Unmanned aerial vehicle pilot short-distance control method and control system based on satellite flash technology

Abstract

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle pilot short-distance control method and control system based on the satellite flash technology, and the method comprises the steps: building directional wireless connection between a real pilot layer and a dummy pilot relay layer, and optimizing a communication frequency band and a signal waveform in real time; performing feature fusion on the real pilot operation behavior features and a preset dummy pilot behavior pattern library; performing multi-hop encryption transmission processing on the camouflage control data stream to form an encrypted camouflage data stream, and then performing multi-path diversity transmission on an unmanned aerial vehicle execution layer; and after receiving the encrypted camouflage data stream, the unmanned aerial vehicle execution layer decrypts and authenticates the encrypted camouflage data stream and then executes flight control operation. According to the invention, an enemy can be effectively prevented from positioning a real pilot through a wireless signal, reliable transmission of a control instruction can be ensured in a complex electromagnetic environment, and an effective solution is provided for an unmanned aerial vehicle control task in a high-confrontation environment.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle control technology, and in particular to a short-distance control method and control system for unmanned aerial vehicle pilots based on star flash technology. Background Art

[0002] In highly confrontational environments such as electronic countermeasures, the strike capability and concealment of drones are crucial. However, drone pilots often face the risk of being located and attacked by the enemy during operation, especially during the transmission of wireless signals, the pilot's position is easily exposed, which leads to the indirect destruction of the drone. Traditional drone control methods mainly rely on a single wireless communication link, whose signal characteristics are easily detected and interfered by the enemy, and it is difficult to meet the concealment and security requirements in highly confrontational environments. In order to solve this problem, there is an urgent need for a drone control method that can achieve low latency and high concealment within a short distance to enhance the survivability of pilots and the task execution efficiency of drones. As an emerging short-range wireless communication technology, Star Flash technology has low latency, high anti-interference and dynamic spectrum perception capabilities, and can provide reliable communication link support for drone control. Based on this, the present invention proposes a short-range control method and control system for drone pilots based on Star Flash technology, which realizes the concealment of the pilot's position and the security of the control instructions by constructing a layered communication architecture of a real pilot layer, a dummy pilot relay layer and a drone execution layer, combined with dynamic camouflage and multi-hop encryption mechanisms. Summary of the invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a short-distance control method and control system for UAV pilots based on the star flash technology.

[0004] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: The first aspect of the present invention discloses a short-distance control method for a UAV pilot based on the star flash technology, comprising the following steps: Establish a directional wireless connection between the real pilot layer and the dummy pilot relay layer, optimize the communication frequency band and signal waveform in real time, and generate an initial control command signal with dynamic camouflage properties; When the dummy pilot relay layer receives the initial control command signal, it fuses the operation behavior characteristics of the real pilot with the preset dummy pilot behavior pattern library to generate a camouflaged control data stream; Implementing multi-hop encrypted transmission processing on the camouflaged control data stream to form an encrypted camouflaged data stream, and then transmitting it to the drone execution layer in a multi-path diversity manner, while continuously optimizing the spatiotemporal distribution parameters during the transmission process; After receiving the encrypted disguised data stream, the drone execution layer decrypts and authenticates the encrypted disguised data stream and then performs flight control operations.

[0005] Preferably, a directional wireless connection is established between the real pilot layer and the dummy pilot relay layer, the communication frequency band and signal waveform are optimized in real time, and an initial control command signal with dynamic camouflage properties is generated, specifically: Perform dynamic spectrum sensing on the electromagnetic environment within the preset range of the real pilot layer, extract the interference intensity and channel characteristic parameters of the available frequency band in real time, and generate dynamic spectrum sensing results; Based on the sensing results, the optimal frequency band for anti-interference is selected and the time-frequency resource allocation strategy is matched to generate a star flash communication link configuration instruction including a frequency hopping sequence and waveform modulation parameters; According to the configuration instructions, the Starflash transceiver module is driven to construct a directional beam, and combined with the preset UAV control instruction coding protocol, the original control signal of the real pilot is converted into a Starflash baseband signal with dynamic time-frequency parameters; Randomized pulse position offset and pseudo-noise envelope characteristics are embedded in the Starflash baseband signal to confuse the signal's time-frequency domain characteristics, generate an initial control command signal with dynamic camouflage properties, and transmit it to the dummy pilot relay layer through the Starflash communication link.

[0006] Preferably, after the dummy pilot relay layer receives the initial control command signal, it fuses the real pilot's operation behavior characteristics with the preset dummy pilot behavior pattern library to generate a camouflaged control data stream, specifically: A camouflage signal generating unit is configured at the dummy pilot relay layer to receive the initial control command signal and analyze its time-frequency domain characteristic parameters to generate an initial signal characteristic vector; Based on a preset randomization rule, a dynamic camouflage parameter set including random delay jitter and power fluctuation characteristics is generated, and the camouflage parameter set is superimposed with the initial signal feature vector to generate a dynamic camouflage signal feature; Deploy a behavior pattern analysis module at the dummy pilot relay layer to extract the real pilot's operation behavior characteristics, including operation frequency, command sequence, and response time, and generate a real pilot's behavior feature vector; Matching the real pilot behavior feature vector with a preset dummy pilot behavior pattern library, screening out the dummy pilot behavior pattern with the greatest similarity to the real pilot behavior feature, and generating a behavior pattern matching result; Based on the matching result, the dynamic camouflage signal feature is subjected to behavioral consistency optimization processing to generate a camouflage control signal including multi-node behavioral features; The camouflaged control signal is feature-fused with the initial control command signal to form a camouflaged control data stream with multi-node behavior consistency, and is transmitted to the next relay node or drone execution layer through the Star Flash communication link.

[0007] Preferably, the camouflage control data stream is subjected to multi-hop encrypted transmission processing to form an encrypted camouflage data stream, and then multi-path diversity transmission is performed to the drone execution layer, and the time-space distribution parameters are continuously optimized during the transmission process, specifically: Deploy quantum key distribution service nodes in the Xingshan communication network, build a quantum key resource pool between relay nodes based on the quantum entanglement pair generation protocol, generate quantum key slices dynamically bound to each relay node, and form a key source for layered encryption; Extract the dynamic camouflage signal features in the camouflage manipulation data stream at each relay node, generate a layered encryption key in combination with the quantum key slice, inject the layered encryption key into the encryption engine, perform segmented asymmetric encryption on the data stream, and generate a layered encrypted ciphertext; Performing spatiotemporal correlation encoding on the layered encrypted ciphertext and the dynamic disguised signal feature to generate a composite signal structure including a quantum key fingerprint and a dynamic spatiotemporal label; Through the multi-path diversity transmission module of the Star Flash link, the composite signal structure is split into multiple sub-signal streams carrying independent camouflage features, and the multiple sub-signal streams carrying independent camouflage features are transmitted to the drone execution layer through multi-path diversity; According to the real-time position feedback of the UAV executive layer, the transmission timing and power spectrum density distribution of the sub-signals are dynamically adjusted on the transmission path of the star flash link to generate a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment. The spatiotemporal distribution parameters of the dynamic camouflage signal characteristics are optimized in real time according to the spatiotemporal chaos parameter set, and the optimized spatiotemporal distribution parameters are synchronized to the behavior pattern library of the quantum key distribution service node and the dummy pilot relay layer through a cross-layer feedback mechanism, forming a closed-loop optimized encryption camouflage collaborative mechanism.

[0008] Preferably, according to the real-time position feedback of the UAV executive layer, the transmission timing and power spectrum density distribution of the sub-signal are dynamically adjusted on the transmission path of the star flash link to generate a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment, specifically: Collect the real-time location nodes of the drone and the electromagnetic interference intensity it is subjected to; map the electromagnetic interference intensity to initial value sensitive parameters to generate an initial chaotic parameter sequence; The initial chaotic parameter sequence is input into the dynamic cognitive graph engine, and combined with the real-time position node of the drone, the transmission timing of the sub-signal is subjected to phase chaos modulation, and the power spectrum density distribution is subjected to dynamic shaping in the fractional Fourier transform domain to generate a power-timing joint control parameter with time-varying non-stationary characteristics; According to the channel response characteristics on the transmission path, the power-timing joint control parameters are combined with multiple objectives to generate an initial spatiotemporal chaos parameter set; The initial spatiotemporal chaotic parameter set is injected into the sub-signal transmission module, and the signal bit error rate, channel capacity and camouflage concealment are synchronously collected to construct dynamic parameter evaluation indicators; If the dynamic parameter evaluation index meets the preset index requirements, the initial spatiotemporal chaos parameter set is converted into a spatiotemporal chaos parameter set; otherwise, the above steps are repeated; The spatiotemporal chaotic parameter set is synchronized to the quantum key distribution service node and the dynamic camouflage module through a quantum security tunnel as the spatiotemporal reference parameter for the next round of multi-hop transmission, thereby realizing cross-layer coordination of encryption camouflage and chaotic modulation.

[0009] Preferably, the spatiotemporal distribution parameters of the dynamic camouflage signal characteristics are optimized in real time according to the spatiotemporal chaos parameter set, specifically: Performing feature decomposition on the spatiotemporal chaotic parameter set, extracting core feature parameters including time-varying phase, power spectrum density and chaotic attractor trajectory, and generating a spatiotemporal feature vector; Based on the spatiotemporal feature vector, the dynamic camouflage signal feature is reconstructed, the chaotic attractor trajectory is mapped to the random jitter feature of the signal in the time-frequency domain, and a reconstructed camouflage signal containing spatiotemporal chaotic characteristics is generated; Based on the UAV position feedback and electromagnetic environment change data, dynamic features including multipath interference intensity, spectrum occupancy and channel response characteristics are extracted to generate an environmental dynamic feature matrix; Based on the environmental dynamic characteristic matrix, a fuzzy rule base including transmission timing, power spectrum density and signal concealment index is constructed to generate a fuzzy control rule set; Inputting the time-space distribution parameters of the reconstructed camouflage signal into the fuzzy control rule set, evaluating its matching degree with the current electromagnetic environment, and generating a parameter matching degree evaluation vector; Based on the parameter matching evaluation vector, the matching relationship between the transmission timing and the power spectrum density is dynamically optimized to generate an optimized spatiotemporal distribution parameter set.

[0010] Preferably, the flight control operation is performed after the encrypted disguised data stream is decrypted and authenticated, specifically: When the drone execution layer receives the encrypted disguised data stream from the dummy pilot relay layer, it extracts the composite signal structure containing the dynamic disguised signal characteristics and the quantum key fingerprint to generate the data stream to be decrypted; Based on the quantum key fingerprint, the corresponding quantum key slice is obtained through the quantum key distribution service node, the data stream to be decrypted is input into the quantum decryption engine, and the layered asymmetric decryption operation is performed to restore the disguised manipulated data stream; Performing spatiotemporal chaos inverse mapping processing on the camouflage manipulation data stream, extracting its dynamic camouflage signal features, performing matching verification with a preset camouflage feature library, and generating feature matching results; Verify the consistency of the behavior characteristics of the control command with the preset dummy pilot behavior pattern library based on the feature matching result, and generate a command legitimacy authentication result; If the command legitimacy authentication result is legal, the restored control command is input into the UAV flight control module to execute the flight control operation; If the command legitimacy authentication result is illegal, the exception handling mechanism is triggered, a safety warning message is generated and the flight control operation is suspended. At the same time, the warning information is synchronized to the real pilot layer and the dummy pilot relay layer through the quantum security tunnel.

[0011] The torso, limbs and head of the dummy pilot adopt a snap-on connection design; the dummy pilot has a built-in multi-layer heating plate array, which is arranged according to the thermodynamic distribution law of the human body to simulate the temperature difference characteristics of the head, chest and limbs.

[0012] The second invention of the present invention discloses a short-distance control system for drone pilots based on Star Flash technology. The control system includes a memory and a processor. The memory stores a program for the short-distance control method for drone pilots based on Star Flash technology. When the program for the short-distance control method for drone pilots based on Star Flash technology is executed by the processor, any step of the short-distance control method for drone pilots based on Star Flash technology is implemented.

[0013] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: establishing a directional wireless connection between the real pilot layer and the dummy pilot relay layer, optimizing the communication frequency band and signal waveform in real time, and generating an initial control command signal with dynamic camouflage attributes; when the dummy pilot relay layer receives the initial control command signal, the real pilot operation behavior characteristics are integrated with the preset dummy pilot behavior pattern library to generate a camouflage control data stream; after the camouflage control data stream is subjected to multi-hop encrypted transmission processing to form an encrypted camouflage data stream, multi-path diversity transmission is performed to the drone execution layer, and the time-space distribution parameters are continuously optimized during the transmission process; after the drone execution layer receives the encrypted camouflage data stream, the encrypted camouflage data stream is decrypted and authenticated to perform flight control operations. The present invention can not only effectively prevent the enemy from locating the real pilot through wireless signals, but also ensure the reliable transmission of control instructions in a complex electromagnetic environment, and provide an effective solution for drone control tasks in a high-confrontation environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0015] Figure 1 This is a flow chart of the first method of the short-distance control method for drone pilots; Figure 2 This is a flow chart of the second method of the short-distance control method for drone pilots; Figure 3 This is the system block diagram of the short-distance control system for UAV pilots. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0018] like Figure 1 As shown, the first aspect of the present invention discloses a short-distance control method for a UAV pilot based on the star flash technology, comprising the following steps: S102, establishing a directional wireless connection between the real pilot layer and the dummy pilot relay layer, optimizing the communication frequency band and signal waveform in real time, and generating an initial control command signal with dynamic camouflage properties; S104, after the dummy pilot relay layer receives the initial control command signal, it fuses the operation behavior characteristics of the real pilot with the preset dummy pilot behavior pattern library to generate a camouflaged control data stream; S106, performing multi-hop encryption transmission processing on the camouflage control data stream to form an encrypted camouflage data stream, and then performing multi-path diversity transmission to the drone execution layer, while continuously optimizing the spatiotemporal distribution parameters during the transmission process; S108. After receiving the encrypted disguised data stream, the drone execution layer decrypts and authenticates the encrypted disguised data stream and then performs flight control operations.

[0019] Preferably, a directional wireless connection is established between the real pilot layer and the dummy pilot relay layer, the communication frequency band and signal waveform are optimized in real time, and an initial control command signal with dynamic camouflage properties is generated, such as Figure 2 As shown, specifically: S202, performing dynamic spectrum sensing on the electromagnetic environment within a preset range of the real pilot layer, extracting the interference intensity and channel characteristic parameters of the available frequency band in real time, and generating dynamic spectrum sensing results; It should be noted that a multi-channel spectrum sensing module is deployed in a preset area to collect spectrum data in the electromagnetic environment in real time, including the signal strength, noise level and multipath interference characteristics of each frequency band; the collected spectrum data is processed by fast Fourier transform (FFT) to extract frequency domain feature parameters and generate spectrum feature vectors; based on the spectrum feature vectors, the interference intensity index of each frequency band is analyzed, and combined with the channel response characteristics analysis, the channel characteristic parameters are extracted, including signal-to-noise ratio, delay spread and Doppler frequency shift, so as to generate dynamic spectrum sensing results.

[0020] It should be noted that dynamic spectrum sensing of the electromagnetic environment within the preset range of the real pilot layer refers to the real-time collection and analysis of electromagnetic environment data in the preset area through the spectrum sensing module deployed in the real pilot layer, including the occupancy of available frequency bands, interference intensity, channel characteristic parameters and other information. This process can dynamically identify the best communication frequency band in the current environment and adjust the communication strategy in real time to avoid interference and optimize signal transmission quality. Through dynamic spectrum sensing, the system can quickly adapt to the complex and changing electromagnetic environment, and provide accurate data support for subsequent frequency band screening, signal waveform optimization and dynamic camouflage, thereby ensuring the concealment and reliability of drone control instructions in a confrontational environment. Among them, the preset area can usually be set to be centered on the pilot, with a radius of 500 meters to 2 kilometers, and the specific value can be flexibly adjusted according to mission requirements and equipment performance.

[0021] S204, based on the sensing result, selecting the best frequency band for anti-interference and matching the time-frequency resource allocation strategy, and generating a star flash communication link configuration instruction including a frequency hopping sequence and waveform modulation parameters; Among them, the time-frequency resource allocation strategy refers to a method of dynamically allocating time (time slots) and frequency (frequency bands) resources in a wireless communication system according to spectrum sensing results and communication requirements to optimize communication performance and resource utilization. Specifically, it includes: determining the best frequency band based on the interference intensity and channel characteristics of the available frequency band; reasonably allocating time slot resources in combination with the needs of communication tasks to avoid signal conflicts and resource waste; and ensuring the reliability and efficiency of signal transmission by dynamically adjusting bandwidth and modulation parameters.

[0022] It should be noted that the dynamic spectrum sensing results are analyzed to screen out the frequency bands with the lowest interference intensity and the best channel characteristics as candidate frequency bands; in combination with the preset communication requirements and environmental constraints, an adaptive time-frequency resource allocation strategy is adopted to allocate time slots and bandwidth resources to the candidate frequency bands; a random frequency hopping sequence is generated according to the allocated time slots and bandwidth resources of the candidate frequency bands, and the optimal modulation method and parameters are determined to generate the Star Flash communication link configuration instructions containing the frequency hopping sequence and waveform modulation parameters; the configuration instructions are injected into the Star Flash transceiver module to build a directional communication link with strong anti-interference and high concealment.

[0023] S206, driving the Starflash transceiver module to construct a directional beam according to the configuration instruction, and converting the original control signal of the real pilot into a Starflash baseband signal with dynamic time-frequency parameters in combination with a preset UAV control instruction coding protocol; The preset drone control command coding protocol refers to a set of standardized coding rules designed in advance for drone control commands, which is used to convert the pilot's original control signal into a digital signal suitable for wireless transmission. The protocol includes data encapsulation format, channel coding method, error correction mechanism, and command priority setting, aiming to ensure the integrity, reliability, and efficiency of control commands.

[0024] It should be noted that according to the frequency hopping sequence and waveform modulation parameters in the configuration instructions, the RF front end of the Starflash transceiver module is initialized, and the carrier frequency, modulation mode and transmission power are configured; and according to the preset beam pointing, a directional beam is generated to ensure the directionality and anti-interference capability of signal transmission; the original control signal of the real pilot is input into the UAV control command encoding module, and the data is encapsulated and channel encoded according to the preset coding protocol to generate a baseband data stream; finally, the baseband data stream is mapped with the dynamic time-frequency parameters to generate a Starflash baseband signal with frequency hopping characteristics and waveform modulation characteristics, preparing for subsequent transmission.

[0025] S208. Embed randomized pulse position offset and pseudo-noise envelope characteristics in the Starflash baseband signal to confuse the signal's time-frequency domain characteristics, generate an initial control command signal with dynamic camouflage properties, and transmit it to the dummy pilot relay layer through the Starflash communication link.

[0026] Exemplarily, a randomized pulse position offset sequence with a length of 1024 is generated by a pseudo-random sequence generator, and the sequence is superimposed with the time domain pulse position of the star flash baseband signal to randomly offset the pulse position within the range of ±10 microseconds, and a pseudo-noise envelope feature with a bandwidth of 5MHz and a power spectrum density of -50dBm / Hz is generated, which is convolved with the frequency domain features of the star flash baseband signal to make the signal spectrum present a random distribution. Finally, the processed signal is input into the time-frequency domain obfuscation module, and the time-frequency domain features are reconstructed through fast Fourier transform (FFT) and inverse transform (IFFT) to generate an initial control command signal with dynamic camouflage properties, wherein the signal features are highly similar to the background noise, thereby improving the concealment and anti-detection capabilities of the signal.

[0027] In summary, this method solves the technical problem of drone pilots being located by the enemy during short-distance control due to the exposure of wireless signal characteristics. Through dynamic spectrum sensing, anti-interference frequency band screening and dynamic time-frequency parameter optimization, combined with randomized pulse position offset and pseudo-noise envelope characteristics, an initial control command signal with dynamic camouflage properties is generated, which improves the concealment and anti-interference capabilities of signal transmission, effectively avoids the enemy's detection of the real pilot's position, enhances the pilot's survivability, and ensures the reliable transmission of control commands in a highly confrontational environment.

[0028] Preferably, after the dummy pilot relay layer receives the initial control command signal, it fuses the real pilot's operation behavior characteristics with the preset dummy pilot behavior pattern library to generate a camouflaged control data stream, specifically: A camouflage signal generating unit is configured at the dummy pilot relay layer to receive the initial control command signal and analyze its time-frequency domain characteristic parameters to generate an initial signal characteristic vector; Based on a preset randomization rule, a dynamic camouflage parameter set including random delay jitter and power fluctuation characteristics is generated, and the camouflage parameter set is superimposed with the initial signal feature vector to generate a dynamic camouflage signal feature; Among them, the preset randomization rules refer to a set of instructions for generating randomized features that are pre-configured in the dummy pilot relay layer, and their purpose is to provide a variety of random parameters for signal camouflage. Including linear congruential random number generators, Gaussian distribution generators, Poisson distribution generators, etc., which can generate a variety of randomized feature parameters such as delay jitter, power fluctuations, and phase offsets. The system can dynamically generate camouflage parameters that are highly similar to the real signal characteristics, thereby effectively confusing the enemy's identification and positioning of the signal, and enhancing the signal's concealment and anti-detection capabilities.

[0029] Exemplarily, a linear congruential random number generator is used to generate a delay jitter parameter with a range of ±5 milliseconds, and a power fluctuation parameter is generated through a Gaussian distribution with a fluctuation range of ±3dB. The generated delay jitter and power fluctuation parameters are encapsulated as a dynamic camouflage parameter set; then, the initial signal feature vector and the dynamic camouflage parameter set are input into the signal superposition module, and the dynamic camouflage signal features are generated through superposition processing by time domain convolution and frequency domain weighting algorithm; finally, the processed signal features are input into the verification module to ensure that they meet the preset concealment indicators (such as signal similarity ≥ 90%), and generate dynamic camouflage signal features that can be used for subsequent transmission.

[0030] Deploy a behavior pattern analysis module at the dummy pilot relay layer to extract the real pilot's operation behavior characteristics, including operation frequency, command sequence, and response time, and generate a real pilot's behavior feature vector; Matching the real pilot behavior feature vector with a preset dummy pilot behavior pattern library, screening out the dummy pilot behavior pattern with the greatest similarity to the real pilot behavior feature, and generating a behavior pattern matching result; Among them, the preset dummy pilot behavior pattern library refers to a database pre-built in the dummy pilot relay layer that contains a variety of virtual pilot operation behavior characteristics. Its purpose is to provide a variety of camouflage references for the real pilot operation behavior. The behavior pattern library includes characteristic parameters such as operation frequency, instruction sequence, response time, etc., which are generated by simulating the operation habits and task requirements of different pilots. During the signal camouflage process, the system selects patterns similar to the behavior characteristics of real pilots from the library to generate camouflaged control signals with multi-node behavior consistency, thereby effectively confusing the enemy's identification and positioning of the real pilot, and enhancing the concealment and confusion of the control signal.

[0031] Based on the matching result, the dynamic camouflage signal feature is subjected to behavioral consistency optimization processing to generate a camouflage control signal including multi-node behavioral features; It should be noted that, based on the behavior pattern matching results, the behavior pattern parameters of the dummy pilot with the highest similarity to the behavior characteristics of the real pilot are extracted, including the operation frequency (such as 2Hz), command sequence (such as "ascend-turn left-descend") and response time (such as 500ms); secondly, the behavior pattern parameters are input into the signal optimization module to adjust the dynamic camouflage signal characteristics so that its time domain and frequency domain characteristics are consistent with the behavior pattern of the dummy pilot.

[0032] The camouflaged control signal is feature-fused with the initial control command signal to form a camouflaged control data stream with multi-node behavior consistency, and is transmitted to the next relay node or drone execution layer through the Star Flash communication link.

[0033] In summary, this method generates a camouflaged control data stream with multi-node behavior consistency by fusing the operating behavior characteristics of the real pilot with the preset dummy pilot behavior pattern library, thereby improving the concealment and confusion of the control signal, effectively confusing the operating behavior characteristics of the real pilot, making it difficult for the enemy to locate the real pilot through signal analysis, and enhancing the pilot's survivability and the safety of the UAV's mission execution.

[0034] Preferably, the camouflage control data stream is subjected to multi-hop encrypted transmission processing to form an encrypted camouflage data stream, and then multi-path diversity transmission is performed to the drone execution layer, and the time-space distribution parameters are continuously optimized during the transmission process, specifically: Deploy quantum key distribution service nodes in the Xingshan communication network, build a quantum key resource pool between relay nodes based on the quantum entanglement pair generation protocol, generate quantum key slices dynamically bound to each relay node, and form a key source for layered encryption; Among them, the quantum entangled pair generation protocol refers to a standardized method that uses the entanglement phenomenon in quantum mechanics to generate one or more pairs of correlated quantum states (such as photon pairs) through specific physical equipment and operation steps. These quantum states remain correlated after being separated in space, and any measurement of one of the quantum states will instantly affect the state of the other quantum state. Common protocols include the BB84 protocol and the E91 protocol, which generate secure and non-copyable quantum keys through the preparation, transmission and measurement of quantum states.

[0035] Exemplarily, the BB84 protocol or the E91 protocol is used to generate a pair of quantum keys with a length of 256 bits, and the keys are distributed to each relay node through the quantum channel. In each relay node, the received quantum key is divided into multiple slices of 128 bits in length, and each slice is dynamically bound to a specific transmission period (such as 10 seconds) and a task type (such as reconnaissance, interference). The generated key slices are stored in the local key resource pool, and a dynamic identifier is added to it to ensure that it can be called in real time during the transmission process; finally, the key resource pool is monitored and updated through the quantum key management system to ensure the availability and security of the key resources, forming a key source for layered encryption.

[0036] Extract the dynamic camouflage signal features in the camouflage manipulation data stream at each relay node, generate a layered encryption key in combination with the quantum key slice, inject the layered encryption key into the encryption engine, perform segmented asymmetric encryption on the data stream, and generate a layered encrypted ciphertext; Among them, the encryption engine (such as OpenSSL, Libsodium, QKD system) refers to a hardware or software module specifically used to perform encryption and decryption operations. Its core function is to convert raw data into ciphertext through a specific encryption algorithm, or to restore ciphertext to raw data. The encryption engine usually includes modules such as key management, algorithm execution, and data processing, and supports multiple encryption methods such as symmetric encryption (such as AES), asymmetric encryption (such as RSA), and hybrid encryption. In high-security scenarios, the encryption engine can also integrate advanced functions such as quantum encryption and layered encryption to ensure the confidentiality, integrity, and anti-cracking capabilities of data during transmission and storage.

[0037] Performing spatiotemporal correlation encoding on the layered encrypted ciphertext and the dynamic disguised signal feature to generate a composite signal structure including a quantum key fingerprint and a dynamic spatiotemporal label; Exemplarily, the quantum key slice identifier (such as a 128-bit hash value) corresponding to each ciphertext is extracted from the layered encrypted ciphertext as a quantum key fingerprint. The real-time location information of the current transmission node (such as longitude 113.52634°, latitude 22.27152°) and the timestamp accurate to the millisecond level (such as 2023-09-15T14:23:05.678Z) are collected to generate a dynamic space-time label. The layered encrypted ciphertext is combined with the dynamic camouflage signal characteristics (such as ±3dB power fluctuation, ±5ms delay jitter), and the quantum key fingerprint and dynamic space-time label are embedded in the data header to form a composite signal structure including an encrypted data area (512 bytes), a camouflage feature area (64 bytes) and a label header (32 bytes).

[0038] Through the multi-path diversity transmission module of the Star Flash link, the composite signal structure is split into multiple sub-signal streams carrying independent camouflage features, and the multiple sub-signal streams carrying independent camouflage features are transmitted to the drone execution layer through multi-path diversity; Exemplarily, the composite signal structure is divided into three sub-signal streams (each sub-stream is 512 bytes long), and each sub-stream is assigned independent camouflage characteristic parameters (such as sub-stream 1 is loaded with ±5ms delay jitter, sub-stream 2 is loaded with ±3dB power fluctuation, and sub-stream 3 is loaded with pseudo-noise envelope). Three independent transmission paths, namely satellite link, ground base station link and relay node link, are configured in the transmission path of the star flash link, and each path corresponds to a sub-signal stream; then, a transmission identifier (such as path number, timestamp 2023-09-15T14:23:05.678Z) is added to each sub-signal stream, and it is assigned to the corresponding path through the transmission scheduling module.

[0039] According to the real-time position feedback of the UAV executive layer, the transmission timing and power spectrum density distribution of the sub-signals are dynamically adjusted on the transmission path of the star flash link to generate a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment. The spatiotemporal distribution parameters of the dynamic camouflage signal characteristics are optimized in real time according to the spatiotemporal chaos parameter set, and the optimized spatiotemporal distribution parameters are synchronized to the behavior pattern library of the quantum key distribution service node and the dummy pilot relay layer through a cross-layer feedback mechanism, forming a closed-loop optimized encryption camouflage collaborative mechanism.

[0040] In summary, in order to solve the problem that the control signal of the UAV is cracked or identified by the enemy during the transmission process due to insufficient encryption strength or single camouflage features. The present invention generates an encrypted camouflage data stream with high concealment and anti-interference through multi-hop encrypted transmission, multi-path diversity transmission and dynamic optimization of spatiotemporal distribution parameters, thereby improving the security and reliability of signal transmission, effectively preventing the enemy from cracking and locating the signal, ensuring the covert transmission of control instructions in a high-confrontation environment, and at the same time, through a closed-loop optimization mechanism, realizing the dynamic coordination of encryption and camouflage features, further enhancing the system's anti-detection capability and task execution efficiency.

[0041] Preferably, according to the real-time position feedback of the UAV executive layer, the transmission timing and power spectrum density distribution of the sub-signal are dynamically adjusted on the transmission path of the star flash link to generate a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment, specifically: Collect the real-time location nodes of the drone and the electromagnetic interference intensity it is subjected to; map the electromagnetic interference intensity to initial value sensitive parameters to generate an initial chaotic parameter sequence; Exemplarily, an electromagnetic interference intensity acquisition module is deployed at the transmission node of the star flash link to collect the electromagnetic interference intensity value of the current environment (such as -50dBm to -30dBm) in real time; secondly, the collected interference intensity value is input into the chaotic mapping model, and the initial chaotic parameter sequence is generated through the preset mapping rule (such as the initial value sensitive parameter increases by 0.01 for every 1dBm increase in interference intensity), with a sequence length of 1024 and each parameter value ranging from 0 to 1. Then, the generated initial chaotic parameter sequence is stored in the local parameter pool, and a timestamp (such as 2023-09-15T14:23:05.678Z) and a node identifier (such as node number 001) are added to it.

[0042] The initial chaotic parameter sequence is input into the dynamic cognitive graph engine, and combined with the real-time position node of the drone, the transmission timing of the sub-signal is subjected to phase chaos modulation, and the power spectrum density distribution is subjected to dynamic shaping in the fractional Fourier transform domain to generate a power-timing joint control parameter with time-varying non-stationary characteristics; Exemplarily, the initial chaotic parameter sequence (length 1024, parameter range 0 to 1) is associated with the real-time location node of the drone (such as longitude 113.52634°, latitude 22.27152°) to generate phase chaos modulation parameters (such as phase offset ±10°). Through the power spectrum density analysis module, the spectrum characteristics of the sub-signal are dynamically shaped to adjust its power spectrum density distribution (such as frequency range 2.4GHz to 2.4835GHz, power fluctuation ±3dB). The phase chaos modulation parameters are combined with the power spectrum density adjustment parameters to generate power-timing joint control parameters (such as timing offset ±5ms, power spectrum density dynamic range -50dBm to -30dBm). Then, the control parameters are evaluated in real time through the verification module (such as signal bit error rate ≤1e-6), and output after ensuring that it meets the preset standards as the control basis for sub-signal transmission.

[0043] According to the channel response characteristics on the transmission path, the power-timing joint control parameters are combined with multiple objectives to generate an initial spatiotemporal chaos parameter set; Exemplarily, the channel response characteristics (such as signal-to-noise ratio ≥ 20dB, multipath delay ≤ 10ns) are collected in real time. The channel response characteristics are correlated with the power-timing joint control parameters (such as timing offset ±5ms, power spectrum density dynamic range -50dBm to -30dBm) to generate multi-objective combination parameters (such as timing optimization weight 0.6, power optimization weight 0.4). The multi-objective combination parameters are integrated with the initial chaotic parameter sequence (length 1024, parameter range 0 to 1) through the parameter combination module to generate the initial spatiotemporal chaotic parameter set (such as timing parameters ±5ms, power parameters ±3dB).

[0044] The initial spatiotemporal chaotic parameter set is injected into the sub-signal transmission module, and the signal bit error rate, channel capacity and camouflage concealment are synchronously collected to construct dynamic parameter evaluation indicators; If the dynamic parameter evaluation index meets the preset index requirements, the initial spatiotemporal chaos parameter set is converted into a spatiotemporal chaos parameter set; otherwise, the above steps are repeated; It should be noted that the dynamic parameter evaluation indicators such as signal bit error rate, channel capacity and camouflage concealment are collected in real time. The collected evaluation indicators are compared and analyzed with the preset indicator requirements to generate the evaluation results. If the signal bit error rate, channel capacity and camouflage concealment meet the preset indicator requirements (such as signal bit error rate ≤ 1e-6, channel capacity ≥ 10Mbps, camouflage concealment ≥ 90%), the initial spatiotemporal chaos parameter set (such as timing parameters ± 5ms, power parameters ± 3dB) is directly converted into a spatiotemporal chaos parameter set and stored in the local parameter pool; otherwise, the electromagnetic interference intensity and channel response characteristics are recollected, and the initial chaos parameter sequence, power-timing joint control parameters and initial spatiotemporal chaos parameter set are regenerated until the evaluation results meet the preset indicator requirements.

[0045] The spatiotemporal chaotic parameter set is synchronized to the quantum key distribution service node and the dynamic camouflage module through a quantum security tunnel as the spatiotemporal reference parameter for the next round of multi-hop transmission, thereby realizing cross-layer coordination of encryption camouflage and chaotic modulation.

[0046] In summary, in order to solve the problem of signal quality degradation or camouflage failure caused by the complex and changeable electromagnetic environment during the transmission of drone control signals, this method collects the drone position and electromagnetic interference intensity in real time, dynamically adjusts the transmission timing and power spectrum density distribution of the sub-signal, and generates a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment, thereby improving the anti-interference ability and concealment of signal transmission.

[0047] Preferably, the spatiotemporal distribution parameters of the dynamic camouflage signal characteristics are optimized in real time according to the spatiotemporal chaos parameter set, specifically: Performing feature decomposition on the spatiotemporal chaotic parameter set, extracting core feature parameters including time-varying phase, power spectrum density and chaotic attractor trajectory, and generating a spatiotemporal feature vector; It should be noted that the spatiotemporal chaos parameter set (such as timing parameters ±5ms, power parameters ±3dB) is input into the module for parsing, and time-varying phase characteristics (such as phase shift ±10°), power spectrum density characteristics (such as frequency range 2.4GHz to 2.4835GHz, power fluctuation ±3dB) and chaotic attractor trajectory characteristics (such as trajectory parameter range 0 to 1) are extracted from the parameter set; the extracted core feature parameters are combined to generate a spatiotemporal feature vector (such as vector length 128, including phase shift, power fluctuation and trajectory parameters).

[0048] Based on the spatiotemporal feature vector, the dynamic camouflage signal feature is reconstructed, the chaotic attractor trajectory is mapped to the random jitter feature of the signal in the time-frequency domain, and a reconstructed camouflage signal containing spatiotemporal chaotic characteristics is generated; It should be noted that the space-time feature vector (such as vector length 128, including phase shift ±10°, power fluctuation ±3dB and trajectory parameter range 0 to 1) is input into the module for analysis; according to the chaotic attractor trajectory characteristics (such as trajectory parameter range 0 to 1), the random jitter characteristics of the signal in the time and frequency domain are generated (such as time domain jitter ±5ms, frequency domain jitter ±1MHz); the random jitter characteristics are superimposed with the dynamic camouflage signal characteristics (such as power spectrum density dynamic range -50dBm to -30dBm) to generate a reconstructed camouflage signal containing space-time chaos characteristics (such as signal length 512 bytes, including time and frequency domain jitter characteristics); finally, the reconstructed camouflage signal is evaluated in real time through the verification module (such as signal concealment ≥90%) to ensure that it meets the preset standards and is output as a camouflage signal for subsequent transmission.

[0049] Based on the UAV position feedback and electromagnetic environment change data, dynamic features including multipath interference intensity, spectrum occupancy and channel response characteristics are extracted to generate an environmental dynamic feature matrix; Based on the environmental dynamic characteristic matrix, a fuzzy rule base including transmission timing, power spectrum density and signal concealment index is constructed to generate a fuzzy control rule set; It should be noted that the environment dynamic feature matrix (such as signal-to-noise ratio ≥ 20dB, multipath delay ≤ 10ns, spectrum occupancy ≤ 70%) is input into the module for parsing, and a fuzzy rule base (such as 256 rules, each rule contains timing, power and concealment parameters) is generated according to the transmission timing (such as timing offset ±5ms), power spectrum density (such as frequency range 2.4GHz to 2.4835GHz, power fluctuation ±3dB) and signal concealment index (such as concealment ≥ 90%). The fuzzy rule base is stored in the local rule pool, and a timestamp (such as 2023-09-15T14:23:05.678Z) and a node identifier (such as node number 001) are added to it.

[0050] Inputting the time-space distribution parameters of the reconstructed camouflage signal into the fuzzy control rule set, evaluating its matching degree with the current electromagnetic environment, and generating a parameter matching degree evaluation vector; It should be noted that the spatiotemporal distribution parameters of the reconstructed camouflage signal (such as timing offset ±5ms, power fluctuation ±3dB) are input into the module for parsing, and fuzzy rules (such as 256 rules) that match the current electromagnetic environment (such as signal-to-noise ratio ≥20dB, multipath delay ≤10ns) are extracted from the fuzzy control rule set to generate a matching rule subset. The spatiotemporal distribution parameters are compared and analyzed with the matching rule subset to generate a parameter matching evaluation vector (such as a vector length of 128, including timing matching, power matching and concealment matching).

[0051] Based on the parameter matching evaluation vector, the matching relationship between the transmission timing and the power spectrum density is dynamically optimized to generate an optimized spatiotemporal distribution parameter set.

[0052] It should be noted that the parameter matching evaluation vector (e.g., vector length 128, including timing matching, power matching, and concealment matching) is input into the module for parsing. According to the matching evaluation result, the matching relationship between the transmission timing (e.g., timing offset is optimized from ±5 ms to ±3 ms) and the power spectrum density (e.g., power fluctuation is optimized from ±3 dB to ±2 dB) is adjusted to generate an optimized spatiotemporal distribution parameter set (e.g., timing parameter ±3 ms, power parameter ±2 dB). Then, the optimized parameter set is stored in the local parameter pool.

[0053] In summary, this method improves the concealment and environmental adaptability of signal transmission by optimizing the spatiotemporal distribution parameters of dynamic camouflage signal characteristics in real time, combining environmental dynamic characteristics with fuzzy logic control, ensuring the stable transmission of control signals in a high dynamic electromagnetic environment, and effectively preventing the enemy from detecting and locating the signal. At the same time, through a closed-loop optimization mechanism, dynamic matching of camouflage characteristics and electromagnetic environment is achieved, thereby enhancing the safety and reliability of UAV mission execution.

[0054] Preferably, the flight control operation is performed after the encrypted disguised data stream is decrypted and authenticated, specifically: When the drone execution layer receives the encrypted disguised data stream from the dummy pilot relay layer, it extracts the composite signal structure containing the dynamic disguised signal characteristics and the quantum key fingerprint to generate the data stream to be decrypted; Based on the quantum key fingerprint, the corresponding quantum key slice is obtained through the quantum key distribution service node, the data stream to be decrypted is input into the quantum decryption engine, and the layered asymmetric decryption operation is performed to restore the disguised manipulated data stream; Among them, the quantum decryption engine is a hardware or software module specifically used to perform decryption operations based on quantum keys. Its core function is to use quantum keys to perform hierarchical asymmetric decryption of encrypted data and restore the original data. The engine obtains quantum key slices corresponding to the encrypted data through the quantum key distribution service node, and decrypts the ciphertext in combination with quantum decryption algorithms (such as Shor's algorithm or Grover's algorithm) to ensure the security and anti-cracking capabilities of data transmission.

[0055] Performing spatiotemporal chaos inverse mapping processing on the camouflage manipulation data stream, extracting its dynamic camouflage signal features, performing matching verification with a preset camouflage feature library, and generating feature matching results; Among them, the feature matching results include but are not limited to the following: signal time domain jitter matching (such as deviation within the range of ±5 ms), frequency domain offset matching (such as deviation within the range of ±1MHz), power fluctuation matching (such as fluctuation within the range of ±3dB), chaotic attractor trajectory matching (such as similarity of trajectory parameters in the range of 0 to 1) and overall signal concealment index (such as concealment ≥90%).

[0056] It should be noted that the inverse mapping of spatiotemporal chaos refers to the process of restoring the signal modulated by spatiotemporal chaos to the original signal through inverse processing. Its core function is to eliminate the chaotic characteristics (such as time domain jitter, frequency domain offset, etc.) introduced by the signal during transmission and restore the original time and frequency domain characteristics of the signal. This process uses the inverse chaos mapping model to perform inverse operations on characteristic parameters such as chaotic attractor trajectory, time-varying phase and power spectrum density to restore the initial state of the signal. The inverse mapping of spatiotemporal chaos is widely used in high-covert communication systems.

[0057] It should be noted that the preset camouflage feature library refers to a database containing a variety of dynamic camouflage signal features pre-built in the drone control system, and its purpose is to provide a reference for signal decryption and authentication. The library includes camouflage feature parameters such as time domain jitter, frequency domain offset, and power fluctuation, and is generated by simulating signal camouflage patterns in different environments. During the signal decryption process, the system extracts camouflage features that match the received signal from the library to verify the legitimacy and integrity of the signal.

[0058] Verify the consistency of the behavior characteristics of the control command with the preset dummy pilot behavior pattern library based on the feature matching result, and generate a command legitimacy authentication result; If the command legitimacy authentication result is legal, the restored control command is input into the UAV flight control module to execute the flight control operation; If the command legitimacy authentication result is illegal, the exception handling mechanism is triggered, a safety warning message is generated and the flight control operation is suspended. At the same time, the warning information is synchronized to the real pilot layer and the dummy pilot relay layer through the quantum security tunnel.

[0059] In summary, in order to solve the technical problem of flight control failure or safety risk caused by decryption failure or authentication failure during the transmission of UAV control commands, this method ensures the legitimacy and reliability of control commands through multiple security mechanisms such as quantum key verification, dynamic camouflage feature matching, and behavior pattern authentication, effectively preventing the enemy from tampering with or forging control commands, ensuring the safe flight of UAVs in highly confrontational environments, and quickly responding to illegal commands through exception handling mechanisms to enhance the system's anti-attack capabilities and task execution efficiency.

[0060] Among them, the torso, limbs and head of the dummy pilot adopt a snap-on connection design; the dummy pilot has a built-in multi-layer heating plate array, which is arranged according to the thermodynamic distribution law of the human body to simulate the temperature difference characteristics of the head, chest and limbs; the dummy pilot also has a built-in digital radio module to forward the received instructions to the drone, and at the same time attract enemy thermal imaging / radio detection equipment through heat source and action simulation.

[0061] It should be noted that the torso, limbs and head of the dummy pilot adopt a snap-on connection design, so that the dummy pilot can be quickly assembled and disassembled, which is convenient for transportation and deployment, while ensuring the stability and flexibility of the connection between the components; the dummy pilot has a built-in multi-layer heating plate array, which is arranged according to the thermodynamic distribution law of the human body to simulate the temperature difference characteristics of the head, chest and limbs. Specifically, heating plates are arranged in key parts such as the head, chest, and limbs of the dummy pilot, and the temperature of each heating plate is accurately controlled by distributed temperature control technology, so that the surface temperature distribution of the dummy pilot conforms to the thermodynamic characteristics of the real human body (such as the temperature of the head is slightly higher than that of the limbs, and the temperature of the chest is moderate); in addition, by wrapping the heating plate array with lightweight PVC material, not only the overall weight of the dummy pilot is reduced, but also the conduction efficiency and simulation degree of the thermal signal are improved; this design enables the dummy pilot to present a thermal signal characteristic that is highly similar to that of a real human body under infrared detection, effectively confusing enemy detection equipment and enhancing the concealment and survivability of the real pilot.

[0062] In this embodiment, the drone pilot short-distance control method may further include the following steps: Wearable biosensors are used to collect the real-time operation posture, electromyographic signals and electroencephalographic signals of real pilots, extract the signal amplitude, frequency and entropy value features, and generate bioelectric signal feature vectors; Inputting the bioelectric signal characteristic vector into a random time series generation module to generate a bionic electrical signal substrate with random time series fluctuation characteristics; The spiking neural convolutional network is used to encode the bioelectric characteristics of the real-time operation posture of the real pilot to form an operation vector; Mapping the operation vector to the phase oscillation space of the bionic substrate signal to generate a phase encoding signal; The phase-encoded signal is nonlinearly fused with the biomimetic base signal to form a composite modulation waveform with biological rhythm synchronization characteristics in the time-frequency domain. It should be noted that, in the signal processing module, the phase coding signal (such as a phase shift of ±10°) and the bionic base signal (such as an amplitude range of 0 to 1, a frequency range of 0.1 Hz to 100 Hz) are extracted to generate a signal feature vector, and the signal feature vector is input into the nonlinear feature fusion module. The phase coding signal and the bionic base signal are superimposed in the time-frequency domain according to a preset fusion rule to generate a preliminary composite modulated waveform (such as a waveform length of 512 bytes, including time-frequency domain features), and the preliminary composite modulated waveform is adjusted by the biorhythm synchronization module to synchronize it with the biorhythm features of the bionic base signal (such as a period of 1 second, an amplitude fluctuation of ±10%), so as to generate a composite modulated waveform with biorhythm synchronization characteristics (such as a waveform length of 512 bytes, including time-frequency domain features and biorhythm synchronization characteristics).

[0063] A multi-dimensional perturbation matrix is ​​constructed based on the amplitude-frequency characteristic parameters of the bionic substrate signal, and a topological structure of the composite modulated waveform is reorganized based on the multi-dimensional perturbation matrix to generate a reorganized signal feature; It should be noted that the amplitude-frequency characteristic parameters of the bionic base signal (such as amplitude range 0 to 1, frequency range 0.1 Hz to 100 Hz) are extracted in the signal processing module to generate an amplitude-frequency characteristic vector, which is input into the multidimensional perturbation matrix generation module to construct a multidimensional perturbation matrix including time domain perturbation, frequency domain perturbation and phase perturbation (such as matrix dimension 3×3, perturbation range ±10%), and the composite modulated waveform (such as waveform length 512 bytes, including time-frequency domain features) and the multidimensional perturbation matrix are input into the topological structure reconstruction module to dynamically adjust the time-frequency domain features of the waveform to generate reconstructed signal features (such as the length of the reconstructed waveform 512 bytes, including time domain jitter ±5 ms, frequency domain offset ±1 MHz).

[0064] The recombinant signal characteristics are projected into the quantum state space, and the final output signal with biological dynamic camouflage is generated through quantum entanglement correlation, and transmitted to the dummy pilot relay layer through the star flash link.

[0065] In summary, in the stage of generating dynamic camouflage attributes, this method introduces the biological noise feature mixing technology, and nonlinearly superimposes the operating behavior characteristics of the real pilot with the randomly generated bioelectric signal characteristics to form a composite signal feature (final output signal) with biological dynamic characteristics, so that the signal characteristics are highly consistent with the real biological dynamics, effectively preventing the enemy from identifying and locating the signal.

[0066] In this embodiment, the drone pilot short-distance control method may further include the following steps: The electromagnetic radiation spectrum characteristics of the real transmission channel are collected in real time through a multi-dimensional electromagnetic field probe array, and the carrier frequency-phase offset joint distribution characteristics are extracted to form a multi-dimensional electromagnetic fingerprint map; a phase modulation parameter set with a random quantum state distribution is dynamically generated based on the time-frequency domain parameters of the electromagnetic fingerprint map; the phase modulation parameter set is subjected to quantum phase convolution operation with a pseudo-random noise base to generate a mirror carrier signal cluster carrying the same electromagnetic fingerprint characteristics; the real transmission data stream and the mirror signal cluster are subjected to spiral phase interleaving modulation to generate a vortex composite waveform with electromagnetic characteristic isomorphism; the topological winding degree parameters of the vortex waveform are dynamically adjusted according to the intensity of environmental electromagnetic interference, so that the mirror channel and the real channel form an electromagnetic characteristic resonant coupling; a quantum teleportation identifier is implanted in the mirror channel, and the electromagnetic characteristic synchronization of the mirror channel and the real channel is verified in real time through a quantum entanglement association mechanism; when the data transmission is completed, a quantum decoherence operation is triggered to cause an irreversible topological structure collapse of the electromagnetic fingerprint characteristics of the mirror channel.

[0067] This method uses quantum phase convolution and spiral phase interleaving modulation to make the mirror signal and the real signal highly consistent in electromagnetic characteristics, effectively preventing the enemy from identifying and locating the signal; at the same time, through the quantum entanglement correlation mechanism and topological self-destruction protocol, it ensures that the electromagnetic characteristics of the mirror channel collapse irreversibly after data transmission is completed, enhancing the system's anti-reverse analysis capability and dynamic coordination.

[0068] like Figure 3 As shown, the second invention of the present invention discloses a UAV pilot short-distance control system 8 based on Star Flash technology, the control system includes a memory 60 and a processor 80, the memory 60 stores a UAV pilot short-distance control method program based on Star Flash technology, when the UAV pilot short-distance control method program based on Star Flash technology is executed by the processor 80, any step of the UAV pilot short-distance control method based on Star Flash technology is implemented.

[0069] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A short-distance control method for a UAV pilot based on star flash technology, characterized in that: The following steps are involved: Establish a directional wireless connection between the real pilot layer and the dummy pilot relay layer, optimize the communication frequency band and signal waveform in real time, and generate an initial control command signal with dynamic camouflage properties; When the dummy pilot relay layer receives the initial control command signal, it fuses the operation behavior characteristics of the real pilot with the preset dummy pilot behavior pattern library to generate a camouflaged control data stream; Implementing multi-hop encrypted transmission processing on the camouflaged control data stream to form an encrypted camouflaged data stream, and then transmitting it to the drone execution layer in a multi-path diversity manner, while continuously optimizing the spatiotemporal distribution parameters during the transmission process; After receiving the encrypted disguised data stream, the drone execution layer decrypts and authenticates the encrypted disguised data stream and then performs flight control operations.

2. According to claim 1, a method for short-distance control of a drone pilot based on the star flash technology is characterized in that: Establish a directional wireless connection between the real pilot layer and the dummy pilot relay layer, optimize the communication frequency band and signal waveform in real time, and generate an initial control command signal with dynamic camouflage properties, specifically: Perform dynamic spectrum sensing on the electromagnetic environment within the preset range of the real pilot layer, extract the interference intensity and channel characteristic parameters of the available frequency band in real time, and generate dynamic spectrum sensing results; Based on the sensing results, the optimal frequency band for anti-interference is selected and the time-frequency resource allocation strategy is matched to generate a star flash communication link configuration instruction including a frequency hopping sequence and waveform modulation parameters; According to the configuration instructions, the Starflash transceiver module is driven to construct a directional beam, and combined with the preset UAV control instruction coding protocol, the original control signal of the real pilot is converted into a Starflash baseband signal with dynamic time-frequency parameters; Randomized pulse position offset and pseudo-noise envelope characteristics are embedded in the Starflash baseband signal to confuse the signal's time-frequency domain characteristics, generate an initial control command signal with dynamic camouflage properties, and transmit it to the dummy pilot relay layer through the Starflash communication link.

3. The short-distance control method for drone pilots based on Star Flash technology according to claim 1 is characterized in that: When the dummy pilot relay layer receives the initial control command signal, it fuses the real pilot's operation behavior characteristics with the preset dummy pilot behavior pattern library to generate a camouflaged control data stream, specifically: A camouflage signal generating unit is configured at the dummy pilot relay layer to receive the initial control command signal and analyze its time-frequency domain characteristic parameters to generate an initial signal characteristic vector; Based on a preset randomization rule, a dynamic camouflage parameter set including random delay jitter and power fluctuation characteristics is generated, and the camouflage parameter set is superimposed with the initial signal feature vector to generate a dynamic camouflage signal feature; Deploy a behavior pattern analysis module at the dummy pilot relay layer to extract the real pilot's operation behavior characteristics, including operation frequency, command sequence, and response time, and generate a real pilot's behavior feature vector; Matching the real pilot behavior feature vector with a preset dummy pilot behavior pattern library, screening out the dummy pilot behavior pattern with the greatest similarity to the real pilot behavior feature, and generating a behavior pattern matching result; Based on the matching result, the dynamic camouflage signal feature is subjected to behavioral consistency optimization processing to generate a camouflage control signal including multi-node behavioral features; The camouflaged control signal is feature-fused with the initial control command signal to form a camouflaged control data stream with multi-node behavior consistency, and is transmitted to the next relay node or drone execution layer through the Star Flash communication link.

4. The short-distance control method for drone pilots based on Star Flash technology according to claim 1 is characterized in that: The camouflage control data stream is subjected to multi-hop encrypted transmission processing to form an encrypted camouflage data stream, and then multi-path diversity transmission is performed to the drone execution layer, and the time-space distribution parameters are continuously optimized during the transmission process, specifically: Deploy quantum key distribution service nodes in the Xingshan communication network, build a quantum key resource pool between relay nodes based on the quantum entanglement pair generation protocol, generate quantum key slices dynamically bound to each relay node, and form a key source for layered encryption; Extract the dynamic camouflage signal features in the camouflage manipulation data stream at each relay node, generate a layered encryption key in combination with the quantum key slice, inject the layered encryption key into the encryption engine, perform segmented asymmetric encryption on the data stream, and generate a layered encrypted ciphertext; Performing spatiotemporal correlation encoding on the layered encrypted ciphertext and the dynamic disguised signal feature to generate a composite signal structure including a quantum key fingerprint and a dynamic spatiotemporal label; Through the multi-path diversity transmission module of the Star Flash link, the composite signal structure is split into multiple sub-signal streams carrying independent camouflage features, and the multiple sub-signal streams carrying independent camouflage features are transmitted to the drone execution layer through multi-path diversity; According to the real-time position feedback of the UAV executive layer, the transmission timing and power spectrum density distribution of the sub-signals are dynamically adjusted on the transmission path of the star flash link to generate a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment. The spatiotemporal distribution parameters of the dynamic camouflage signal characteristics are optimized in real time according to the spatiotemporal chaos parameter set, and the optimized spatiotemporal distribution parameters are synchronized to the behavior pattern library of the quantum key distribution service node and the dummy pilot relay layer through a cross-layer feedback mechanism, forming a closed-loop optimized encryption camouflage collaborative mechanism.

5. The short-distance control method for drone pilots based on Star Flash technology according to claim 4 is characterized in that: According to the real-time position feedback of the UAV executive layer, the transmission timing and power spectrum density distribution of the sub-signal are dynamically adjusted on the transmission path of the star flash link to generate a spatiotemporal chaos parameter set that is adaptive to the electromagnetic environment. Specifically: Collect the real-time location nodes of the drone and the electromagnetic interference intensity it is subjected to; map the electromagnetic interference intensity to initial value sensitive parameters to generate an initial chaotic parameter sequence; The initial chaotic parameter sequence is input into the dynamic cognitive graph engine, and combined with the real-time position node of the drone, the transmission timing of the sub-signal is subjected to phase chaos modulation, and the power spectrum density distribution is subjected to dynamic shaping in the fractional Fourier transform domain to generate a power-timing joint control parameter with time-varying non-stationary characteristics; According to the channel response characteristics on the transmission path, the power-timing joint control parameters are combined with multiple objectives to generate an initial spatiotemporal chaos parameter set; The initial spatiotemporal chaotic parameter set is injected into the sub-signal transmission module, and the signal bit error rate, channel capacity and camouflage concealment are synchronously collected to construct dynamic parameter evaluation indicators; If the dynamic parameter evaluation index meets the preset index requirements, the initial spatiotemporal chaos parameter set is converted into a spatiotemporal chaos parameter set; otherwise, the above steps are repeated; The spatiotemporal chaotic parameter set is synchronized to the quantum key distribution service node and the dynamic camouflage module through a quantum security tunnel as the spatiotemporal reference parameter for the next round of multi-hop transmission, thereby realizing cross-layer coordination of encryption camouflage and chaotic modulation.

6. The short-distance control method for drone pilots based on Star Flash technology according to claim 4 is characterized in that: The spatiotemporal distribution parameters of the dynamic camouflage signal characteristics are optimized in real time according to the spatiotemporal chaos parameter set, specifically: Performing feature decomposition on the spatiotemporal chaotic parameter set, extracting core feature parameters including time-varying phase, power spectrum density and chaotic attractor trajectory, and generating a spatiotemporal feature vector; Based on the spatiotemporal feature vector, the dynamic camouflage signal feature is reconstructed, the chaotic attractor trajectory is mapped to the random jitter feature of the signal in the time-frequency domain, and a reconstructed camouflage signal containing spatiotemporal chaotic characteristics is generated; Based on the UAV position feedback and electromagnetic environment change data, dynamic features including multipath interference intensity, spectrum occupancy and channel response characteristics are extracted to generate an environmental dynamic feature matrix; Based on the environmental dynamic characteristic matrix, a fuzzy rule base including transmission timing, power spectrum density and signal concealment index is constructed to generate a fuzzy control rule set; Inputting the time-space distribution parameters of the reconstructed camouflage signal into the fuzzy control rule set, evaluating its matching degree with the current electromagnetic environment, and generating a parameter matching degree evaluation vector; Based on the parameter matching evaluation vector, the matching relationship between the transmission timing and the power spectrum density is dynamically optimized to generate an optimized spatiotemporal distribution parameter set.

7. The short-distance control method for drone pilots based on Star Flash technology according to claim 1 is characterized in that: After decrypting and authenticating the encrypted disguised data stream, the flight control operations are performed, specifically: When the drone execution layer receives the encrypted disguised data stream from the dummy pilot relay layer, it extracts the composite signal structure containing the dynamic disguised signal characteristics and the quantum key fingerprint to generate the data stream to be decrypted; Based on the quantum key fingerprint, the corresponding quantum key slice is obtained through the quantum key distribution service node, the data stream to be decrypted is input into the quantum decryption engine, and the layered asymmetric decryption operation is performed to restore the disguised manipulated data stream; Performing spatiotemporal chaos inverse mapping processing on the camouflage manipulation data stream, extracting its dynamic camouflage signal features, performing matching verification with a preset camouflage feature library, and generating feature matching results; Verify the consistency of the behavior characteristics of the control command with the preset dummy pilot behavior pattern library based on the feature matching result, and generate a command legitimacy authentication result; If the command legitimacy authentication result is legal, the restored control command is input into the UAV flight control module to execute the flight control operation; If the command legitimacy authentication result is illegal, the exception handling mechanism is triggered, a safety warning message is generated and the flight control operation is suspended. At the same time, the warning information is synchronized to the real pilot layer and the dummy pilot relay layer through the quantum security tunnel.

8. The short-distance control method for a UAV pilot based on the Star Flash technology according to claim 1 is characterized by: The torso, limbs and head of the dummy pilot are designed with snap-on connections; The dummy pilot has a built-in multi-layer heating element array, which is arranged according to the thermodynamic distribution law of the human body to simulate the temperature difference characteristics of the head, chest and limbs.

9. A short-distance control system for drone pilots based on Star Flash technology, characterized in that: The control system includes a memory and a processor, wherein the memory stores a program for the short-distance control method for drone pilots based on Star Flash technology. When the program for the short-distance control method for drone pilots based on Star Flash technology is executed by the processor, the steps of the short-distance control method for drone pilots based on Star Flash technology as described in any one of claims 1 to 8 are implemented.

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