Unmanned aerial vehicle parking evaluation method and system based on internal and external measurement data fusion

Abstract

The invention belongs to the technical field of electrical data processing, and particularly relates to an unmanned aerial vehicle parking evaluation method and system based on internal and external measurement data fusion, and the method comprises the steps: obtaining measurement and control chain data, guide chain data and external photoelectric measurement data of an aircraft in a process of parking a mobile platform; the position information of the aircraft in the measurement and control chain data, the guide chain data and the external photoelectric measurement data is fused and displayed on an interface containing an ideal glide path; the position information difference value of the measurement and control chain data and the guide chain data relative to the external photoelectric measurement data is obtained, and the position information difference value of the external photoelectric measurement data relative to the ideal lower slide way is obtained. According to the method, a heterogeneous data multi-source fusion method is adopted, space-time synchronization logic is designed, photoelectric external measurement data, measurement and control link data and radar guide data are compared and evaluated, and the test flight efficiency and the test flight safety are greatly improved.

Description

Technical Field

[0001] The present application belongs to the field of electrical data processing technology, and in particular relates to a method and system for evaluating the landing of an unmanned aerial vehicle based on the fusion of internal and external measurement data. Background Art

[0002] The attitude control and trajectory keeping capabilities of aircraft are crucial to the success rate of aircraft landing on a mobile platform, so how to evaluate the attitude control and trajectory keeping of aircraft has become a top priority. Most existing methods use the aircraft's recorded data to compare with the guidance data after the fact to evaluate the system itself, lacking a more intuitive third-party evaluation method that can monitor in real time. Summary of the invention

[0003] In order to solve the above problems, this application provides a UAV landing assessment method based on the fusion of internal and external measurement data, including:

[0004] Step S1: Acquire the measurement and control chain data, guidance chain data, and external photoelectric measurement data of the aircraft during the landing on the mobile platform;

[0005] Step S2: The position information of the aircraft in the measurement and control chain data, the guidance chain data, and the external photoelectric measurement data is integrated and displayed on an interface including an ideal glide slope;

[0006] Step S3: Make a position information difference between the measurement and control chain data and the guidance chain data relative to the external photoelectric measurement data, and make a position information difference between the external photoelectric measurement data and the ideal glide path.

[0007] Step S4: Obtain the deviation of the measurement and control chain data and the guidance chain data relative to the external measurement data, as well as the deviation of the glide path during the landing process of the aircraft from the ideal glide path.

[0008] Preferably, before step S2, the measurement and control chain data, the guidance chain data, and the external photoelectric measurement data are subjected to data preprocessing, code conversion, and coordinate conversion.

[0009] Preferably, the position information of the aircraft in the measurement and control chain data, guidance chain data, and external photoelectric measurement data in step S2 is uniformly established in the mobile platform coordinate system.

[0010] Preferably, the measurement and control chain data includes aircraft position information data after differential fusion of the aircraft body inertial navigation and GPS.

[0011] Preferably, the guidance chain data includes aircraft position information data measured by ground guidance radar.

[0012] Preferably, the external optoelectronic measurement data includes data obtained by performing dual-station rendezvous external measurement using a high-precision optoelectronic tracking and measurement system.

[0013] Preferably, in step S4, a difference diagram between the external photoelectric measurement data and the ideal glide path is drawn with the ideal glide path as the reference axis; and a difference diagram between the measurement and control chain data and the guidance chain data relative to the external measurement data is drawn with the external photoelectric measurement data as the reference.

[0014] A drone landing assessment system based on internal and external measurement data fusion, using the drone landing assessment method based on internal and external measurement data fusion, comprising:

[0015] Data input module: used to obtain the measurement and control chain data, guidance chain data, and external photoelectric measurement data of the aircraft during the landing on the mobile platform;

[0016] Data merging module: used to fuse the position information of the aircraft in the measurement and control chain data, guidance chain data, and external optoelectronic measurement data and display them on an interface containing the ideal glide slope;

[0017] Data calculation module: used to make the position information difference of the measurement and control chain data and the guidance chain data relative to the external photoelectric measurement data, and to make the position information difference of the external photoelectric measurement data relative to the ideal glide path.

[0018] Data collation module: obtains the deviation of the measurement and control chain data and the guidance chain data relative to the external measurement data, as well as the deviation of the descent trajectory of the aircraft during landing from the ideal descent path.

[0019] Preferably, the data sorting module includes a picture generating unit for making a difference graph between the external photoelectric measurement data and the ideal glide path with the ideal glide path as the reference axis; and making a difference graph between the measurement and control chain data and the guidance chain data relative to the external measurement data with the external photoelectric measurement data as the reference.

[0020] The advantages of this application include: adopting a method of multi-source fusion of heterogeneous data and designing spatiotemporal synchronization logic to compare and evaluate optoelectronic external measurement data with measurement and control link data and radar guidance data, greatly improving flight test efficiency and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of a drone landing assessment method based on the fusion of internal and external measurement data in a preferred implementation mode of the present application. DETAILED DESCRIPTION

[0022] In order to make the technical solution and advantages of the present application clearer, the technical solution of the present application will be further described in detail in detail and in detail in conjunction with the accompanying drawings. It can be understood that the specific embodiments described here are only partial embodiments of the present application, which are only used to explain the present application, not to limit the present application. It should be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, and other related parts can refer to the general design. In the absence of conflict, the embodiments in the present application and the technical features in the embodiments can be combined with each other to obtain new embodiments.

[0023] like Figure 1 As shown, the present application provides a method for evaluating the landing of a UAV based on the fusion of internal and external measurement data, including:

[0024] Step S1: Acquire the measurement and control chain data, guidance chain data, and external photoelectric measurement data of the aircraft during the landing on the mobile platform; the measurement and control chain data includes the aircraft position information data after the differential fusion of the aircraft body inertial navigation and GPS; the guidance chain data includes the aircraft position information data measured by the ground guidance radar. The external photoelectric measurement data includes the data obtained by using a high-precision photoelectric tracking and measurement system to perform dual-station rendezvous external measurement, and the external photoelectric measurement is used as a third-party measurement method (dynamically verified, its measurement accuracy is better than 0.1m within the high-precision measurement range).

[0025] Step S2: Preprocess the measurement and control chain data, guide chain data, and external photoelectric measurement data, perform code conversion, and coordinate conversion. The position information of the aircraft in the measurement and control chain data, guide chain data, and external photoelectric measurement data is integrated and displayed on an interface containing an ideal glide path. The position information of the aircraft in the measurement and control chain data, guide chain data, and external photoelectric measurement data is uniformly established in the mobile platform coordinate system.

[0026] Step S3: Make a position information difference between the measurement and control chain data and the guidance chain data relative to the external photoelectric measurement data, and make a position information difference between the external photoelectric measurement data and the ideal glide path.

[0027] Step S4: Obtain the deviation of the measurement and control chain data and the guidance chain data relative to the external measurement data, as well as the deviation of the glide path during the landing process of the aircraft from the ideal glide path.

[0028] In step S4, taking the ideal glide path as the reference axis, a difference diagram between the external photoelectric measurement data and the ideal glide path is drawn; taking the external photoelectric measurement data as the reference, a difference diagram between the measurement and control chain data and the guidance chain data relative to the external measurement data is drawn.

[0029] The above method is a unified space method and also includes a unified time method: the same method can be used to perform difference analysis on the location information of the collected multi-source data based on time.

[0030] The small sample estimation method is used to evaluate the landing point accuracy.

[0031] A drone landing assessment system based on internal and external measurement data fusion, using the drone landing assessment method based on internal and external measurement data fusion, comprising:

[0032] Data input module: used to obtain the measurement and control chain data, guidance chain data, and external photoelectric measurement data of the aircraft during the landing on the mobile platform;

[0033] Data merging module: used to fuse the position information of the aircraft in the measurement and control chain data, guidance chain data, and external optoelectronic measurement data and display them on an interface containing the ideal glide slope;

[0034] Data calculation module: used to make the position information difference of the measurement and control chain data and the guidance chain data relative to the external photoelectric measurement data, and to make the position information difference of the external photoelectric measurement data relative to the ideal glide path.

[0035] Data collation module: obtains the deviation of the measurement and control chain data and the guidance chain data relative to the external measurement data, as well as the deviation of the descent trajectory of the aircraft during landing from the ideal descent path.

[0036] Preferably, the data sorting module includes a picture generating unit for making a difference graph between the external photoelectric measurement data and the ideal glide path with the ideal glide path as the reference axis; and making a difference graph between the measurement and control chain data and the guidance chain data relative to the external measurement data with the external photoelectric measurement data as the reference.

[0037] The advantages of this application include: adopting a method of multi-source fusion of heterogeneous data and designing spatiotemporal synchronization logic to compare and evaluate optoelectronic external measurement data with measurement and control link data and radar guidance data, greatly improving flight test efficiency and safety.

[0038] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for evaluating the landing of a UAV based on the fusion of internal and external measurement data, characterized in that: include: Step S1: Acquire the measurement and control chain data, guidance chain data, and external photoelectric measurement data of the aircraft during the landing on the mobile platform; Step S2: The position information of the aircraft in the measurement and control chain data, the guidance chain data, and the external photoelectric measurement data is integrated and displayed on an interface including an ideal glide slope; Step S3: Make a position information difference between the measurement and control chain data and the guidance chain data relative to the external photoelectric measurement data, and make a position information difference between the external photoelectric measurement data and the ideal glide path. Step S4: Obtain the deviation of the measurement and control chain data and the guidance chain data relative to the external measurement data, as well as the deviation of the glide path during the landing process of the aircraft from the ideal glide path.

2. The method for evaluating the landing of a UAV based on the fusion of internal and external measurement data according to claim 1, characterized in that: Before step S2, the measurement and control chain data, the guidance chain data, and the external photoelectric measurement data are subjected to data preprocessing, code conversion, and coordinate conversion.

3. The method for evaluating the landing of a UAV based on the fusion of internal and external measurement data according to claim 1, characterized in that: The position information of the aircraft in the measurement and control chain data, guidance chain data, and external optoelectronic measurement data in step S2 is uniformly established in the mobile platform coordinate system.

4. The method for evaluating the landing of a UAV based on the fusion of internal and external measurement data according to claim 1, characterized in that: The measurement and control chain data includes the aircraft position information data after differential fusion of the aircraft body inertial navigation and GPS.

5. The method for evaluating the landing of a UAV based on the fusion of internal and external measurement data according to claim 1, characterized in that: The guidance chain data includes aircraft position information data measured by ground guidance radar.

6. The method for evaluating the landing of a UAV based on the fusion of internal and external measurement data according to claim 1, characterized in that: The external photoelectric measurement data includes data obtained by performing dual-station rendezvous external measurement using a high-precision photoelectric tracking and measurement system.

7. The method for evaluating the landing of a UAV based on the fusion of internal and external measurement data according to claim 1, characterized in that: In step S4, taking the ideal glide path as the reference axis, a difference diagram between the external photoelectric measurement data and the ideal glide path is drawn; taking the external photoelectric measurement data as the reference, a difference diagram between the measurement and control chain data and the guidance chain data relative to the external measurement data is drawn.

8. A drone landing assessment system based on internal and external measurement data fusion, using the drone landing assessment method based on internal and external measurement data fusion as described in any one of claims 1 to 7, characterized in that: include: Data input module: used to obtain the measurement and control chain data, guidance chain data, and external photoelectric measurement data of the aircraft during the landing on the mobile platform; Data merging module: used to fuse the position information of the aircraft in the measurement and control chain data, guidance chain data, and external optoelectronic measurement data and display them on an interface containing the ideal glide slope; Data calculation module: used to make the position information difference of the measurement and control chain data and the guidance chain data relative to the external photoelectric measurement data, and to make the position information difference of the external photoelectric measurement data relative to the ideal glide path. Data collation module: obtains the deviation of the measurement and control chain data and the guidance chain data relative to the external measurement data, as well as the deviation of the descent trajectory of the aircraft during landing from the ideal descent path.

9. The drone landing assessment system based on internal and external measurement data fusion as claimed in claim 7, characterized in that: The data sorting module includes a picture generating unit, which is used to make a difference map between the external photoelectric measurement data and the ideal glide path with the ideal glide path as the reference axis; and to make a difference map between the measurement and control chain data and the guidance chain data relative to the external measurement data with the external photoelectric measurement data as the reference.

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