A GNSS side signal injection method and device for a drone nest and related media

Abstract

The application discloses a GNSS side signal injection method and device for a UAV nest and related media, which comprises coordinate matching correction on dynamic positioning data, triggering the injection module to perform power-on self-test to inject test signals and detect loss, setting initial gain, performing near-field coupling injection on GNSS side signals received by the nest side, and dynamically adjusting the relay gain to a target interval according to a preset closed-loop adjustment algorithm to obtain gain optimization data; performing steady-state determination on the gain optimization data, respectively determining take-off release and coupling removal, and integrating output reset learning data. The application sets the initial gain and injects the GNSS side signals received by the nest side in a near-field coupling mode to enhance, finally determines the take-off release and coupling removal in combination with take-off transition data through a series of calculations, and outputs reset learning data, so that the satellite signal receiving capability of the UAV is effectively improved without changing the UAV body structure.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to a method, apparatus, and related medium for injecting GNSS signals into a UAV nest. Background Technology

[0002] As the application of swarm performance drones develops towards high-density, vertically stacked multi-layered nests, the Global Navigation Satellite System (GNSS) antennas on top of drones located in the lower compartments are easily blocked by the fuselage, power components, and other obstructions of the upper drones. This causes significant attenuation of satellite signals in the first and second frequency bands inside the nest, resulting in a decrease in carrier-to-noise ratio, insufficient available satellite observations, and failures in real-time dynamic positioning initialization.

[0003] In existing technologies, methods such as using a high-gain antenna on the top of the drone nest for wired distribution, adding an external antenna to the drone, or using omnidirectional reception and increasing transmission power are all insufficient to meet the independent reception needs of each drone in a multi-layered, compact space for the original observation data. Especially when small performance drones generally use a sealed module integrating the receiver and antenna, lack external radio frequency interfaces, and are inconvenient to modify the drone's structure, existing solutions cannot effectively improve the satellite signal reception capability of the lower-level drones without altering the drone's structure, thus failing to eliminate the positioning instability problem caused by obstruction of the lower-level drones. Summary of the Invention

[0004] This invention provides a method, apparatus, and related medium for injecting GNSS signals into a UAV nest, aiming to solve the technical problem in the prior art that it is difficult to improve the satellite signal reception capability of a UAV without altering its main structure.

[0005] In a first aspect, embodiments of the present invention provide a GNSS-side signal injection method for a UAV nest, comprising:

[0006] The dynamic positioning data of the UAV is acquired, and the coordinate matching correction is performed on the dynamic positioning data to obtain the nest entry pose data.

[0007] The injection module is triggered to perform a power-on self-test based on the nesting pose data to inject test signals and detect losses, thereby obtaining path self-test data.

[0008] The initial gain is set using the self-test data of the path, and near-field coupling injection is performed on the GNSS signal received by the nest side to obtain injection enhancement operation data;

[0009] Based on the injected enhanced operating data, the relay gain is dynamically adjusted to the target range according to a preset closed-loop adjustment algorithm to obtain gain optimization data.

[0010] The gain optimization data is steady-state determined, and the gain is locked and the optimal gain value is recorded when the preset stable duration and fluctuation threshold are met. At the same time, the relay gain is reduced to the minimum value and the radio frequency switch is disconnected in a linear transition mode before the preset takeoff, so as to obtain takeoff transition data.

[0011] The takeoff transition data is used to determine takeoff release and coupling release respectively, and the reset learning data is integrated and output.

[0012] Secondly, embodiments of the present invention provide a GNSS-side signal injection device for a UAV nest, comprising:

[0013] The data acquisition unit is used to acquire the dynamic positioning data of the UAV and perform coordinate matching correction on the dynamic positioning data to obtain the nest entry pose data.

[0014] The data injection unit is used to trigger the injection module to perform a power-on self-test based on the nesting pose data, so as to inject test signals and detect losses to obtain path self-test data.

[0015] The data enhancement unit is used to set the initial gain using the path self-test data, and simultaneously perform near-field coupling injection on the GNSS side signal received by the nest side to obtain injection enhancement operation data.

[0016] The data gain unit is used to dynamically adjust the relay gain to the target range based on the injected enhanced operating data according to a preset closed-loop adjustment algorithm, so as to obtain gain-optimized data.

[0017] The data adjustment unit is used to perform steady-state determination on the gain optimization data and lock the gain and record the optimal gain value when the preset stable duration and fluctuation threshold are met. At the same time, before the preset takeoff, the relay gain is reduced to the minimum value in a linear transition mode and the radio frequency switch is disconnected to obtain takeoff transition data.

[0018] The data output unit is used to determine takeoff release and coupling release respectively using the takeoff transition data, and integrate and output reset learning data.

[0019] Thirdly, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the GNSS-side signal injection method for UAV nests of the first aspect.

[0020] Fourthly, embodiments of the present invention provide a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements the GNSS-side signal injection method for the UAV nest of the first aspect.

[0021] This invention provides a GNSS-side signal injection method for a UAV nest, comprising: acquiring dynamic positioning data of the UAV and performing coordinate matching correction on the dynamic positioning data to obtain nest entry pose data; triggering the injection module to perform a power-on self-test based on the nest entry pose data to inject a test signal and detect loss, thereby obtaining path self-test data; setting an initial gain using the path self-test data, and simultaneously performing near-field coupling injection on the GNSS-side signal received by the nest side to obtain injection enhancement operation data; dynamically adjusting the relay gain to the target range based on the injection enhancement operation data according to a preset closed-loop adjustment algorithm to obtain gain optimization data; performing steady-state determination on the gain optimization data and locking the gain and recording the optimal gain value when a preset stable duration and fluctuation threshold are met; simultaneously reducing the relay gain to the minimum value and disconnecting the RF switch in a linear transition manner before a preset takeoff to obtain takeoff transition data; and using the takeoff transition data to determine takeoff release and coupling deactivation respectively, and integrating and outputting reset learning data. This invention enhances the satellite signal reception capability of UAVs by setting an initial gain and injecting the GNSS signal received by the UAV nest side into the receiver via near-field coupling. Then, through a series of calculations, it determines the takeoff release and coupling decoupling by combining takeoff transition data and outputs reset learning data. In this way, the satellite signal reception capability of UAVs can be effectively improved without changing the structure of the UAV itself.

[0022] This invention also provides a GNSS-side signal injection device, computer equipment, and storage medium for a UAV nest, which also have the above-mentioned beneficial effects. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating a GNSS-side signal injection method for an unmanned aerial vehicle (UAV) nest, provided as an embodiment of the present invention;

[0025] Figure 2 This is a schematic block diagram of a GNSS-side signal injection device for a drone nest, provided as an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0028] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0029] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0030] Please see below. Figure 1 , Figure 1 The flowchart of a GNSS-side signal injection method for a UAV nest provided in an embodiment of the present invention specifically includes steps S101 to S106.

[0031] S101. Acquire the dynamic positioning data of the UAV and perform coordinate matching correction on the dynamic positioning data to obtain the nest entry pose data.

[0032] S102. Trigger the injection module to perform power-on self-test according to the nesting pose data to inject test signals and detect losses, and obtain the path self-test data.

[0033] S103. Set the initial gain using the self-test data of the channel, and simultaneously perform near-field coupling injection on the GNSS signal received by the nest side to obtain injection enhancement operation data.

[0034] S104. Based on the injected enhanced operation data, dynamically adjust the relay gain to the target range according to the preset closed-loop adjustment algorithm to obtain gain optimization data;

[0035] S105. The gain optimization data is steady-state determined and the gain is locked and the optimal gain value is recorded when the preset stable duration and fluctuation threshold are met. At the same time, the relay gain is reduced to the minimum value and the radio frequency switch is disconnected in a linear transition mode before the preset takeoff, so as to obtain takeoff transition data.

[0036] S106. Use the takeoff transition data to determine takeoff release and coupling release respectively, and integrate and output reset learning data.

[0037] In one embodiment, the UAV nest faces a multi-layered vertically stacked scenario, with lateral signal acquisition and near-field injection arranged: multiple GNSS transmission windows are opened on the four side walls or diagonal side walls of the nest. The window material is a composite transmission material with low dielectric constant and low loss tangent, such as polytetrafluoroethylene (PTFE) as the matrix and filled with ceramic microparticles; the transmittance is not less than 90% in multiple frequency bands, the reflection and absorption loss is less than 1 dB, and the window position is aligned with the GNSS receiving area of ​​each UAV layer inside. The GNSS status can include C / N0, number of satellites, RTK status, etc. C / N0 is a signal quality indicator commonly used in global navigation satellite system reception, also known as carrier-to-noise spectral density ratio. In a specific scenario, five layers of UAV nests can be vertically stacked, and near-field coupled radiation patches are installed at preset positions on the bottom or side wall of each UAV compartment as units of the inter-layer micro directional patch antenna array. The patch is connected to the relay signal network via a signal transmission channel. When the UAV is placed in the cabin, the radiator or ground plane of its sealed integrated onboard GNSS antenna is brought close to the near-field coupling radiation patch in the vertical or horizontal direction, typically at a distance of 1 to 10 mm, to achieve near-field electromagnetic coupling.

[0038] To compensate for transmission losses within the nest, a low-noise amplifier (LNA) is integrated inside each side window, with a noise figure no greater than 0.8 dB and a gain no less than 20 dB. Multiple LNA outputs are connected to a microstrip power divider network to merge relay signals into one or more low-interference signals. The relay antenna signals corresponding to each side window are transmitted via low-loss coaxial cables, such as RG-316 or semi-flexible coaxial cables, with a loss of no more than 0.3 dB / m in the L1 band, and are aggregated to the GNSS signal enhancement module at the top of the nest. This module serves as an auxiliary signal source, inputting the signal received by the UAV's own antenna to the UAV's GNSS receiver front-end to improve the C / N0 ratio, without replacing the original observation data acquisition. To ensure consistent near-field coupling efficiency during multiple nest entry processes, a precise mechanical positioning structure, such as guide pins, limiting slots, or magnetic adsorption devices, is installed inside the nest to ensure that the UAV's own GNSS antenna is aligned in three-dimensional space with the near-field coupling radiation patch within the compartment each time the UAV is parked. A signal strength adaptive control module can also be set up, which monitors the coupling status and received signal quality of each compartment and dynamically adjusts the amplification gain of the corresponding branch to avoid receiver saturation caused by excessively strong signals or insufficient enhancement caused by excessively weak signals.

[0039] Regarding signal fusion logic, the UAV's GNSS reception can employ intelligent switching or weighted fusion algorithms, automatically activating relay signal assistance before takeoff or in weak signal conditions to support rapid RTK (real-time dynamic positioning) convergence. Taking a five-layer drone nest as an example, five rectangular wave-transparent windows are opened on each of the east and west side walls of the nest, measuring 30mm x 40mm, with longitudinal spacing consistent with the drone's layer height, for example, 120mm. The windows are made of a 2mm thick PTFE and Al2O3 composite board. Approximately 2.2 The actual L1 transmittance is 92%, approximately 0.001. A 20 mm by 20 mm RHCP patch antenna is installed tightly on the inner side of each window, with a center frequency of 1575.42 MHz and a 3-dB beamwidth of not less than 90° in the horizontal plane. The antenna back end integrates a Mini-Circuits LNA, such as the GPSA1500. Five LNA outputs on each side are connected to a Wilkinson microstrip 1-to-5 power divider. The two signals are led to the central distribution network via low-loss coaxial cables. A circular coupling patch with a diameter of about 25 mm is installed in the center of the floor of each UAV compartment. The coupling patch receives relay signals from the corresponding layer's side window. The compartment is equipped with a tapered guide post and the UAV's belly is equipped with a guide hole, so that the height of the UAV's own GNSS antenna relative to the coupling patch can be repeated when the UAV is placed in the compartment, and the spacing is controlled within 5±2 mm. After power-on, the gain of each branch LNA can be controlled to increase slowly from low to high, and the C / N0 reported by the UAV can be detected. When the C / N0 reaches a preset target, such as 40 dB-Hz, the current gain is locked to achieve adaptive enhancement.

[0040] Based on the above structure, in step S101, the dynamic positioning data of the UAV is acquired, and the dynamic positioning data is corrected by coordinate matching so that the current pose of the UAV is aligned with the preset parking position of the nest under the same coordinate caliber, thereby obtaining the nest entry pose data; the nest entry pose data is used to characterize that the UAV has entered the parking state where side signal injection can be performed, and to provide input for triggering subsequent injection actions.

[0041] In one embodiment, step S101 includes:

[0042] The dynamic positioning data of the UAV is acquired, and the dynamic positioning data is matched and corrected with the preset coordinates of the UAV nest to obtain the matching and correction result;

[0043] Based on the matching and correction results, a drone landing guidance signal is generated, and landing matching data is obtained by integrating the results.

[0044] Speed ​​control is applied to the landing matching data to make the UAV land at a preset speed, and the contact status between the bottom guide structure of the UAV and the guide pin of the nest is detected to obtain guide contact data;

[0045] The guide contact data is subjected to horizontal deviation correction processing to obtain horizontal correction data;

[0046] The final pose is determined based on the horizontal correction data to obtain the nest entry pose data.

[0047] In this embodiment, dynamic positioning data of the UAV is acquired, which may include the UAV's real-time coordinates, heading angle, pitch angle, roll angle, and RTK positioning results. This dynamic positioning data is then matched and corrected with the nest's preset coordinates to align the UAV's current position with the nest's preset parking point on the same coordinate reference, and the matching correction result is output. Here, the RTK positioning provides a positional accuracy on the order of ±1 cm, supporting high-precision guidance and alignment of the UAV before entering the nest, enabling the UAV to perform nest entry actions near the nest's preset coordinates. After obtaining the matching correction result, a UAV landing guidance signal is generated and integrated to obtain landing matching data. The landing guidance signal may include the desired descent channel, desired attitude angle, desired landing point deviation, and allowable deviation range during the descent process, instructing the UAV to enter along the center area of ​​the nest opening and gradually align with the cabin position. The landing matching data serves as input for subsequent motion control, recording the difference between the UAV's current pose and the target pose for continuous correction during descent.

[0048] Furthermore, the landing matching data is subjected to speed control, causing the UAV to land at a preset speed, and the contact status between the UAV's bottom guide structure and the nest guide pin is detected to obtain guide contact data. The preset speed can be set to a slow landing speed of 0.3-0.5 m / s to reduce the impact at the moment of contact and improve positioning stability. As the UAV continues to descend, contact detection confirms that the UAV's bottom guide structure has made contact with the nest conical guide pin; the guide contact data can record the contact time, contact position, contact direction, and the deviation trend of the UAV relative to the cabin center after contact, which is used to support subsequent deviation correction. After obtaining the guide contact data, the guide contact data is processed for horizontal deviation correction to obtain horizontal correction data. Specifically, the nest conical guide pin performs automatic correction for the UAV's horizontal deviation, which can gradually converge the horizontal deviation on the order of ±1 cm; at the same time, combined with the real-time measurement of the UAV's attitude and position, the residual deviation during the correction process is compensated, so that the final positioning accuracy reaches less than ±0.5 mm. The horizontal correction data may include the corrected lateral offset, longitudinal offset, remaining deviation, and correction completion flag, which are used to indicate that the UAV has been accurately aligned in the horizontal plane.

[0049] Finally, the final pose is determined based on the horizontal correction data to obtain the nest entry pose data. After the UAV continues to descend until its fuselage contacts the limiting surface, the vertical parking height is determined using the limiting surface, and the nest entry pose is locked at this height. In this embodiment, the coupling distance can be controlled at 5.0 ± 0.2 mm to ensure the repeatability of the relative position during the subsequent near-field coupling injection stage. The nest entry pose data can be summarized and recorded, including the corrected three-dimensional position, attitude angles, and alignment status with key structural components of the cabin, providing input for the power-on self-test trigger in the subsequent step S102.

[0050] In step S102, the injection module is triggered to perform a power-on self-test based on the nesting pose data. After power-on, the injection module executes the self-test process and injects a test signal into the injection module. The loss is detected by the transmission result of the test signal to obtain the path self-test data. The path self-test data is used to characterize whether the current cabin signal injection channel meets the preset injection conditions and to provide data input for the initial gain setting.

[0051] In one embodiment, step S102 includes:

[0052] The arrival status of the drone is detected based on the nesting pose data, and a communication connection is established to obtain connection establishment data;

[0053] The relay system is powered on using the connection establishment data, and the parameters of the low-noise amplifier and power divider in the injection module are self-tested to obtain hardware self-test data.

[0054] Based on the hardware self-test data, a test signal is injected into the injection module, and the test signal is transmitted to the coupling patch to obtain test injection data.

[0055] Near-field probe detection is performed on the injected test data to obtain the test signal strength and thus the path detection result.

[0056] When the path detection result is abnormal, the corresponding channel identifier is recorded and a backup channel is enabled or the current channel is skipped. When the path detection result is normal, the channel identifier is retained and the channel processing data is integrated.

[0057] Based on the channel processing data, navigation status data reported by the UAV is received, and the channel self-test data is calculated.

[0058] In this embodiment, the arrival status of the UAV is detected based on the nesting posture data. Arrival detection can be comprehensively determined through cabin arrival sensor signals, charging contact status, cabin access control status, or parking confirmation flags reported by the UAV. After arrival is confirmed, the nest and the UAV establish a communication connection and a charging connection. The communication connection can be wired or wireless. The connection establishment data records at least the connection method identifier, connection establishment time, connection status code, and corresponding cabin identifier for subsequent traceability and management of the injection process. After obtaining the connection establishment data, the relay system is powered on using this data, and parameter self-checks are performed on key components such as the low-noise amplifier (LNA) and power divider within the injection module. After power-on, the self-check content may include whether the supply voltage and current are within the allowable range, whether the LNA gain setting is responsive, whether the power divider port is usable, and whether the RF switch is controllable. Hardware self-check data can be recorded at the cabin and channel granularity, including self-check results, error codes, and corresponding component identifiers, serving as input for subsequent injection testing and channel selection. Then, based on the hardware self-test data, a test signal is injected into the injection module, causing the test signal to be transmitted along a preset RF channel to the coupling patch, thus obtaining test injection data. The test signal can be a test signal with a power of -80dBm to cover the complete path from the side window receiver, LNA amplifier, power divider network to the coupling patch. The test injection data should at least record the test signal power, frequency band identifier, injection channel identifier, and injection duration to facilitate correspondence with the test results.

[0059] After the test injection data is generated, a near-field probe is used to detect the test signal strength at the coupling patch, thus obtaining the path detection result. The near-field probe can be set at a preset detection position or a maintenance detection position on the coupling patch to collect test signal amplitude information and calculate path loss. The path detection result may include the measured signal strength, path loss value, and a judgment flag indicating whether a preset threshold is met, where the path loss threshold can be set to less than 3dB. If the path detection result is abnormal, the corresponding channel identifier is recorded, and a channel handling strategy is executed, including activating a backup channel or skipping the current channel. If the path detection result is normal, the channel identifier remains unchanged, and the channel identifier and the detection pass flag are written into the channel processing data. Finally, navigation status data reported by the UAV is received based on the channel processing data, and path self-test data is calculated. The navigation status data reported by the UAV may include at least the GNSS receive quality C / N0, the number of available satellites, and the RTK status. The UAV nest performs status negotiation and enhancement decisions based on this navigation status data. For example, if C / N0 is less than 32 dB-Hz, it determines that enhancement needs to be enabled; if C / N0 is greater than or equal to 40 dB-Hz, it determines that enhancement can be disabled or disabled. The channel self-test data may comprehensively include channel processing data, navigation status data, and enhancement decision flags, thus providing directly callable data input for the initial gain setting and near-field coupling injection in subsequent steps S103.

[0060] In step S103, the initial gain is set using the path self-test data, and near-field coupling injection is performed on the GNSS signal received by the nest side to obtain injected enhanced operational data. Specifically, the GNSS signal received by the nest side window is amplified and divided by low noise, and then distributed to the near-field coupling radiation patch of the corresponding compartment. Under the condition that the mechanical precision positioning structure ensures the repeatability of the relative position, the near-field coupling radiation patch provides electromagnetic energy injection to the UAV's own GNSS antenna within a close range, so that the relay signal and the real satellite signal received by the UAV's own antenna are superimposed at the receiver front end, thereby obtaining injected enhanced operational data.

[0061] In one embodiment, step S103 includes:

[0062] The initial gain data is obtained by using the self-test data of the aforementioned path to acquire historical data or default values ​​of the UAV model.

[0063] The radio frequency switch of the UAV compartment is turned off according to the initial gain data, and the signal received by the UAV compartment side is transmitted to the coupling patch as a relay signal to obtain patch drive data.

[0064] The coupled patch is driven to radiate electromagnetic energy in the GNSS band using the patch driving data to obtain near-field energy data.

[0065] The electromagnetic energy of the GNSS band is transferred to the UAV antenna using the near-field energy data through a hybrid coupling method of capacitive or inductive coupling, thus obtaining coupled injection data;

[0066] Based on the coupled injection data, the UAV antenna is controlled to receive satellite signals and relay signals to obtain dual-source received data;

[0067] The dual-source received data is vector-superimposed at the antenna feed point to obtain the injected enhanced operating data.

[0068] In this embodiment, the path self-test data is used to obtain historical data or default values ​​for the UAV model to determine the initial gain setting method corresponding to the current model and cabin. The historical data may include gain setting records and signal quality records for the same model in the same or similar cabins. The default values ​​are used to provide an executable initial setting when historical data is unavailable. This yields initial gain data, which can be set to provide an initial boost of 10–15 dB for the relay gain, aligning with the target range for subsequent closed-loop adjustment. After obtaining the initial gain data, the RF switch of the UAV cabin is turned off based on this data, switching it to a state that allows the relay signal to enter the cabin coupling patch. Simultaneously, the signal received at the pod side is used as the relay signal, amplified and divided by the injection module, and transmitted to the coupling patch port to obtain patch drive data. The patch drive data may include the relay signal's frequency band identifier, power level, phase information, and a drive enable flag corresponding to the RF switch state, used to define the radiation operating parameters of the coupling patch in the GNSS band.

[0069] Furthermore, the coupled patch is driven by the patch driving data to radiate GNSS band electromagnetic energy, obtaining near-field energy data. The coupled patch operates at a preset installation position within the cabin, and its radiated GNSS band electromagnetic energy manifests as near-field energy injection conditions at close range. For example, when the relative distance between the patch and the UAV's own antenna is on the order of 5mm, the near-field energy data can be characterized as a field strength of approximately -40 to -30 dBm@5mm, for correlation calculation and recording with subsequent coupling injection data. After the near-field energy data is generated, the GNSS band electromagnetic energy is transferred to the UAV antenna using a hybrid coupling method of capacitive or inductive coupling, obtaining coupling injection data. Specifically, capacitive coupling is used to characterize the near-range electric field coupling component between the coupled patch and the UAV's own antenna radiator or the ground plane, while inductive coupling is used to characterize the near-range magnetic field coupling component. The hybrid coupling method allows both types of coupling components to act together in the same injection process, enabling the coupling injection data to simultaneously reflect the injected power level, injection phase characteristics, and coupling stability parameters, and to correspond with the initial gain data and RF switch status.

[0070] After obtaining the coupling injection data, the UAV antenna is controlled to receive satellite signals and relay signals based on the coupling injection data, resulting in dual-source reception data. The UAV antenna simultaneously receives a direct satellite signal from the top direction and a relay coupling signal from the bottom coupling patch at the same reception time; the direct satellite signal can be in the range of approximately -130 dBm, and the relay coupling signal can be in the range of approximately -85 dBm. These two signals are recorded as two components of the dual-source reception data and written into the data items of the injection enhancement operation process along with the current initial gain setting. Finally, the dual-source reception data is vector-superimposed at the antenna feed point to obtain the injection enhancement operation data. The vector superposition operation is used to characterize the combined reception result of the two signals at the feed point, enabling the injection enhancement operation data to output a quantitative representation related to signal quality; for example, after injection, C / N0 can enter the 40–45 dB-Hz range and serve as input data for the closed-loop adjustment of the relay gain in the subsequent step S104 to support dynamic convergence to the target range.

[0071] In step S104, the relay gain is dynamically adjusted to the target range based on the injection enhancement operation data using a preset closed-loop adjustment algorithm to obtain gain optimization data. The control unit continuously acquires signal quality characterization information related to the injection enhancement operation, such as C / N0, and performs closed-loop adjustment of the relay gain with the target range as the adjustment target. During the adjustment process, the signal strength adaptive control module is used to limit the gain boundary to reduce the risk of receiver saturation and ensure the enhancement effect, thereby outputting gain optimization data.

[0072] In one embodiment, step S104 includes:

[0073] Based on the injected enhanced operational data, the carrier-to-noise ratio data and positioning status data reported by the UAV every second are received and integrated to obtain real-time monitoring feedback data;

[0074] Incremental calculations are performed on the real-time monitoring feedback data to obtain monitoring evaluation data;

[0075] Based on the monitoring and evaluation data, a target range for the carrier-to-noise ratio is set, and the target range data is obtained;

[0076] Based on the target interval data, the proportional-integral-derivative control algorithm is invoked to dynamically adjust the relay gain, thereby obtaining gain adjustment data;

[0077] The gain adjustment data is subjected to security limitation processing to obtain secure gain data;

[0078] The relay gain is updated using the security gain data, and the acquisition of real-time monitoring feedback data and the updating of the security gain data are performed cyclically to obtain gain optimization data.

[0079] In this embodiment, based on the injected enhanced operational data, the nest control unit receives the carrier-to-noise ratio (C / N0) data and positioning status data reported by the UAV at second-level intervals. It then aligns and summarizes the C / N0, satellite-related status fields, and RTK status fields at the same time to obtain real-time monitoring feedback data. The positioning status data can be used to characterize the UAV's different stages, such as unsolved, floating-point, or fixed-solution states, facilitating the nest's synchronous evaluation of positioning convergence progress during gain adjustment. After obtaining the real-time monitoring feedback data, incremental calculations are performed to obtain monitoring evaluation data. The monitoring evaluation data may include the C / N0 improvement amount and corresponding evaluation indicators: for example, the current C / N0 is differentiated from the pre-injection baseline value or the previous cycle's C / N0 to obtain the C / N0 improvement amount; and the improvement efficiency is calculated in conjunction with the current relay gain level to characterize the responsiveness of gain changes to C / N0 improvement, ensuring that subsequent adjustment strategies remain stable and controllable. A target C / N0 range is set based on the monitoring evaluation data to obtain target range data. In this embodiment, the target C / N0 range can be set to 38–42 dB-Hz to balance the enhancement effect with the receiver's operating margin; the target interval data can include the target lower limit, the target upper limit, and the target center value used for control calculation, so that the closed-loop adjustment can converge around the target interval, rather than causing jitter due to single-point tracking.

[0080] After obtaining the target range data, the proportional-integral-derivative (PID) control algorithm is invoked to dynamically adjust the relay gain based on the target range data, resulting in gain adjustment data. The control unit uses the deviation between the target center value and the current C / N0 as the input error term, calculates the gain correction amount according to the proportional, integral, and derivative terms, and outputs the adjustment command in an discrete step size manner. In this embodiment, the gain adjustment step size can be set to 1–2 dB to ensure that the adjustment amplitude is moderate each time, reduce the risk of overshoot, and facilitate rapid attainment of the target range. After generating the gain adjustment data, the gain adjustment data is subjected to safety limiting processing to obtain safe gain data. The safety limiting processing is used to limit the range of relay gain values: firstly, a maximum gain upper limit is set to prevent the receiver front-end from saturating due to excessively strong signals; secondly, a minimum gain lower limit is set to ensure that the enhancement is at a perceptible level and avoid insufficient enhancement due to excessively low gain. The safe gain data can carry the target gain value after limiting and a limit reason marker, which is convenient for subsequent operation recording and fault diagnosis.

[0081] Finally, the relay gain is updated using the security gain data, and the acquisition of real-time monitoring feedback data and the updating of the security gain data are cyclically executed to obtain gain optimization data. This cycle runs continuously at a second-level interval: when C / N0 falls into the 38–42 dB-Hz range and the positioning status tends to stabilize, the gain adjustment amplitude automatically converges; when the positioning status shows that RTK has not yet converged, maintaining a high-quality C / N0 can accelerate the carrier phase correlation solution process and, under typical operating conditions, support RTK fixed convergence within 30 seconds; during this process, the nest can also provide differential data to the UAV as auxiliary information to improve positioning accuracy in high C / N0 environments. The gain optimization data output by the above cyclic process can include at least the C / N0 sequence, positioning status sequence, gain update sequence, and corresponding evaluation index sequence for each cycle, used to support subsequent steady-state determination and optimal gain recording.

[0082] In step S105, steady-state determination is performed on the gain optimization data, and the gain is locked and the optimal gain value is recorded when the preset stability duration and fluctuation threshold are met. Simultaneously, before takeoff, the relay gain is reduced to the minimum value using a linear transition method, and the RF switch is disconnected to obtain takeoff transition data. The steady-state determination is used to identify whether the signal quality after relay gain adjustment has entered a stable range. When it enters a stable range, the current gain is locked and the optimal gain value is recorded for subsequent rapid initialization with the same aircraft type or cabin class. Before takeoff, the relay gain is smoothly reduced to the minimum value using a linear transition method, and the RF switch is disconnected, so that the UAV gradually returns to a state where it primarily receives data directly from its own antenna during takeoff, thus obtaining takeoff transition data.

[0083] In one embodiment, step S105 includes:

[0084] The continuous monitoring sequence in the gain optimization data is analyzed, and the stability of the continuous monitoring sequence is detected to obtain the steady-state determination result;

[0085] When the steady-state determination result meets the preset conditions, the current relay gain is locked, and the optimal gain value is extracted to obtain the locked gain data;

[0086] The locked gain data is recorded to write the optimal gain value into the database, thus obtaining gain recording data;

[0087] Before the preset takeoff time, the relay gain is reduced to a minimum value based on the gain recording data in a linear transition manner to obtain the pre-takeoff landing gain data;

[0088] The takeoff gain data is used for direct signal verification, and the radio frequency switch is disconnected after the verification is successful to obtain takeoff transition data.

[0089] In this embodiment, the continuous monitoring sequence in the gain optimization data is first parsed. This continuous monitoring sequence may include at least a C / N0 sequence updated every second, a relay gain update sequence, and its corresponding positioning status identifier. Based on this, stability testing is performed on the continuous monitoring sequence to obtain a steady-state determination result. Stability testing can employ a time window determination method, for example, requiring C / N0 to be in a stable state for 10 consecutive seconds with a fluctuation amplitude of less than 1 dB. When the above stability duration and fluctuation threshold are met, a steady state is determined, and a steady-state determination result is output.

[0090] When the steady-state determination result meets the preset conditions, the current relay gain is locked, and the optimal gain value is extracted to obtain locked gain data. The locking operation freezes the adjustment state of the relay gain, ensuring that the injected enhancement maintains the steady-state gain level at the current cabin location. The optimal gain value is the relay gain setting value corresponding to the locking moment, which can be written into the locked gain data along with the cabin location identifier, UAV model identifier, and steady-state determination result for subsequent tracing of the source and applicable scope of the optimal gain value. The locked gain data is recorded to write the optimal gain value into the database, obtaining gain record data. The recording process can establish index fields for aircraft model and cabin location in the database and store the optimal gain value and its corresponding stability index together, forming reusable gain record data. This gain record data is used to quickly load the initial gain when the same aircraft model re-enters the nest or when the same cabin location is repeatedly run, thereby reducing the convergence time required for subsequent closed-loop adjustment.

[0091] After recording the optimal gain value, the relay gain is reduced to its minimum value using a linear transition based on the recorded gain data before the preset takeoff time, resulting in pre-takeoff gain reduction data. The pre-takeoff linear transition can be set to trigger 5 seconds before takeoff, linearly reducing the relay gain to its minimum value and completing the reduction process within 2 seconds, smoothly switching the relay enhancement from steady-state operation to minimum enhancement. The pre-takeoff gain reduction data is used to record the start and end times of the linear transition, the transition slope, the minimum value setting, and the C / N0 changes during the transition process, so as to be correlated with subsequent takeoff decisions.

[0092] Finally, the pre-takeoff gain reduction data is used for direct signal verification, and the RF switch is disconnected after successful verification to obtain takeoff transition data. Direct signal verification is used to confirm that the UAV can still maintain usable reception quality by relying solely on direct satellite signals after the relay gain is reduced to the minimum value. In this embodiment, the verification condition can be set to a C / N0 of pure direct signal greater than 35 dB-Hz. When this condition is met, the verification is deemed successful, and the RF switch is disconnected to remove the relay signal path from the working state. The resulting takeoff transition data may include at least a steady-state lockout flag, optimal gain value, linear transition parameters, direct signal verification results, and RF switch disconnection status, which are used to support the subsequent step S106 in determining takeoff release and coupling decoupling.

[0093] In step S106, takeoff transition data is used to determine takeoff release and coupling decoupling, and reset learning data is integrated and output. Takeoff release is used to characterize the key node of the UAV switching from the nest parking state to the takeoff state, and coupling decoupling is used to characterize the node where the coupling effect diminishes due to the increase in the relative distance between the UAV and the near-field coupling radiation patch. After the determination is completed, the control unit performs reset processing on the relevant states of the injection module and summarizes and records the key data of this enhancement operation process to obtain reset learning data to support subsequent gain parameter updates and operation and maintenance.

[0094] In one embodiment, step S106 includes:

[0095] The mechanical lock release mechanism is triggered based on the takeoff transition data, and the takeoff status of the UAV is obtained to obtain the takeoff release data;

[0096] Distance monitoring is performed on the takeoff and release data to determine the distance between the UAV and the coupling patch, thereby obtaining coupling release determination data;

[0097] Based on the coupling release determination data, the signal source is subjected to transition processing to obtain transition control data;

[0098] The radio frequency output of the UAV compartment is turned off based on the transition control data to obtain radio frequency shutdown data;

[0099] Perform a gain controller reset operation on the RF shutdown data and clear the status flag to obtain system reset data;

[0100] The system uses reset data to record performance data throughout the process, updates the optimal gain mapping table between the UAV model and the UAV cabin, and outputs reset learning data.

[0101] In this embodiment, step S106 is used to perform takeoff release, coupling release determination, signal source smooth switching, RF path shutdown, system reset, and experience data learning update after completing the takeoff transition processing in step S105. This maintains the continuity of reception quality during the UAV's takeoff from the nest and provides reusable gain parameters for subsequent re-entry of the same model. Specifically, the mechanical locking mechanism is triggered based on the takeoff transition data, and the UAV's takeoff status is acquired simultaneously to obtain takeoff release data. The mechanical locking mechanism can be used to limit the UAV's displacement or attitude deviation within the bay during parking. When takeoff release is triggered, the nest releases the mechanical restriction on the UAV, and the UAV enters the takeoff action phase. The takeoff release data can record information such as the release time, bay identifier, RF switch status, and UAV takeoff confirmation flag, which is used for time correlation with subsequent coupling release determination. After obtaining the takeoff release data, distance monitoring is performed on the takeoff release data to determine the distance between the UAV and the coupling patch, thus obtaining coupling release determination data. Distance monitoring can be calculated based on cabin distance sensors, takeoff altitude estimation, or altitude information reported by the UAV. When the distance between the UAV and the coupling patch is detected to be greater than 20 mm, it can be determined that the near-field coupling efficiency has dropped sharply. The coupling release determination data is recorded based on this, including the distance threshold trigger flag, the trigger time, and the corresponding distance value, thereby obtaining an executable coupling release determination result.

[0102] Based on the coupling release determination data, transition processing is performed on the signal source to obtain transition control data. This transition processing is used to gradually switch the UAV receiver from relay-coupled signal-assisted operation to a direct satellite signal-based mode during periods of decreased coupling efficiency, avoiding abnormal fluctuations in C / NO caused by signal abrupt changes. The transition control data may include the transition start point, transition duration, signal source switching flag, and control parameters associated with the RF path shutdown action to ensure continuous signal switching. Then, the RF output of the UAV compartment is shut down according to the transition control data to obtain RF shutdown data. RF shutdown data indicates that the relay output of the corresponding compartment has been shut down, including fields such as shutdown time, shutdown channel identifier, and shutdown result code. By executing RF output shutdown after the coupling release determination is established, relay coupling signals are no longer generated within the compartment, thus ending the current side signal injection operation. After the RF output is shut down, a gain controller reset operation is performed on the RF shutdown data, and the status flag is cleared to obtain system reset data. The gain controller reset is used to restore the relay gain control parameters to the initial state or standby state and clear the status flags of the current operation, including the steady-state lock flag, transition flag, channel occupancy flag, etc., so that the UAV will not be affected by the residual state of the previous operation when it re-enters the nest. The system reset data is used to record the reset completion flag, the initial gain value after reset, and the status flag clearing result.

[0103] Finally, the system reset data is used to record the entire process performance data, and the optimal gain mapping table between the UAV model and the UAV cabin is updated, outputting reset learning data. The entire process performance data may include at least the C / N0 sequence, gain adjustment sequence, steady-state determination and locking results, takeoff transition parameters, and coupling release trigger time from nest entry to takeoff, and is written to the database using the UAV model identifier and cabin identifier as indexes. Based on this, the model-cabin optimal gain mapping table is updated, so that the updated optimal gain value can be preferentially called when the same model runs in the same cabin. Furthermore, the channel health status can be recorded and monitored in conjunction with the periodic self-check maintenance process to support equipment health status management. The resulting reset learning data is the output of step S106, used to support parameter reuse and maintenance management in subsequent operations.

[0104] In summary, this application provides stable GNSS signal assistance to each UAV compartment in a multi-layered vertical stacking scenario by setting a transparent window on the side wall of the UAV nest and combining distributed relay reception with compartment near-field coupling injection. This effectively improves the attenuation of satellite signals in the first and second frequency bands caused by obstruction in the bottom compartment, resulting in a carrier-to-noise ratio improvement of over 15 dB. Furthermore, the non-contact near-field coupling method eliminates the need for external antennas or reserved RF interfaces on the UAV side, and does not require changes to the UAV's hardware structure or software configuration, making it compatible with models using integrated receiver and antenna sealed modules. Without replacing the UAV's original observation and measurement data acquisition, the application improves signal quality through relay assistance and, combined with closed-loop gain adjustment, supports real-time dynamic positioning, enabling faster centimeter-level initialization and status stabilization before takeoff. Moreover, the enhancement components are integrated inside the nest body, resulting in a compact structure that is easy to deploy and maintain, suitable for both indoor and outdoor applications. In addition, the combination of adaptive control for dynamic signal strength adjustment can reduce unnecessary energy consumption while meeting enhancement requirements, achieving better operational efficiency.

[0105] Combination Figure 2 As shown, Figure 2 This is a schematic block diagram of a GNSS-side signal injection device for an unmanned aerial vehicle (UAV) navigator provided in an embodiment of the present invention. The GNSS-side signal injection device 200 for the UAV navigator includes:

[0106] The data acquisition unit 201 is used to acquire the dynamic positioning data of the UAV and perform coordinate matching correction on the dynamic positioning data to obtain the nest entry pose data.

[0107] The data injection unit 202 is used to trigger the injection module to perform a power-on self-test based on the nesting pose data, so as to inject test signals and detect losses to obtain path self-test data.

[0108] Data enhancement unit 203 is used to set the initial gain using the path self-test data, and simultaneously perform near-field coupling injection on the GNSS side signal received by the nest side to obtain injection enhancement operation data;

[0109] Data gain unit 204 is used to dynamically adjust the relay gain to the target range based on the injected enhanced operating data according to a preset closed-loop adjustment algorithm, so as to obtain gain optimization data;

[0110] Data adjustment unit 205 is used to perform steady-state determination on the gain optimization data and lock the gain and record the optimal gain value when the preset stable duration and fluctuation threshold are met. At the same time, before the preset takeoff, the relay gain is reduced to the minimum value in a linear transition mode and the radio frequency switch is disconnected to obtain takeoff transition data.

[0111] The data output unit 206 is used to determine takeoff release and coupling release respectively using the takeoff transition data, and integrate and output reset learning data.

[0112] In this embodiment, the data acquisition unit 201 acquires the dynamic positioning data of the UAV and performs coordinate matching correction on the dynamic positioning data to obtain nest entry pose data; the data injection unit 202 triggers the injection module to perform power-on self-test according to the nest entry pose data to inject test signals and detect losses to obtain path self-test data; the data enhancement unit 203 uses the path self-test data to set the initial gain, and at the same time performs near-field coupling injection on the GNSS side signal received by the nest side to obtain injection enhancement operation data; the data gain unit 204 dynamically adjusts the relay gain to the target range according to the injection enhancement operation data and a preset closed-loop adjustment algorithm to obtain gain optimization data; the data adjustment unit 205 performs steady-state determination on the gain optimization data and locks the gain and records the optimal gain value when the preset stable duration and fluctuation threshold are met, and at the same time reduces the relay gain to the minimum value and disconnects the radio frequency switch in a linear transition mode before the preset takeoff to obtain takeoff transition data; the data output unit 206 uses the takeoff transition data to determine takeoff release and coupling release respectively, and integrates and outputs reset learning data.

[0113] In one embodiment, the data acquisition unit 201 is specifically used for:

[0114] The dynamic positioning data of the UAV is acquired, and the dynamic positioning data is matched and corrected with the preset coordinates of the UAV nest to obtain the matching and correction result;

[0115] Based on the matching and correction results, a drone landing guidance signal is generated, and landing matching data is obtained by integrating the results.

[0116] Speed ​​control is applied to the landing matching data to make the UAV land at a preset speed, and the contact status between the bottom guide structure of the UAV and the guide pin of the nest is detected to obtain guide contact data;

[0117] The guide contact data is subjected to horizontal deviation correction processing to obtain horizontal correction data;

[0118] The final pose is determined based on the horizontal correction data to obtain the nest entry pose data.

[0119] In one embodiment, the data injection unit 202 is specifically used for:

[0120] The arrival status of the drone is detected based on the nesting pose data, and a communication connection is established to obtain connection establishment data;

[0121] The relay system is powered on using the connection establishment data, and the parameters of the low-noise amplifier and power divider in the injection module are self-tested to obtain hardware self-test data.

[0122] Based on the hardware self-test data, a test signal is injected into the injection module, and the test signal is transmitted to the coupling patch to obtain test injection data.

[0123] Near-field probe detection is performed on the injected test data to obtain the test signal strength and thus the path detection result.

[0124] When the path detection result is abnormal, the corresponding channel identifier is recorded and a backup channel is enabled or the current channel is skipped. When the path detection result is normal, the channel identifier is retained and the channel processing data is integrated.

[0125] Based on the channel processing data, navigation status data reported by the UAV is received, and the channel self-test data is calculated.

[0126] In one embodiment, the data enhancement unit 203 is specifically used for:

[0127] The initial gain data is obtained by using the self-test data of the aforementioned path to acquire historical data or default values ​​of the UAV model.

[0128] The radio frequency switch of the UAV compartment is turned off according to the initial gain data, and the signal received by the UAV compartment side is transmitted to the coupling patch as a relay signal to obtain patch drive data.

[0129] The coupled patch is driven to radiate electromagnetic energy in the GNSS band using the patch driving data to obtain near-field energy data.

[0130] The electromagnetic energy of the GNSS band is transferred to the UAV antenna using the near-field energy data through a hybrid coupling method of capacitive or inductive coupling, thus obtaining coupled injection data;

[0131] Based on the coupled injection data, the UAV antenna is controlled to receive satellite signals and relay signals to obtain dual-source received data;

[0132] The dual-source received data is vector-superimposed at the antenna feed point to obtain the injected enhanced operating data.

[0133] In one embodiment, the data gain unit 204 is specifically used for:

[0134] Based on the injected enhanced operational data, the carrier-to-noise ratio data and positioning status data reported by the UAV every second are received and integrated to obtain real-time monitoring feedback data;

[0135] Incremental calculations are performed on the real-time monitoring feedback data to obtain monitoring evaluation data;

[0136] Based on the monitoring and evaluation data, a target range for the carrier-to-noise ratio is set, and the target range data is obtained;

[0137] Based on the target interval data, the proportional-integral-derivative control algorithm is invoked to dynamically adjust the relay gain, thereby obtaining gain adjustment data;

[0138] The gain adjustment data is subjected to security limitation processing to obtain secure gain data;

[0139] The relay gain is updated using the security gain data, and the acquisition of real-time monitoring feedback data and the updating of the security gain data are performed cyclically to obtain gain optimization data.

[0140] In one embodiment, the data adjustment unit 205 is specifically used for:

[0141] The continuous monitoring sequence in the gain optimization data is analyzed, and the stability of the continuous monitoring sequence is detected to obtain the steady-state determination result;

[0142] When the steady-state determination result meets the preset conditions, the current relay gain is locked, and the optimal gain value is extracted to obtain the locked gain data;

[0143] The locked gain data is recorded to write the optimal gain value into the database, thus obtaining gain recording data;

[0144] Before the preset takeoff time, the relay gain is reduced to a minimum value based on the gain recording data in a linear transition manner to obtain the pre-takeoff landing gain data;

[0145] The takeoff gain data is used for direct signal verification, and the radio frequency switch is disconnected after the verification is successful to obtain takeoff transition data.

[0146] In one embodiment, the data output unit 206 is specifically used for:

[0147] The mechanical lock release mechanism is triggered based on the takeoff transition data, and the takeoff status of the UAV is obtained to obtain the takeoff release data;

[0148] Distance monitoring is performed on the takeoff and release data to determine the distance between the UAV and the coupling patch, thereby obtaining coupling release determination data;

[0149] Based on the coupling release determination data, the signal source is subjected to transition processing to obtain transition control data;

[0150] The radio frequency output of the UAV compartment is turned off based on the transition control data to obtain radio frequency shutdown data;

[0151] Perform a gain controller reset operation on the RF shutdown data and clear the status flag to obtain system reset data;

[0152] The system uses reset data to record performance data throughout the process, updates the optimal gain mapping table between the UAV model and the UAV cabin, and outputs reset learning data.

[0153] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0154] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0155] This invention also provides a computer device, which may include a memory and a processor. The memory stores a computer program, and when the processor calls the computer program in the memory, it can implement the steps provided in the above embodiments. Of course, the computer device may also include various network interfaces, a power supply, a graphics card, etc., to utilize the graphics card's performance to operate the model, such as for inference and training.

[0156] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0157] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for injecting GNSS-side signals into a UAV nest, characterized in that, include: The dynamic positioning data of the UAV is acquired, and the coordinate matching correction is performed on the dynamic positioning data to obtain the nest entry pose data. The injection module is triggered to perform a power-on self-test based on the nesting pose data to inject test signals and detect losses, thereby obtaining path self-test data. The initial gain is set using the self-test data of the path, and near-field coupling injection is performed on the GNSS signal received by the nest side to obtain injection enhancement operation data; Based on the injected enhanced operating data, the relay gain is dynamically adjusted to the target range according to a preset closed-loop adjustment algorithm to obtain gain optimization data. The gain optimization data is steady-state determined, and the gain is locked and the optimal gain value is recorded when the preset stable duration and fluctuation threshold are met. At the same time, the relay gain is reduced to the minimum value and the radio frequency switch is disconnected in a linear transition mode before the preset takeoff, so as to obtain takeoff transition data. The takeoff transition data is used to determine takeoff release and coupling release respectively, and the reset learning data is integrated and output.

2. The GNSS-side signal injection method for UAV nests according to claim 1, characterized in that, The process of acquiring the UAV's dynamic positioning data and performing coordinate matching correction on the dynamic positioning data to obtain the nest entry pose data includes: The dynamic positioning data of the UAV is acquired, and the dynamic positioning data is matched and corrected with the preset coordinates of the UAV nest to obtain the matching and correction result; Based on the matching and correction results, a drone landing guidance signal is generated, and landing matching data is obtained by integrating the results. Speed ​​control is applied to the landing matching data to make the UAV land at a preset speed, and the contact status between the bottom guide structure of the UAV and the guide pin of the nest is detected to obtain guide contact data; The guide contact data is subjected to horizontal deviation correction processing to obtain horizontal correction data; The final pose is determined based on the horizontal correction data to obtain the nest entry pose data.

3. The GNSS-side signal injection method for UAV nests according to claim 1, characterized in that, The step of triggering the injection module to perform a power-on self-test based on the nesting pose data, injecting a test signal and detecting loss, and obtaining path self-test data includes: The arrival status of the drone is detected based on the nesting pose data, and a communication connection is established to obtain connection establishment data; The relay system is powered on using the connection establishment data, and the parameters of the low-noise amplifier and power divider in the injection module are self-tested to obtain hardware self-test data. Based on the hardware self-test data, a test signal is injected into the injection module, and the test signal is transmitted to the coupling patch to obtain test injection data. Near-field probe detection is performed on the injected test data to obtain the test signal strength and thus the path detection result. When the path detection result is abnormal, the corresponding channel identifier is recorded and a backup channel is enabled or the current channel is skipped. When the path detection result is normal, the channel identifier is retained and the channel processing data is integrated. Based on the channel processing data, navigation status data reported by the UAV is received, and the channel self-test data is calculated.

4. The GNSS-side signal injection method for UAV nests according to claim 1, characterized in that, The process involves setting the initial gain using the path self-test data and simultaneously performing near-field coupling injection on the GNSS signal received at the nest side to obtain injection enhancement operation data, including: The initial gain data is obtained by using the self-test data of the aforementioned path to acquire historical data or default values ​​of the UAV model. The radio frequency switch of the UAV compartment is turned off according to the initial gain data, and the signal received by the UAV compartment side is transmitted to the coupling patch as a relay signal to obtain patch drive data. The coupled patch is driven to radiate electromagnetic energy in the GNSS band using the patch driving data to obtain near-field energy data. The electromagnetic energy of the GNSS band is transferred to the UAV antenna using the near-field energy data through a hybrid coupling method of capacitive or inductive coupling, thus obtaining coupled injection data; Based on the coupled injection data, the UAV antenna is controlled to receive satellite signals and relay signals to obtain dual-source received data; The dual-source received data is vector-superimposed at the antenna feed point to obtain the injected enhanced operating data.

5. The GNSS-side signal injection method for UAV nests according to claim 1, characterized in that, The process of dynamically adjusting the relay gain to the target range based on the injected enhanced operating data using a preset closed-loop adjustment algorithm to obtain gain optimization data includes: Based on the injected enhanced operational data, the carrier-to-noise ratio data and positioning status data reported by the UAV every second are received and integrated to obtain real-time monitoring feedback data; Incremental calculations are performed on the real-time monitoring feedback data to obtain monitoring evaluation data; Based on the monitoring and evaluation data, a target range for the carrier-to-noise ratio is set, and the target range data is obtained; Based on the target interval data, the proportional-integral-derivative control algorithm is invoked to dynamically adjust the relay gain, thereby obtaining gain adjustment data; The gain adjustment data is subjected to security limitation processing to obtain secure gain data; The relay gain is updated using the security gain data, and the acquisition of real-time monitoring feedback data and the updating of the security gain data are performed cyclically to obtain gain optimization data.

6. The GNSS-side signal injection method for UAV nests according to claim 1, characterized in that, The process involves performing a steady-state determination on the gain optimization data, locking the gain and recording the optimal gain value when a preset stable duration and fluctuation threshold are met, and simultaneously reducing the relay gain to the minimum value and disconnecting the RF switch in a linear transition manner before a preset takeoff, to obtain takeoff transition data, including: The continuous monitoring sequence in the gain optimization data is analyzed, and the stability of the continuous monitoring sequence is detected to obtain the steady-state determination result; When the steady-state determination result meets the preset conditions, the current relay gain is locked, and the optimal gain value is extracted to obtain the locked gain data; The locked gain data is recorded to write the optimal gain value into the database, thus obtaining gain recording data; Before the preset takeoff time, the relay gain is reduced to a minimum value based on the gain recording data in a linear transition manner to obtain the pre-takeoff landing gain data; The takeoff gain data is used for direct signal verification, and the radio frequency switch is disconnected after the verification is successful to obtain takeoff transition data.

7. The GNSS-side signal injection method for UAV nests according to claim 1, characterized in that, The process of using the takeoff transition data to determine takeoff release and coupling release, and integrating and outputting reset learning data, includes: The mechanical lock release mechanism is triggered based on the takeoff transition data, and the takeoff status of the UAV is obtained to obtain the takeoff release data; Distance monitoring is performed on the takeoff and release data to determine the distance between the UAV and the coupling patch, thereby obtaining coupling release determination data; Based on the coupling release determination data, the signal source is subjected to transition processing to obtain transition control data; The radio frequency output of the UAV compartment is turned off based on the transition control data to obtain radio frequency shutdown data; Perform a gain controller reset operation on the RF shutdown data and clear the status flag to obtain system reset data; The system uses reset data to record performance data throughout the process, updates the optimal gain mapping table between the UAV model and the UAV cabin, and outputs reset learning data.

8. A GNSS-side signal injection device for an unmanned aerial vehicle (UAV) nest, characterized in that, include: The data acquisition unit is used to acquire the dynamic positioning data of the UAV and perform coordinate matching correction on the dynamic positioning data to obtain the nest entry pose data. The data injection unit is used to trigger the injection module to perform a power-on self-test based on the nesting pose data, so as to inject test signals and detect losses to obtain path self-test data. The data enhancement unit is used to set the initial gain using the path self-test data, and simultaneously perform near-field coupling injection on the GNSS side signal received by the nest side to obtain injection enhancement operation data. The data gain unit is used to dynamically adjust the relay gain to the target range based on the injected enhanced operating data according to a preset closed-loop adjustment algorithm, so as to obtain gain-optimized data. The data adjustment unit is used to perform steady-state determination on the gain optimization data and lock the gain and record the optimal gain value when the preset stable duration and fluctuation threshold are met. At the same time, before the preset takeoff, the relay gain is reduced to the minimum value in a linear transition mode and the radio frequency switch is disconnected to obtain takeoff transition data. The data output unit is used to determine takeoff release and coupling release respectively using the takeoff transition data, and integrate and output reset learning data.

9. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the GNSS-side signal injection method for a UAV nest as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the GNSS-side signal injection method for a UAV nest as described in any one of claims 1 to 7.

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