Aircraft navigation method and device, controller, aircraft and medium

Abstract

The invention relates to an aircraft navigation method and device, a controller, an aircraft and a medium, the aircraft comprises a flight control calculation unit group and a navigation unit group, the flight control calculation unit group comprises a main flight control calculation unit and a standby flight control calculation unit, and a first navigation data set corresponding to the main flight control calculation unit is obtained; according to a first navigation data set corresponding to the main flight control calculation unit and a second navigation data set corresponding to the standby flight control calculation unit, a preset redundancy voting algorithm is used for processing the first navigation data set to obtain a main flight control navigation result, and a preset fault diagnosis voting algorithm is used for processing the second navigation data set to obtain a standby flight control navigation result; and determining a final navigation result according to the main flight control navigation result and the standby flight control navigation result, and performing navigation control on the aircraft according to the final navigation result, thereby avoiding navigation errors caused by faults of a single calculation unit, ensuring that the navigation precision is always maintained at a relatively high level, and greatly improving the navigation reliability and safety of the aircraft.

Description

Technical Field

[0001] This invention relates to the field of aircraft technology, and in particular to an aircraft navigation method, device, controller, aircraft, and medium. Background Technology

[0002] With the rapid development of urban air traffic, the demand for remote control of electric vertical takeoff and landing (eVTOL) aircraft is increasing daily. During mission execution, aircraft navigation is crucial for achieving autonomous flight, completing tasks, and ensuring safe operation. It requires the continuous provision of accurate navigation information to provide strong support for flight control, mission planning, and obstacle avoidance functions.

[0003] However, in existing technologies, due to the lack of adaptive navigation algorithms, aircraft may output incorrect navigation information when faced with complex and ever-changing external interference factors (such as strong electromagnetic interference and extreme weather conditions). This can lead to navigation deviations or even failures, posing a significant threat to flight safety and making it difficult to guarantee consistently high navigation accuracy. Therefore, ensuring consistently high navigation accuracy is a pressing technical problem that needs to be solved. Summary of the Invention

[0004] Based on this, it is necessary to address the above-mentioned technical problems by providing an aircraft navigation method, device, controller, aircraft, and medium in this embodiment of the invention, thereby ensuring that navigation accuracy is always maintained at a high level.

[0005] A first aspect of this application provides an aircraft navigation method, the aircraft including a flight control computing unit group and a navigation unit group, the flight control computing unit group including a main flight control computing unit and a backup flight control computing unit, the method including: The system acquires a first navigation data set corresponding to the main flight control computing unit and a second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol, and the second navigation data set is transmitted by the navigation unit group through a single communication protocol. The first navigation data set is processed using a preset redundancy voting algorithm to obtain the primary flight control navigation result, and the second navigation data set is processed using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. Based on the primary flight control navigation results and the backup flight control navigation results, the final navigation result is determined, and the aircraft is controlled for navigation according to the final navigation result.

[0006] A second aspect of this application provides an aircraft navigation device, the aircraft including a flight control computing unit group and a navigation unit group, the flight control computing unit group including a main flight control computing unit and a backup flight control computing unit, the device comprising: The acquisition module is used to acquire the first navigation data set corresponding to the main flight control computing unit and the second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through dual communication protocols, and the second navigation data set is transmitted by the navigation unit group through a single communication protocol. The processing module is used to process the first navigation data set using a preset redundancy voting algorithm to obtain the main flight control navigation result, and to process the second navigation data set using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. The navigation module is used to determine the final navigation result based on the primary flight control navigation result and the backup flight control navigation result, and to perform navigation control on the aircraft according to the final navigation result.

[0007] Thirdly, a controller is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aircraft navigation method as described in the first aspect.

[0008] Fourthly, an aircraft is provided, including a navigation system, a power system, and a controller. The navigation system includes a flight control computing unit group and a navigation unit group. The controller is connected to the navigation system and the power system respectively, and the controller is used to execute the aircraft navigation method as described in the first aspect.

[0009] Fifthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements the aircraft navigation method as described in the first aspect.

[0010] In summary, this invention provides an aircraft navigation method, device, controller, aircraft, and medium. The aircraft includes a flight control computing unit group and a navigation unit group. The flight control computing unit group includes a main flight control computing unit and a backup flight control computing unit. By acquiring a first navigation data set corresponding to the main flight control computing unit and a second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol and the second navigation data set is transmitted by the navigation unit group through a single communication protocol, the first navigation data set is processed using a preset redundancy voting algorithm to obtain the main flight control navigation result, and the second navigation data set is processed using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. Based on the main flight control navigation result and the backup flight control navigation result, the final navigation result is determined, and the aircraft is navigated and controlled according to the final navigation result. As can be seen, this application determines the final navigation result based on the main flight control navigation result corresponding to the main flight control computing unit and the backup flight control navigation result corresponding to the backup flight control computing unit, thereby avoiding navigation errors caused by the failure of a single computing unit, ensuring that the navigation accuracy is always maintained at a high level, and greatly improving the reliability and safety of aircraft navigation. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart illustrating an aircraft navigation method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of an aircraft navigation device according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a controller provided in an embodiment of the present invention. Detailed Implementation

[0013] 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0014] It should be understood that, when used in this specification and the appended claims, terms include indicating the presence of a described feature, integral, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0015] It should also be understood that the terms used in this specification and the appended claims refer to any combination of one or more of the associated listed items and all possible combinations, and include such combinations.

[0016] As used in this specification and the appended claims, terms if can be interpreted in context as when... or once or in response to determination. Similarly, the phrase if determined or if matched to [described condition or event] can be interpreted in context as once determined or in response to determination or once matched to [described condition or event] or in response to matching to [described condition or event].

[0017] Furthermore, in the description of this invention and the appended claims, the terms first, second, third, etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0018] References to one or more embodiments described in this specification mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the invention. Therefore, phrases appearing in different parts of this specification as referring to one embodiment, some embodiments, some other embodiments, and others do not necessarily refer to the same embodiment, but rather mean one or more, but not all, embodiments, unless otherwise specifically emphasized. The terms include, comprise, have, and variations thereof mean including but not limited to, unless otherwise specifically emphasized.

[0019] It should be understood that the sequence number of each step in the following embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0020] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0021] See Figure 1 This is a flowchart illustrating an aircraft navigation method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the aircraft includes a flight control computing unit group and a navigation unit group. The flight control computing unit group includes a main flight control computing unit and a backup flight control computing unit. The aircraft navigation method can be implemented through the following steps.

[0022] S101: Obtain the first navigation data set corresponding to the main flight control computing unit and the second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol, and the second navigation data set is transmitted by the navigation unit group through a single communication protocol.

[0023] In one implementation, the aircraft is internally configured with a flight control computing unit group and a navigation unit group. The flight control computing unit group consists of a primary flight control computing unit and a backup flight control computing unit. The primary flight control computing unit is responsible for the calculation and control of the main flight missions, while the backup flight control computing unit exists as a backup unit and is activated when the primary unit fails. The navigation unit group contains various sensors, such as a Global Positioning System (GPS) receiver and an Inertial Measurement Unit (IMU), used to acquire initial navigation data such as the aircraft's position, velocity, and attitude in real time. After generating initial navigation data, the navigation unit group sends this data to the primary flight control computing unit and the backup flight control computing unit respectively. The data received by the primary flight control computing unit is identified as the first navigation data set, and the data received by the backup flight control computing unit is identified as the second navigation data set. These data sets can contain various navigation parameters such as position, velocity, attitude, and timestamps.

[0024] In this embodiment, when the navigation unit group transmits the first navigation data set to the main flight control computing unit, a dual communication protocol is used. For example, data can be transmitted simultaneously via a CAN bus and an RS485 bus. This approach aims to provide redundant configuration for data transmission, preventing data loss or errors due to single-point bus failures. The heterogeneous protocols—CAN and RS485 have different electrical characteristics and protocols—can resist interference specific to certain bus types, improving the robustness of the communication link. When the navigation unit group transmits the second navigation data set to the backup flight control computing unit, a single communication protocol is used. For example, data can be transmitted via a single CAN bus, reducing the complexity of the backup link. Therefore, by acquiring the first navigation data set corresponding to the main flight control computing unit and the second navigation data set corresponding to the backup flight control computing unit, comprehensive and reliable data support can be provided for the aircraft's flight control. During actual flight, the main flight control computing unit performs major flight attitude adjustments, path planning, and other operations based on the first navigation data set. The high reliability and strong robustness brought by the dual communication protocol transmission ensure that the aircraft can fly stably even in complex environments. The backup flight control computing unit is based on the second navigation data set. When the main flight control computing unit fails or malfunctions, it quickly takes over the flight control task. The use of a single communication protocol reduces the complexity of the backup link, enabling the backup flight control computing unit to respond quickly and ensure the safety of the aircraft. Through the cooperation between the main and backup units, the safety and stability of the aircraft's flight are greatly improved.

[0025] S102: The first navigation data set is processed using a preset redundancy voting algorithm to obtain the main flight control navigation result, and the second navigation data set is processed using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result.

[0026] In one implementation, after receiving the first navigation data set, the primary flight control computing unit processes it using a preset redundancy voting algorithm. This algorithm comprehensively analyzes and compares multiple redundant data points in the first navigation data set, eliminating potentially erroneous or abnormal data according to specific rules, ultimately generating an accurate and reliable primary flight control navigation result. This result serves as a crucial basis for the primary flight control computing unit to perform operations such as flight attitude adjustment and path planning, ensuring the aircraft flies stably along the predetermined route. After receiving the second navigation data set, the backup flight control computing unit processes it using a preset fault diagnosis voting algorithm. This algorithm meticulously examines each data point in the second navigation data set to determine the presence of fault characteristics or abnormal conditions. Once a data problem that may affect flight safety is detected, the algorithm, according to a predetermined strategy, filters out relatively reliable data from multiple data points, thereby generating a backup flight control navigation result. This result serves as a key reference for the backup flight control computing unit to take over flight control tasks and perform related operations when the primary flight control computing unit malfunctions, ensuring the aircraft can still fly safely under complex conditions.

[0027] In this embodiment, a preset redundancy voting algorithm is used to process the first navigation data set to obtain the primary flight control navigation result, and a preset fault diagnosis voting algorithm is used to process the second navigation data set to obtain the backup flight control navigation result. This effectively improves the reliability and safety of the aircraft navigation system. On one hand, the redundancy voting algorithm, through comprehensive analysis and comparison of multiple redundant data, minimizes the impact of erroneous or abnormal data on the primary flight control navigation result, enabling the primary flight control computing unit to adjust flight attitude and plan paths based on accurate and reliable data, providing a solid guarantee for the stable flight of the aircraft. On the other hand, the fault diagnosis voting algorithm's meticulous detection of the second navigation data set can promptly identify data problems that may affect flight safety and select relatively reliable data to generate the backup flight control navigation result. This ensures that when the primary flight control computing unit malfunctions, the backup flight control computing unit can quickly take over the flight control task, guaranteeing the safe flight of the aircraft under complex conditions.

[0028] S103: Based on the primary flight control navigation result and the backup flight control navigation result, determine the final navigation result, and perform navigation control on the aircraft according to the final navigation result.

[0029] In one implementation, the final navigation result is determined by selecting or combining the primary and backup flight control navigation results. For example, the primary flight control navigation result can be used first, and the backup result is only switched on when the primary result is unavailable. Alternatively, a weighted average of the two results can be taken to obtain the final navigation result. Once the final navigation result is determined, the flight control system generates corresponding control commands based on the result, such as adjusting parameters like the aircraft's heading, altitude, and speed, to guide the aircraft to fly along a preset path or according to the commands.

[0030] In this embodiment, by determining the final navigation result based on the primary flight control navigation result and the backup flight control navigation result, and then controlling the aircraft according to the final navigation result, the accuracy and reliability of the aircraft's navigation can be effectively improved. This dual flight control navigation result determination mechanism fully considers the different states of the primary flight control computing unit and the backup flight control computing unit. By flexibly selecting or combining the results of both, it maximizes the use of effective data and avoids navigation errors that may be caused by the failure of a single flight control computing unit. At the same time, the control commands generated based on the final navigation result can accurately adjust various flight parameters of the aircraft, ensuring that the aircraft can fly stably and safely in various flight environments. For example, when the primary flight control computing unit is affected by external interference or experiences a hardware failure, causing its output navigation result to deviate, the backup flight control computing unit can promptly play its role by generating a reliable backup flight control navigation result based on a fault diagnosis voting algorithm, preventing the aircraft from falling into danger due to the failure of a single navigation source. Moreover, the selection and combination method for determining the final navigation result can be flexibly adjusted according to different flight scenarios and requirements. In simple flight missions, prioritizing the use of primary flight control navigation results can ensure the efficient operation of the system; however, in complex and harsh flight environments, weighted averaging of primary and backup flight control navigation results can combine the advantages of both to provide more accurate navigation guidance for the aircraft, ensuring that the aircraft is always in a safe and controllable flight state.

[0031] In summary, this invention provides an aircraft navigation method, device, controller, aircraft, and medium. The aircraft includes a flight control computing unit group and a navigation unit group. The flight control computing unit group includes a main flight control computing unit and a backup flight control computing unit. By acquiring a first navigation data set corresponding to the main flight control computing unit and a second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol and the second navigation data set is transmitted by the navigation unit group through a single communication protocol, the first navigation data set is processed using a preset redundancy voting algorithm to obtain the main flight control navigation result, and the second navigation data set is processed using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. Based on the main flight control navigation result and the backup flight control navigation result, the final navigation result is determined, and the aircraft is navigated and controlled according to the final navigation result. As can be seen, this application determines the final navigation result based on the main flight control navigation result corresponding to the main flight control computing unit and the backup flight control navigation result corresponding to the backup flight control computing unit, thereby avoiding navigation errors caused by the failure of a single computing unit, ensuring that the navigation accuracy is always maintained at a high level, and greatly improving the reliability and safety of aircraft navigation.

[0032] In one embodiment, prior to step S102, that is, before processing the first navigation data set using a preset redundancy voting algorithm to obtain the main flight control navigation result, the following steps are included: Perform a validity check on the first navigation data set; If the first navigation data set passes the validity check, then determine whether the communication transmission time of the first navigation data set exceeds a preset communication time threshold. If the communication transmission time of the first navigation data set does not exceed the preset communication time threshold, then the first navigation data set is time-aligned and data-synchronized to obtain the processed first navigation data set.

[0033] Specifically, the validity of the first navigation data set is verified. This verification can be implemented in various ways. For example, a Cyclic Redundancy Check (CRC) or Checksum calculation can be performed on the received data packets, and the result can be compared with the checksum carried in the data packets to verify the integrity and accuracy of the data. If the verification fails, the data is considered invalid. Alternatively, a physical rationality check can be performed on key parameters in the navigation data (such as position coordinates, velocity, attitude angles, etc.). For example, it can be checked whether the position is within a preset flight area, whether the velocity exceeds the aircraft's maximum design speed, and whether the attitude angle is within a reasonable range. Data outside the reasonable range will be marked as invalid. After the first navigation data set passes the validity verification, it is necessary to determine whether the communication transmission time of the first navigation data set exceeds a preset communication time threshold. The purpose of this step is to avoid using outdated or excessively delayed data, as such data may lead to inaccurate navigation results. For example, a timestamp of data generation can be included in the navigation data packets. After receiving the data, the receiving end records the current system time and calculates the time difference between the current system time and the data generation timestamp. If this time difference is greater than the preset communication time threshold, the data is considered to be outdated or the transmission delay is too large. Alternatively, the system can maintain an expected data reception period. When a data packet arrives, it checks the time interval between the packet and the previous valid data packet. If the interval significantly exceeds the expected period, or if the internal timestamp of the data packet deviates significantly from the current system time, it is determined that the communication transmission time has exceeded the limit.

[0034] Furthermore, if the communication transmission time of the first navigation data set does not exceed a preset communication time threshold, time alignment and data synchronization processing of the first navigation data set are required. This can be achieved using timestamp interpolation. For navigation data from different sources or with slightly different arrival times, a common reference time point is selected. Then, using linear interpolation, spline interpolation, or other methods, the navigation data value at that reference time point is estimated based on the timestamp and value of the data points, thus achieving time alignment. Alternatively, a data buffering and matching method can be used. Received multiple navigation data streams are stored in their respective buffers according to their timestamps. Before the redundancy voting algorithm, the set of data with the closest timestamps is selected from each buffer for matching. Alternatively, the timestamp of one data stream can be used as a benchmark to find corresponding data from other data streams within a similar time window, ensuring high temporal consistency among the data participating in the voting. These technical solutions significantly improve the quality and reliability of the input data, laying a solid foundation for the accurate operation of the subsequent redundancy voting algorithm. This effectively improves the accuracy of aircraft navigation and the robustness of the system, reducing the risk of navigation failure under complex external interference.

[0035] In one embodiment, specifically in step S102, the first navigation data set includes multiple navigation data paths. Specifically, the first navigation data set is processed using a preset redundancy voting algorithm to obtain the main flight control navigation result, including the following steps: Using a preset redundancy voting algorithm, determine whether the multi-path navigation data in the first navigation data set are consistent; If the multiple navigation data in the first navigation data set are consistent, the multiple navigation data in the first navigation data set are fused to obtain a first navigation result, and the first navigation result is used as the main flight control navigation result; If the multiple navigation data in the first navigation data set are inconsistent, the multiple navigation data are processed according to the inconsistency of the multiple navigation data in the first navigation data set to obtain a second navigation result, and the second navigation result is used as the main flight control navigation result.

[0036] Specifically, the first navigation data set includes multi-path navigation data, meaning that the navigation data acquired from the navigation unit group and used by the main flight control computing unit is not from a single source, but rather a data stream provided by multiple independent or redundant channels, sensors, or processing links. For example, this multi-path navigation data may originate from multiple physically independent navigation sensors. Determining the consistency of the multi-path navigation data in the first navigation data set using a preset redundancy voting algorithm involves the system comparing and analyzing the received multi-path navigation data to determine if there are significant differences between them. This consistency determination is a key step in the redundancy voting algorithm, used to identify potential data deviations or sensor malfunctions. For example, a preset deviation threshold can be set to calculate the difference between any two or more navigation data streams. If the difference exceeds the threshold, the data is considered inconsistent. Alternatively, the statistical dispersion (such as variance or standard deviation) of all multi-channel navigation data can be calculated. If the dispersion exceeds a preset threshold, it is judged as inconsistent. If the multi-channel navigation data in the first navigation data set is consistent, the multi-channel navigation data in the first navigation data set is fused to obtain the first navigation result, which is then used as the main flight control navigation result. This means that when the system confirms that all or most of the multi-channel navigation data are consistent within a preset tolerance range, these data are comprehensively processed to generate a more accurate and reliable navigation result. For example, a simple arithmetic mean method can be used to average all consistent data points; or a weighted average method can be used, assigning different weights to each data source based on its accuracy, reliability, or historical performance; or, state estimation algorithms such as Kalman filtering can be used to fuse multi-channel data under the premise of data consistency through optimal estimation theory to further improve navigation accuracy and stability.

[0037] Furthermore, if the multiple navigation data in the first navigation data set are inconsistent, the multiple navigation data in the first navigation data set are processed according to the inconsistency to obtain a second navigation result, which is then used as the main flight control navigation result. This means that when the system detects significant differences between multiple navigation data, it no longer simply merges them, but instead initiates a specialized anomaly handling mechanism to generate a usable navigation result. For example, a fault isolation and elimination strategy can be adopted, using diagnostic algorithms to identify abnormal or faulty data sources and remove them from the data set, then merging the remaining healthy data; alternatively, based on preset priority rules, a data source considered the most reliable can be selected as the output when data is inconsistent; or, robust statistical methods, such as the RANSAC (Random Sample Consensus) algorithm, can be used to identify a subset of data that conforms to the majority pattern from the inconsistent data, and a navigation result can be generated based on this subset to ensure that continuous and relatively reliable navigation information can still be provided when data conflicts occur. The above technical solutions significantly enhance the robustness and fault tolerance of aircraft navigation systems in complex and ever-changing environments, effectively preventing data deviations caused by external interference from affecting flight safety, thereby ensuring that navigation accuracy is always maintained at a high level.

[0038] In one embodiment, specifically in step S102, the navigation unit group includes multiple first navigation units with identical configuration information and second navigation units with different configuration information from the first navigation units. That is, if the multi-path navigation data in the first navigation data set is inconsistent, the multi-path navigation data is processed according to the inconsistency in the first navigation data set to obtain the second navigation result, including the following steps: If the data in the multi-path navigation data are completely inconsistent, a comprehensive diagnosis is performed on the multi-path navigation data to obtain a comprehensive diagnosis result; Based on the comprehensive diagnostic results, the navigation data with the highest reliability is selected as the second navigation result; If the navigation data corresponding to multiple first navigation units is consistent, and there is a navigation data among the multiple first navigation units that is inconsistent with the navigation data corresponding to the second navigation unit, then the data rationality verification is performed on the navigation data corresponding to the second navigation unit to obtain the verification result; If the verification result is passed, then the navigation data corresponding to the second navigation unit is used as the second navigation result; If the verification result is unsuccessful, the navigation data corresponding to multiple first navigation units will be merged, and the merged navigation data will be used as the second navigation result. If the navigation data corresponding to multiple first navigation units is inconsistent, and there is data in the navigation data corresponding to multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit, then the navigation data in the multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit is merged with the navigation data corresponding to the second navigation unit, and the merged navigation data is used as the second navigation result.

[0039] Specifically, the navigation unit group includes multiple first navigation units with identical configuration information and second navigation units with different configuration information. For example, if the navigation unit group includes three navigation units, navigation unit A and navigation unit B operate with the same software structure, while navigation unit C operates with a different software structure. Navigation units A and B, as first navigation units, have the same configuration information and can perform data processing and navigation calculations under the same conditions. Navigation unit C, as a second navigation unit, has different configuration information and may use different algorithms or models for navigation processing. This setup can prevent common software failures triggered by the same algorithmic logic errors under the same input conditions. That is, when multiple navigation data in the first navigation data set are completely inconsistent, it means that the data output by all navigation units cannot be mutually verified. At this time, a deeper comprehensive diagnosis is required. This comprehensive diagnosis can include checking the internal state of each navigation unit (such as sensor health status, signal quality, algorithm convergence, etc.) and evaluating it in conjunction with external environmental information (such as electromagnetic interference intensity, satellite signal availability, etc.). For example, the current reliability of each navigation unit can be determined by analyzing its self-test report, data confidence index, or historical performance data. Based on the comprehensive diagnostic results, the navigation data with the highest reliability is selected as the second navigation result. If the navigation data corresponding to multiple first navigation units is consistent, and there are inconsistencies between the navigation data corresponding to multiple first navigation units and the navigation data corresponding to the second navigation unit, then the data rationality verification of the navigation data corresponding to the second navigation unit is performed to obtain the verification results. In this scenario, the data consistency between homogeneous first navigation units indicates that they may be working normally, but the data of heterogeneous second navigation units is inconsistent with them. At this time, the second navigation unit cannot be simply ruled out, but its data rationality verification is required. Data rationality verification can include comparing the data of the second navigation unit with the data of other independent sensors of the aircraft (such as barometric altimeter, pitot tube, radar altimeter, etc.), or comparing it with the predicted values ​​of the aircraft's motion model. For example, verifying whether the speed, position, or attitude changes output by the second navigation unit conform to the physical motion laws of the aircraft and the current flight state. Alternatively, the rationality of the data can be determined by checking the internal state parameters of the second navigation unit itself (such as its unique sensor health indicators, algorithm convergence status, signal source quality, etc.).

[0040] Furthermore, if the verification result is successful, the navigation data output by the second navigation unit is used as the second navigation result. If the data from the second navigation unit is confirmed to be reasonable and reliable after rationality verification, it should be adopted even if it is inconsistent with the data from the first navigation unit. In this case, the system directly uses the navigation data currently output by the second navigation unit as the second navigation result for determining the subsequent main flight control navigation result. If the verification result is unsuccessful, the navigation data output by multiple first navigation units is fused, and the fused navigation data is used as the second navigation result. If the data from the second navigation unit fails the rationality verification, it indicates that its data may have problems. In this case, consistent first navigation unit data should be trusted and utilized. The fusion of navigation data output by multiple first navigation units can be achieved using statistical methods such as averaging, weighted averaging, and median filtering. For example, the arithmetic mean of all consistent first navigation unit data can be calculated as the fused navigation data. Alternatively, fusion can also employ state estimation algorithms such as Kalman filtering or extended Kalman filtering, using the data from multiple first navigation units as input observations and combining them with the aircraft's motion model to obtain more accurate fused navigation data.

[0041] Furthermore, if the navigation data corresponding to multiple first navigation units is inconsistent, and there is data in the navigation data corresponding to multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit, then the navigation data in the multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit is merged with the navigation data corresponding to the second navigation unit, and the merged navigation data is used as the second navigation result. In this complex scenario, the data within the first navigation unit is inconsistent, but some of the data is consistent with the data of the second navigation unit. This indicates that the data of the second navigation unit may have high reliability and can help identify abnormal data in the first navigation unit. First, identify those navigation data in the first navigation unit that are consistent with the data of the second navigation unit. Then, merge these consistent first navigation unit data with the data of the second navigation unit. The fusion method can be a simple average or a weighted average, or the data of the second navigation unit can be given a higher weight during fusion, because it can maintain consistency with some first navigation unit data even when there is inconsistency within the first navigation unit, which is itself a strong verification. Through the above-mentioned hierarchical and adaptive data processing mechanism, this application can effectively deal with the data conflict problem caused by the configuration differences of navigation unit groups, and significantly improve the reliability, accuracy and robustness of navigation results in complex environments.

[0042] In one embodiment, specifically in step S103, the second navigation data set includes multiple navigation data streams. Specifically, the second navigation data set is processed using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result, including the following steps: Using a preset fault diagnosis voting algorithm, the multi-path navigation data in the second navigation data set are fused to obtain the optimal navigation data; Calculate the deviation between the multipath navigation data and the optimal navigation data in the second navigation data set sequentially; Determine if any navigation data deviation exceeds a preset fault detection threshold. If no deviation value of any navigation data exceeds the preset fault judgment threshold, then the optimal navigation data is taken as the backup flight control navigation result.

[0043] In one implementation, the second navigation data set includes multiple navigation data streams, which can originate from multiple navigation sensors within a navigation unit group. For example, it can be navigation data output by multiple independent navigation units (INUs). The hardware heterogeneity configuration ensures that the three INUs use IMU sensors and GNSS boards from different suppliers / technology routes. The software heterogeneity configuration includes navigation units with the same operating configuration and navigation units with different operating configurations. The optimal navigation data is obtained by fusing the multiple navigation data streams in the second navigation data set using a preset fault diagnosis voting algorithm. For example, a weighted average method can be used, assigning different weights to each data stream based on its historical performance, sensor type, or confidence level. Another implementation uses a median voting method, selecting the median of the multiple data streams as the fusion result. This method has good robustness to outliers. Furthermore, state estimation algorithms such as Kalman filtering and extended Kalman filtering can be used to fuse the multiple navigation data streams as observations to obtain the optimal state estimate. The optimal navigation data refers to the navigation data considered closest to the true value after processing by the fault diagnosis voting algorithm. It is usually a comprehensive result that combines the advantages of multiple data streams and eliminates the influence of outlier data.

[0044] Furthermore, when calculating the deviation values ​​between the multiple navigation data streams and the optimal navigation data in the second navigation data set, the deviation value refers to the difference between each original navigation data stream and the fused optimal navigation data. Various mathematical methods can be used to calculate the deviation value; for example, the absolute difference or relative difference can be calculated directly. Euclidean distance, Mahalanobis distance, and other metrics can also be used to quantify the differences between multi-dimensional navigation data (such as position, velocity, and attitude). When determining whether the deviation value of any navigation data stream exceeds a preset fault judgment threshold, the preset fault judgment threshold is used as a standard to determine whether the navigation data is abnormal. This threshold can be set according to the aircraft's performance requirements, the accuracy of the navigation sensors, the complexity of the external environment, and historical fault data. For example, it can be set to a fixed value, such as a position deviation exceeding 10 meters or a velocity deviation exceeding 1 meter per second. Alternatively, the threshold can be dynamically adjusted, for example, adaptively adjusted based on the aircraft's current flight state (such as speed, altitude, and rate of change of attitude) or environmental conditions (such as electromagnetic interference intensity). When the deviation value exceeds this threshold, the navigation data stream is considered to be potentially faulty. If no deviation value of any navigation data exceeds a preset fault judgment threshold, the optimal navigation data is used as the backup flight control navigation result. This step ensures that the fused optimal navigation data is used as the backup flight control navigation result only when all input navigation data are considered reliable and consistent. This is a rigorous quality control mechanism designed to prevent any potential fault data from contaminating the final navigation output. Through the above technical solution, potential abnormal or faulty data can be accurately identified. Only when the deviation values ​​of all navigation data are within acceptable limits is the fused optimal navigation data used as the backup flight control navigation result, thus avoiding the problem of unreliable backup flight control navigation results due to a single or a few faulty data points.

[0045] In one embodiment, specifically step S103, which involves determining the final navigation result based on the primary flight control navigation result and the backup flight control navigation result, includes the following steps: Acquire the main signal status data corresponding to the main flight control computing unit and the backup signal status data corresponding to the backup flight control computing unit; Determine whether the main signal status data and the backup signal status data meet preset status conditions; If the main signal status data meets the preset status conditions and the backup signal status data does not meet the preset status conditions, then the main flight control navigation result corresponding to the main flight control calculation unit shall be taken as the final navigation result. If the main signal status data does not meet the preset status conditions and the backup signal status data meets the preset status conditions, then the main flight control navigation result corresponding to the backup flight control calculation unit shall be taken as the final navigation result. If the main signal status data meets the preset status conditions and the backup signal status data meets the preset status conditions, then the main flight control navigation result corresponding to the main flight control computing unit and the main flight control navigation result corresponding to the backup flight control computing unit are fused together, and the fused navigation result is taken as the final navigation result.

[0046] In one implementation, the system acquires the main signal status data corresponding to the primary flight control computing unit and the backup signal status data corresponding to the backup flight control computing unit. This aims to obtain real-time operational health information of the primary and backup flight control computing units. The main and backup signal status data may include, but are not limited to, CPU load, memory usage, sensor data input integrity, navigation algorithm operation status, packet loss rate or latency of the communication link, and power supply voltage stability. This data can be periodically collected by the diagnostic module within the computing unit and transmitted to the decision module via an internal bus or dedicated communication interface. Alternatively, status data can be indirectly acquired by monitoring the quality of the navigation data streams output by the primary and backup flight control computing units. For example, monitoring the update frequency of navigation data, the checksum of data packets, and the reasonable range of data fields. Any anomalies can be considered part of the status data, indicating potential problems. The system then determines whether the main and backup signal status data meet preset status conditions. These preset conditions serve as the benchmark for judging whether the computing unit is operating normally, ensuring that only computing units in good condition can participate in determining the final navigation result. Preset state conditions can be a set of logical judgment rules, such as specifying that CPU load is below 80%, memory utilization is below 90%, sensor data input is complete, navigation algorithm output is within a reasonable range, and communication link packet loss rate is below 1%. When all these conditions are met, the state of the computing unit is considered to meet the preset conditions. Alternatively, preset state conditions can also be defined through machine learning models or expert systems. During normal operation, the system collects a large amount of state data and trains the model to identify "normal" and "abnormal" patterns. In actual operation, the real-time acquired state data is input into the model for evaluation, and the model outputs a confidence score or classification result to determine whether the preset state conditions are met.

[0047] Furthermore, if the primary signal status data meets the preset status conditions but the backup signal status data does not, the primary flight control navigation result corresponding to the primary flight control computing unit will be used as the final navigation result, and may trigger a fault alarm or diagnostic process in the backup flight control computing unit. In this case, in addition to directly selecting the primary flight control navigation result, the system can also perform a quick rationality check on the primary flight control navigation result, such as comparing it with historical data or a rough estimate, to further enhance its reliability. If the primary signal status data does not meet the preset status conditions but the backup signal status data meets the preset status conditions, the primary flight control navigation result corresponding to the backup flight control computing unit will be used as the final navigation result, and may initiate a fault diagnosis or restart process in the primary flight control computing unit. To ensure a smooth handover, the backup flight control navigation result can be briefly monitored or smoothed before switching to it, to avoid impacting flight control due to data jumps during the handover. If both the primary and backup signal status data meet preset state conditions, the primary flight control navigation results from the primary flight control computing unit and the backup flight control computing unit are fused together, and the fused navigation result is used as the final navigation result. The fusion method can employ weighted averaging, Kalman filtering, or extended Kalman filtering, among others. This technical solution further improves navigation accuracy and reliability, providing strong support for the safe and stable flight of the aircraft. Furthermore, this technical solution possesses adaptive adjustment capabilities, dynamically selecting the optimal navigation result output based on the actual state of the primary and backup flight control computing units, thereby ensuring that the aircraft obtains accurate and reliable navigation information under different flight scenarios.

[0048] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of an aircraft navigation device provided in an embodiment of the present invention. This aircraft navigation device corresponds one-to-one with the aircraft navigation methods described in the above embodiments. Please refer to [link / reference] for details. Figure 1 as well as Figure 1 The relevant descriptions in the corresponding embodiments are shown below. For ease of explanation, only the parts relevant to this embodiment are shown. The aircraft includes a flight control computing unit group and a navigation unit group. The flight control computing unit group includes a main flight control computing unit and a backup flight control computing unit. See [link to documentation]. Figure 2 The aircraft navigation device 20 includes: an acquisition module 21, a determination module 22, and a navigation module 23.

[0049] The acquisition module 21 is used to acquire the first navigation data set corresponding to the main flight control computing unit and the second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol and the second navigation data set is transmitted by the navigation unit group through a single communication protocol. The processing module 22 is used to process the first navigation data set using a preset redundancy voting algorithm to obtain the main flight control navigation result, and to process the second navigation data set using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. The navigation module 23 is used to determine the final navigation result based on the main flight control navigation result and the backup flight control navigation result, and to perform navigation control on the aircraft according to the final navigation result.

[0050] Optionally, the aforementioned processing module 22 is specifically used for: Perform a validity check on the first navigation data set; If the first navigation data set passes the validity check, then determine whether the communication transmission time of the first navigation data set exceeds a preset communication time threshold. If the communication transmission time of the first navigation data set does not exceed the preset communication time threshold, then the first navigation data set is time-aligned and data-synchronized to obtain the processed first navigation data set.

[0051] Optionally, the above processing module 22 is specifically used for: The first navigation data set includes multiple navigation data. A preset redundancy voting algorithm is used to determine whether the multiple navigation data in the first navigation data set are consistent. If the multiple navigation data in the first navigation data set are consistent, the multiple navigation data in the first navigation data set are fused to obtain a first navigation result, and the first navigation result is used as the main flight control navigation result; If the multiple navigation data in the first navigation data set are inconsistent, the multiple navigation data are processed according to the inconsistency of the multiple navigation data in the first navigation data set to obtain a second navigation result, and the second navigation result is used as the main flight control navigation result.

[0052] Optionally, the determining module 22 is further configured to: The navigation unit group includes multiple first navigation units with identical configuration information and second navigation units with different configuration information from the first navigation units; If the data in the multi-path navigation data are completely inconsistent, a comprehensive diagnosis is performed on the multi-path navigation data to obtain a comprehensive diagnosis result; Based on the comprehensive diagnostic results, the navigation data with the highest reliability is selected as the second navigation result; If the navigation data corresponding to multiple first navigation units is consistent, and there is a navigation data among the multiple first navigation units that is inconsistent with the navigation data corresponding to the second navigation unit, then the data rationality verification is performed on the navigation data corresponding to the second navigation unit to obtain the verification result; If the verification result is passed, then the navigation data corresponding to the second navigation unit is used as the second navigation result; If the verification result is unsuccessful, the navigation data corresponding to multiple first navigation units will be merged, and the merged navigation data will be used as the second navigation result. If the navigation data corresponding to multiple first navigation units is inconsistent, and there is data in the navigation data corresponding to multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit, then the navigation data in the multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit is merged with the navigation data corresponding to the second navigation unit, and the merged navigation data is used as the second navigation result.

[0053] Optionally, the determining module 22 is further configured to: The second navigation data set includes multi-path navigation data; Using a preset fault diagnosis voting algorithm, the multi-path navigation data in the second navigation data set are fused to obtain the optimal navigation data; Calculate the deviation between the multipath navigation data and the optimal navigation data in the second navigation data set sequentially; Determine if any navigation data deviation exceeds a preset fault detection threshold. If no deviation value of any navigation data exceeds the preset fault judgment threshold, then the optimal navigation data is taken as the backup flight control navigation result.

[0054] Optionally, the navigation module 33 described above is specifically used for: Acquire the main signal status data corresponding to the main flight control computing unit and the backup signal status data corresponding to the backup flight control computing unit; Determine whether the main signal status data and the backup signal status data meet preset status conditions; If the main signal status data meets the preset status conditions and the backup signal status data does not meet the preset status conditions, then the main flight control navigation result corresponding to the main flight control calculation unit shall be taken as the final navigation result. If the main signal status data does not meet the preset status conditions and the backup signal status data meets the preset status conditions, then the main flight control navigation result corresponding to the backup flight control calculation unit shall be taken as the final navigation result. If the main signal status data meets the preset status conditions and the backup signal status data meets the preset status conditions, then the main flight control navigation result corresponding to the main flight control computing unit and the main flight control navigation result corresponding to the backup flight control computing unit are fused together, and the fused navigation result is taken as the final navigation result.

[0055] It should be noted that the information interaction and execution process between the above-mentioned units are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0056] Figure 3 This is a schematic diagram of the structure of a controller provided in an embodiment of the present invention. Figure 3 As shown, the controller of this embodiment includes: at least one processor ( Figure 3 Only one is shown in the diagram), a memory, and a computer program stored in the memory and capable of running on at least one processor, which, when executing the computer program, implements the steps in any of the above-described aircraft navigation method embodiments.

[0057] The controller may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 3 This is merely an example of a controller and does not constitute a limitation on the controller. A controller may include more or fewer components than shown in the figure, or a combination of certain components, or different components, such as network interfaces, displays, and input systems.

[0058] In one embodiment, an aircraft is provided, which includes a navigation system, a power system, and a controller. The navigation system includes a flight control computing unit group and a navigation unit group. The controller is connected to the navigation system and the power system respectively, so that the controller can execute the various steps of any embodiment of the aircraft navigation method disclosed in this invention, which will not be repeated here.

[0059] In one embodiment, a computer-readable storage medium is provided that, when the instructions in the computer-readable storage medium are executed by a processor in a controller, enables the controller to perform the steps of any embodiment of the aircraft navigation method disclosed in this invention, which will not be repeated here. The computer-readable storage medium may be non-volatile or volatile.

[0060] The processor referred to can be a CPU, but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0061] The memory includes readable storage media, internal memory, etc., wherein the internal memory can be the controller's RAM, providing an environment for the operation of the operating system and computer-readable instructions stored in the readable storage media. The readable storage media can be the controller's hard drive, or in other embodiments, an external storage device for the controller, such as a plug-in hard drive, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard. Furthermore, the memory can include both internal storage units and external storage devices of the controller. The memory is used to store the operating system, cooperative applications, bootloader, data, and other programs, such as program code for computer programs. The memory can also be used to temporarily store data that has been output or will be output.

[0062] Those skilled in the art will understand that implementing all or part of the processes in the above embodiments can be accomplished by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0063] Those familiar with the technical field will understand that, for ease of description and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0064] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. An aircraft navigation method, characterized in that, The aircraft includes a flight control computing unit group and a navigation unit group, the flight control computing unit group includes a main flight control computing unit and a backup flight control computing unit, and the method includes: The system acquires a first navigation data set corresponding to the main flight control computing unit and a second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol, and the second navigation data set is transmitted by the navigation unit group through a single communication protocol. The first navigation data set is processed using a preset redundancy voting algorithm to obtain the primary flight control navigation result, and the second navigation data set is processed using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. Based on the primary flight control navigation results and the backup flight control navigation results, the final navigation result is determined, and the aircraft is controlled for navigation according to the final navigation result.

2. The aircraft navigation method as described in claim 1, characterized in that, The first navigation data set includes multiple navigation data streams. The step of processing the first navigation data set using a preset redundancy voting algorithm to obtain the main flight control navigation result includes: Using a preset redundancy voting algorithm, determine whether the multi-path navigation data in the first navigation data set are consistent; If the multiple navigation data in the first navigation data set are consistent, the multiple navigation data in the first navigation data set are fused to obtain a first navigation result, and the first navigation result is used as the main flight control navigation result; If the multiple navigation data in the first navigation data set are inconsistent, the multiple navigation data are processed according to the inconsistency of the multiple navigation data in the first navigation data set to obtain a second navigation result, and the second navigation result is used as the main flight control navigation result.

3. The aircraft navigation method as described in claim 2, characterized in that, The navigation unit group includes multiple first navigation units with identical configuration information and second navigation units with different configuration information. If the multi-path navigation data in the first navigation data set is inconsistent, the multi-path navigation data is processed according to the inconsistency to obtain a second navigation result, including: If the data in the multi-path navigation data are completely inconsistent, a comprehensive diagnosis is performed on the multi-path navigation data to obtain a comprehensive diagnosis result; Based on the comprehensive diagnostic results, the navigation data with the highest reliability is selected as the second navigation result; If the navigation data corresponding to multiple first navigation units is consistent, and there is a navigation data among the multiple first navigation units that is inconsistent with the navigation data corresponding to the second navigation unit, then the data rationality verification is performed on the navigation data corresponding to the second navigation unit to obtain the verification result; If the verification result is passed, then the navigation data corresponding to the second navigation unit is used as the second navigation result; If the verification result is unsuccessful, the navigation data corresponding to multiple first navigation units will be merged, and the merged navigation data will be used as the second navigation result. If the navigation data corresponding to multiple first navigation units is inconsistent, and there is data in the navigation data corresponding to multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit, then the navigation data in the multiple first navigation units that is consistent with the navigation data corresponding to the second navigation unit is merged with the navigation data corresponding to the second navigation unit, and the merged navigation data is used as the second navigation result.

4. The aircraft navigation method as described in claim 1, characterized in that, The second navigation data set includes multiple navigation data streams. The process of processing the second navigation data set using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result includes: Using a preset fault diagnosis voting algorithm, the multi-path navigation data in the second navigation data set are fused to obtain the optimal navigation data; Calculate the deviation between the multipath navigation data and the optimal navigation data in the second navigation data set sequentially; Determine if any navigation data deviation exceeds a preset fault detection threshold. If no deviation value of any navigation data exceeds the preset fault judgment threshold, then the optimal navigation data is taken as the backup flight control navigation result.

5. The aircraft navigation method as described in claim 1, characterized in that, Before processing the first navigation data set using a preset redundancy voting algorithm to obtain the main flight control navigation result, the following steps are included: Perform a validity check on the first navigation data set; If the first navigation data set passes the validity check, then determine whether the communication transmission time of the first navigation data set exceeds a preset communication time threshold. If the communication transmission time of the first navigation data set does not exceed the preset communication time threshold, then the first navigation data set is time-aligned and data-synchronized to obtain the processed first navigation data set.

6. The aircraft navigation method as described in claim 1, characterized in that, The step of determining the final navigation result based on the primary flight control navigation result and the backup flight control navigation result includes: Acquire the main signal status data corresponding to the main flight control computing unit and the backup signal status data corresponding to the backup flight control computing unit; Determine whether the main signal status data and the backup signal status data meet preset status conditions; If the main signal status data meets the preset status conditions and the backup signal status data does not meet the preset status conditions, then the main flight control navigation result corresponding to the main flight control calculation unit shall be taken as the final navigation result. If the main signal status data does not meet the preset status conditions and the backup signal status data meets the preset status conditions, then the main flight control navigation result corresponding to the backup flight control calculation unit shall be taken as the final navigation result. If the main signal status data meets the preset status conditions and the backup signal status data meets the preset status conditions, then the main flight control navigation result corresponding to the main flight control computing unit and the main flight control navigation result corresponding to the backup flight control computing unit are fused together, and the fused navigation result is used as the final navigation result.

7. An aircraft navigation device, characterized in that, The aircraft includes a flight control computing unit group and a navigation unit group. The flight control computing unit group includes a main flight control computing unit and a backup flight control computing unit. The device includes: The acquisition module is used to acquire a first navigation data set corresponding to the main flight control computing unit and a second navigation data set corresponding to the backup flight control computing unit, wherein the first navigation data set is transmitted by the navigation unit group through a dual communication protocol, and the second navigation data set is transmitted by the navigation unit group through a single communication protocol. The processing module is used to process the first navigation data set using a preset redundancy voting algorithm to obtain the main flight control navigation result, and to process the second navigation data set using a preset fault diagnosis voting algorithm to obtain the backup flight control navigation result. The navigation module is used to determine the final navigation result based on the primary flight control navigation result and the backup flight control navigation result, and to perform navigation control on the aircraft according to the final navigation result.

8. A controller comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the aircraft navigation method as described in any one of claims 1 to 6.

9. An aircraft, the aircraft comprising a navigation system, a power system, and a controller, the navigation system comprising a flight control computing unit group and a navigation unit group, characterized in that, The controller is connected to the navigation system and the power system respectively, and is used to execute the aircraft navigation method as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the aircraft navigation method as described in any one of claims 1 to 6.

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