A data interpolation prediction method based on a multilateration system

Abstract

The application discloses a data interpolation prediction method based on a multilateration system, acquires different target message data, and interpolates one kind of message data to another kind of message data, so that asynchronization between different message data is reduced, and the problems of large positioning precision analysis error and complex method in the existing multilateration system are solved.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more specifically to a data interpolation prediction method based on a multi-point positioning system. Background Technology

[0002] Multipoint positioning systems have been identified by the International Civil Aviation Organization (ICAO) as a major direction for future surveillance technology development, and leading aviation powers in Europe and the United States are accelerating the application of multipoint positioning technology. Multipoint positioning technology primarily utilizes multiple receiving stations to receive the same response signal transmitted by a target, and achieves target location by calculating the Time Difference of Arrival (TDOA) of the signals received by each station. Compared with traditional radar equipment, multipoint positioning systems are not only compatible with secondary radar and ADS-B downlink data transmission links, but also offer advantages such as high positioning accuracy, fast update rate, simple system structure, low deployment and maintenance costs, wide coverage, and less susceptibility to the geographical environment of the deployment sites.

[0003] Taking wide-area multi-point positioning (WAN) as an example, to achieve better monitoring performance, WAN systems integrate existing ADS-B technologies and install at least four base stations to receive signals, perform decoding calculations, and record the current signal time information. To verify the accuracy of location positioning in a multi-point positioning system, design accuracy error calculation is a crucial method in the development of air traffic control equipment. In the civil aviation WAN system, CAT020 wide-area data and ADS-B data are output to a specified file through the same data interface. The data recorded in the file is parsed, and finally, latitude and longitude coordinates, time, and other data items are extracted for data analysis.

[0004] However, in existing multi-point positioning systems, the data outputs of CAT020 and CAT021 are not synchronized. If the positioning accuracy is calculated directly, the position difference between the two sets of data is relatively large. Summary of the Invention

[0005] The purpose of this application is to provide a data interpolation prediction method based on a multi-point positioning system, which solves the problems existing in the prior art.

[0006] This invention is achieved through the following technical solution:

[0007] A data interpolation prediction method based on a multi-point positioning system includes:

[0008] Receive message data sent by the aircraft and filter the message data to obtain first target message data and second target message data;

[0009] The first target message data is stored in the first container, and the second target message data is stored in the second container;

[0010] Based on the first target message data in the first container, determine the second target message data located between two adjacent first target message data in the second container;

[0011] Based on the determined second target message data, interpolation data is obtained and verified. The verified interpolation data is then inserted into the first container to complete the data interpolation of the multi-point positioning system.

[0012] In one possible implementation, filtering the message data includes:

[0013] Determine whether the format corresponding to the message data is the same as the format corresponding to the first target message data and the second target message data. If so, filter out the corresponding message data; otherwise, obtain the preliminary filtered message data.

[0014] Determine whether the data source corresponding to the preliminary filtered message data is a pre-set data source. If so, obtain the first target message data and the second target message data; otherwise, filter out the preliminary filtered message data.

[0015] In one possible implementation, storing the first target message data in a first container includes:

[0016] Using the S-mode address as the key, a first node corresponding to the first target message data is created in the first container. The time information and latitude and longitude information corresponding to the first target message data are used as the first node information, and the first node information is stored in the corresponding first node in the first container. The same S-mode address indicates message data corresponding to the same track; different S-mode addresses indicate message data corresponding to different tracks. Message data corresponding to the same track are stored with the same S-mode address, and the S-mode address corresponds one-to-one with the map container.

[0017] In one possible implementation, storing the second target message data in a second container includes:

[0018] A second node corresponding to the second target message data is created in the second container using the S-mode address as the key value. The time information and latitude and longitude information corresponding to the second target message data are used as the second node information, and the second node information is stored in the corresponding second node in the second container. The same S-mode address indicates message data corresponding to the same track. The different S-mode addresses indicate message data corresponding to different tracks. Message data corresponding to the same track are stored with the same S-mode address, and the S-mode address corresponds one-to-one with the map container.

[0019] In one possible implementation, determining second target message data located between two adjacent first target message data in the second container based on the first target message data in the first container includes:

[0020] Retrieve node data based on S-mode addresses from the first container to obtain the first node data;

[0021] In the second container, check if there is node data with the same S-mode address as the first node data. If so, retrieve the node data to obtain the second node data; otherwise, end the data interpolation process.

[0022] Determine whether there is second node data between any two adjacent first node data. If so, obtain the second target message data located between the two adjacent first target message data. Otherwise, end the data interpolation process.

[0023] In one possible implementation, based on the determined second target message data, interpolated data is obtained, and the interpolated data is verified. The verified interpolated data is then inserted into a first container, including:

[0024] Based on the determined second target message data and the two first target message data adjacent to the second target message data, obtain the prediction time information and prediction latitude and longitude information corresponding to the interpolation data;

[0025] Based on the prediction time information and prediction latitude and longitude information corresponding to the interpolated data, the accuracy error corresponding to the interpolated data is obtained.

[0026] Verify whether the accuracy error is greater than a preset threshold. If so, discard the corresponding interpolated data; otherwise, determine that the corresponding interpolated data has passed the verification and insert the verified interpolated data into the first container.

[0027] In one possible implementation, the prediction time information corresponding to the interpolated data is:

[0028] T s =T i +Δs

[0029] Δs=(T i' -T i ) / Δt

[0030] Δt=T j -T i

[0031] Among them, T s T represents the predicted time information. iThis indicates the time preceding one of the two first target message data adjacent to the second target message data; Δs represents the interpolation time length; T i' T represents the time corresponding to the determined second target message data. j Δt represents the time interval between two adjacent first target message data, which is the second target message data.

[0032] In one possible implementation, the predicted latitude and longitude information corresponding to the interpolated data is:

[0033] xA i' =xA i +(xA j -xA i )*Δs

[0034] yA i' =yA i +(yA j -yA i )*Δs

[0035] Among them, xA i' This represents the east coordinate corresponding to the interpolated data, yA i' This represents the north coordinates corresponding to the interpolated data, xA i Representing time T i The corresponding east coordinate, yA i Representing time T i The corresponding north coordinates, xA j Representing time T j The corresponding east coordinate, yA j Representing time T j The corresponding north coordinates.

[0036] In one possible implementation, the precision error corresponding to the interpolated data is:

[0037]

[0038] Where d represents the precision error, xW i' This represents the east coordinates corresponding to the determined second target message data, yW i' This indicates the north coordinates corresponding to the determined second target message data.

[0039] In one possible implementation, inserting the validated interpolated data into the first container includes:

[0040] Based on the prediction time information corresponding to the interpolation data of the validation pass, at time T i With time T jCreate new nodes between them and use the predicted latitude and longitude information as the node information corresponding to the new nodes, thereby inserting the verified interpolation data into the first container.

[0041] This application provides a data interpolation prediction method based on a multi-point positioning system, which acquires different target message data and interpolates one message data to another, reducing the asynchrony between different message data, thereby solving the problems of large positioning accuracy analysis errors and complex methods in existing multi-point positioning systems. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0043] Figure 1 A flowchart illustrating a data interpolation prediction method based on a multi-point positioning system, provided in an embodiment of this application.

[0044] Figure 2 This is a schematic diagram of the structure of a data interpolation prediction device based on a multi-point positioning system provided in an embodiment of this application.

[0045] Figure 3 This is a schematic diagram of the structure of a data interpolation prediction device based on a multi-point positioning system, provided in an embodiment of this application.

[0046] The attached diagram shows the markings and corresponding component names:

[0047] 21-Data filtering module, 22-Data storage module, 23-Data determination module, 24-Data verification module, 31-Memory, 32-Processor, 33-Bus. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0049] Example 1

[0050] like Figure 1 As shown in the figure, this application provides a data interpolation prediction method based on a multi-point positioning system, including:

[0051] S11. Receive the message data sent by the aircraft, and filter the message data to obtain the first target message data and the second target message data.

[0052] After the receiving station receives the message data sent by the aircraft, there may be various kinds of message data. Therefore, the message data can be converted into a String type for storage first. Then, the format of the message data can be judged, and only the required message data can be retained, that is, message data other than the corresponding formats of the first target message data and the second target message data can be filtered out.

[0053] S12. Store the first target message data in the first container and store the second target message data in the second container.

[0054] When the first target message data is stored in the first container and the second target message data is stored in the second container, the message data can be stored in chronological order to build a track-based data link.

[0055] S13. Based on the first target message data in the first container, determine the second target message data located between two adjacent first target message data in the second container.

[0056] It is worth noting that, once the second target message data is determined, interpolation prediction can be performed between the first message data based on this second target message data. Alternatively, the first target message data located between two adjacent second target message data can be determined, and interpolation prediction can be performed between the second message data based on the first target message data.

[0057] S14. Based on the determined second target message data, obtain the interpolated data, verify the interpolated data, insert the verified interpolated data into the first container, and complete the data interpolation of the multi-point positioning system.

[0058] In one possible implementation, filtering the message data includes:

[0059] Determine whether the format of the message data is the same as that of the first target message data and the second target message data. If so, filter out the corresponding message data; otherwise, obtain the preliminary filtered message data.

[0060] Determine whether the data source corresponding to the preliminary filtered message data is a pre-set data source. If so, obtain the first target message data and the second target message data; otherwise, filter out the preliminary filtered message data.

[0061] For example, the first target message data can be CAT020 data (i.e., WAM data), and the second target message data can be CAT021 data (i.e., ADS-B data). During filtering, non-CAT020 and non-CAT021 data can be filtered out to obtain the target data. It is worth noting that the first and second target message data can also be other message data containing time and latitude / longitude information.

[0062] It is worth noting that the interpolation method described in this application can be applied to other instances of data processing comparison, that is, the interpolation method can be used for comparisons with time errors.

[0063] In one possible implementation, storing the first target message data in a first container includes:

[0064] Using the S-mode address as the key, a first node corresponding to the first target message data is created in the first container. The time information and latitude and longitude information corresponding to the first target message data are used as the first node information, and the first node information is stored in the corresponding first node in the first container. The same S-mode address indicates message data corresponding to the same track; different S-mode addresses indicate message data corresponding to different tracks. Message data corresponding to the same track are stored with the same S-mode address, and the S-mode address corresponds one-to-one with the map container.

[0065] After acquiring the first target message data (e.g., CAT020 or CAT021 data; by extracting time and latitude / longitude data from different target reports, it can be used for accuracy analysis), the first target message data can be stored. Within each message type, it is categorized and stored using the Mode S address (the Mode S address refers to the address code corresponding to an aircraft equipped with a Mode S transponder; it is a unique identifier used by the aircraft to communicate with the ground station and to determine flight routes and location information) as the key value. Clustering of the same message is achieved through continuous insertion and retrieval of the corresponding key value in the map container. It is worth noting that the storage of the second target message data is similar to that of the first target message, and will not be elaborated upon here.

[0066] In one possible implementation, storing the second target message data in a second container includes:

[0067] Using the S-mode address as the key, a second node corresponding to the second target message data is created in the second container. The time information and latitude and longitude information corresponding to the second target message data are used as the second node information, and the second node information is stored in the corresponding second node in the second container. The same S-mode address indicates message data corresponding to the same track; different S-mode addresses indicate message data corresponding to different tracks. Message data corresponding to the same track are stored with the same S-mode address, and the S-mode address corresponds one-to-one with the map container.

[0068] The target message data is inserted into the map container as a node, thereby caching the target message data in the map container. Using the S-mode address as an index, the track corresponding to the S-mode address can be extracted.

[0069] By storing high-precision time and latitude / longitude information using the S-mode index, a flight path can be saved, as both CAT020 and CAT021 target data contain this information. Finally, by comparing the two sets of data and indexing the S-mode address, identical flight paths can be found in both sets. For a given flight path, different messages may exhibit relative errors; interpolation and predictive analysis are then performed based on time.

[0070] In one possible implementation, determining second target message data located between two adjacent first target message data in a second container based on first target message data in a first container includes:

[0071] The node data based on the S-mode address is retrieved from the first container to obtain the first node data.

[0072] In the second container, check if there is node data with the same S-mode address as the first node data. If so, retrieve the node data to obtain the second node data; otherwise, end the data interpolation process.

[0073] Determine whether there is second node data between any two adjacent first node data. If so, obtain the second target message data located between the two adjacent first target message data. Otherwise, end the data interpolation process.

[0074] In one possible implementation, based on the determined second target message data, interpolated data is obtained, and the interpolated data is verified. The verified interpolated data is then inserted into a first container, including:

[0075] Based on the determined second target message data and the two first target message data adjacent to the second target message data, obtain the prediction time information and prediction latitude and longitude information corresponding to the interpolation data.

[0076] Based on the prediction time information and prediction latitude and longitude information corresponding to the interpolated data, the accuracy error corresponding to the interpolated data is obtained.

[0077] Verify whether the accuracy error is greater than a preset threshold. If so, discard the corresponding interpolated data; otherwise, determine that the corresponding interpolated data has passed the verification and insert the verified interpolated data into the first container.

[0078] Optionally, the interpolation prediction can be:

[0079] (1) Based on the CAT020 data, first retrieve a map container of CAT020 data based on the S mode address according to the storage order.

[0080] (2) Search for CAT021 data with the same S mode address. If it exists, proceed to step (3). If it does not exist, return to step (1).

[0081] (3) Determine whether the map container corresponding to the CAT020 data is empty. If it is, return to step (1); otherwise, proceed to step (4).

[0082] (4) Determine whether the map container corresponding to the CAT021 data is empty. If it is, return to step (1); otherwise, proceed to step (5).

[0083] (5) If there exists a CAT021 data time that is between the times of two adjacent CAT020 data, and the time difference between the two adjacent CAT020 data is within a certain time range, then take the CAT021 data, and use the two adjacent CAT020 data and the CAT021 data (both types of data include time information and latitude and longitude information) to predict the CAT020 data corresponding to the current time point of the CAT021 data.

[0084] (6) Obtain the accuracy error between the latitude and longitude coordinates of the extracted CAT021 data and the predicted CAT020 data, and filter out the data based on the accuracy error.

[0085] (7) Traverse all CAT020 data and CAT021 data to complete the data interpolation prediction.

[0086] In one possible implementation, the prediction time information corresponding to the interpolated data is:

[0087] T s =T i +Δs

[0088] Δs=(T i' -T i ) / Δt

[0089] Δt=T j -T i

[0090] Among them, T s T represents the predicted time information. i This indicates the time preceding one of the two first target message data adjacent to the second target message data; Δs represents the interpolation time length; T i' T represents the time corresponding to the determined second target message data. j Δt represents the time interval between two adjacent first target message data, which is the second target message data.

[0091] In one possible implementation, the predicted latitude and longitude information corresponding to the interpolated data is:

[0092] xA i' =xA i +(xA j -xA i )*Δs

[0093] yA i' =yA i +(yA j -yA i )*Δs

[0094] Among them, xA i' This represents the east coordinate corresponding to the interpolated data, yA i' This represents the north coordinates corresponding to the interpolated data, xA i Representing time T i The corresponding east coordinate, yA i Representing time T i The corresponding north coordinates, xA j Representing time T j The corresponding east coordinate, yA j Representing time T j The corresponding north coordinates.

[0095] In one possible implementation, the precision error corresponding to the interpolated data is:

[0096]

[0097] Where d represents the precision error, xW i' This represents the east coordinates corresponding to the determined second target message data, yW i' This indicates the north coordinates corresponding to the determined second target message data.

[0098] In one possible implementation, inserting the validated interpolated data into the first container includes:

[0099] Based on the prediction time information corresponding to the interpolation data of the validation pass, at time T i With time T j Create new nodes between them and use the predicted latitude and longitude information as the node information corresponding to the new nodes, thereby inserting the verified interpolation data into the first container.

[0100] This application provides a data interpolation prediction method based on a multi-point positioning system, which acquires different target message data and interpolates one message data to another, reducing the asynchrony between different message data, thereby solving the problems of large positioning accuracy analysis errors and complex methods in existing multi-point positioning systems.

[0101] This application offers smaller positioning accuracy errors, higher reliability and accuracy, providing strong support for the reliable operation and flight calibration of equipment in subsequent multi-point positioning systems. It can be independently developed, maintained and operated, and can be integrated into the existing monitoring software of the multi-point positioning system, providing relevant data interfaces for later use as real-time message display software. It achieves multiple objectives such as low maintenance costs, quick and simple usage, user-friendly human-computer interaction, practicality for engineering projects, and high portability.

[0102] Example 2

[0103] like Figure 2 As shown, this application provides a data interpolation prediction device based on a multi-point positioning system, including a data filtering module 21, a data storage module 22, a data determination module 23, and a data verification module 24.

[0104] The data filtering module 21 is used to receive the message data sent by the aircraft and filter the message data to obtain the first target message data and the second target message data.

[0105] The data storage module 22 is used to store the first target message data in the first container and the second target message data in the second container;

[0106] The data determination module 23 is used to determine, based on the first target message data in the first container, the second target message data located between two adjacent first target message data in the second container;

[0107] The data verification module 24 is used to obtain interpolated data based on the determined second target message data, verify the interpolated data, insert the verified interpolated data into the first container, and complete the data interpolation of the multi-point positioning system.

[0108] The data interpolation prediction device based on a multi-point positioning system provided in this embodiment can execute the technical solution described in claim 1. Its principle and beneficial effects are similar and will not be repeated here.

[0109] Example 3

[0110] like Figure 3 As shown, this embodiment provides a data interpolation prediction device based on a multi-point positioning system, including a memory 31 and a processor 32, which are interconnected via a bus 33.

[0111] Memory 31 stores computer-executed instructions.

[0112] The processor 32 executes computer execution instructions stored in the memory, causing the processor to perform a data interpolation prediction method based on a multi-point positioning system as described in Embodiment 1.

[0113] For specific examples, memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory, etc.; specifically, processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). Furthermore, the processor may include a main processor and coprocessors. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.

[0114] In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. For example, the processor may not be limited to microprocessors of the STM32F105 series, reduced instruction set computer (RISC) microprocessors, x86 architecture processors, or processors with integrated neural network processing units (NPUs). The transceiver may be, but is not limited to, a Wi-Fi transceiver, a Bluetooth transceiver, a General Packet Radio Service (GPRS) transceiver, a ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard) transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. Furthermore, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0115] Example 4

[0116] This embodiment provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement a data interpolation prediction method based on a multi-point positioning system as described in Embodiment 1.

[0117] Example 5

[0118] This application embodiment may also provide a computer program product, including a computer program that, when executed by a processor, implements a data interpolation prediction method based on a multi-point positioning system as described in Embodiment 1.

[0119] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A data interpolation prediction method based on a multi-point positioning system, characterized in that, include: Receive message data sent by the aircraft and filter the message data to obtain first target message data and second target message data; Using the S-mode address as the key, create a first node corresponding to the first target packet data in the first container, and create a second node corresponding to the second target packet data in the second container; The time information and latitude and longitude information corresponding to the first target message data and the second target message data are respectively used as the first node information and the second node information. The first node information is stored in the corresponding first node in the first container, and the second node information is stored in the corresponding second node in the second container. The same S-mode address indicates that the message data corresponds to the same track; The different S-mode addresses indicate message data corresponding to different tracks; message data corresponding to the same track are stored using the same S-mode address, and the S-mode address corresponds one-to-one with the map container. Take out the node data based on the S-mode address from the first container to obtain the first node data; check in the second container whether there is node data with the same S-mode address as the first node data. If so, take out the node data to obtain the second node data; otherwise, end the data interpolation process. Determine whether there is second node data between any two adjacent first node data. If so, obtain the second target message data located between the two adjacent first target message data. Otherwise, end the data interpolation process. Based on the determined second target message data, interpolation data is obtained and verified. The verified interpolation data is then inserted into the first container to complete the data interpolation of the multi-point positioning system.

2. The data interpolation prediction method based on a multi-point positioning system according to claim 1, characterized in that, Filtering the message data includes: Determine whether the format corresponding to the message data is the same as the format corresponding to the first target message data and the second target message data. If so, filter out the corresponding message data; otherwise, obtain the preliminary filtered message data. Determine whether the data source corresponding to the preliminary filtered message data is a pre-set data source. If so, obtain the first target message data and the second target message data; otherwise, filter out the preliminary filtered message data.

3. The data interpolation prediction method based on a multi-point positioning system according to claim 1, characterized in that, Based on the determined second target message data, interpolated data is obtained and verified. The verified interpolated data is then inserted into the first container, including: Based on the determined second target message data and the two first target message data adjacent to the second target message data, obtain the prediction time information and prediction latitude and longitude information corresponding to the interpolation data; Based on the prediction time information and prediction latitude and longitude information corresponding to the interpolated data, the accuracy error corresponding to the interpolated data is obtained. Verify whether the accuracy error is greater than a preset threshold. If so, discard the corresponding interpolated data; otherwise, determine that the corresponding interpolated data has passed the verification and insert the verified interpolated data into the first container.

4. The data interpolation prediction method based on a multi-point positioning system according to claim 3, characterized in that, The prediction time information corresponding to the interpolated data is as follows: ； ； ； in, Indicates the predicted time information. This indicates the earlier time among two adjacent first target message data. Indicates the interpolation time length. This indicates the time corresponding to the determined second target message data. This indicates the later time among the two first target message data adjacent to the second target message data. This indicates the time interval between two first target message data that are adjacent to the second target message data.

5. The data interpolation prediction method based on a multi-point positioning system according to claim 4, characterized in that, The predicted latitude and longitude information corresponding to the interpolated data is as follows: ； ； in, This indicates the east coordinates corresponding to the interpolated data. This represents the north coordinates corresponding to the interpolated data. Indicates time The corresponding east coordinates, Indicates time The corresponding north coordinates, Indicates time The corresponding east coordinates, Indicates time The corresponding north coordinates.

6. The data interpolation prediction method based on a multi-point positioning system according to claim 5, characterized in that, The precision error corresponding to the interpolated data is: ； Where d represents the precision error. This indicates the east coordinates corresponding to the determined second target message data. This indicates the north coordinates corresponding to the determined second target message data.

7. The data interpolation prediction method based on a multi-point positioning system according to claim 6, characterized in that, Insert the validated interpolated data into the first container, including: Based on the prediction time information corresponding to the interpolation data from the validation process, in time... With time Create new nodes between them and use the predicted latitude and longitude information as the node information corresponding to the new nodes, thereby inserting the verified interpolation data into the first container.

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