Low-altitude flight dynamic data compression conversion method and system

Abstract

The invention discloses a low-altitude flight dynamic data compression conversion method and system. The method comprises the following steps: obtaining structured data information based on a low-altitude flight dynamic data message; performing data item separation processing on the structured data information, and storing the structured data information to a static data pool and a dynamic data pool; performing data conversion processing on the data information stored in the static data pool and the dynamic data pool; storing a data conversion processing result; the data is separated and stored in the static data pool and the dynamic data pool, and data compression conversion in a non-coding form is carried out, so that repeated data is effectively eliminated, data storage resources and data transmission bandwidth are saved, and the data is easy to query and use by other operation management systems.

Description

Technical Field

[0001] The present invention relates to the technical field of data compression conversion, and in particular to a method and system for compressing and converting low-altitude flight dynamic data. Background Art

[0002] In traditional low-altitude data storage and transmission, data is mainly transferred in the form of messages and data tables, or transmitted using conventional compression methods. Conventional track compression mostly uses general data compression methods, such as LZMA and LZMA2. Because the business logic relationship of the data is not taken into account, although the compression rate is high, decompression takes a lot of time, and the compressed data is unreadable. When using this method, the computing load is high when facing large amounts of data storage and access. Traditional data compression methods cannot quickly access aircraft flight dynamics data through attributes, which is not conducive to the rapid growth of low-altitude operation management and the requirements for fast and efficient work of air traffic control. The existing general compression technology and original data table method for low-altitude flight dynamics data cannot meet the needs of both data compression and fast data access.

[0003] From a high-dimensional perspective, low-altitude data is a relatively stable Markov process, and the integrity requirements of flight dynamics data are lower than those of transport aviation. The positioning of flight dynamics data mostly comes from satellite positioning, and the positioning accuracy is relatively high. Low-altitude flight dynamics data uses spatiotemporal semantic relationships. Due to the particularity of low-altitude operations, the accuracy requirements are not high, so lossy compression is allowed to a certain extent. Based on this operating characteristic, compressed data that can both describe the flight status of low-altitude aircraft and achieve readability can be obtained.

[0004] The traditional low-altitude flight dynamic data compression and dumping solutions have the following obvious disadvantages:

[0005] 1. The traditional low-altitude flight dynamic data conversion method is relatively backward. It uses the computer's own database compression storage technology, which is heavily dependent on inherent hardware resources, prone to duplicate storage of data items, and wastes a lot of storage resources.

[0006] 2. The file compression conversion method has a certain compression ratio, but it does not take into account the spatiotemporal semantic characteristics of the data. When the external system wants to access the running data, it needs to decompress it, which wastes a lot of computing resources and increases time.

[0007] 3. Using other general data compression and conversion methods makes it difficult to obtain the spatiotemporal semantic relationship of the data, and cannot reflect the data quality. Abnormal data can only be found by sequential search, which increases the difficulty of data query and makes it difficult to meet data analysis needs.

[0008] In view of this, based on the needs of low-altitude operation management in my country, a low-altitude flight dynamic data compression and conversion method based on the spatiotemporal semantic information of low-altitude aircraft operation was invented, which provided technical means and tools for low-altitude aviation operation safety, flight management and data services, and realized the process and standardized management of the whole process operation data of low-altitude aviation operation equipment. Summary of the invention

[0009] In order to overcome the shortcomings of the prior art, the present invention provides a low-altitude flight dynamic data compression and conversion method and system, which separates the data and saves them in a static data pool and a dynamic data pool, and performs data compression conversion in a non-coded form, thereby effectively eliminating duplicate data, saving data storage resources and data transmission bandwidth, and facilitating the query and use of other operation management systems.

[0010] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0011] The first aspect of the present application provides a low-altitude flight dynamic data compression conversion method, comprising the following steps:

[0012] S101, acquiring structured data information based on low-altitude flight dynamic data messages;

[0013] S102, performing data item separation processing on the structured data information, and storing them in a static data pool and a dynamic data pool;

[0014] S103, performing data conversion processing on the data information stored in the static data pool and the dynamic data pool respectively;

[0015] S104: Store the data conversion processing result.

[0016] Furthermore, the structured data information includes card number, call sign, tail number, 24-bit address code, timestamp, status, location, and free text.

[0017] Furthermore, the data item separation processing is performed on the structured data information, and the storage is performed in the static data pool and the dynamic data pool, including the following steps:

[0018] Separate the structured data information into data items to obtain static data and dynamic data;

[0019] Store static data into a static data pool;

[0020] Store dynamic data into the dynamic data pool.

[0021] Furthermore, the card number, call sign, tail number, 24-bit address code, and status in the structured data information are classified as static data, and the card number, location, free text, and timestamp in the structured data information are classified as dynamic data.

[0022] Furthermore, the data information stored in the static data pool and the dynamic data pool are respectively converted into data, which includes the following steps:

[0023] Perform data conversion processing on the static data information stored in the static data pool by maintaining the sliding window comparison method of the benchmark table;

[0024] The dynamic data information stored in the dynamic data pool is converted and processed by the synchronous Euclidean distance method.

[0025] Furthermore, performing data conversion processing on the static data information stored in the static data pool by maintaining the sliding window comparison method of the reference table includes the following steps:

[0026] Obtain static data information from the static data pool and determine whether it is in the established benchmark table through card number matching;

[0027] If it is determined to be in the established reference table, the split static data will be compared with each item in the character-to-digital conversion basic table; if the data item changes, the changed data will be written to the persistent storage buffer and the reference table will be updated.

[0028] Furthermore, performing data conversion processing on the dynamic data information stored in the dynamic data pool by using the synchronous Euclidean distance method includes the following steps:

[0029] Get dynamic data information from the dynamic data pool and calculate the track distance between two points of low-altitude aircraft based on the card number;

[0030] The NUCp, NIC and NACp values ​​of the aircraft at all times are counted, the data is smoothed using B-spline, the motion data is extracted through the static determination method of positioning error, and the error threshold is set according to the positioning accuracy;

[0031] The track compression calculation is performed by using the DP algorithm of the vertical Euclidean distance to remove redundant points, and the track turning point is obtained. The first point is used as the reference, and the compressed point track is obtained by position offset.

[0032] The dynamic data is written into the persistent storage buffer in the format of card number, time offset, and position offset.

[0033] Furthermore, the data conversion processing result is stored in a manner of placing a static data persistent storage buffer in front and a dynamic data persistent storage buffer in the back, and then splicing the data.

[0034] The second aspect of the present application provides a low-altitude flight dynamic data compression and conversion system, comprising:

[0035] A data acquisition unit, used to acquire structured data information based on low-altitude flight dynamic data messages;

[0036] The first processing unit is used to separate the structured data information into data items and store them in a static data pool and a dynamic data pool;

[0037] The second processing unit is used to perform data conversion processing on the data information stored in the static data pool and the dynamic data pool respectively; wherein the second processing unit performs data conversion processing on the static data information stored in the static data pool based on the sliding window comparison method of the maintenance reference table; the second processing unit performs data conversion processing on the dynamic data information stored in the dynamic data pool based on the synchronous Euclidean distance method;

[0038] The data storage unit is used to store the data conversion processing results.

[0039] Furthermore, the second processing unit performs data conversion processing on the static data information stored in the static data pool based on the sliding window comparison method of the maintenance reference table, including the following steps:

[0040] Obtain static data information from the static data pool and determine whether it is in the established benchmark table through card number matching;

[0041] If it is determined to be in the established reference table, the split static data is compared with each item in the character-to-digital conversion basic table; if the data item changes, the changed data is written to the persistent storage buffer and the reference table is updated;

[0042] If it is determined that the card number is not in the established reference table, a static data reference table is established based on the card number and written into the static data persistent storage buffer, and the string data items therein are converted into digital form using the character encoding Base48.

[0043] Furthermore, the second processing unit performs data conversion processing on the dynamic data information stored in the dynamic data pool based on the synchronous Euclidean distance method, including the following steps:

[0044] Get dynamic data information from the dynamic data pool and calculate the track distance between two points of low-altitude aircraft based on the card number;

[0045] The NUCp, NIC and NACp values ​​of the aircraft at all times are counted, the data is smoothed using B-spline, the motion data is extracted through the static determination method of positioning error, and the error threshold is set according to the positioning accuracy;

[0046] The track compression calculation is performed by using the DP algorithm of the vertical Euclidean distance to remove redundant points, and the track turning point is obtained. The first point is used as the reference, and the compressed point track is obtained by position offset.

[0047] The dynamic data is written into the persistent storage buffer in the format of card number, time offset, and position offset.

[0048] The beneficial effects of the present application are as follows: by analyzing the spatiotemporal semantic relationship of low-altitude operation data, low-altitude flight dynamic data can be compressed and converted under error control, thereby achieving effective elimination of duplicate data and saving data storage resources and data transmission bandwidth. By means of non-coding data compression and conversion, the time index of the original data is converted into an attribute index. The compressed data is readable and does not need to be decompressed, making it easy for other operation management systems to query and use it. Rapid retrieval of general aviation operation data, through compression and conversion of general aviation operation data, and external systems accessing it through static data indexes, can quickly query the full-scenario operation status of the aircraft, improving the ease of data access.

[0049] It realizes the separation of static data and dynamic data of low-altitude flight dynamic data, processes static and dynamic data in different threads to improve processing performance, and uses card number as index to splice and store the processed data stored in static data and dynamic data persistent storage buffer.

[0050] The static data processing is realized by maintaining the sliding window comparison method of the reference table. The key node data of the track data is extracted by using the synchronous Euclidean distance method to realize dynamic data compression conversion.

[0051] Static data is realized by maintaining static reference tables and updating reference tables, and the changed data is written into the persistent storage buffer, thus reducing the storage space of static data; the general aviation operation dynamic data is eliminated by smoothing the abnormal points and stationary points of low-altitude operation in the queue, and the satellite navigation error is used to set the compression threshold, and the vertical Euclidean distance track compression algorithm is used to screen and extract data points of low-altitude data; the processed data is spliced ​​according to the card number, and it has the static data indexing capability, which provides an efficient compression and conversion data method for the low-altitude general aviation operation management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 It is a schematic diagram of the steps of a low-altitude flight dynamic data compression conversion method of the present invention;

[0054] Figure 2 It is the original trajectory diagram of the present invention;

[0055] Figure 3 It is the track after static and smooth processing of the present invention, and the local enlarged picture;

[0056] Figure 4 It is the track diagram after dynamic data compression conversion of the present invention. DETAILED DESCRIPTION

[0057] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0058] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0059] Embodiment 1:

[0060] A low-altitude flight dynamic data compression conversion method comprises the following steps:

[0061] S101, acquiring structured data information based on low-altitude flight dynamic data messages;

[0062] The structured data information can be obtained by decoding the original low-altitude flight dynamics data message and storing it in a data item queue. The structured data information includes the card number (recording the unique identification number of the device), call sign, tail number, 24-bit address code, timestamp, status, location, and free text. The flight dynamics report data bit of the low-altitude flight dynamics report data item can be used to determine whether the aircraft has landed or ended.

[0063] S102, performing data item separation processing on the structured data information, and storing them in a static data pool and a dynamic data pool;

[0064] The structured data information is decomposed, and the card number, call sign, tail number, 24-bit address code, and status in the structured data information are divided into static data, and the card number, position, free text, and timestamp in the structured data information are divided into dynamic data. The data can be arranged in ascending order according to the timestamp. It should be noted that since a low-altitude aircraft will only use the same airborne terminal when performing an operation, the static data is stored in the static data pool as: card number, call sign, tail number, 24-bit address code, status, timestamp; the dynamic data is stored in the dynamic data pool as: card number, position, free text, timestamp.

[0065] The data item separation process of the structured data information and the storage in the static data pool and the dynamic data pool includes the following steps:

[0066] The structured data information is processed by separating the data items to obtain static data and dynamic data; for example, the card number, call sign, tail number, 24-bit address code, and status in the structured data information are classified as static data, and the card number, location, free text, and timestamp in the structured data information are classified as dynamic data.

[0067] Store static data into a static data pool;

[0068] Store dynamic data into the dynamic data pool.

[0069] S103, performing data conversion processing on the data information stored in the static data pool and the dynamic data pool respectively;

[0070] If the low-altitude aircraft has landed, or the aircraft data has not been obtained for a set time (for example, more than 10 minutes), it can be confirmed that the aircraft flight has ended, and all the data of the aircraft can be indexed from the data pool. Since the device card number is unique, the card number can be used as the unique index of the aircraft. At the same time, a data conversion processing signal is issued to trigger the execution of static data processing and dynamic data processing.

[0071] The data conversion process for the data information stored in the static data pool and the dynamic data pool includes the following steps:

[0072] Perform data conversion processing on the static data information stored in the static data pool by maintaining the sliding window comparison method of the benchmark table;

[0073] The dynamic data information stored in the dynamic data pool is converted and processed by the synchronous Euclidean distance method.

[0074] The data conversion process of the static data information stored in the static data pool by maintaining the sliding window comparison method of the reference table includes the following steps:

[0075] Obtain static data information from the static data pool and determine whether it is in the established benchmark table through card number matching;

[0076] If it is determined to be in the established reference table, the split static data is compared with each item in the character-to-digital conversion basic table; if the data item changes, the changed data is written to the persistent storage buffer and the reference table is updated;

[0077] If it is determined that the card number is not in the established reference table, a static data reference table is established based on the card number and written into the static data persistent storage buffer, and the string data items (for example, call sign, tail number, 24-bit address code) are converted into digital form through the character encoding Base48.

[0078] For example, if it is determined that it is not in the established reference table, the static data that has been split according to the data items of card number, call sign, tail number, 24-bit address code, status, and timestamp is obtained, a data index is established, and a reference table is established, and written into the static data persistent storage buffer, as shown in Table 1:

[0079] Table 1

[0080] Data Item card number Call Sign Tail number 24 address code state Timestamp Data Types uint32 char[8] char[8] char[6] uint8 uint64

[0081] The string data items: call sign, tail number, 24-bit address code, are converted into digital form through character encoding Base48, as shown in Table 2:

[0082] Table 2

[0083] Data Item card number Call Sign Tail number 24 address code state Timestamp Data Types uint32 uint64 uint64 uint32 uint8 uint64

[0084] For example, if it is determined that the split static data is obtained in the established benchmark table, and compared with each item in the character-to-digital conversion basic table, if the data item changes, the change is written to the persistent storage buffer and recorded as: time difference and change item, where the time offset value is the offset value between the timestamp of the current data and the timestamp of the first data in the persistent storage buffer. Because aircraft usually collect data once a second and transmit it down, the update time interval is set to 1s, and the flight duration is no longer than 18 hours, so the time difference is stored in uint16 and the benchmark table is updated at the same time. The storage structure of the change item is shown in Table 3:

[0085] Table 3

[0086] Data Item Time offset Change Number Update Value Data Types uint16 uint8 Table 2 Data Types

[0087] The data conversion process of the dynamic data information stored in the dynamic data pool by the synchronous Euclidean distance method includes the following steps:

[0088] Get dynamic data information from the dynamic data pool and calculate the track distance between two points of the low-altitude aircraft based on the card number;

[0089] The NUCp, NIC and NACp values ​​of the aircraft at all times are counted, the data is smoothed using B-spline, the motion data is extracted through the static determination method of positioning error, and the error threshold is set according to the positioning accuracy;

[0090] The track compression calculation is performed by using the DP algorithm of the vertical Euclidean distance to remove redundant points, and the track turning point is obtained. The first point is used as the reference, and the compressed point track is obtained by position offset.

[0091] The dynamic data is written into the persistent storage buffer in the format of card number, time offset, and position offset.

[0092] For example, dynamic data is obtained from the dynamic data pool, and the card number is used as the unique identifier of the low-altitude aircraft track. The distance between the two-point track is calculated. Due to the positioning error of satellite navigation, NACp is used in aviation to represent the positioning accuracy. When the calculated distance is outside the 95% interval of the measurement error distribution, it is considered that the target has shifted. That is, when the positioning accuracy is 1m, when the displacement is greater than 1.6168m, it is considered that the aircraft has shifted. Otherwise, the target is considered to be stationary. The data that has moved is used as the candidate track data, and the time series is used as the basis for track smoothing. The B-spline curve smoothing algorithm is used to smooth the track.

[0093] For example, count the NUCp, NIC and NACp values ​​of the aircraft in all periods, sort them from large to small, take the 80% percentile data as the threshold value for track compression, and find the HFOM value through Table 4. To avoid data rounding errors, the minimum value should be greater than 6m of the aircraft size. If the aircraft does not have this value, 10m is usually sufficient.

[0094] Table 4 NUCp coding standard

[0095] NUC HPL(10-7) HFOM (95%) 0 Unknown Unknown 1 <20nm <10nm 2 <10nm <5nm 3 <2nm <1nm 4 <1nm <0.5nm 5 <0.5nm <h2 style=";text-align:left;direction:ltr"><0.25nm<h2 style=";text-align:left;direction:ltr"> 6 <0.2nm <0.1nm 7 <0.1nm <0.05nm 8 TBD <10m 9 TBD <3m … TBD TBD

[0096] That is, the threshold is set to: ρ = max(HFOM,6).

[0097] For example, since it is an offline data analysis, the DP algorithm of the vertical Euclidean distance is used for track compression calculation, which can remove redundant points to the greatest extent while retaining the key feature points of the track, thereby achieving track compression. The inflection point of the track obtained after calculation is extracted, and the first point is used as the reference, and the compressed point track is obtained by position offset.

[0098] For example, the format of card number, time offset, and position offset is written into the dynamic data persistent storage buffer, as shown in Table 5:

[0099] Table 5

[0100]

[0101] S104, storing the data conversion processing result;

[0102] After both static and dynamic data are processed, the converted data is stored. The data conversion results are stored by placing the static data persistent storage buffer in front and the dynamic data persistent storage buffer in the back, and splicing the data. By placing the static data persistent storage buffer in front and the dynamic data persistent storage buffer in the back, and splicing the data, the entire low-altitude flight dynamic data compression conversion process is completed.

[0103] This application uses real data for verification. A total of 38,365 pieces of low-altitude flight dynamic data were collected on a certain day. On that day, 43 aircraft flew. The actual measurement showed that when the threshold was set to 10m, the average compression rate of data compression conversion was 24.4%; when the threshold was set to 100m, the average compression rate of data compression conversion was 13.7%. If the aircraft data is stable, the compression rate of compression conversion will be higher.

[0104] Taking the aircraft with equipment card number 1015488 as an example, 13284 pieces of aircraft operation data were received, some of which are shown in Table 6:

[0105] Table 6 Example navigation track data

[0106]

[0107]

[0108] The tail number "BX" is found in the table to be 173283608608 in decimal and 0x002858820820 in hexadecimal. Figure 2 The original trajectory diagram is shown, which contains 13284 points. Figure 3 The following figure shows the static and smoothed tracks, as well as a partial enlarged image. The threshold is set to 10m. The smoothed track is obtained by removing static points and smoothing the track. The total number of track points is 390. Figure 4 The figure shows the track diagram after dynamic data compression conversion. The threshold is set to 10m. The track is processed through track compression processing, and the number of points remaining after compression is 84. According to the description in the technology, the original aircraft data items include timestamp, tail number, card number, longitude, and latitude, totaling 13284×5=66420 items of data. The compressed data items include 84 processed points and two starting and ending points totaling 86 points, totaling 262=4+86×3 items.

[0109] The processed data is displayed in Json format as follows:

[0110]

[0111]

[0112] The above is a low-altitude flight dynamic data compression and conversion method provided in an embodiment of the present application, and the following is a low-altitude flight dynamic data compression and conversion system provided in an embodiment of the present application.

[0113] A low-altitude flight dynamic data compression and conversion system, comprising:

[0114] A data acquisition unit, used to acquire structured data information based on low-altitude flight dynamic data messages;

[0115] The first processing unit is used to separate the structured data information into data items and store them in a static data pool and a dynamic data pool;

[0116] The second processing unit is used to perform data conversion processing on the data information stored in the static data pool and the dynamic data pool respectively; wherein the second processing unit performs data conversion processing on the static data information stored in the static data pool based on the sliding window comparison method of the maintenance reference table; the second processing unit performs data conversion processing on the dynamic data information stored in the dynamic data pool based on the synchronous Euclidean distance method;

[0117] The data storage unit is used to store the data conversion processing results.

[0118] The second processing unit performs data conversion processing on the static data information stored in the static data pool based on the sliding window comparison method of the maintenance reference table, including the following steps:

[0119] Obtain static data information from the static data pool and determine whether it is in the established benchmark table through card number matching;

[0120] If it is determined to be in the established reference table, the split static data is compared with each item in the character-to-digital conversion basic table; if the data item changes, the changed data is written to the persistent storage buffer and the reference table is updated;

[0121] If it is determined that the card number is not in the established reference table, a static data reference table is established based on the card number and written into the static data persistent storage buffer, and the string data items therein are converted into digital form using the character encoding Base48.

[0122] The second processing unit performs data conversion processing on the dynamic data information stored in the dynamic data pool based on the synchronous Euclidean distance method, including the following steps:

[0123] Get dynamic data information from the dynamic data pool and calculate the track distance between two points of low-altitude aircraft based on the card number;

[0124] The NUCp, NIC and NACp values ​​of the aircraft at all times are counted, the data is smoothed using B-spline, the motion data is extracted through the static determination method of positioning error, and the error threshold is set according to the positioning accuracy;

[0125] The track compression calculation is performed by using the DP algorithm of the vertical Euclidean distance to remove redundant points, and the track turning point is obtained. The first point is used as the reference, and the compressed point track is obtained by position offset.

[0126] The dynamic data is written into the persistent storage buffer in the format of card number, time offset, and position offset.

[0127] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0128] The terms "first", "second" and "third" etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0129] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0130] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0131] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0132] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A low-altitude flight dynamic data compression conversion method, characterized in that: The following steps are involved: S101, acquiring structured data information based on low-altitude flight dynamic data messages; S102, performing data item separation processing on the structured data information, and storing them in a static data pool and a dynamic data pool; S103, performing data conversion processing on the data information stored in the static data pool and the dynamic data pool respectively; S104: Store the data conversion processing result.

2. The low-altitude flight dynamic data compression conversion method according to claim 1 is characterized in that: The structured data information includes card number, call sign, tail number, 24-bit address code, timestamp, status, location, and free text; the card number, call sign, tail number, 24-bit address code, and status in the structured data information are classified as static data, and the card number, location, free text, and timestamp in the structured data information are classified as dynamic data.

3. The low-altitude flight dynamic data compression conversion method according to claim 1 is characterized in that: The step of separating the structured data information into data items and storing them in the static data pool and the dynamic data pool includes the following steps: Separate the structured data information into data items to obtain static data and dynamic data; Store static data into a static data pool; Store dynamic data into the dynamic data pool.

4. The low-altitude flight dynamic data compression conversion method according to claim 1 is characterized in that: The data conversion process for the data information stored in the static data pool and the dynamic data pool comprises the following steps: Perform data conversion processing on the static data information stored in the static data pool by maintaining the sliding window comparison method of the benchmark table; The dynamic data information stored in the dynamic data pool is converted and processed by the synchronous Euclidean distance method.

5. The low-altitude flight dynamic data compression conversion method according to claim 4 is characterized in that: The data conversion process of the static data information stored in the static data pool by the sliding window comparison method of maintaining the reference table includes the following steps: Obtain static data information from the static data pool and determine whether it is in the established benchmark table through card number matching; If it is determined to be in the established reference table, the split static data will be compared with each item in the character-to-digital conversion basic table; if the data item changes, the changed data will be written to the persistent storage buffer and the reference table will be updated.

6. The low-altitude flight dynamic data compression conversion method according to claim 4 is characterized in that: The data conversion process of the dynamic data information stored in the dynamic data pool by the synchronous Euclidean distance method comprises the following steps: Get dynamic data information from the dynamic data pool and calculate the track distance between two points of the low-altitude aircraft based on the card number; The NUCp, NIC and NACp values ​​of the aircraft at all times are counted, the data is smoothed using B-spline, the motion data is extracted through the static determination method of positioning error, and the error threshold is set according to the positioning accuracy; The track compression calculation is performed by using the DP algorithm of the vertical Euclidean distance to remove redundant points, and the track turning point is obtained. The first point is used as the reference, and the compressed point track is obtained by position offset. The dynamic data is written into the persistent storage buffer in the format of card number, time offset, and position offset.

7. The low-altitude flight dynamic data compression conversion method according to claim 1 is characterized in that: The method for storing the data conversion processing result is: placing the static data persistent storage buffer in front and the dynamic data persistent storage buffer in the back, and then splicing the data.

8. A low-altitude flight dynamic data compression and conversion system, used to execute the low-altitude flight dynamic data compression and conversion method according to any one of claims 1 to 7, characterized in that: include: A data acquisition unit, used to acquire structured data information based on low-altitude flight dynamic data messages; The first processing unit is used to separate the structured data information into data items and store them in a static data pool and a dynamic data pool; The second processing unit is used to perform data conversion processing on the data information stored in the static data pool and the dynamic data pool respectively; wherein the second processing unit performs data conversion processing on the static data information stored in the static data pool based on the sliding window comparison method of the maintenance reference table; the second processing unit performs data conversion processing on the dynamic data information stored in the dynamic data pool based on the synchronous Euclidean distance method; The data storage unit is used to store the data conversion processing results.

9. The low-altitude flight dynamic data compression and conversion system according to claim 8, characterized in that: The second processing unit performs data conversion processing on the static data information stored in the static data pool based on the sliding window comparison method of the maintenance reference table, including the following steps: Obtain static data information from the static data pool and determine whether it is in the established benchmark table through card number matching; If it is determined to be in the established reference table, the split static data is compared with each item in the character-to-digital conversion basic table; if the data item changes, the changed data is written to the persistent storage buffer and the reference table is updated; If it is determined that the card number is not in the established reference table, a static data reference table is established based on the card number and written into the static data persistent storage buffer, and the string data items therein are converted into digital form using the character encoding Base48.

10. The low-altitude flight dynamic data compression and conversion system according to claim 8, characterized in that: The second processing unit performs data conversion processing on the dynamic data information stored in the dynamic data pool based on the synchronous Euclidean distance method, including the following steps: Get dynamic data information from the dynamic data pool and calculate the track distance between two points of the low-altitude aircraft based on the card number; The NUCp, NIC and NACp values ​​of the aircraft at all times are counted, the data is smoothed using B-spline, the motion data is extracted through the static determination method of positioning error, and the error threshold is set according to the positioning accuracy; The track compression calculation is performed by using the DP algorithm of the vertical Euclidean distance to remove redundant points, and the track turning point is obtained. The first point is used as the reference, and the compressed point track is obtained by position offset. The dynamic data is written into the persistent storage buffer in the format of card number, time offset, and position offset.

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