to receive computing requests from other subunits, perform the relevant calculations, and send the calculation results to the corresponding subunits.

[0019] Each subunit of the signal processing unit is connected to the data exchange network.

[0020] The resource monitoring and management subunit is used to monitor the hardware resource usage of the antenna array unit and the signal processing unit, obtain occupied resource information and idle resource information, and send the idle resource information to the resource allocation subunit. Based on the resource allocation scheme received from the resource allocation subunit and the spectrum monitoring data of the antenna radiation unit, a spectrum management scheme is generated using the spectrum allocation model, and the spectrum management scheme is sent to the radar signal processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the agile jamming processing subunit, and the modulation and demodulation processing subunit. The radar signal processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the agile jamming processing subunit, and the modulation and demodulation processing subunit determine the frequency band they use according to the received spectrum management scheme.

[0021] The signal processing result data includes target motion parameter signals, reconnaissance processing results, deception jamming signal waveforms or parameters, suppression jamming signal waveforms or parameters, agile jamming signal waveforms or parameters, modulation waveforms, and resource allocation schemes.

[0022] The data exchange network is used to realize data exchange and transmission between the various sub-units included in the signal processing unit, and between the signal processing unit and the data processing and display unit.

[0023] The data processing and display unit is used to classify and display the signal processing results data, generate communication transmission data, and send it to the data exchange network.

[0024] The resource allocation subunit is used to receive resource usage demand information from other subunits included in the signal processing unit and idle resource information sent by the resource monitoring and management subunit, process the resource usage demand information and idle resource information using a resource allocation model, and generate a resource allocation scheme, including:

[0025] The resource allocation subunit obtains the unmanned platform's working mode information and task objective information from the resource usage requirements; it compares the idle resource information and the resource usage requirements information. If the idle resource information contains the resource usage requirements information, it generates a corresponding resource allocation plan according to the resource usage requirements information; if the idle resource information does not contain the resource usage requirements information, it generates a resource allocation plan based on the unmanned platform's working mode information and task objective information.

[0026] If the idle resource information does not include resource usage demand information, a resource allocation scheme is generated based on the unmanned platform's working mode information and task objective information, including:

[0027] Task information to be assigned is extracted from the mission objective information. Based on the unmanned platform's operating mode information, the assignment priority of these tasks is set. The unmanned platform's operating modes include measurement mode, interference mode, and silent mode. The types of tasks performed by the unmanned platform include active detection tasks, passive detection tasks, signal reconnaissance tasks, active interference tasks, and communication tasks. When the unmanned platform is in measurement mode, active detection tasks are set as the first priority, and the remaining tasks as the second priority. When the unmanned platform is in interference mode, signal reconnaissance tasks and active interference tasks are set as the first priority, and the remaining tasks as the second priority. Among the first priority tasks, signal reconnaissance tasks are assigned first. When the unmanned platform is in silent mode, passive detection tasks and signal reconnaissance tasks are set as the first priority, and only passive detection tasks and signal reconnaissance tasks are assigned.

[0028] Threat assessment methods are used to obtain threat information for each mission objective.

[0029] Extract the task information to be assigned and the corresponding resource requirement information from the task target information. Use the task information to be assigned and the corresponding resource requirement information to establish a task assignment queue, which is a sequence of tasks to be assigned. Based on the resource requirement information of each task to be assigned in the task assignment queue, establish a resource description model for the task to be assigned. Establish a set of tasks to be executed and a set of tasks to be executed.

[0030] The tasks to be assigned in the task allocation queue are sorted according to their allocation priority to obtain the task allocation queue sequence. In the task allocation queue sequence, the tasks to be assigned with higher allocation priority are placed first. Tasks with the same allocation priority are sorted according to the threat level of their corresponding task objectives, with the tasks to be assigned with higher threat level of their task objectives placed first. The platform's task capability range is established based on the idle resource information.

[0031] For all tasks to be assigned in the task assignment queue, resources are allocated sequentially according to their order in the task assignment queue, and a resource allocation scheme for each task to be assigned is obtained in turn; using the resource allocation schemes of all tasks to be assigned, a resource allocation scheme is generated.

[0032] The process involves all tasks in the task allocation queue being allocated resources sequentially according to their order in the queue, resulting in a resource allocation scheme for each task, including:

[0033] S1. Using the resource description model of the task to be assigned, determine whether the resource usage requirements of the task to be assigned are within the platform's task capacity. If they are not within the platform's task capacity, remove the task to be assigned from the task assignment queue and add it to the set of tasks to be executed. Restart step S1 and continue to determine the resource usage requirements of the next task to be assigned in the task assignment queue. If they are within the platform's task capacity, proceed to step S2.

[0034] S2, determine whether the current time is within the execution time range of the task to be assigned. If it is, generate a corresponding resource allocation scheme based on the resource usage requirements of the task to be assigned; delete the task to be assigned from the task allocation queue, store the task to be assigned in the execution task set, and start the execution of the task to be assigned; delete the resources allocated to the task to be assigned from the platform task capability range, and update the platform task capability range; after the resource allocation of a certain number of tasks to be assigned in the task allocation queue is completed, proceed to step S3; otherwise, return to step S1.

[0035] S3: After allocating resources to a certain number of tasks in the task allocation queue, determine whether the execution time of the assigned tasks has exceeded the time limit of the assigned tasks. If the execution time limit of an assigned task has exceeded the time limit, remove the task from the task execution set and add the resources allocated to the task to the platform's task capability range. If all tasks in the task allocation queue have completed resource allocation, continue to the tasks in the task execution set and determine whether their resource usage requirements are within the platform's task capability range. If they are within the platform's task capability range, generate a corresponding resource allocation scheme based on the resource usage requirements of the assigned tasks, remove the assigned tasks from the task execution set, and remove the resources allocated to the assigned tasks from the platform's task capability range.

[0036] For both active and passive detection tasks, after generating a resource allocation scheme, based on the task objective information and the resource allocation scheme, an optimization model for the detection antenna array parameters is established with target tracking performance as the objective function and the detection antenna array parameters as the decision variables. The optimization model is then solved to obtain the optimized values ​​of the detection antenna array parameters. These optimized values ​​are then added to the resource allocation scheme for the active or passive detection task, thus updating the resource allocation scheme.

[0037] The parameters of the probe antenna array include the operating state vector, weighting vector, and phase vector of each antenna element in the probe antenna array.

[0038] The optimization model for the probe antenna array parameters is expressed as follows:

[0039] minF(x)

[0040]

[0041] Where F() represents the target tracking error function, x represents the decision vector, and x i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let represent the upper limit of the value of the i-th decision variable, m be the number of decision variables included in the decision vector, Ch represent the chance measure, and g j (x) is the j-th constraint function on the decision vector x, g j0 α is the upper limit of the value of the j-th constraint function of the decision vector x. j and β j Let j represent the confidence level parameter for the j-th constraint function of decision vector x, where j0 is the number of constraint functions for decision vector x.

[0042] The optimization model for the probe antenna array parameters is solved using an optimization solution method.

[0043] The optimization solution method includes artificial intelligence methods, genetic algorithms, particle filtering methods, or convex optimization methods.

[0044] The target tracking error function is characterized by the maximum tracking error for all task targets, or by the sum of the tracking errors for all task targets, or by the tracking errors for all targets.

[0045] When the target tracking error function is characterized by the tracking errors of all targets, the probe antenna array parameter optimization model is a multi-objective optimization mode, which is solved using a multi-objective optimization solution method.

[0046] For active jamming tasks, after obtaining the resource allocation scheme, based on the task objective information and the resource allocation scheme, an optimization model for the jamming antenna array parameters is established with the jamming effect as the objective function and the jamming antenna array parameters as the decision variables. The optimization model is solved to obtain the optimized values ​​of the jamming antenna array parameters. The optimized values ​​of the jamming antenna array parameters are then added to the resource allocation scheme of the active jamming task to complete the update of the resource allocation scheme.

[0047] The parameters of the jamming antenna array include the operating state vector, weighting vector, and phase vector of each antenna element in the jamming antenna array.

[0048] The objective function is to use the interference effect as the objective function and the interference antenna array parameters as the decision variables. An optimization model for the interference antenna array parameters is established, and one of the following corresponding methods is used to achieve this, depending on the type of interference employed:

[0049] For suppressing interference, with the suppression effect as the primary objective function and the interference antenna array parameters as decision variables, an optimization model for the first interference antenna array parameters is established, the expression of which is:

[0050] maxK(x)P H (x)C d (J,S)

[0051]

[0052] Where K(x) is the interference effect coefficient under the condition of decision vector x, P H (x) represents the entropy power of the suppressed interference signal under the condition of decision vector x, C d (J,S) represents the detection factor for suppressing the jamming target, where J is the jamming power received by the target during detection, and S is the target signal power received by the target during detection. i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let p represent the upper limit of the value of the i-th decision variable, m be the number of decision variables contained in the decision vector, and p be the upper limit of the value of the i-th decision variable. j (x) is the j-th constraint function for suppressing interference on the decision vector x, p j0 is the upper limit of the value of the j-th constraint function for suppressing interference on decision vector x, and p0 is the number of constraint functions for suppressing interference on decision vector x.

[0053] For deception jamming against false targets, the deception jamming effect is taken as the second objective function, and the jamming antenna array parameters are used as decision variables. An optimization model for the second jamming antenna array parameters is established, and its expression is:

[0054] maxtK(x)P df (x)P dif (x)

[0055]

[0056] Where K(x) is the interference effect coefficient under the decision vector x, and t is the number of false targets generated by the false target deception interference. P df (x) represents the probability of detecting a false target given the decision vector x, where P is the false target deceiving the target. dif (x) represents the probability that a target misleading an interfering target will identify the false target as the real target given the decision vector x. iLet x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let represent the upper limit of the value of the i-th decision variable, m be the number of decision variables contained in the decision vector, and q be the upper limit of the value of the i-th decision variable. j (x) is the j-th constraint function of the false target deception interference on the decision vector x, q j0 q0 is the upper limit of the value of the j-th constraint function of the false target deception interference on the decision vector x, and q0 is the number of constraint functions of the false target deception interference on the decision vector x.

[0057] For drag-and-spoof interference, with the drag-and-spoof interference effect as the third objective function and the interference antenna array parameters as decision variables, an optimization model for the third interference antenna array parameters is established, the expression of which is:

[0058]

[0059] Among them, L V (dB) represents the interference-to-signal ratio loss after dragging spoofing interference, expressed in dB. The interference-to-signal ratio loss after dragging spoofing interference is used as the dragging spoofing interference effect. V(x) is the dragging velocity under the decision vector x. m B is the maximum velocity value that the target can respond to in order to deceive and interfere. t To reduce the detection bandwidth of the target being deceived or interfered with, x i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let r represent the upper limit of the value of the i-th decision variable, m be the number of decision variables contained in the decision vector, and r be the upper limit of the value of the i-th decision variable. j (x) is the j-th constraint function of drag-and-spoof interference on the decision vector x, r j0 is the upper limit of the value of the j-th constraint function of the dragging deception interference on the decision vector x, and r0 is the number of constraint functions of the dragging deception interference on the decision vector x;

[0060] For solving the parameter optimization model of the interference antenna array, artificial intelligence methods, particle filtering methods, convex optimization methods, or genetic algorithms are used.

[0061] The threat assessment method used to obtain threat information for each task objective includes:

[0062] For each task objective in the task objective information, a threat factor weighting method is used to sum the threat factors of the objective to obtain the threat level information of each objective. For moving targets, the threat factors include distance threat factor, attribute threat factor, speed threat factor, and altitude threat factor. The distance threat factor y... d The calculation formula is as follows:

[0063]

[0064] Where χ is the distance scaling constant, d c Where D is the maximum target detection range of the interference detection and communication multi-functional radio frequency system, and D is the target distance information given in the mission target information or the target distance information detected by the interference detection and communication multi-functional radio frequency system. Attribute threat factor y t The target type information is determined from the mission objective information, which includes aircraft, ships, unidentified targets, high-speed aircraft, etc. The speed threat factor y... v The calculation formula is as follows:

[0065]

[0066] Wherein, κ is a speed proportionality constant, vmax is the maximum target detection speed of the interference detection and communication multi-functional radio frequency system, and v is the target speed information given in the mission target information or the target speed information detected by the interference detection and communication multi-functional radio frequency system.

[0067] The high threat factor y h The calculation formula is as follows:

[0068]

[0069] Where H is the high threat setting value, h is the target height information given in the mission target information or the target height information detected by the interference detection communication multi-functional radio frequency system, and η is the height ratio constant.

[0070] For radar signal targets, the threat factors include range threat factor, signal type threat factor, and radar operational status threat factor. The range threat factor for radar signal targets can be calculated using the same method as for moving targets, or it can be obtained by multiplying the radar distance to the unmanned platform by a scaling factor. The signal type threat factor is determined by the radar signal type, which includes terminal guidance radar signals, fire control radar signals, early warning radar signals, and ground target indication radar signals. The radar operational status threat factor is determined by the radar's operational status, which includes guidance, search, and tracking.

[0071] The threat assessment method used to obtain threat information for each task objective includes:

[0072] Using fuzzy reasoning, threat level information for each task objective is obtained, specifically including:

[0073] The target state information and target attribute information are extracted from the task target information. The target state information and target attribute information are then fuzzified to obtain a fuzzy set in a given domain. Fuzzy inference is performed on the fuzzy set to obtain the fuzzy inference result. The fuzzy inference result is then defuzzified to obtain the threat level information of the task target.

[0074] The fuzzification process refers to mapping a real-valued point to a fuzzy set. Fuzzification methods include single-valued fuzzification, triangular fuzzification, and Gaussian fuzzification.

[0075] The fuzzy reasoning operation refers to the process of deriving a definite conclusion from a fuzzy set according to certain fuzzy reasoning rules. The definite conclusion is the fuzzy reasoning result.

[0076] The fuzzy inference operation can be implemented using the Maddane fuzzy inference method or the Zadeh fuzzy inference method.

[0077] The defuzzification operation maps the fuzzy inference result to clear points. Defuzzification operations include the maximum membership method, the centroid method, and the center-average method.

[0078] The beneficial effects of this invention are as follows:

[0079] 1. Based on an unmanned platform, this invention designs a multi-functional integrated radio frequency system architecture with flexible configuration, providing a hardware foundation for the integration and intelligence of unmanned platforms and promoting the development of unmanned platforms towards intelligence and stealth.

[0080] 2. This invention provides a resource allocation scheme for a multi-functional radio frequency platform, which can meet various task requirements and target requirements, achieve flexible and efficient resource allocation, improve the utilization rate of various hardware resources, and enhance the ability of the multi-functional radio frequency system to autonomously execute and complete various tasks. Attached Figure Description

[0081] Figure 1 This is a structural diagram of a multi-functional radio frequency system for interference detection and communication for unmanned platforms, as disclosed in this invention.

[0082] Figure 2 This is a flowchart illustrating the implementation of the resource allocation method of the present invention. Detailed Implementation

[0083] To better understand the content of this invention, an embodiment is provided here.

[0084] Figure 1 This is a structural diagram of a multi-functional radio frequency system for interference detection and communication for unmanned platforms, as disclosed in this invention. Figure 2This is a flowchart illustrating the implementation of the resource allocation method of the present invention. It should be noted that... Figure 2 The given flowchart is only a simplified implementation of the resource allocation method of this invention, illustrating the basic idea of ​​the method. Some detailed and optimal operations during the resource allocation process are not fully shown. Figure 2 middle.

[0085] To address the challenges of designing and implementing a multifunctional radio frequency (RF) system on an unmanned platform that is electromagnetically compatible, stealthy, and capable of performing various tasks, as well as the efficient allocation and use of RF resources by various RF functional payloads, this invention discloses a multifunctional RF system for interference detection and communication on unmanned platforms. The system includes an antenna array unit, a digital RF / IF switching network, a signal processing unit, a data switching network, and a data processing and display unit.

[0086] The antenna array unit includes antenna radiating elements, digital T / R components, and power supply.

[0087] The antenna radiating unit is used to receive and transmit radio frequency signals, detect the spectrum environment, and obtain spectrum monitoring data. The antenna radiating unit includes a communication antenna array, a probe antenna array, and an interference antenna array. The digital T / R component is used to perform low-noise amplification, down-conversion, phase shifting, and intermediate frequency sampling operations on the signals received by the antenna radiating unit, or to perform waveform generation, phase shifting, up-conversion, and high-power amplification operations on the received signal parameters, or to perform up-conversion, phase shifting, and high-power amplification operations on the received signal waveform. The power supply is used to provide voltage and current to the digital T / R component.

[0088] Communication antenna arrays, detection antenna arrays, and jamming antenna arrays are not fixed; they can be flexibly configured by adjusting the antenna radiating elements according to system requirements.

[0089] The digital T / R module includes a transmit link, a receive link, and a transceiver switch. The digital T / R module is connected to the antenna radiating element via the transceiver switch; both the transmit and receive links are connected to the transceiver switch. The transmit link of the digital T / R module includes a DDS signal generator, a phase shifter, an up-converter, and a high-power amplifier, connected sequentially. The receive link of the digital T / R module includes an intermediate frequency sampler, a phase shifter, a down-converter, and a low-noise amplifier, connected sequentially. Both the high-power amplifier and the low-noise amplifier are connected to the transceiver switch.

[0090] The digital radio frequency / intermediate frequency switching network is used to select the corresponding signal from the receiving link of the digital T / R component of the antenna array unit according to the signal selection command of the signal processing unit, and send it to the signal processing unit, or send the signal parameters and signal waveforms sent by the signal processing unit to the corresponding digital T / R component.

[0091] The signal processing unit is used to implement the signal processing processes for detection, communication, and interference, and obtain signal processing result data; according to the signal processing requirements, it sends signal selection instructions to the digital radio frequency / intermediate frequency switching network; according to the signal processing result data for detection, communication, and interference, it sends signal parameters and signal waveforms to the digital radio frequency / intermediate frequency switching network; and it sends the signal processing result data for detection, communication, and interference to the data switching network.

[0092] The signal processing unit includes a digital beamforming (DBF) processing subunit, a radar signal processing subunit, a signal reconnaissance processing subunit, a deception jamming processing subunit, a suppression jamming processing subunit, a smart jamming processing subunit, a modulation and demodulation processing subunit, a resource allocation subunit, a resource monitoring and management subunit, and a computing resource subunit.

[0093] The radar signal processing subunit, signal reconnaissance processing subunit, and modulation / demodulation processing subunit generate corresponding radar signal selection instructions, jamming signal selection instructions, and communication signal selection instructions according to their respective signal processing needs. They then use the corresponding signal selection instructions to obtain the signals received by the detection antenna array, the jamming antenna array, and the communication antenna array from the antenna array unit through the digital radio frequency / intermediate frequency switching network.

[0094] The digital beamforming processing subunit is used to perform receive beamforming processing on the output signal of the receive link of the digital T / R component of the antenna array unit, and to perform transmit beamforming processing on the input signal of the transmit link of the digital T / R component of the antenna array unit.

[0095] The digital beamforming processing subunit, resource allocation subunit, and spectrum management unit are all connected to the digital radio frequency / intermediate frequency switching network. The digital beamforming processing subunit is also connected to the radar signal processing subunit, signal reconnaissance processing subunit, deception jamming processing subunit, suppression jamming processing subunit, smart jamming processing subunit, and modulation and demodulation processing subunit.

[0096] The radar signal processing subunit is used to perform pulse compression, target detection, track filtering, distance measurement, and angle measurement processing on the signals received by the detection antenna array to obtain target motion parameters.

[0097] The signal reconnaissance and processing subunit is used to intercept, measure parameters, sort pulses and identify threats to the signals received by the jamming antenna array, obtain the signal reconnaissance and processing results, and send the signal reconnaissance and processing results to the deception jamming processing subunit, the suppression jamming processing subunit and the agile jamming processing subunit.

[0098] The deception interference processing subunit, the suppression interference processing subunit, and the agile interference processing subunit are used to generate deception interference signal waveforms or parameters, suppression interference signal waveforms or parameters, and agile interference signal waveforms or parameters, respectively, based on the signal reconnaissance and processing results.

[0099] The modulation and demodulation processing subunit is used to perform equalization, demodulation, decoding and detection processing of the signals received by the communication antenna array. It is used to receive the communication transmission data generated by the data processing and display unit, encode and modulate the communication transmission data to obtain the modulated waveform, and send the modulated waveform to the digital radio frequency / intermediate frequency switching network.

[0100] The resource allocation subunit is used to receive resource usage demand information from other subunits included in the signal processing unit and idle resource information sent by the resource monitoring and management subunit. It processes the resource usage demand information and idle resource information using a resource allocation model to generate a resource allocation scheme and allocates various resources to the corresponding subunits according to the resource allocation scheme.

[0101] The computing resource subunit is used to receive computing requests from other subunits, perform the relevant calculations, and send the calculation results to the corresponding subunits.

[0102] Each subunit of the signal processing unit is connected to the data exchange network.

[0103] The resource monitoring and management subunit is used to monitor the hardware resource usage of the antenna array unit and the signal processing unit, obtain occupied resource information and idle resource information, and send the idle resource information to the resource allocation subunit. Based on the resource allocation scheme received from the resource allocation subunit and the spectrum monitoring data of the antenna radiation unit, a spectrum management scheme is generated using the spectrum allocation model, and the spectrum management scheme is sent to the radar signal processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the agile jamming processing subunit, and the modulation and demodulation processing subunit. The radar signal processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the agile jamming processing subunit, and the modulation and demodulation processing subunit determine the frequency band they use according to the received spectrum management scheme.

[0104] The signal processing result data includes target motion parameter signals, reconnaissance processing results, deception jamming signal waveforms or parameters, suppression jamming signal waveforms or parameters, agile jamming signal waveforms or parameters, modulation waveforms, and resource allocation schemes.

[0105] The data exchange network is used to realize data exchange and transmission between the various sub-units included in the signal processing unit, and between the signal processing unit and the data processing and display unit.

[0106] The data processing and display unit is used to classify and display the signal processing results data, generate communication transmission data, and send it to the data exchange network.

[0107] The resource allocation subunit is used to receive resource usage demand information from other subunits included in the signal processing unit and idle resource information sent by the resource monitoring and management subunit, process the resource usage demand information and idle resource information using a resource allocation model, and generate a resource allocation scheme, including:

[0108] The resource allocation subunit obtains the unmanned platform's working mode information and task objective information from the resource usage requirements; it compares the idle resource information and the resource usage requirements information. If the idle resource information contains the resource usage requirements information, it generates a corresponding resource allocation plan according to the resource usage requirements information; if the idle resource information does not contain the resource usage requirements information, it generates a resource allocation plan based on the unmanned platform's working mode information and task objective information.

[0109] If the idle resource information does not include resource usage demand information, a resource allocation scheme is generated based on the unmanned platform's working mode information and task objective information, including:

[0110] Task information to be assigned is extracted from the mission objective information. Based on the unmanned platform's operating mode information, the assignment priority of these tasks is set. The unmanned platform's operating modes include measurement mode, interference mode, and silent mode. The types of tasks performed by the unmanned platform include active detection tasks, passive detection tasks, signal reconnaissance tasks, active interference tasks, and communication tasks. When the unmanned platform is in measurement mode, active detection tasks are set as the first priority, and the remaining tasks as the second priority. When the unmanned platform is in interference mode, signal reconnaissance tasks and active interference tasks are set as the first priority, and the remaining tasks as the second priority. Among the first priority tasks, signal reconnaissance tasks are assigned first. When the unmanned platform is in silent mode, passive detection tasks and signal reconnaissance tasks are set as the first priority, and only passive detection tasks and signal reconnaissance tasks are assigned.

[0111] Threat assessment methods are used to obtain threat information for each mission objective.

[0112] Extract the task information to be assigned and the corresponding resource requirement information from the task target information. Use the task information to be assigned and the corresponding resource requirement information to establish a task assignment queue, which is a sequence of tasks to be assigned. Based on the resource requirement information of each task to be assigned in the task assignment queue, establish a resource description model for the task to be assigned. Establish a set of tasks to be executed and a set of tasks to be executed.

[0113] The resource description model for the tasks to be assigned describes the resource requirements of the tasks to be assigned. It is represented in set form, where D is the resource description model for the i-th task to be assigned. i The expression is:

[0114] D i ={t i1 ,t i2 ,θ 1i ,θ 2i ,θ 3i ,θ 4i},

[0115] Among them, t i1 t represents the requested start time of the execution of the i-th task to be assigned. i2 θ represents the requested execution completion time of the i-th task to be assigned. 1i ,θ 2i ,θ 3i ,θ 4i These represent the antenna resources, channel resources, signal processing resources, and computing resources requested by the i-th task to be assigned, respectively.

[0116] The tasks to be assigned in the task allocation queue are sorted according to their allocation priority to obtain the task allocation queue sequence. In the task allocation queue sequence, the tasks to be assigned with higher allocation priority are placed first. Tasks with the same allocation priority are sorted according to the threat level of their corresponding task objectives, with the tasks to be assigned with higher threat level of their task objectives placed first. The platform's task capability range is established based on the idle resource information.

[0117] For all tasks to be assigned in the task assignment queue, resources are allocated sequentially according to their order in the task assignment queue, and a resource allocation scheme for each task to be assigned is obtained in turn; using the resource allocation schemes of all tasks to be assigned, a resource allocation scheme is generated.

[0118] The process involves all tasks in the task allocation queue being allocated resources sequentially according to their order in the queue, resulting in a resource allocation scheme for each task, including:

[0119] S1. Using the resource description model of the task to be assigned, determine whether the resource usage requirements of the task to be assigned are within the platform's task capacity. If they are not within the platform's task capacity, remove the task to be assigned from the task assignment queue and add it to the set of tasks to be executed. Restart step S1 and continue to determine the resource usage requirements of the next task to be assigned in the task assignment queue. If they are within the platform's task capacity, proceed to step S2.

[0120] The step of using the resource description model of the task to be assigned to determine whether the resource usage requirements of the task to be assigned are within the platform's task capabilities includes:

[0121] The platform's task capabilities are represented by a set Φ, and its expression is:

[0122]

[0123] in, Represents the direct product operation, [P min ,P max ] represents the power range of the interference detection communication multi-functional radio frequency system, [F min ,F max [T] indicates the operating frequency range of the interference detection and communication multi-functional radio frequency system. min ,T max ] represents the operating time range of the interference detection and communication multi-functional radio frequency system, [θ min ,θ max ] represents the operating angle range of the interference detection and communication multi-functional radio frequency system. If the resource description model of the i-th task to be assigned... Then it is determined that the resource usage requirements of the task to be assigned are within the platform's task capacity.

[0124] S2, determine whether the current time is within the execution time range of the task to be assigned. If it is, generate a corresponding resource allocation scheme based on the resource usage requirements of the task to be assigned; delete the task to be assigned from the task allocation queue, store the task to be assigned in the execution task set, and start the execution of the task to be assigned; delete the resources allocated to the task to be assigned from the platform task capability range, and update the platform task capability range; after the resource allocation of a certain number of tasks to be assigned in the task allocation queue is completed, proceed to step S3; otherwise, return to step S1.

[0125] S3: After allocating resources to a certain number of tasks in the task allocation queue, determine whether the execution time of the assigned tasks has exceeded the time limit of the assigned tasks. If the execution time limit of an assigned task has exceeded the time limit, remove the task from the task execution set and add the resources allocated to the task to the platform's task capability range. If all tasks in the task allocation queue have completed resource allocation, continue to the tasks in the task execution set and determine whether their resource usage requirements are within the platform's task capability range. If they are within the platform's task capability range, generate a corresponding resource allocation scheme based on the resource usage requirements of the assigned tasks, remove the assigned tasks from the task execution set, and remove the resources allocated to the assigned tasks from the platform's task capability range.

[0126] For both active and passive detection tasks, after generating a resource allocation scheme, based on the task objective information and the resource allocation scheme, an optimization model for the detection antenna array parameters is established with target tracking performance as the objective function and the detection antenna array parameters as the decision variables. The optimization model is then solved to obtain the optimized values ​​of the detection antenna array parameters. These optimized values ​​are then added to the resource allocation scheme for the active or passive detection task, thus updating the resource allocation scheme.

[0127] The parameters of the probe antenna array include the operating state vector, weighting vector, and phase vector of each antenna element in the probe antenna array.

[0128] The optimization model for the probe antenna array parameters is expressed as follows:

[0129] minF(x)

[0130]

[0131] Where F() represents the target tracking error function, x represents the decision vector, and x i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let represent the upper limit of the value of the i-th decision variable, m be the number of decision variables included in the decision vector, Ch represent the chance measure, and g j (x) is the j-th constraint function on the decision vector x, g j0 α is the upper limit of the value of the j-th constraint function of the decision vector x. j and β j Let j represent the confidence level parameter for the j-th constraint function of decision vector x, where j0 is the number of constraint functions for decision vector x.

[0132] The optimization model for the probe antenna array parameters is solved using an optimization solution method.

[0133] The optimization solution method includes artificial intelligence methods, genetic algorithms, particle filtering methods, or convex optimization methods.

[0134] The target tracking error function is characterized by the maximum tracking error for all task targets, or by the sum of the tracking errors for all task targets, or by the tracking errors for all targets.

[0135] When the target tracking error function is characterized by the tracking errors of all targets, the probe antenna array parameter optimization model is a multi-objective optimization mode, which is solved using a multi-objective optimization solution method.

[0136] For active jamming tasks, after obtaining the resource allocation scheme, based on the task objective information and the resource allocation scheme, an optimization model for the jamming antenna array parameters is established with the jamming effect as the objective function and the jamming antenna array parameters as the decision variables. The optimization model is solved to obtain the optimized values ​​of the jamming antenna array parameters. The optimized values ​​of the jamming antenna array parameters are then added to the resource allocation scheme of the active jamming task to complete the update of the resource allocation scheme.

[0137] The parameters of the jamming antenna array include the operating state vector, weighting vector, and phase vector of each antenna element in the jamming antenna array.

[0138] The objective function is to use the interference effect as the objective function and the interference antenna array parameters as the decision variables. An optimization model for the interference antenna array parameters is established, and one of the following corresponding methods is used to achieve this, depending on the type of interference employed:

[0139] For suppressing interference, with the suppression effect as the primary objective function and the interference antenna array parameters as decision variables, an optimization model for the first interference antenna array parameters is established, the expression of which is:

[0140] maxK(x)P H (x)C d (J,S)

[0141]

[0142] Where K(x) is the interference effect coefficient under the condition of decision vector x, P H (x) represents the entropy power of the suppressed interference signal under the condition of decision vector x, C d (J,S) represents the detection factor for suppressing the jamming target, where J is the jamming power received by the target during detection, and S is the target signal power received by the target during detection. i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable.i0 Let p represent the upper limit of the value of the i-th decision variable, m be the number of decision variables contained in the decision vector, and p be the upper limit of the value of the i-th decision variable. j (x) is the j-th constraint function for suppressing interference on the decision vector x, p j0 C is the upper limit of the value of the j-th constraint function for suppressing interference on the decision vector x, and p0 is the number of constraint functions for suppressing interference on the decision vector x; d The formula for calculating (J,S) is (2S+J) / 2S.

[0143] For deception jamming against false targets, the deception jamming effect is taken as the second objective function, and the jamming antenna array parameters are used as decision variables. An optimization model for the second jamming antenna array parameters is established, and its expression is:

[0144] max tK(x)P df (x)P dif (x)

[0145]

[0146] Where K(x) is the interference effect coefficient under the decision vector x, and t is the number of false targets generated by the false target deception interference. P df (x) represents the probability of detecting a false target given the decision vector x, where P is the false target deceiving the target. dif (x) represents the probability that a target misleading an interfering target will identify the false target as the real target given the decision vector x. i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let represent the upper limit of the value of the i-th decision variable, m be the number of decision variables contained in the decision vector, and q be the upper limit of the value of the i-th decision variable. j (x) is the j-th constraint function of the false target deception interference on the decision vector x, q j0 q0 is the upper limit of the value of the j-th constraint function of the false target deception interference on the decision vector x, and q0 is the number of constraint functions of the false target deception interference on the decision vector x.

[0147] For drag-and-spoof interference, with the drag-and-spoof interference effect as the third objective function and the interference antenna array parameters as decision variables, an optimization model for the third interference antenna array parameters is established, the expression of which is:

[0148]

[0149] Among them, L V (dB) represents the interference-to-signal ratio loss after dragging spoofing interference, expressed in dB. The interference-to-signal ratio loss after dragging spoofing interference is used as the dragging spoofing interference effect. V(x) is the dragging velocity under the decision vector x. mB is the maximum velocity value that the target can respond to in order to deceive and interfere. t To reduce the detection bandwidth of the target being deceived or interfered with, x i Let x represent the i-th element in the decision vector, i.e., the i-th decision variable. i0 Let r represent the upper limit of the value of the i-th decision variable, m be the number of decision variables contained in the decision vector, and r be the upper limit of the value of the i-th decision variable. j (x) is the j-th constraint function of drag-and-spoof interference on the decision vector x, r j0 is the upper limit of the value of the j-th constraint function of the dragging deception interference on the decision vector x, and r0 is the number of constraint functions of the dragging deception interference on the decision vector x;

[0150] For solving the parameter optimization model of the interference antenna array, artificial intelligence methods, particle filtering methods, convex optimization methods, or genetic algorithms are used.

[0151] For evaluating the interference effect of smart jamming, the interference effect evaluation methods of drag-and-drop deception jamming or false target deception jamming are adopted, and a corresponding interference antenna array parameter optimization model is established.

[0152] The threat assessment method used to obtain threat information for each task objective includes:

[0153] For each task objective in the task objective information, a threat factor weighting method is used to sum the threat factors of the objective to obtain the threat level information of each objective. For moving targets, the threat factors include distance threat factor, attribute threat factor, speed threat factor, and altitude threat factor. The distance threat factor y... d The calculation formula is as follows:

[0154]

[0155] Where χ is the distance scaling constant, d c Where D is the maximum target detection range of the interference detection and communication multi-functional radio frequency system, and D is the target distance information given in the mission target information or the target distance information detected by the interference detection and communication multi-functional radio frequency system. Attribute threat factor y t The target type information is determined from the mission objective information, which includes aircraft, ships, unidentified targets, high-speed aircraft, etc. The speed threat factor y... v The calculation formula is as follows:

[0156]

[0157] Wherein, κ is a speed proportionality constant, vmax is the maximum target detection speed of the interference detection and communication multi-functional radio frequency system, and v is the target speed information given in the mission target information or the target speed information detected by the interference detection and communication multi-functional radio frequency system.

[0158] The high threat factor y h The calculation formula is as follows:

[0159]

[0160] Where H is the high threat setting value, h is the target height information given in the mission target information or the target height information detected by the interference detection communication multi-functional radio frequency system, and η is the height ratio constant.

[0161] For radar signal targets, the threat factors include range threat factor, signal type threat factor, and radar operational status threat factor. The range threat factor for radar signal targets can be calculated using the same method as for moving targets, or it can be obtained by multiplying the radar distance to the unmanned platform by a scaling factor. The signal type threat factor is determined by the radar signal type, which includes terminal guidance radar signals, fire control radar signals, early warning radar signals, and ground target indication radar signals. The radar operational status threat factor is determined by the radar's operational status, which includes guidance, search, and tracking.

[0162] The threat assessment method used to obtain threat information for each task objective includes:

[0163] Using fuzzy reasoning, threat level information for each task objective is obtained, specifically including:

[0164] The target state information and target attribute information are extracted from the task target information. The target state information and target attribute information are then fuzzified to obtain a fuzzy set in a given domain. Fuzzy inference is performed on the fuzzy set to obtain the fuzzy inference result. The fuzzy inference result is then defuzzified to obtain the threat level information of the task target.

[0165] The fuzzification process refers to mapping a real-valued point to a fuzzy set. Fuzzification methods include single-valued fuzzification, triangular fuzzification, and Gaussian fuzzification.

[0166] The fuzzy reasoning operation refers to the process of deriving a definite conclusion from a fuzzy set according to certain fuzzy reasoning rules. The definite conclusion is the fuzzy reasoning result.

[0167] The fuzzy inference operation can be implemented using the Maddane fuzzy inference method or the Zadeh fuzzy inference method.

[0168] The defuzzification operation maps the fuzzy inference result to clear points. Defuzzification operations include the maximum membership method, the centroid method, and the center-average method.

[0169] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. An unmanned platform-oriented interference detection communication multifunctional radio system, characterized by, The antenna array unit, the digital radio frequency / intermediate frequency exchange network, the signal processing unit, the data exchange network, the data processing and display unit; The antenna array unit includes an antenna radiation unit, a digital T / R component and a power supply; The antenna radiation unit is used to realize the reception and transmission of radio frequency signals, detect the spectrum environment, and obtain spectrum monitoring data; the antenna radiation unit includes a communication antenna array, a detection antenna array and an interference antenna array; The digital T / R component is used to realize low-noise amplification, down-conversion, phase shift and intermediate frequency sampling operations on the signals received by the antenna radiation unit, or waveform generation, phase shift, up-conversion and high-power amplification operations on the signal parameters, or up-conversion, phase shift and high-power amplification operations on the signal waveform; the power supply is used to provide voltage and current for the digital T / R component; The digital T / R component includes a transmission link, a reception link and a transceiver switch, and the digital T / R component is connected with the antenna radiation unit through the transceiver switch; the transmission link and the reception link are connected with the transceiver switch; The transmission link of the digital T / R component includes a signal generator, a phase shifter, an up-converter and a high-power amplifier, which are connected in sequence; the reception link of the digital T / R component includes an intermediate frequency sampler, a phase shifter, a down-converter and a low-noise amplifier, which are connected in sequence; the high-power amplifier and the low-noise amplifier are connected with the transceiver switch; The digital radio frequency / intermediate frequency exchange network is used to select corresponding signals from the reception link of the digital T / R component of the antenna array unit according to the signal selection instruction of the signal processing unit, and send the signals to the signal processing unit, or send the signal parameters and the signal waveform output by the signal processing unit to the corresponding digital T / R component; The signal processing unit is used to realize the signal processing process of detection, communication and interference, and obtain signal processing result data; according to the signal processing requirement, the signal selection instruction is sent to the digital radio frequency / intermediate frequency exchange network; according to the signal processing result data of detection, communication and interference, the signal parameters and the signal waveform are sent to the digital radio frequency / intermediate frequency exchange network; the signal processing result data of detection, communication and interference is sent to the data exchange network; the signal processing unit includes a digital beam forming processing subunit, a radar signal processing subunit, a signal reconnaissance processing subunit, a deception jamming processing subunit, a suppression jamming processing subunit, a smart jamming processing subunit, a modulation and demodulation processing subunit, a resource allocation subunit, a resource monitoring and management subunit and a computing resource subunit; the resource allocation subunit is used to receive the resource use demand information of each subunit included in the signal processing unit and the idle resource information sent by the resource monitoring and management subunit, process the resource use demand information and the idle resource information by using a resource allocation model, generate a resource allocation scheme, and allocate various resources to the corresponding subunits according to the resource allocation scheme; the task types performed by the unmanned platform include active detection task, passive detection task, signal reconnaissance task, active interference task and communication task. For the active detection task or the passive detection task, after generating the resource allocation scheme, according to the task target information and the resource allocation scheme, taking the target tracking performance as an objective function and taking the detection antenna array parameters as decision variables, a detection antenna array parameter optimization model is established, the detection antenna array parameter optimization model is solved, the detection antenna array parameter optimization value is obtained, the detection antenna array parameter optimization value is added to the resource allocation scheme of the active detection task or the passive detection task, and the update of the resource allocation scheme is completed; The detection antenna array parameters include an operating state vector, a weighting vector and a phase vector of each antenna element of the detection antenna array; The detection antenna array parameter optimization model has an expression as follows: min F (x) where F() represents a target tracking error function, x represents a decision vector, x i represents the i-th element in the decision vector, i.e., the i-th decision variable, x i0 represents the upper limit of the i-th decision variable, m is the number of decision variables contained in the decision vector, Ch represents a chance measure, g j (x) is the j-th constraint function for the decision vector x, g j0 is the upper limit of the j-th constraint function for the decision vector x, a j and β j represent the confidence level parameters of the j-th constraint function for the decision vector x, j0 is the number of constraint functions for the decision vector x; The data exchange network is used for realizing data exchange and transmission between each subunit included in the signal processing unit and between the signal processing unit and the data processing and display unit. The data processing and display unit is used for classifying and processing the signal processing result data and displaying, generating and sending communication sending data to the data exchange network.

2. The unmanned platform-oriented interference detection communication multifunctional radio frequency system of claim 1, wherein the radar signal processing subunit, the signal reconnaissance processing subunit and the modulation and demodulation processing subunit generate corresponding radar signal selection instructions, interference signal selection instructions and communication signal selection instructions according to respective signal processing requirements, and respectively acquire signals received by the detection antenna array, signals received by the interference antenna array and signals received by the communication antenna array from the antenna array surface unit through the digital radio frequency / intermediate frequency exchange network by using the corresponding signal selection instructions; The digital beam forming processing subunit is used for completing receiving beam forming processing of output signals of a receiving link of a digital T / R component of the antenna array surface unit and transmitting beam forming processing of input signals of a transmitting link of the digital T / R component of the antenna array surface unit; The digital beam forming processing subunit, the resource allocation subunit and the spectrum management unit are connected with the digital radio frequency / intermediate frequency exchange network, and the digital beam forming processing subunit is connected with the radar signal processing subunit, the signal reconnaissance processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the smart jamming processing subunit and the modulation and demodulation processing subunit; The radar signal processing subunit is used for completing pulse compression, target detection, track filtering, distance measurement and angle measurement processing of the signals received by the detection antenna array, and obtaining target motion parameters; The signal reconnaissance processing subunit is used for completing interception, parameter measurement, pulse sorting and threat identification processing of the signals received by the interference antenna array, obtaining signal reconnaissance processing results, and sending the signal reconnaissance processing results to the deception jamming processing subunit, the suppression jamming processing subunit and the smart jamming processing subunit. ​ The deception jamming processing subunit, the suppression jamming processing subunit and the smart jamming processing subunit are used for generating deception jamming signal waveforms or parameters, suppression jamming signal waveforms or parameters and smart jamming signal waveforms or parameters respectively according to the signal reconnaissance processing result; The modulation and demodulation processing subunit is used for completing equalization, demodulation, decoding and detection processing of signals received by the communication antenna array, encoding and modulating communication transmission data generated by the receiving data processing and display unit to obtain modulated waveforms, and transmitting the modulated waveforms to the digital radio frequency / intermediate frequency exchange network; The computing resource subunit is used for receiving computing requirements of other subunits, completing relevant computing and sending the computing result to the corresponding subunit; Each subunit included in the signal processing unit is connected with the data exchange network; The resource monitoring and management subunit is used for monitoring hardware resource usage of the antenna array unit and the signal processing unit to obtain occupied resource information and idle resource information, sending the idle resource information to the resource allocation subunit, generating a spectrum management scheme by using a spectrum allocation model according to the received resource allocation scheme of the resource allocation subunit and the spectrum monitoring data of the antenna radiation unit, and sending the spectrum management scheme to the radar signal processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the smart jamming processing subunit and the modulation and demodulation processing subunit; The radar signal processing subunit, the deception jamming processing subunit, the suppression jamming processing subunit, the smart jamming processing subunit and the modulation and demodulation processing subunit determine the frequency bands used by them respectively according to the received spectrum management scheme; The signal processing result data includes target motion parameter signals, reconnaissance processing results, deception jamming signal waveforms or parameters, suppression jamming signal waveforms or parameters, smart jamming signal waveforms or parameters, modulated waveforms and resource allocation schemes.

3. The unmanned platform-centric interference detection and communication multi-functional radio system of claim 2, wherein, The resource allocation subunit is used for receiving resource usage demand information of other subunits included in the signal processing unit and idle resource information sent by the resource monitoring and management subunit, processing the resource usage demand information and the idle resource information by using a resource allocation model, and generating a resource allocation scheme, including: The resource allocation subunit obtains unmanned platform working mode information and task target information from resource usage demand, compares the idle resource information and the resource usage demand information, generates a corresponding resource allocation scheme according to the resource usage demand information if the idle resource information contains the resource usage demand information, and generates a resource allocation scheme according to the unmanned platform working mode information and the task target information if the idle resource information does not contain the resource usage demand information.

4. The unmanned platform-centric interference detection and communication multi-functional radio system of claim 3, wherein, The resource allocation subunit obtains unmanned platform working mode information and task target information from resource usage demand, compares the idle resource information and the resource usage demand information, generates a corresponding resource allocation scheme according to the resource usage demand information if the idle resource information contains the resource usage demand information, and generates a resource allocation scheme according to the unmanned platform working mode information and the task target information if the idle resource information does not contain the resource usage demand information. The task target information is extracted from the task target information, and the allocation priority of the to-be-allocated task is set according to the unmanned platform working mode information. The unmanned platform working mode includes a measurement mode, an interference mode and a silence mode. When the unmanned platform is in the measurement mode, the active detection task is set as the first priority, and the remaining tasks are set as the second priority. When the unmanned platform is in the interference mode, the signal reconnaissance task and the active interference task are set as the first priority, and the remaining tasks are set as the second priority. In the first priority, the signal reconnaissance task is preferentially allocated. When the unmanned platform is in the silence mode, the passive detection task and the signal reconnaissance task are set as the first priority, and only the passive detection task and the signal reconnaissance task are allocated; The threat degree information of each task target is obtained by using a threat degree evaluation method on the task target information; The to-be-allocated task information and corresponding resource demand information are extracted from the task target information, and a task allocation queue is established by using the to-be-allocated task information and the corresponding resource demand information. The task allocation queue is a sequence composed of to-be-allocated tasks. A resource description model of the to-be-allocated task is established according to the resource demand information of each to-be-allocated task in the task allocation queue. An execution task set and a to-be-executed task set are established; The to-be-allocated tasks in the task allocation queue are sorted according to their allocation priorities to obtain a task allocation queue sequence. In the task allocation queue sequence, the to-be-allocated task with a high allocation priority is arranged in front, and the tasks with the same allocation priority are sorted according to the threat degree of the corresponding task target. The to-be-allocated task with a high threat degree of the task target is arranged in front. A platform task capability range is established according to the idle resource information. All the to-be-allocated tasks in the task allocation queue sequence are sequentially allocated resources according to their order in the task allocation queue sequence to sequentially obtain a resource allocation scheme of each to-be-allocated task. A resource allocation scheme is generated by using the resource allocation schemes of all the to-be-allocated tasks.

5. The unmanned platform-centric interference detection and communication multi-functional radio system of claim 4, wherein, The method for allocating resources to the to-be-allocated tasks in the task allocation queue sequence according to their order in the task allocation queue sequence to sequentially obtain a resource allocation scheme of each to-be-allocated task, comprises the following steps: S1, it is judged whether the resource use demand of the to-be-allocated task is within the platform task capability range by using the resource description model of the to-be-allocated task. If not, the to-be-allocated task is deleted from the task allocation queue sequence, and the to-be-allocated task is added to the to-be-executed task set. Step S1 is restarted to continue judging the resource use demand of the next to-be-allocated task in the task allocation queue sequence. If it is within the platform task capability range, step S2 is entered. S2, judging whether the current time is in the execution time range of the to-be-allocated task, if in the execution time range of the to-be-allocated task, generating a corresponding resource allocation scheme according to resource use demand information of the to-be-allocated task; deleting the to-be-allocated task from the task allocation queuing sequence, storing the to-be-allocated task into an execution task set, and making the to-be-allocated task start execution; deleting the allocated resource for the to-be-allocated task from the platform task capability range, and updating the platform task capability range; when resource allocation of a certain number of to-be-allocated tasks in the task allocation queuing sequence is completed, entering step S3, otherwise, returning to step S1; S3, after resource allocation of a certain number of to-be-allocated tasks in the task allocation queuing sequence is completed, judging whether the current time has exceeded the execution time range of the allocated resource task, if the execution time range of the certain allocated resource task is exceeded, deleting the task from the execution task set, and adding the allocated resource for the task to the platform task capability range; if all to-be-allocated tasks in the task allocation queuing sequence have completed resource allocation, continuing to judge whether resource use demand of a task in the to-be-executed task set is in the platform task capability range, if in the platform task capability range, generating a corresponding resource allocation scheme according to resource use demand information of the to-be-allocated task, deleting the to-be-allocated task from the to-be-executed task set, and deleting the allocated resource for the to-be-allocated task from the platform task capability range.

6. The unmanned platform-centric interference detection and communication multi-functional radio system of claim 4, wherein, For the active interference task, after obtaining the resource allocation scheme, a parameter optimization model of the interference antenna array is established according to the task target information and the resource allocation scheme, with the interference effect as a target function and the interference antenna array parameter as a decision variable, the parameter optimization model of the interference antenna array is solved to obtain an optimized value of the interference antenna array parameter, the optimized value of the interference antenna array parameter is added to the resource allocation scheme of the active interference task, and updating of the resource allocation scheme is completed. The interference antenna array parameter includes an operating state vector, a weighting vector and a phase vector of each antenna element of the interference antenna array.

7. The unmanned platform-centric interference detection and communication multi-functional radio system of claim 6, wherein, For the suppression interference, a first interference antenna array parameter optimization model is established with the suppression interference effect as a first target function and the interference antenna array parameter as a decision variable, and an expression of the first interference antenna array parameter optimization model is as follows: where K(x) is the interference effect coefficient under the condition of decision vector x, P H (x) is the entropy power of the jamming signal under the condition of decision vector x, C d (J, S) is the detection factor of the jamming target, J is the received jamming power of the jamming target when it is detected, S is the received target signal power of the jamming target when it is detected, x i represents the i-th element in the decision vector, i.e. the i-th decision variable, x i0 represents the upper limit of the value of the i-th decision variable, m is the number of decision variables contained in the decision vector, p j (x) is the j-th constraint function of the jamming to the decision vector x, p j0 is the upper limit of the value of the j-th constraint function of the jamming to the decision vector x, p0 is the number of constraint functions of the jamming to the decision vector x.

8. The unmanned platform-centric interference detection and communication multi-functional radio system of claim 6, wherein, For the false target deception jamming, a second interference antenna array parameter optimization model is established with the false target deception jamming effect as a second target function and the interference antenna array parameter as a decision variable, and an expression of the second interference antenna array parameter optimization model is as follows: where K(x) is the interference effect coefficient under the decision vector x, t is the number of false targets generated by the false target deception jamming; P df (x) is the detection probability of the target of the false target deception jamming under the decision vector x, P dif (x) is the probability of identifying the false target as the true target by the target of the false target deception jamming under the decision vector x, x i represents the i-th element in the decision vector, i.e. the i-th decision variable, x i0 represents the upper limit of the value of the i-th decision variable, m is the number of decision variables contained in the decision vector, q j (x) is the j-th constraint function of the decision vector x of the false target deception jamming, q j0 is the upper limit of the value of the j-th constraint function of the decision vector x of the false target deception jamming, q0 is the number of constraint functions of the decision vector x of the false target deception jamming.

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