Small and medium-sized load-carrying unmanned aerial vehicle interference perception and link layer anti-interference method and system

Abstract

The application discloses a small and medium-sized load-carrying unmanned aerial vehicle interference sensing and link layer anti-interference method and system, and belongs to the technical field of wireless communication and unmanned aerial vehicle link control; the application aims to solve the technical problems of single sensing capability, inaccurate interference identification, fixed and rigid anti-interference strategy and large resource consumption of the existing method. The application comprises the following steps: a lightweight embedded communication architecture is built, and multi-source data such as radio frequency interference characteristics, unmanned aerial vehicle attitude and link state are collected in real time; a sliding window statistical method and a threshold comparison method are used to identify rotor electromagnetic interference, external same-frequency suppression interference and low-altitude multipath interference, and four interference levels are divided according to a signal-to-interference-and-noise ratio (SINR) value; and adaptive matching filtering anti-interference, frequency hopping anti-interference, modulation coding and retransmission mechanism, double-link redundancy switching and other strategies are matched according to the interference type and level.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication and UAV link control technology, and particularly relates to a method and system for interference perception and link layer anti-interference of small and medium-sized heavy-duty UAVs. Background Technology

[0002] With the rapid development of the low-altitude economy and the drone transportation industry, small and medium-sized heavy-duty drones (typically with a payload of 5-20 kg) are widely used in scenarios such as material delivery, emergency rescue, engineering transportation, and multi-drone swarm collaborative operations. These drones fly year-round in a low-altitude, ground-hugging environment of 0-1000m, facing challenges such as obstruction from buildings and mountains, complex terrain, and harsh electromagnetic environments. Furthermore, heavy-load missions place far higher demands on the reliability, real-time performance, and continuity of communication links than ordinary consumer-grade drones. Interference, bit errors, or disconnections in the communication link can easily lead to safety accidents such as deviations in material delivery, flight path deviations, or even drone crashes.

[0003] Currently, existing anti-jamming technologies for drone communication links are mostly designed for consumer-grade lightweight drones. Publicly available general link-layer communication protocols and anti-jamming solutions (such as general frequency hopping communication, simple ARQ error reporting and retransmission mechanisms, and fixed filtering suppression strategies) still have many technical shortcomings, specifically: The lack of ability to identify and suppress the strong electromagnetic interference of small and medium-sized heavy-duty UAVs is a problem. The multi-rotor rotation of small and medium-sized heavy-duty UAVs generates strong electromagnetic radiation. This interference is concentrated in the 2.4GHz±50MHz frequency band, with an interference intensity of -30dBm to -10dBm. Traditional fixed anti-interference strategies cannot specifically identify and suppress this self-interference, which can easily lead to high link error rate and poor communication stability.

[0004] Lack of multi-source fusion sensing capabilities. Existing technologies rely solely on single-spectrum information for interference judgment, failing to simultaneously collect multi-dimensional data such as radio frequency interference characteristics, UAV attitude (e.g., pitch, roll, vibration), and link status (e.g., bit error rate, latency, CQI channel quality indication). This results in a single identification dimension, low accuracy, and difficulty in adapting to complex operating conditions such as low-altitude multipath fading and strong airframe vibration.

[0005] The existing solutions cannot accurately distinguish between different types of interference and lack a quantitative classification mechanism. Conventional interference identification methods struggle to differentiate between three typical types of interference: rotor electromagnetic interference, external co-frequency suppression interference, and low-altitude multipath interference. Furthermore, the lack of a quantitative classification mechanism based on the signal-to-interference-plus-noise ratio (SINR) prevents the classification of interference levels into no interference, weak interference, strong interference, and severe interference. This necessitates a uniform anti-interference strategy, leading to resource waste under weak interference and insufficient anti-interference capability under strong interference.

[0006] Lacking adaptive strategy matching capabilities and incurring high resource overhead, existing link-layer anti-interference strategies are mostly one-size-fits-all fixed configurations. They cannot adaptively match different mechanisms such as filtering suppression, modulation and coding, frequency hopping avoidance, and dual-link redundancy switching according to the type and level of interference. This makes it difficult to achieve low-latency link self-healing within 10ms and also fails to meet the requirement of a bit error rate ≤10% for heavy-load transportation tasks. -6 The system requires highly reliable transmission. However, most anti-interference algorithms have high code size and memory consumption, making them difficult to deploy in real-time on resource-constrained lightweight embedded architectures such as STM32 and ARM Cortex-R, resulting in poor adaptability.

[0007] In summary, existing technologies suffer from the following technical problems when implementing anti-interference methods at the link layer for small and medium-sized heavy-duty transport UAVs: limited sensing capabilities, inaccurate interference identification, fixed and rigid anti-interference strategies, and high resource consumption. Summary of the Invention

[0008] The present invention aims to provide a method and system for interference perception and link layer anti-interference of small and medium-sized heavy-duty UAVs, so as to solve the technical problems of single perception capability, inaccurate interference identification, fixed and rigid anti-interference strategy and high resource consumption in the prior art.

[0009] To achieve the above objectives, the technical solution created by this invention is implemented as follows: A method for interference perception and link-layer anti-interference of small and medium-sized heavy-duty UAVs includes the following steps: S1: Build an embedded communication architecture, select a microcontroller as the core control unit, and configure an RF communication module, an interference detection module, and an attitude perception module. S2: Real-time acquisition of multi-source data, including: radio frequency interference characteristics acquired by the interference detection module, UAV attitude data acquired by the attitude perception module, and link status data obtained by the radio frequency communication module; S3: Based on the collected multi-source data, the sliding window statistical method is used to perform rolling analysis on the multi-source data and filter out random noise. Combined with the threshold comparison method, the measured data is compared with the preset threshold range to identify the type and intensity of interference to the current wireless communication link. S4: The interference intensity is classified into multiple levels based on the signal-to-interference-plus-noise ratio (SINR); S5: Based on the identified interference type and interference level, adaptively match and execute the corresponding anti-interference strategy; wherein, for different interference types, respectively perform filtering anti-interference or frequency hopping anti-interference, and dynamically adjust communication transmission parameters or execute link switching strategy according to the interference level; S6: Data transmission is performed using a hierarchical anti-interference frame structure at the link layer. Anti-interference transmission at the link layer is achieved through differentiated frame coding, data interleaving, and synchronization information embedding. S7: For the data transmitted by the hierarchical anti-interference frame structure, the lightweight reinforcement learning DQN algorithm is used to dynamically optimize the frequency hopping decision and modulation and coding switching strategy; S8: In multi-drone cluster operation scenarios, the quality of each drone's communication channel is scored, and independent communication channels are dynamically allocated based on the scoring results.

[0010] Furthermore, the core control unit has a main frequency of 168MHz to 216MHz and an instruction execution cycle of ≤1μs; The radio frequency communication module operates in frequency bands covering 2.4GHz, 5.8GHz, and 1.4GHz; The interference detection module covers a frequency band of 1.4GHz to 5.8GHz; The attitude perception module has a sampling frequency of ≥100Hz, an attitude measurement accuracy of ≤0.1°, and uses an interrupt-triggered method to collect multi-source data with a data acquisition cycle of ≤100μs. The anti-interference code size at the link layer is limited to ≤32KB, and the memory usage is limited to ≤8KB. Radio frequency interference characteristics include amplitude, frequency, and phase; The attitude data of the drone includes pitch angle, roll angle and vibration frequency. When the vibration frequency is >10Hz, it is determined to be a strong vibration state of the aircraft. Link state data includes bit error rate, latency, and channel quality index (CQI).

[0011] Furthermore, the window length of the sliding window statistical method is 10 to 20 data frames, and the sliding step size is 1 data frame. Interference types include rotor-on-rotor electromagnetic interference, external co-frequency suppression interference, and low-altitude multipath interference; Among them, external co-frequency suppression interference and low-altitude multipath interference are identified as independent interference types. The preset amplitude range for electromagnetic interference from the rotor itself is -30dBm to -10dBm, and the preset amplitude range for external co-frequency suppression interference is -40dBm to -20dBm. When the amplitude range of electromagnetic interference from the rotor itself overlaps with that of external interference at the same frequency, the determination is made based on the frequency landing point, phase fluctuation, and whether the interference signal is synchronized with the rotor rotation frequency or the airframe vibration frequency. If the interference frequency is located at 2.4GHz±50MHz and is synchronized with the rotor rotation frequency or airframe vibration frequency in the range of 20Hz~50Hz, it is determined to be electromagnetic interference from the rotor itself. If the interference signal is out of sync with the rotor rotation frequency or the airframe vibration frequency, and continues to appear in the same frequency communication channel, it is determined to be external same frequency suppression interference. The determination of low-altitude multipath interference includes: if no interference component synchronized with the rotor rotation frequency or the airframe vibration frequency is detected, and no continuous suppression signal of the same frequency communication channel is detected, if deep fading or rapid fluctuation of received amplitude, short-term fluctuation of channel quality (CQI), transmission delay jitter, and rapid phase fluctuation occur within the sliding window, then the current wireless communication link is determined to be subject to low-altitude multipath interference.

[0012] Furthermore, in step S4, the interference intensity is divided into four interference levels based on the signal-to-interference-plus-noise ratio (SINR): Level 1, SINR > 15dB, is an interference-free scenario; Level 2, 5dB≤SINR≤15dB, is a weak interference scenario; Level 3, -5dB≤SINR<5dB, is a strong interference scenario; Level 4, SINR < -5dB, indicates a severe interference scenario.

[0013] Furthermore, the filtering and interference suppression in step S5 targets the electromagnetic interference of the rotor itself, and adopts a combined filtering algorithm consisting of IIR low-pass filtering and adaptive notch filtering. The combined filtering algorithm adopts a cascaded processing approach. First, IIR low-pass filtering is applied to the interference feature sequence, interference amplitude envelope, or baseband features to filter out random high-frequency noise and smooth the interference variation trend. The cutoff frequency of the IIR low-pass filter is 100Hz. Then, the notch center frequency is adaptively determined according to the rotor rotation frequency or the airframe vibration frequency. The periodic interference components that are synchronized with the rotor rotation frequency are suppressed by adaptive notch filtering. The notch frequency corresponds to the rotor rotation frequency of 20Hz to 50Hz. The frequency hopping anti-interference step S5 targets external co-frequency suppression interference and low-altitude multipath interference, and adopts an adaptive frequency hopping mechanism. The adaptive frequency hopping mechanism establishes an available frequency point table, a disturbed frequency point table, and a candidate recovery frequency point table based on the SINR value, bit error rate, and CQI, and dynamically updates the available frequency point table, disturbed frequency point table, and candidate recovery frequency point table according to the real-time channel quality of each frequency point; The available frequency table is used to store the frequency points whose current channel quality meets the communication requirements; The harassed frequency table is used to store frequency points where the SINR value is lower than a preset threshold, the bit error rate is higher than a preset threshold, or suppression interference occurs continuously in the same frequency channel; The candidate recovery frequency table is used to store frequency points that were previously added to the disturbed frequency point table but whose channel quality indicators subsequently recovered to a preset range; when a candidate recovery frequency point remains stable within multiple consecutive sliding windows, it is added back to the available frequency point table; The communication transmission parameters and link switching strategies corresponding to Level 4 interference are as follows: Level 1: Using 64QAM modulation and Turbo code with a code rate of 3 / 4, with a target throughput of ≥1Mbps; Level 2: Employs 16QAM modulation, Turbo code with a code rate of 1 / 2, enables basic ARQ retransmission mechanism, performs 2 retransmissions, and aims for a bit error rate ≤10. -4 ; Level 3: Employs QPSK modulation and LDPC encoding at 1 / 3 bit rate, combined with data interleaving, and activates a hybrid ARQ retransmission mechanism. The number of retransmissions is dynamically adjusted to 3-5 times, with a target bit error rate ≤10%. -5 ; Among them, data interleaving is used to discretize continuous burst errors into random errors, making error correction codes easier to correct; Level 4: Trigger dual-link redundancy switching strategy and adaptive frequency hopping mechanism, remove disturbed frequency points with SINR < -5dB, and add the disturbed frequency points to the disturbed frequency point table with a frequency point interval ≥ 5MHz.

[0014] Furthermore, the dual-link redundancy handover strategy is as follows: The airborne terminal and the ground station deploy a primary link and a backup link simultaneously. The primary link uses the 2.4 GHz frequency band, and the backup link uses the 5.8 GHz frequency band. The two links hop independently and transmit in parallel. When the main link bit error rate > 10 -4 When SINR < 0dB, a seamless handover mechanism from the primary link to the backup link is triggered, with a handover latency of < 10ms. During the handover process, control frame buffering and retransmission and data frame breakpoint resumption mechanisms are used. After switching to the backup link, continuously monitor the quality of the primary link; when the primary link bit error rate is ≤10... -4 When SINR ≥ 5dB and channel quality score ≥ 80 points for three consecutive sliding windows, the system will automatically switch back to the main link; otherwise, the system will maintain transmission on the backup link.

[0015] Furthermore, in step S6: The hierarchical anti-jamming frame structure includes: control frames, data frames, and anti-jamming frames. The control frame is a fixed length of 16 bytes, using LDPC encoding at a bit rate of 1 / 2 and an encoding gain of ≥5dB, and the timestamp is encrypted using the AES-128 algorithm; The length of the data frame is 64 to 512 bytes. The minimum frame length of 64 bytes is used under strong interference, and the maximum frame length of 512 bytes is used under weak or no interference. The interleaving delay is ≤1ms. The anti-interference frame is a fixed length of 32 bytes, and one frame is transmitted every 5 data frames. The synchronization accuracy is ≤1μs. The synchronization information of channel quality (CQI), interference intensity, and frequency hopping sequence is embedded in the frame.

[0016] Furthermore, in step S7: The lightweight reinforcement learning algorithm DQN optimizes frequency hopping decision and modulation-coding switching strategies through offline pre-training and online fine-tuning. The offline pre-training training samples are ≥100,000 sets, covering different interference scenarios and flight attitudes; The fine-tuning step size for online fine-tuning is ≤0.01, and the response latency is ≤8ms. For data longer than 512 bytes, it is transmitted in multiple subframes. Each subframe carries independent verification information, and 2 to 3 redundant copies are set for flight control commands and cargo status data.

[0017] Furthermore, in step S8: a weighted summation method is used to score the SINR, bit error rate, and transmission delay of the communication channel, and an independent communication channel is assigned to each UAV with a channel spacing of ≥5MHz.

[0018] The interference detection and link-layer anti-jamming system for small and medium-sized heavy-duty UAVs includes: Embedded communication architecture for building a lightweight embedded communication runtime environment; The data acquisition module is used to collect multi-source data in real time; The interference identification module, based on the collected multi-source data, uses the sliding window statistical method to perform rolling analysis on the multi-source data and filter out random noise. It also uses the threshold comparison method to compare the measured data with the preset threshold range to identify the type and intensity of interference currently affecting the wireless communication link. The interference classification module is used to classify the interference intensity into multiple levels based on the signal-to-interference-plus-noise ratio (SINR). The strategy matching and execution module is used to match and execute the corresponding anti-interference strategy based on the identified interference type and interference level. The link transmission module is used to achieve anti-interference transmission at the link layer by employing a hierarchical anti-interference frame structure at the link layer for data transmission. The strategy optimization module is used to dynamically optimize the frequency hopping decision and modulation and coding switching strategy for data transmitted in a hierarchical anti-interference frame structure. The cluster channel management module is used to score the quality of each UAV's communication channel in a multi-UAV cluster operation scenario and dynamically allocate independent communication channels based on the scoring results. The closed-loop control module is used to cyclically call the data acquisition module to the cluster channel management module throughout the entire UAV flight mission.

[0019] Compared with the prior art, the present invention can achieve the following beneficial effects: First, it has strong anti-interference targeting and outstanding adaptability: In response to the unique problem of electromagnetic interference from the rotors of small and medium-sized heavy-duty transport drones, a special filtering and interference identification strategy is designed, which can accurately distinguish between self-interference and external interference. Compared with existing general anti-interference solutions, the bit error rate caused by internal interference is reduced by more than 80%, significantly improving the link's anti-interference capability.

[0020] Second, lightweight deployment, adaptable to embedded resource constraints: adopting a C / C++ hybrid programming mode, strictly controlling the code size to ≤32KB and RAM usage to ≤8KB, it can be directly deployed on low-cost MCUs such as STM32 and ARM Cortex-R series, without the need for additional hardware costs, reducing resource consumption by more than 60%.

[0021] Third, excellent link continuity and real-time performance: Fast frequency switching and channel self-healing are achieved through C / C++ state machine, with a switching delay of <10ms. Combined with adaptive adjustment of transmission parameters based on flight attitude, it can effectively avoid link disconnection problems caused by low-altitude obstruction, multipath fading and airframe vibration, reducing the probability of link interruption by more than 90%.

[0022] Fourth, high transmission reliability and guaranteed transportation safety: Optimized frame structure and retransmission mechanism, combined with CRC32 checksum, data interleaving, framed transmission, and redundant copy design, ensure the link bit error rate is stably controlled at ≤10. -6 Compared to existing simple retransmission schemes, the error rate is reduced by three orders of magnitude, ensuring that critical data is not lost and avoiding security incidents caused by link failures.

[0023] Fifth, adapt to cluster operations and improve collaborative efficiency: The design of link layer adaptive channel avoidance and dynamic channel allocation strategy can effectively solve the problems of mutual interference and channel congestion when multiple machines are operating in a cluster. The efficiency of multi-machine collaborative communication is improved by more than 50%, which is suitable for multi-machine collaborative material delivery, emergency rescue and other scenarios.

[0024] The overall technical solution has a simple structure and low implementation cost. It does not require major modifications to the existing hardware structure and can be directly upgraded and deployed on the existing embedded platform. Furthermore, the C / C++ code is highly portable and has strong engineering practicality and promotional value. Attached Figure Description

[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention.

[0026] In the attached diagram: Figure 1 This is a flowchart of the interference perception and link layer anti-interference method for small and medium-sized heavy-duty UAVs described in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the principle of an anti-interference wireless communication link according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating interference identification and classification in an embodiment of the present invention; Figure 4 This is a schematic diagram of the hierarchical anti-interference frame structure according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the interference perception and link layer anti-interference system for small and medium-sized heavy-duty UAVs according to an embodiment of the present invention.

[0027] Explanation of reference numerals in the attached diagram: 1. Embedded communication architecture; 2. Data acquisition module; 3. Interference identification module; 4. Interference classification module; 5. Policy matching and execution module; 6. Link transmission module; 7. Policy optimization module; 8. Cluster channel management module; 9. Closed-loop control module. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0029] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0030] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0031] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0032] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a method for interference perception and link-layer adaptive anti-interference of small and medium-sized heavy-duty unmanned aerial vehicles (UAVs). It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Furthermore, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0034] The specific implementation steps of this method will be described in detail below.

[0035] This invention aims to solve the technical problems of existing technologies, such as limited sensing capabilities, inaccurate interference identification, and fixed and rigid anti-interference strategies with high resource consumption. The interference sensing and link-layer anti-interference method and system for small and medium-sized heavy-duty UAVs provided by this invention have the main technical objectives of lightweight embedded architecture adaptation, targeted interference processing, and high-reliability link protection. Specifically, it includes the following steps: Step S1: Building a lightweight embedded communication architecture. The embedded communication architecture is built by selecting a microcontroller as the core control unit, configuring an RF communication module, an interference detection module, and an attitude sensing module, and constructing a lightweight embedded communication operating environment. The first step in implementing this method is to build a lightweight communication architecture adapted to the embedded resource constraints of small to medium-sized heavy-duty UAVs. In one specific embodiment, an ARM Cortex-R series real-time security processor (such as the Cortex-R52) or an STMicroelectronics STM32F4 series high-performance microcontroller (such as the STM32F407) is selected as the core control unit. The ARM Cortex-R series is suitable for high real-time communication requirements, while the STM32F4 / F7 series high-performance microcontrollers are suitable for low-cost, lightweight deployment requirements. The main frequency of the core control unit is set to 168MHz~216MHz to ensure that the instruction execution cycle is ≤1μs.

[0036] The compatible RF communication module can be either the SX1278 (long-range low-power RF transceiver chip) or the nRF24L01+ (2.4GHz monolithic wireless transceiver chip). Its operating frequency bands must cover 2.4GHz, 5.8GHz, and 1.4GHz, with RF transmit power controlled between 10dBm and 20dBm and receive sensitivity no less than -120dBm. The interference detection module uses the AD8302 (RF amplitude and phase detection chip), covering the detection frequency band from 1.4GHz to 5.8GHz, with a detection accuracy better than 0.5dB. The attitude sensing module uses either the MPU6050 (six-axis inertial measurement unit) or the BMI088 (high vibration resistance six-axis inertial measurement unit), with a sampling frequency of no less than 100Hz and an attitude measurement accuracy better than 0.1°.

[0037] The resource overhead of the entire embedded communication architecture is strictly controlled: the amount of code related to anti-interference at the link layer is ≤32KB, and the RAM usage is ≤8KB. The underlying driver and real-time data acquisition adopt interrupt triggering, with an acquisition cycle of ≤100μs. The link layer protocol stack adopts a layered modular design, independently encapsulating functions such as anti-interference strategies, frame processing, and channel management.

[0038] It should be noted that the above-mentioned hardware models (such as ARM Cortex-R52, STM32F407, SX1278, nRF24L01+, AD8302, MPU6050, BMI088) are merely exemplary implementations. Any microcontroller, radio frequency communication chip, interference detection chip, and attitude sensor that can achieve the same or similar functions can be used as an implementation of the present invention and all fall within the protection scope of the present invention.

[0039] Step S2 involves real-time acquisition of multi-source data, including: radio frequency interference characteristics acquired by the interference detection module, UAV attitude data acquired by the attitude perception module, and link status data obtained by the radio frequency communication module.

[0040] After the architecture is built, step S2 is executed, which involves real-time acquisition of multi-source data through the interference detection module and attitude perception module. The multi-source data includes three categories: radio frequency interference characteristics (amplitude, frequency, phase); UAV attitude data (pitch angle, roll angle, vibration frequency; when the vibration frequency is >10Hz, it is determined to be a strong vibration state of the aircraft); and link status data (bit error rate BER, transmission delay, channel quality CQI).

[0041] Step S3 Interference identification and classification: Based on the collected multi-source data, the sliding window statistical method is used to perform rolling analysis on the multi-source data and filter out random noise. Combined with the threshold comparison method, the measured data is compared with the preset threshold range to identify the type and intensity of interference to the current wireless communication link.

[0042] Step S4 classifies the interference intensity into multiple levels based on the signal-to-interference-plus-noise ratio (SINR). Interference types are identified using a sliding window statistical method (window length 10-20 frames, sliding step size 1 frame) combined with a threshold comparison method. By extracting the amplitude, frequency, and phase characteristics of the radio frequency signal and comparing them with preset thresholds, accurate differentiation can be achieved. Electromagnetic interference from the rotor itself (interference frequency at 2.4GHz±50MHz, amplitude range -30dBm to -10dBm, and synchronized with rotor rotation frequency of 20Hz to 50Hz or airframe vibration frequency). External co-frequency suppression interference (amplitude range -40dBm to -20dBm, and lacks synchronization characteristics with rotor rotation frequency or airframe vibration frequency, and continuously appears in co-frequency communication channels). The determination of low-altitude multipath interference includes: If, under conditions where no interference component synchronized with the rotor rotation frequency or airframe vibration frequency is detected, and no continuous suppression signal is detected from the same-frequency communication channel, deep fading or rapid fluctuations in received amplitude, short-term fluctuations in channel quality (CQI), transmission delay jitter, and rapid phase fluctuations occur within the sliding window, then the current wireless communication link is determined to be subject to low-altitude multipath interference. The interference identification accuracy is ≥98%, and the detection delay is ≤1ms.

[0043] When the amplitude ranges of the rotor's own electromagnetic interference and external co-frequency suppression interference overlap, a comprehensive judgment is made based on the frequency landing point, phase fluctuation, and whether the interference signal is synchronized with the rotor rotation frequency or the airframe vibration frequency. This avoids misjudgment caused by the overlap range of -30dBm to -20dBm. When the judgment conditions for rotor's own electromagnetic interference and external co-frequency suppression interference are met simultaneously, it is preferentially judged as rotor's own electromagnetic interference, and a filtering and anti-interference strategy is implemented.

[0044] In step S4, the interference intensity is divided into four levels based on the signal-to-interference-plus-noise ratio (SINR): Level 1 (no interference): SINR > 15dB; Level 2 (weak interference): 5dB≤SINR≤15dB; Level 3 (Strong Interference): -5dB≤SINR<5dB; Level 4 (Severe Interference): SINR < -5dB.

[0045] Step S5 Adaptive anti-interference strategy matching and execution: Based on the identified interference type and interference level, adaptive matching and execution of corresponding anti-interference strategies are performed; wherein, filtering anti-interference or frequency hopping anti-interference is performed for different interference types, and communication transmission parameters are dynamically adjusted or link switching strategies are executed according to the interference level.

[0046] After completing the identification of interference type and the determination of level, step S5 is executed to adaptively match and implement anti-interference strategy.

[0047] It should be noted that frequency hopping is used to mitigate low-altitude multipath interference by taking advantage of the differences in multipath propagation paths and fading characteristics at different frequencies. By switching to a frequency with shallower multipath fading, the link quality can be improved.

[0048] To address electromagnetic interference from the rotor itself, a combined filtering algorithm consisting of IIR low-pass filtering and adaptive notch filtering is employed. This combined filtering algorithm uses a cascaded processing approach. First, IIR low-pass filtering is applied to the interference characteristic sequence, interference amplitude envelope, or baseband characteristics to filter out random high-frequency noise and smooth the interference variation trend. The cutoff frequency of the IIR low-pass filter is 100Hz. Then, the notch center frequency is adaptively determined based on the rotor rotation frequency or the airframe vibration frequency. Adaptive notch filtering is then used to suppress periodic interference components synchronized with the rotor rotation frequency. The notch frequency corresponds to the rotor rotation frequency of 20Hz–50Hz, thereby achieving dynamic filtering of the rotor's own electromagnetic interference.

[0049] Cascaded processing is a term used in the field of signal processing, referring to two or more filters connected in series in sequence, with the output of the previous filter serving as the input of the next filter, rather than the two filters being processed in parallel and then fused together.

[0050] Specifically in this application, the first stage: IIR low-pass filtering first processes the interference feature sequence, interference amplitude envelope or baseband features to filter out random high-frequency noise and make the interference features smooth; The second stage: The adaptive notch filter receives the smoothed feature sequence output from the first stage and then performs notch filtering to suppress the periodic interference components that are synchronized with the rotor rotation frequency.

[0051] The adaptive frequency hopping mechanism establishes an available frequency table, a disturbed frequency table, and a candidate recovery frequency table based on SINR, bit error rate, and CQI, and dynamically updates these three tables according to the real-time channel quality of each frequency. The available frequency table stores frequencies whose current channel quality meets communication requirements; the disturbed frequency table stores frequencies with SINR values ​​below a preset threshold, bit error rates above a preset threshold, or those experiencing continuous suppression interference in the same-frequency channel; the candidate recovery frequency table stores frequencies that were previously added to the disturbed frequency table but whose channel quality indicators subsequently recovered to a preset range. When a candidate recovery frequency remains stable within multiple consecutive sliding windows, it is re-added to the available frequency table. The frequency hopping interval is ≥5MHz, the frequency hopping rate is ≥100 hops / second, and the frequency hopping switching delay is ≤5ms, achieving dynamic avoidance of external interference frequency bands.

[0052] At the same time, the following transmission and retransmission strategies are implemented based on the differences in interference levels: Level 1 (Interference-free): Using 64QAM modulation and Turbo code with a code rate of 3 / 4, the target throughput is ≥1Mbps.

[0053] Level 2 (weak interference): Uses 16QAM modulation, Turbo code with a code rate of 1 / 2, enables basic ARQ retransmission mechanism, retransmissions twice, target bit error rate ≤ 10. -4 .

[0054] Level 3 (Strong Interference): Employs QPSK modulation and LDPC coding at 1 / 3 code rate, combined with data interleaving, and activates a hybrid ARQ retransmission mechanism. The number of retransmissions is dynamically adjusted to 3-5 times, with a target bit error rate ≤10%. -5 .

[0055] Level 4 (Severe Interference): Trigger the dual-link redundancy switching strategy and the adaptive frequency hopping mechanism to remove the disturbed frequency points with SINR values ​​< -5dB and add the disturbed frequency points to the disturbed frequency point table with a frequency point interval of ≥ 5MHz to ensure that the link is not interrupted.

[0056] The dual-link redundancy switching strategy is as follows: The airborne terminal and ground station simultaneously deploy a primary link and a backup link. The primary link uses the 2.4GHz frequency band, and the backup link uses the 5.8GHz frequency band. Both links operate with independent frequency hopping and parallel transmission. When the primary link bit error rate > 10... -4 If SINR < 0dB, a seamless handover mechanism from the primary link to the backup link is triggered, with a handover latency < 10ms. During the handover process, control frame buffering and retransmission (buffer depth 10 frames) and data frame interruption resumption mechanisms are employed. After handover to the backup link, the quality of the primary link is continuously monitored; when the primary link bit error rate ≤ 10... -4When SINR ≥ 5dB and channel quality score ≥ 80 points for three consecutive sliding windows, the system automatically switches back to the primary link; otherwise, it maintains transmission on the backup link. Both manual and automatic switching modes are supported; link disconnection protection and severe interference avoidance have the highest priority, manual switching commands have higher priority than automatic switchback commands, and automatic switching logic performs link switching and switchback when no manual command is received.

[0057] This method particularly emphasizes the deep integration of UAV attitude perception data and link layer anti-interference strategies. When the attitude perception module measures a pitch angle or roll angle > 15° or a vibration frequency > 10Hz, it is determined to be a state of strong airframe vibration or large attitude angle. At this time, the link layer will dynamically reduce the transmission rate and increase the number of retransmissions to effectively avoid the problem of easy link disconnection under complex low-altitude conditions.

[0058] Step S6: Link Layer Hierarchical Anti-interference Frame Structure Transmission and Optimization. A link layer hierarchical anti-interference frame structure is adopted for data transmission. Through differentiated frame coding, data interleaving, and synchronization information embedding, link layer anti-interference transmission is achieved.

[0059] As described in step S6, a hierarchical anti-interference frame structure at the link layer is used for data transmission. The hierarchical anti-interference frame structure includes three types of frame bodies: Control frame (16-byte fixed length): LDPC encoding with a bit rate of 1 / 2 and an encoding gain of ≥5dB; timestamps are encrypted using the AES-128 algorithm, and the key dynamic update cycle is ≤10 seconds.

[0060] Data frames (length 64-512 bytes): dynamically fragmented according to interference level. The minimum frame length is 64 bytes in strong interference scenarios and dynamically adjusted to 512 bytes in weak or no interference scenarios. A data interleaving module is added with an interleaving depth of 16 and an interleaving delay of ≤1ms. When the data frame adopts a minimum frame length of 64 bytes and an interleaving depth of 16, the interleaving processing delay of a single data frame is no more than 1ms based on a block size of 256 bits.

[0061] Anti-interference frame (32-byte fixed length): transmitted once every 5 data frames, embedding channel quality CQI, interference intensity SINR and frequency hopping sequence synchronization information within the frame, with synchronization accuracy ≤1μs.

[0062] To further adapt to low-altitude heavy-load scenarios, this method also adopts the following optimized transmission mechanism: The frame synchronization header length is shortened to 8 bits, and Manchester encoding is used to achieve frame synchronization, with a synchronization capture time of ≤2μs.

[0063] A CRC32 check module has been added, covering the frame header, data segment, and frame trailer, with a check error rate ≤10. -9 .

[0064] Data interleaving adopts block interleaving with a block size of 256 bits, forming a dual anti-interference guarantee of "check + interleaving".

[0065] For large data volumes longer than 512 bytes, the data is transmitted in multiple subframes, each carrying independent verification information; 2 to 3 redundant copies are set up for flight control commands and cargo status data.

[0066] A state machine is used to achieve fast frequency switching and channel self-healing. The state machine includes four states: "normal transmission, interference detection, frequency switching, and channel recovery". The state switching delay is <10ms.

[0067] When the attitude sensing module measures a pitch or roll angle >15° or a vibration frequency >10Hz, it dynamically reduces the transmission rate and increases the number of retransmissions to avoid link disconnection caused by body vibration.

[0068] Step S7 Cross-layer collaborative anti-interference optimization: For the data transmitted by the hierarchical anti-interference frame structure, a lightweight reinforcement learning DQN algorithm is used to dynamically optimize the frequency hopping decision and modulation and coding switching strategy.

[0069] Step S7 implements cross-layer collaborative interference mitigation optimization between the link layer, physical layer, and network layer. Specifically, the link layer sends frequency hopping sequences and frequency avoidance instructions to the physical layer to accurately eliminate interfering frequencies; at the same time, it reports link quality, CQI value, and available bandwidth data to the network layer to guide the network layer in dynamically adjusting its routing strategy.

[0070] In a preferred embodiment, this method employs a lightweight reinforcement learning algorithm, DQN, to optimize frequency hopping decisions and modulation-coding switching strategies. First, offline pre-training is performed using over 100,000 samples covering different interference scenarios and flight attitudes; then, online fine-tuning is performed with a step size ≤0.01. In this way, the response latency is ≤8ms, making it suitable for embedded systems with computing power not exceeding 100 MIPS.

[0071] Step S8 Multi-UAV Cluster Channel Allocation: In a multi-UAV cluster operation scenario, the communication channels of each UAV are scored for quality. Independent communication channels are dynamically allocated based on the scoring results. The number of retransmissions and the transmission rate of the sliding window are dynamically adjusted according to the interference intensity level to achieve interference avoidance of the multi-UAV cluster communication link.

[0072] Step S8 designs a specialized channel allocation and retransmission mechanism for multi-drone cluster collaborative operation scenarios. A weighted summation method is used to score the SINR value, bit error rate, and transmission delay of each communication channel in real time, with a scoring range of 0-100. Channels scoring above 80 are considered high-quality channels, those between 60 and 80 are usable backup channels, and those below 60 are considered disturbed channels. Based on the scoring results, channels scoring above 80 are allocated first, channels between 60 and 80 are used as usable backup channels, and channels below 60 are not allocated temporarily. When no channel scoring above 80 exists, the highest-scoring usable backup channel (not lower than 60) is selected, and the modulation order is simultaneously reduced and the number of retransmissions is increased. This dynamically allocates an independent communication channel to each UAV, with a channel spacing ≥ 5MHz, effectively avoiding co-channel interference.

[0073] Simultaneously, a sliding window retransmission mechanism is implemented based on received acknowledgments (ACK / NACK), and the retransmission strategy is dynamically adjusted according to the interference intensity: 2 retransmissions are made under weak interference and 5 retransmissions are made under strong interference. The transmission rate is ≥1Mbps under no interference and ≥256kbps under strong interference, ultimately ensuring that the overall link bit error rate is ≤10% during cluster operation. -6 .

[0074] Closed-loop execution and link status monitoring: It also includes step S9. Steps S2 to S8 are executed cyclically throughout the entire UAV flight mission, and the link status is monitored in real time during the cycle; when the link bit error rate is detected to be >10... -4 If the SINR value is less than 0 dB, the link self-healing action is triggered, and the link status is fed back to step S2 to maintain the closed-loop control of the link layer anti-interference communication.

[0075] The link status monitoring module monitors the link quality in real time and maintains the current transmission parameters under normal circumstances. Once link deterioration is detected, the state machine is triggered to complete channel self-healing within 10ms to ensure the continuity and stability of the communication link.

[0076] In addition, as Figure 5 As shown, the interference perception and link-layer anti-interference system for small and medium-sized heavy-duty UAVs includes: Embedded communication architecture 1, including a microcontroller, an RF communication module, an interference detection module, and an attitude sensing module, is used to build a lightweight embedded communication operating environment; The data acquisition module 2 is used to acquire multi-source data in real time. The multi-source data includes: radio frequency interference characteristics acquired by the interference detection module, UAV attitude data acquired by the attitude perception module, and link status data acquired by the radio frequency communication module. Interference identification module 3 is used to perform rolling analysis on the multi-source data based on the collected multi-source data using the sliding window statistical method and filter out random noise, and to compare the measured data with the preset threshold range using the threshold comparison method to identify the type and intensity of interference received by the current wireless communication link. Interference classification module 4 is used to classify the interference intensity into multiple levels based on the signal-to-interference-plus-noise ratio (SINR). The strategy matching and execution module 5 is used to adaptively match and execute the corresponding anti-interference strategy according to the identified interference type and interference level; wherein, filtering anti-interference or frequency hopping anti-interference is executed for different interference types, and communication transmission parameters are dynamically adjusted or link switching strategies are executed according to the interference level. The link transmission module 6 is used to transmit data using a hierarchical anti-interference frame structure at the link layer. Through differentiated frame coding, data interleaving, and synchronization information embedding, it achieves anti-interference transmission at the link layer. Strategy optimization module 7 is used to dynamically optimize the frequency hopping decision and modulation and coding switching strategy for the data transmitted by the hierarchical anti-interference frame structure using a lightweight reinforcement learning DQN algorithm. The cluster channel management module 8 is used to score the quality of each UAV communication channel in a multi-UAV cluster operation scenario, dynamically allocate independent communication channels based on the scoring results, and dynamically adjust the sliding window retransmission count and transmission rate according to the interference intensity level to achieve interference avoidance of the multi-UAV cluster communication link. Closed-loop control module 9 is used to cyclically call the data acquisition module 2 to the cluster channel management module 8 throughout the entire UAV flight mission, and monitor the link status in real time during the loop; when the link bit error rate is detected to be >10... -4 If the SINR value is less than 0 dB, the link self-healing action is triggered, and the link status is fed back to the data acquisition module 2 to maintain the closed-loop control of the link layer anti-interference communication.

[0077] The data acquisition module 2 to the closed-loop control module 9 are connected in sequence. The multi-source data acquired by the data acquisition module 2 is transmitted to the interference identification module 3. The interference type and intensity identified by the interference identification module 3 are transmitted to the interference classification module 4 for classification. The interference classification module 4 transmits the classification of interference levels to the strategy matching and execution module 5 to match the corresponding anti-interference strategy. The execution result of the strategy matching and execution module 5 is transmitted to the link transmission module 6 for anti-interference encapsulation. The strategy optimization module 7 dynamically optimizes the frequency hopping decision and modulation and coding switching strategy of the strategy matching and execution module 5. The cluster channel management module 8 allocates communication channels and adjusts transmission parameters in multi-machine cluster scenarios. The closed-loop control module 9 continuously calls the data acquisition module 2 to the cluster channel management module 8, and triggers the link self-healing action when the link quality is lower than the threshold, feeding back the link status to the data acquisition module 2 to form closed-loop control.

[0078] Through the above description of specific embodiments, it can be clearly understood that the method and system proposed in this invention effectively solve the link reliability problem of small and medium-sized heavy-duty UAVs in complex electromagnetic environments through a series of innovative mechanisms such as multi-source sensing, precise identification, hierarchical adaptation, and cross-layer collaboration, and meet the requirements of lightweight embedded deployment, thus possessing extremely high practical value.

[0079] Furthermore, steps S1 to S8 are not executed once, but form a continuous closed-loop control process. The link status monitoring module monitors the link quality in real time and maintains the current transmission parameters under normal circumstances. Once link deterioration is detected, the state machine is triggered to complete channel self-healing within 10ms and feeds back the link status to step S2, re-triggering multi-source data acquisition and interference identification, thereby achieving continuous dynamic adaptive adjustment. The entire process is executed cyclically throughout the entire UAV flight mission until the mission ends, ensuring the continuity and stability of the communication link.

[0080] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Those skilled in the art can make various improvements and modifications without departing from the spirit and principles of the invention, and these improvements and modifications should also be considered within the scope of protection of the invention. It should be understood that the various processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0081] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for interference perception and link-layer anti-interference of small and medium-sized heavy-duty unmanned aerial vehicles (UAVs), characterized in that, Includes the following steps: S1: Build an embedded communication architecture, select a microcontroller as the core control unit, and configure an RF communication module, an interference detection module, and an attitude perception module. S2: Real-time acquisition of multi-source data, including: radio frequency interference characteristics acquired by the interference detection module, UAV attitude data acquired by the attitude perception module, and link status data obtained by the radio frequency communication module; S3: Based on the collected multi-source data, the sliding window statistical method is used to perform rolling analysis on the multi-source data and filter out random noise. Combined with the threshold comparison method, the measured data is compared with the preset threshold range to identify the type and intensity of interference to the current wireless communication link. S4: The interference intensity is classified into multiple levels based on the signal-to-interference-plus-noise ratio (SINR); S5: Based on the identified interference type and interference level, adaptively match and execute the corresponding anti-interference strategy; wherein, for different interference types, respectively perform filtering anti-interference or frequency hopping anti-interference, and dynamically adjust communication transmission parameters or execute link switching strategy according to the interference level; S6: Data transmission is performed using a hierarchical anti-interference frame structure at the link layer. Anti-interference transmission at the link layer is achieved through differentiated frame coding, data interleaving, and synchronization information embedding. S7: For the data transmitted by the hierarchical anti-interference frame structure, the lightweight reinforcement learning DQN algorithm is used to dynamically optimize the frequency hopping decision and modulation and coding switching strategy. S8: In multi-drone cluster operation scenarios, the quality of each drone's communication channel is scored, and independent communication channels are dynamically allocated based on the scoring results.

2. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 1, characterized in that, The core control unit has a main frequency of 168MHz to 216MHz and an instruction execution cycle of ≤1μs. The radio frequency communication module operates in frequency bands covering 2.4GHz, 5.8GHz and 1.4GHz; The interference detection module covers a frequency band of 1.4 GHz to 5.8 GHz; The attitude sensing module has a sampling frequency of ≥100Hz, an attitude measurement accuracy of ≤0.1°, and uses an interrupt-triggered method to collect the multi-source data with a data acquisition period of ≤100μs. The anti-interference code size at the link layer is limited to ≤32KB, and the memory usage is limited to ≤8KB. The radio frequency interference characteristics include amplitude, frequency, and phase; The UAV attitude data includes pitch angle, roll angle and vibration frequency. When the vibration frequency is greater than 10Hz, it is determined to be a strong vibration state of the aircraft. The link state data includes bit error rate, latency, and channel quality index (CQI).

3. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 2, characterized in that, The sliding window statistical method has a window length of 10 to 20 data frames and a sliding step size of 1 data frame. The types of interference include rotor electromagnetic interference, external co-frequency suppression interference, and low-altitude multipath interference. Among them, the external co-frequency suppression interference and the low-altitude multipath interference are identified as independent interference types; The preset amplitude range of the rotor's own electromagnetic interference is -30dBm to -10dBm, and the preset amplitude range of the external co-frequency suppression interference is -40dBm to -20dBm. When the amplitude range of the rotor's own electromagnetic interference overlaps with that of the external same-frequency suppression interference, the determination is made based on the frequency landing point, phase fluctuation, and whether the interference signal is synchronized with the rotor rotation frequency or the body vibration frequency. If the interference frequency is located at 2.4GHz±50MHz and is synchronized with the rotor rotation frequency or airframe vibration frequency in the range of 20Hz~50Hz, it is determined to be electromagnetic interference from the rotor itself. If the interference signal is out of sync with the rotor rotation frequency or the airframe vibration frequency, and continues to appear in the same frequency communication channel, it is determined to be external same frequency suppression interference. The determination of low-altitude multipath interference includes: if no interference component synchronized with the rotor rotation frequency or the airframe vibration frequency is detected, and no continuous suppression signal of the same frequency communication channel is detected, if deep fading or rapid fluctuation of received amplitude, short-term fluctuation of channel quality (CQI), transmission delay jitter, and rapid phase fluctuation occur within the sliding window, then the current wireless communication link is determined to be subject to low-altitude multipath interference.

4. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 3, characterized in that, In step S4, the interference intensity is divided into four levels based on the signal-to-interference-plus-noise ratio (SINR): Level 1, SINR > 15dB, is an interference-free scenario; Level 2, 5dB≤SINR≤15dB, is a weak interference scenario; Level 3, -5dB≤SINR<5dB, is a strong interference scenario; Level 4, SINR < -5dB, indicates a severe interference scenario.

5. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 4, characterized in that, The filtering and interference suppression in step S5 targets the electromagnetic interference of the rotor itself, and adopts a combined filtering algorithm consisting of IIR low-pass filtering and adaptive notch filtering. The combined filtering algorithm adopts a cascaded processing method. First, IIR low-pass filtering is applied to the interference feature sequence, interference amplitude envelope or baseband features to filter out random high-frequency noise and smooth the interference change trend. The cutoff frequency of the IIR low-pass filter is 100Hz. The notch center frequency is then adaptively determined based on the rotor rotation frequency or the airframe vibration frequency. The periodic interference components that are synchronized with the rotor rotation frequency are suppressed by adaptive notch filtering. The notch frequency corresponds to the rotor rotation frequency of 20Hz to 50Hz. The frequency hopping anti-interference in step S5 is aimed at the external co-frequency suppression interference and the low-altitude multipath interference, and adopts an adaptive frequency hopping mechanism. The adaptive frequency hopping mechanism establishes an available frequency point table, a disturbed frequency point table, and a candidate recovery frequency point table based on the SINR value, bit error rate, and CQI, and dynamically updates the available frequency point table, the disturbed frequency point table, and the candidate recovery frequency point table according to the real-time channel quality of each frequency point. The available frequency table is used to store frequency points whose current channel quality meets communication requirements; The disturbed frequency table is used to store frequency points whose SINR value is lower than a preset threshold, whose bit error rate is higher than a preset threshold, or whose suppression interference occurs continuously in the same frequency channel. The candidate recovery frequency point table is used to store frequency points that were previously added to the disturbed frequency point table but whose channel quality indicators subsequently recovered to a preset range; when a candidate recovery frequency point remains stable within multiple consecutive sliding windows, it is added back to the available frequency point table; The communication transmission parameters and link switching strategies corresponding to the fourth level of interference are as follows: Level 1: Using 64QAM modulation and Turbo code with a code rate of 3 / 4, with a target throughput of ≥1Mbps; Level 2: Employs 16QAM modulation, Turbo code with a code rate of 1 / 2, enables basic ARQ retransmission mechanism, performs 2 retransmissions, and aims for a bit error rate ≤10. -4 ; Level 3: Employs QPSK modulation and LDPC encoding at 1 / 3 bit rate, combined with data interleaving, and activates a hybrid ARQ retransmission mechanism. The number of retransmissions is dynamically adjusted to 3-5 times, with a target bit error rate ≤10%. -5 ; Level 4: Trigger the dual-link redundancy switching strategy and the adaptive frequency hopping mechanism, remove the disturbed frequency points with SINR < -5dB, and add the disturbed frequency points to the disturbed frequency point table with a frequency point interval ≥ 5MHz.

6. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 5, characterized in that, The dual-link redundancy handover strategy is as follows: The airborne terminal and the ground station deploy a primary link and a backup link simultaneously. The primary link uses the 2.4 GHz frequency band, and the backup link uses the 5.8 GHz frequency band. The two links hop independently and transmit in parallel. When the main link bit error rate > 10 -4 When SINR < 0dB, a seamless handover mechanism from the primary link to the backup link is triggered, with a handover latency of < 10ms. During the handover process, control frame buffering and retransmission and data frame breakpoint resumption mechanisms are used. After switching to the backup link, continuously monitor the quality of the primary link; when the primary link bit error rate is ≤10... -4 If SINR ≥ 5dB and channel quality score ≥ 80 points for three consecutive sliding windows, the system will automatically switch back to the main link; otherwise, the system will maintain transmission on the backup link.

7. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 6, characterized in that, In step S6: The hierarchical anti-interference frame structure includes: control frames, data frames, and anti-interference frames. The control frame is a fixed length of 16 bytes, using LDPC encoding with a code rate of 1 / 2 and an encoding gain of ≥5dB, and the timestamp is encrypted using the AES-128 algorithm; The length of the data frame is 64 to 512 bytes. The minimum frame length of 64 bytes is used under strong interference, and the maximum frame length of 512 bytes is used under weak interference or no interference. The interleaving delay is ≤1ms. The anti-interference frame is a fixed length of 32 bytes, and one frame is transmitted every 5 data frames. The synchronization accuracy is ≤1μs. The synchronization information of the channel quality (CQI), the interference intensity, and the frequency hopping sequence is embedded in the frame.

8. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 3, characterized in that, In step S7: The lightweight reinforcement learning DQN algorithm optimizes frequency hopping decision and modulation-coding switching strategies through offline pre-training and online fine-tuning. The offline pre-training training samples are ≥100,000 sets, covering different interference scenarios and flight attitudes; The fine-tuning step size for online fine-tuning is ≤0.01, and the response latency is ≤8ms. For data longer than 512 bytes, it is transmitted in multiple subframes. Each subframe carries independent verification information, and 2 to 3 redundant copies are set for flight control commands and cargo status data.

9. The interference perception and link-layer anti-interference method for small and medium-sized heavy-duty UAVs according to claim 1, characterized in that, In step S8: The SINR, bit error rate and transmission delay of the communication channel are scored using a weighted summation method, and an independent communication channel is assigned to each UAV with a channel spacing of ≥5MHz.

10. A system for interference perception and link-layer anti-interference of small and medium-sized heavy-duty unmanned aerial vehicles (UAVs), characterized in that, include: Embedded communication architecture (1) is used to build a lightweight embedded communication runtime environment; The data acquisition module (2) is used to acquire multi-source data in real time; The interference identification module (3) uses the sliding window statistical method to perform rolling analysis on the multi-source data and filter out random noise based on the collected multi-source data. It also uses the threshold comparison method to compare the measured data with the preset threshold range to identify the type and intensity of interference to the current wireless communication link. Interference classification module (4) is used to classify the interference intensity into multiple levels based on the signal-to-interference-plus-noise ratio (SINR). The strategy matching and execution module (5) is used to match and execute the corresponding anti-interference strategy according to the identified interference type and interference level; The link transmission module (6) is used to implement anti-interference transmission at the link layer by using a hierarchical anti-interference frame structure at the link layer for data transmission. The strategy optimization module (7) is used to dynamically optimize the frequency hopping decision and modulation and coding switching strategy for the data transmitted by the hierarchical anti-interference frame structure; The cluster channel management module (8) is used to score the quality of each UAV communication channel in a multi-UAV cluster operation scenario and dynamically allocate independent communication channels based on the scoring results. The closed-loop control module (9) is used to cyclically call the data acquisition module (2) to the cluster channel management module (8) throughout the entire UAV flight mission.

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