An autonomous flight reliable positioning system and method based on multi-source data

Abstract

The application provides a kind of autonomous flight reliable positioning system and method based on multi-source data, including five main function layers: multi-source perception data acquisition layer, sensor end trusted layer, trusted center verification processing layer, trust perception weighted fusion layer, and security output and audit layer.The application multi-source sensor cooperative collection improves the adaptability of complex environment, and the cryptography mechanism ensures the authenticity and integrity of data, resists fraud and tampering attacks;Dynamic trust weighted fusion optimizes positioning accuracy, and can adaptively adjust sensor weight;Full-link log and encrypted evidence storage realize traceable audit of positioning process;Modular design supports distributed deployment and scenario expansion, suitable for multiple autonomous platforms;Abnormal response mechanism guarantees system safety fault tolerance, and can still operate stably under attack or interference, which comprehensively improves the reliability and security of autonomous flight positioning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent navigation and positioning, in particular to an autonomous flight reliable positioning system and method based on multi-source data. BACKGROUND

[0002] In a traditional multi-source fusion positioning system, the positioning accuracy and robustness are usually improved by fusing sensor data such as GNSS, IMU, SLAM, etc. However, existing methods mainly focus on physical redundancy and algorithm optimization, lacking verification mechanisms for data source authenticity, integrity, and timeliness. In complex or hostile environments, such as GPS spoofing, visual data tampering, and communication link hijacking, security threats will seriously affect the reliability and security of the positioning system.

[0003] Although the prior art has related autonomous positioning methods, it still does not solve the core problem of data source verification, and the positioning reliability is insufficient when facing malicious attacks. Therefore, there is an urgent need for a solution that maintains positioning accuracy while enhancing the anti-attack capability of the positioning system. SUMMARY

[0004] The purpose of the present application is to provide an autonomous flight reliable positioning system and method based on multi-source data, which designs a verification mechanism for data source authenticity, integrity, and timeliness through cryptographic tools, providing trusted fusion autonomous positioning.

[0005] According to one object of the present application, the present application provides an autonomous flight reliable positioning system based on multi-source data, comprising:

[0006] A multi-source perception data acquisition layer is used to deploy heterogeneous sensors to collect environmental information and motion state;

[0007] A sensor-end trusted layer includes a trusted signature module and a trusted encryption module, which is used to perform trusted verification and packaging of data output by the heterogeneous sensors;

[0008] A trusted center verification processing layer is used to uniformly receive, verify, and schedule processing of data output by the sensor-end trusted layer;

[0009] A trust perception weighted fusion layer is used to weight and fuse data that passes the verification based on sensor trust degree, and output positioning results and error covariance;

[0010] A secure output and audit layer is used to encrypt and store evidence of the positioning results, interface with the navigation control module, and trigger a security response strategy when an anomaly is detected.

[0011] Further, the heterogeneous sensors include a GPS / GNSS positioning and navigation module, an IMU inertial module, a barometer module, and a visual / laser SLAM module.

[0012] Further, the GPS / GNSS positioning navigation module is used to receive satellite navigation signals to calculate the position and speed information of the device, the IMU inertial module measures angular velocity and linear acceleration through gyroscopes and accelerometers to obtain attitude changes, speed and relative position estimates, the barometer module measures atmospheric pressure and converts it into relative height information, and the visual / laser SLAM module is used to realize positioning and map construction in unknown environments.

[0013] Further, the trusted signature module interacts with the GPS / GNSS positioning navigation module to digitally sign the positioning coordinates and attach timestamps and randomization factors; the trusted signature module interacts with the visual / laser SLAM module to sign each frame of SLAM pose.

[0014] Further, the trusted encryption module interacts with the IMU inertial module to encrypt acceleration and angular velocity information using symmetric encryption and concatenate HMAC integrity checks; the trusted encryption module interacts with the barometer module to symmetrically encrypt height measurement information and concatenate HMAC integrity checks.

[0015] Further, the trusted center verification processing layer includes:

[0016] The data receiving and scheduling module is used to uniformly receive, time synchronize and schedule manage data from the sensor-side trusted layer;

[0017] The signature / HMAC verification module is used to perform public key signature verification or HMAC verification on incoming data packets to confirm source trustworthiness;

[0018] The timestamp / randomization factor checking module is used to compare the timestamps and randomization factors of data to prevent replay attacks;

[0019] The structural integrity verification module is used to determine whether the data packet structure conforms to the trusted protocol specification to filter abnormal packets;

[0020] The trusted data cache module is used to store data that has passed signature / HMAC verification, timestamp / randomization factor checking and structural integrity verification for the trust-aware weighted fusion layer to call;

[0021] The abnormal log recording module records verification failure data for security auditing.

[0022] Further, the trust-aware weighted fusion layer includes:

[0023] The trust weight calculation module is used to dynamically evaluate the trustworthiness of sensors based on the historical reliability, error distribution and attack detection of sensor data and generate weight coefficients;

[0024] The trust-weighted fusion module is used to input the source data into an extended Kalman filter or an unscented Kalman filter, and fuse the trust weights to achieve the optimal estimation of position and attitude.

[0025] The integrated positioning result output module outputs spatial position coordinates and heading angle, which are then connected to the downstream control unit.

[0026] The covariance output module is used to output the error covariance matrix and update the trust weights in the trust weight calculation module through a dynamic feedback mechanism.

[0027] Furthermore, the security output and audit layer includes:

[0028] The location and trajectory encryption and evidence storage module is used to encrypt and store key location results for later retrospective auditing.

[0029] The navigation / control module directly interfaces with downstream control units such as the flight control system;

[0030] The security response strategy module is used to trigger source degradation, backup sensor activation, mission abort, or return-to-home strategies when persistent anomalies or signs of attack are detected.

[0031] Furthermore, the sensor modules of the multi-source sensing data acquisition layer are deployed on the same device or distributed platform to achieve collaborative acquisition of heterogeneous data.

[0032] According to another objective of the present invention, the present invention provides a positioning method for an autonomous flight reliable positioning system based on multi-source data, characterized by comprising the following steps:

[0033] S1. Data Acquisition Steps: Through the GPS / GNSS positioning and navigation module, IMU inertial module, barometer module, and visual / laser SLAM module of the multi-source sensing data acquisition layer, position velocity, angular velocity / acceleration, relative altitude, environmental features, and pose data are acquired respectively.

[0034] S2, Data Trusted Encapsulation Steps: Use the trusted signature module of the trusted layer at the sensor end to digitally sign the GPS / GNSS positioning coordinates and SLAM pose, and add a timestamp and randomization factor. Use the trusted encryption module to symmetrically encrypt the IMU data and barometer altitude information and then perform HMAC integrity verification.

[0035] S3, data verification processing step: the trusted center verification processing layer receives the scheduling module to encapsulated data unified reception and time synchronization, in turn according to data scheduling rule through signature / HMAC verification, timestamp / randomization factor check, structure integrity verification, the data that passes through verification is stored in trusted data cache module, the data that does not pass through verification is carried out abnormal log record;

[0036] S4, trust weighted fusion step: the trust weight calculation module of the trust perception weighted fusion layer generates trust weight based on sensor historical reliability, error distribution and attack detection, the trust weighted fusion module inputs the Kalman filter and fuses the trust weight, and outputs the positioning result and error covariance, and the error covariance output module feeds back the error covariance to the trust weight calculation module to update the weight;

[0037] S5, secure output and response step: the secure output and audit layer transmits the positioning result to the navigation / control module, and simultaneously, the positioning and trajectory encryption storage module is optionally encrypted and stored, and if an exception or attack is detected, the security response strategy module triggers the preset fault tolerance mechanism.

[0038] The technical scheme of the application multi-source sensor cooperative collection improves the adaptability of complex environment, the cryptography mechanism ensures the authenticity and integrity of data, resists fraud and tampering attacks, the dynamic trust weighted fusion optimizes the positioning accuracy, the sensor weight can be adaptively adjusted, the full-link log and encrypted evidence realize the traceable audit of the positioning process, the modular design supports distributed deployment and scene expansion, is suitable for multiple autonomous platforms, the abnormal response mechanism guarantees system safety and fault tolerance, and the system can still operate stably under attack or interference, and the reliability and safety of autonomous flight positioning are comprehensively improved. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical scheme in the specific embodiments or prior art of the present application, the drawings needed in the specific embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0040] Figure 1 It is a structural schematic view of the embodiment of the present application. DETAILED DESCRIPTION

[0041] The technical scheme of the present application will be described in detail below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the protection scope of the present application.

[0042] In the description of the present application, it needs to be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0043] In addition, the terms "first" and "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can include one or more of the features explicitly or implicitly. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited. In addition, the terms "mounting", "connection", "connection" should be broadly understood, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through intermediate medium, or the communication between two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0044] Embodiment 1

[0045] As Figure 1 shown, the autonomous flight reliable positioning system based on multi-source data of the present application adopts modular structure design, introduces cryptography mechanism to encrypt and protect sensor data, authentication verification, trust evaluation and fusion calculation, and the overall structure is divided into five main functional layers:

[0046] 1. Multi-source perception data acquisition layer

[0047] This layer includes a variety of heterogeneous sensor devices:

[0048] GPS / GNSS positioning and navigation module: receives satellite signals to calculate position and speed, which is the basis for outdoor navigation, but is susceptible to interference in weak signal environment;

[0049] IMU inertial module: composed of gyroscopes and accelerometers, attitude, speed and relative position estimation are obtained by integration, response is fast but long-term accuracy is limited;

[0050] Barometer module: measures atmospheric pressure to convert to relative height, assists vertical direction positioning accuracy;

[0051] Visual / Laser SLAM module: Achieve localization and mapping in unknown environment, strong autonomy but sensitive to computing resources and perception conditions.

[0052] 2. Sensor-end trust layer

[0053] Ensure that data has tamper-proof, anti-replay and identity traceability capabilities before entering the system:

[0054] Trusted signature module: Interact with GPS / GNSS module for coordinate digital signature, add timestamp and randomization factor; interact with visual / laser SLAM module for pose signature to prevent forgery and tampering;

[0055] Trusted encryption module: Interact with IMU module to symmetrically encrypt acceleration and angular velocity information and splice HMAC check; interact with barometer module to encrypt and protect height information.

[0056] 3. Trusted center verification processing layer

[0057] Unified reception and scheduling processing of sensor data, including:

[0058] Data reception and scheduling module: Unified data reception, time synchronization and scheduling management to avoid data loss or timing disorder;

[0059] Signature / HMAC verification module: Verify the trustworthiness of data packet source, cache if passed, and trigger security response if failed;

[0060] Timestamp / randomization factor checking module: Prevent replay attacks and verify data timeliness and uniqueness;

[0061] Structural integrity verification module: Filter abnormal packets to ensure data structure conforms to protocol specifications;

[0062] Trusted data cache module: Store data that passes all verifications for subsequent fusion calls;

[0063] Abnormal log recording module: Record verification failed data for security audit.

[0064] 4. Trust-aware weighted fusion layer

[0065] Introduce trust management mechanism and weighted fusion method to integrate multi-source information:

[0066] Trust weight calculation module: Dynamically evaluate sensor trust based on historical reliability, error distribution, attack detection, etc. to generate weight coefficients;

[0067] Trust-weighted fusion module: Input data into Kalman filter to fuse trust weights for optimal estimation;

[0068] Fusion positioning result output module: output spatial position coordinates and heading angle, and connect downstream control unit;

[0069] Covariance output module: output error covariance matrix, feedback for updating trust weight.

[0070] 5. Security output and audit layer

[0071] With log audit and real-time response function:

[0072] Positioning and trajectory encryption storage module (optional): encrypt storage of key positioning results, for later backtracking audit;

[0073] Navigation / control module: directly connect downstream control unit such as flight control system;

[0074] Security response strategy module: detect abnormality and trigger fault tolerance mechanism such as source weight reduction, backup sensor activation or task suspension.

[0075] The present application introduces the mechanism of cryptographic signature and randomization factor to multi-source sensor data stream; the data receiving end is embedded with trusted verification chain, which reviews each data packet layer by layer; the fusion algorithm dynamically adjusts the participation degree based on trust weight, resists malicious sensors or data pollution; the system provides closed-loop output and audit mechanism, and the positioning result has verifiability and traceability; it can be extended to edge computing or distributed collaborative positioning scene.

[0076] Embodiment 2

[0077] The structure of this embodiment is basically the same as that of embodiment 1, the difference is that the autonomous flight reliable positioning system based on multi-source data in this embodiment aims to improve the safety and robustness of multi-source fusion positioning technology in complex environment, adopts modular structure design, and introduces cryptographic mechanism to encrypt, protect, authenticate, verify, trust evaluate and fusion calculate sensor data, to ensure that the output positioning result still has high reliability and auditability in the attack scene of forgery, replay, interference and the like.

[0078] The overall structure of the system of this embodiment includes five main functional layers: multi-source perception data acquisition layer, sensor end trusted layer, trusted center verification processing layer, trust perception weighted fusion layer, and security output and audit layer, wherein:

[0079] 1. Multi-source perception data acquisition layer

[0080] The layer includes multiple heterogeneous sensor devices, respectively GPS / GNSS positioning navigation module, IMU inertial module, barometer module, and visual / laser SLAM module. These modules independently collect environmental information and motion state to form multiple data source inputs. Each module can be deployed on the same device or distributed platform. They each have unique measurement mechanisms and technical advantages, and collaborative action can improve the robustness and accuracy of the system in complex environments.

[0081] 1) GPS / GNSS positioning navigation module, a module that calculates the position and velocity information of the device on the earth's surface by receiving signals from global positioning system, Beidou, etc. Satellite navigation system. This module can provide relatively stable global positioning capability and is the basis for outdoor navigation, but it is easily affected by shielding and multipath interference in weak signal environments such as tunnels, urban high-rise areas, or indoors;

[0082] 2) IMU inertial module, composed of gyroscopes and accelerometers, respectively used to measure angular velocity and linear acceleration. By integrating these data, attitude changes, speed, and relative position estimates can be obtained. IMU inertial module has the characteristics of fast response speed and independence from external signal sources, and can still provide short-term high-frequency position estimates when the GPS / GNSS positioning navigation module signal is interrupted, but its long-term accuracy is limited due to cumulative error;

[0083] 3) Barometer module, used to measure atmospheric pressure and convert it to relative height information through the international standard atmospheric model. This module is small in size and low in power consumption, and is commonly used to assist in height estimation. In a multi-source sensor fusion system, the barometer can serve as a height reference to enhance the positioning accuracy of the IMU inertial module and the GPS / GNSS positioning navigation module in the vertical direction, especially in situations where the GPS / GNSS positioning navigation module has low accuracy or no height reference;

[0084] 4) Visual / laser SLAM module, a technology that uses cameras or laser radars to achieve real-time positioning and map construction in unknown environments. Visual SLAM uses image extraction to extract environmental feature points, while laser SLAM scans the environment's geometric structure. Both can provide high-precision positioning and mapping capabilities in areas without GPS / GNSS positioning navigation signals. Visual / laser SLAM module has strong autonomy and is suitable for complex environments, but it is sensitive to computing resources, lighting, and reflectivity, among other sensing conditions.

[0085] 2. Sensor-end trusted layer

[0086] The purpose of this layer is to ensure that each type of data has tamper-proofing, anti-replay and identity traceability capability before entering the trusted center verification processing layer. After data collection, each sensor module will package its output for trusted verification. The packaging process is carried out through the trusted signature module and the trusted encryption module.

[0087] 1) Trusted signature module, mainly including two aspects of functions, one is to interact with GPS / GNSS positioning and navigation module, to digitally sign the positioning coordinates and attach timestamp and randomization factor, to ensure uniqueness and anti-replay; the other is to interact with visual / laser SLAM module, to sign each frame of SLAM pose to prevent forgery and frame tampering;

[0088] 2) Trusted encryption module, mainly including two aspects of functions, one is to interact with IMU inertial module, to use symmetric encryption to encrypt acceleration, angular velocity and other information, to splice HMAC integrity check, to perform trusted packaging of transmission information of IMU inertial module; the other is to interact with barometer module, to symmetrically encrypt height measurement information, to splice HMAC integrity check, to perform trusted transmission protection of communication content.

[0089] 3. Trusted center verification processing layer

[0090] All data sent by sensors are uniformly received and processed by the trusted center verification processing layer. This layer includes data receiving and scheduling module, signature / HMAC verification module, timestamp / randomization factor checking module, structural integrity verification module, trusted data cache module, and abnormal log recording module.

[0091] 1) Data receiving and scheduling module, which is the core coordination unit in the multi-sensor system, mainly responsible for unified reception, time synchronization and scheduling management of trusted data from various sensors. The basic task of this module is to ensure that sensor data can enter the data processing flow of the system in an orderly and efficient manner, avoiding problems such as data loss, delay or timing disorder, thereby providing accurate and timely information support for subsequent positioning, navigation and control;

[0092] 2) Signature / HMAC verification module, which verifies the incoming data packet with public key signature or HMAC, to ensure the source is trusted. If the verification is passed, the data is transmitted to the trusted data cache module, and if the verification fails, the data is transmitted to the security response strategy module;

[0093] 3) Timestamp / randomization factor checking module, which compares whether the timestamp and randomization factor of the data are reasonable and have been used, to prevent replay attacks. If the verification is passed, the data is transmitted to the trusted data cache module, and if the verification fails, the data is transmitted to the security response strategy module;

[0094] 4) Structure integrity verification module, judge whether the data packet structure conforms to the trusted protocol specification, filter abnormal packets, pass the data to the trusted data cache module, and transmit the data to the security response strategy module if the verification fails;

[0095] 5) Trusted data cache module, only data that passes all verifications will enter the trusted data cache module for subsequent trust-aware weighted fusion layer calls;

[0096] 6) Abnormal log recording module, record all verification failed data for security audit and subsequent risk judgment.

[0097] This layer is the security core of the entire system, ensuring that the data has complete identity authentication, time validity verification and structure constraint ability before entering the trust-aware weighted fusion layer.

[0098] 4. Trust-aware weighted fusion layer

[0099] On the basis of ensuring data credibility, the system introduces trust management mechanism and weighted fusion method to integrate multiple information sources. This layer improves positioning accuracy and fault tolerance in complex dynamic environments by fusing redundant and trusted multi-source information while considering sensor trust degree. This layer includes trust weight calculation module, trust weighted fusion module, fusion positioning result output module, and covariance output module.

[0100] 1) Trust weight calculation module, based on historical reliability, error distribution, attack detection of sensor data and other factors, dynamically evaluate the current trust degree of each sensor, generate weight coefficient, and transmit to trust weighted fusion module;

[0101] 2) Trust weighted fusion module, input each source data into extended Kalman filter or unscented Kalman filter, and fuse trust weight to realize optimal estimation of position and attitude. Finally, output data to fusion positioning result output module and covariance output module;

[0102] 3) Fusion positioning result output module, output the final estimated x, y, z coordinates and heading angle θ to represent the spatial position, and transmit the data to the positioning and trajectory encryption storage module (optional) and navigation / control module;

[0103] 4) Covariance output module, output error covariance matrix, ensure the stability and adaptability of the positioning system through dynamic feedback mechanism, and finally output data to trust weight calculation module to update trust weight and assist navigation control and behavior decision.

[0104] 5. Security output and audit layer

[0105] The security output and audit layer is the end output interface of the positioning system, and has the functions of log auditing and real-time response, thereby enhancing the recovery ability and accountability of the system in the face of attacks or failures. The layer includes a positioning and trajectory encryption storage module (optional), a navigation / control module, and a security response strategy module.

[0106] 1) The positioning and trajectory encryption storage module (optional) is data-sourced from the fusion positioning result output module, and stores key positioning results in an encrypted manner, for later backtracking auditing.

[0107] 2) The navigation / control module is data-sourced from the fusion positioning result output module, and is directly connected to downstream control units such as the flight control system and the automatic driving module.

[0108] 3) The security response strategy module is data-sourced from the abnormal log recording module, and if persistent abnormalities or attack signs are detected in the data verification stage or the fusion stage, fault-tolerant mechanisms such as source weight reduction, backup sensor activation, task suspension or return strategy can be triggered to ensure the safe operation of the system.

[0109] The present application introduces a cryptography signature and randomization factor mechanism to multi-source sensor data streams; a trusted verification chain is embedded in the data receiving end, and each data packet is reviewed layer by layer; the fusion algorithm dynamically adjusts the participation degree based on trust weight, effectively resisting malicious sensors or data pollution; the system provides a closed-loop output and audit mechanism, and the positioning results are verifiable and traceable; it can be extended to edge computing or distributed collaborative positioning scenarios.

[0110] Embodiment 3

[0111] The present embodiment is basically the same as the structures of Embodiment 1 and Embodiment 2, except that in practical applications, the present embodiment takes the autonomous flight of a UAV as an example.

[0112] The multi-source perception data acquisition layer is deployed on a UAV platform, the GPS / GNSS module receives satellite signals in real time, the IMU module collects attitude data at a high frequency, the barometer obtains height information, and the visual SLAM module extracts environmental features through a camera.

[0113] In the trusted layer of the sensor end, the GPS coordinates are digitally signed after being appended with a timestamp and a randomization factor by the trusted signature module, and the IMU data is symmetrically encrypted by the trusted encryption module and spliced with an HMAC check.

[0114] The data is transmitted to the trusted center verification processing layer of the ground station, and is sequentially subjected to data scheduling, signature verification, timestamp checking, and structure integrity verification according to the data scheduling rules. The data that passes the verification is stored in the cache.

[0115] The trust-aware weighted fusion layer evaluates the trust weight according to historical data of each sensor, for example, a higher weight is given when the GPS signal is good, the weight is automatically reduced when the signal is disturbed and the weight of the SLAM data is increased, data is fused through an extended Kalman filter, and the real-time position and error covariance of the unmanned aerial vehicle are output.

[0116] The security output and audit layer stores the positioning result in an encrypted manner, simultaneously interfaces with the flight control system to realize navigation control, if continuous abnormal data is detected, the security response strategy module triggers the unmanned aerial vehicle homing or task suspension strategy.

[0117] The embodiment cooperates with each functional layer to realize reliable positioning and safe operation of the unmanned aerial vehicle in a complex environment.

[0118] Compared with the prior art, the technical scheme of the present application realizes data source authenticity, integrity and timeliness verification through a cryptography mechanism, improves the attack resistance of the system, the trusted verification chain ensures the safety of data in the transmission and processing process, avoids forgery and replay attacks, the trust weighted fusion mechanism dynamically adapts to changes in sensor reliability, guarantees positioning accuracy in a complex environment, the closed-loop audit mechanism makes the positioning trajectory traceable, meets the safety audit requirement, and the modular design supports the expansion application of the system in edge computing and distributed scenarios.

[0119] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. An autonomous flight reliable positioning system based on multi-source data, characterized in that, The method comprises the following steps: a multi-source perception data acquisition layer is used to deploy heterogeneous sensors to collect environmental information and motion state; a sensor-end trusted layer comprises a trusted signature module and a trusted encryption module, which are used to perform trusted verification and packaging on data output by the heterogeneous sensors; a trusted center verification processing layer is used to perform unified receiving, verification and scheduling processing on data output by the sensor-end trusted layer; a trust perception weighted fusion layer is used to perform weighted fusion on data passing the verification based on sensor trust degree, and output positioning result and error covariance; a secure output and audit layer is used to perform encrypted storage of the positioning result, interface with a navigation control module, and trigger a security response strategy when an anomaly is detected; the heterogeneous sensors comprise a GPS / GNSS positioning navigation module, an IMU inertial module, a barometer module and a visual / laser SLAM module; the GPS / GNSS positioning navigation module is used to receive satellite navigation signals to calculate position and speed information of the device; the IMU inertial module measures angular velocity and linear acceleration through a gyroscope and an accelerometer to obtain attitude change, speed and relative position estimation; the barometer module measures atmospheric pressure and converts it into relative height information; and the visual / laser SLAM module is used to realize positioning and map construction in an unknown environment; the trust perception weighted fusion layer comprises: a trust weight calculation module is used to dynamically evaluate the trust degree of the sensors based on historical reliability, error distribution and attack detection situation of the sensor data, and generate a weight coefficient; a trust weighted fusion module is used to input each source data into an extended Kalman filter or an unscented Kalman filter, and fuse the trust weight to realize optimal estimation of position and attitude; a fused positioning result output module outputs spatial position coordinates and a heading angle, and interfaces with a downstream control unit; a covariance output module is used to output an error covariance matrix, and update the trust weight in the trust weight calculation module through a dynamic feedback mechanism; each sensor module of the multi-source perception data acquisition layer is deployed on the same device or a distributed platform to realize collaborative collection of heterogeneous data.

2. The multi-source data based autonomous flight reliable positioning system of claim 1, wherein, the trusted signature module interacts with the GPS / GNSS positioning navigation module to digitally sign the positioning coordinates, and attach a timestamp and a randomization factor; the trusted signature module interacts with the visual / laser SLAM module to sign each frame of SLAM pose.

3. The multi-source data based autonomous flight reliable positioning system of claim 1, wherein, the trusted encryption module interacts with the IMU inertial module, uses symmetric encryption to encrypt acceleration and angular velocity information, and splices an HMAC integrity check; the trusted encryption module interacts with the barometer module, performs symmetric encryption on height measurement information, and splices an HMAC integrity check.

4. The multi-source data based autonomous flight reliable positioning system of claim 1, wherein, the trusted center verification processing layer comprises: a data receiving and scheduling module is used to perform unified receiving, time synchronization and scheduling management on data from the sensor-end trusted layer; a signature / HMAC verification module is used to perform public key signature verification or HMAC verification on incoming data packets to confirm source trustworthiness; a timestamp / randomization factor checking module is used to compare the timestamp and randomization factor of the data to prevent replay attacks; a structure integrity verification module for judging whether the data packet structure conforms to the trusted protocol specification to filter abnormal packets; a trusted data cache module for storing data that passes signature / HMAC verification, timestamp / randomization factor checking, and structure integrity verification for calling by the trust-aware weighted fusion layer; an abnormal log recording module for recording verification failure data for security auditing.

5. The multi-source data based autonomous flight reliable positioning system of claim 1, wherein, The security output and auditing layer includes: a positioning and trajectory encryption storage module for encrypting storage of key positioning results to realize later backtracking auditing; a navigation / control module directly connected to a downstream control unit of a flight control system; a security response strategy module for triggering a source weight reduction, a backup sensor activation, a task suspension, or a homeward strategy when detecting persistent abnormalities or attack signs.

6. The positioning method of the multi-source data based autonomous flight reliable positioning system according to claim 1, characterized in that, The method includes the following steps: S1, a data acquisition step: acquiring position speed, angular velocity / acceleration, relative height, environment feature, and pose data through a GPS / GNSS positioning navigation module, an IMU inertial module, a barometer module, and a visual / laser SLAM module of the multi-source perception data acquisition layer; S2, a data trusted packaging step: using a trusted signature module of the sensor-end trusted layer to digitally sign GPS / GNSS positioning coordinates and SLAM poses and attach timestamps and randomization factors, and using a trusted encryption module to symmetrically encrypt and splice IMU data and barometer height information and perform HMAC integrity checking; S3, a data verification processing step: a receiving and scheduling module of the trusted center verification processing layer uniformly receives and time synchronizes the packaged data, sequentially performs signature / HMAC verification, timestamp / randomization factor checking, and structure integrity verification according to data scheduling rules, stores the verified data in a trusted data cache module, and records abnormal logs for the unverified data; S4, a trust weighted fusion step: a trust weight calculation module of the trust-aware weighted fusion layer generates trust weights based on sensor historical reliability, error distribution, and attack detection, and a trust weighted fusion module inputs the trusted data into a Kalman filter and fuses the trust weights, outputs positioning results and error covariance, and a covariance output module feeds back the error covariance to the trust weight calculation module to update the weights; S5, a security output and response step: the security output and auditing layer transmits the positioning results to the navigation / control module, and optionally performs encryption storage through the positioning and trajectory encryption storage module, and if an abnormality or attack is detected, the security response strategy module triggers a preset fault tolerance mechanism.

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