CN110048725B

CN110048725B - Topographic data compression and decompression algorithm based on TAWS system

Info

Publication number: CN110048725B
Application number: CN201910396834.1A
Authority: CN
Inventors: 陈锡莲; 祝正燕; 杨珍; 刘永刚
Original assignee: Sichuan Jiuzhou ATC Technology Co Ltd
Current assignee: Sichuan Jiuzhou ATC Technology Co Ltd
Priority date: 2019-05-14
Filing date: 2019-05-14
Publication date: 2023-07-07
Anticipated expiration: 2039-05-14
Also published as: CN110048725A

Abstract

The invention relates to the technical field of data compression and discloses a topographic data compression and decompression algorithm based on a TAWS system. The compression algorithm is used for quantizing different quantization units of the topographic data, circularly analyzing, compressing a large amount of topographic data and storing the compressed topographic data in a storage space, so that a large amount of storage resources are saved, and the model which can be selected even for smaller storage devices is achieved. When the TAWS system normally operates, all terrain data are not loaded at the same time, the terrain data in the range of the front and left and right covered by the current position are selected for processing and displaying, and are updated when crossing the area, so that a great amount of time is not consumed for decompression, and the stability of the system performance is achieved.

Description

Topographic data compression and decompression algorithm based on TAWS system

Technical Field

The invention relates to the technical field of data compression, in particular to a topographic data compression and decompression algorithm based on a TAWS system.

Background

The TAWS (terrain awareness and warning system) system compares and analyzes by acquiring various state parameters in the aircraft system and using alarm envelope thresholds in different forms to give alarm information, and in the TSO-C151B standard, the enhanced alarm function comprises: the front view avoids the topographic alert and the topographic two-dimensional display. Not only is the warning predicted in advance, but also the terrain display is performed on the areas in front of and below the flight, and under the condition that the TAWS system does not have the terrain detection capability, a large number of accurate and reliable terrain databases are needed to provide support for the enhanced functions. The accuracy of the terrain data in TSO-C151B has a hard index requirement, this makes the capacity of the terrain data enormous. For example, the SRTM China topography is as high as 22GB in the topography data capacity with the resolution of 90m, on one hand, the memory capacity in the system design is required to reach the standard, but the development of the ultra-large capacity memory in the domestic process is imperfect, and the cost control and the reliability of the system are greatly challenged; on the other hand, loading a large amount of data by the system during the initialization process can take a lot of time, resulting in slow system start-up. The above problems can be solved by compressing the topographic data and reducing the storage space. TAWS system designs run in embedded systems and cannot utilize compression decompression software in mature systems, requiring more straightforward compression algorithms.

Disclosure of Invention

The technical problems to be solved by the invention are as follows: aiming at the problems, a terrain data compression and decompression algorithm based on a TAWS system is provided.

A TAWS system-based terrain data compression algorithm comprising:

step S1, starting compression, setting a circulation variable i from 0, wherein the circulation times are the total number SUM of data in the text minus 1;

step S2, if i exceeds SUM-1, the loop exits to step S8; otherwise, the ith data D is read _i Performing integral multiple quantification on the data, and storing an integral multiple quantification result as SO;

step S3, performing eight-bit quantization on SO to obtain quotient SS and remainder SY, setting the highest bit of the quotient SS and the remainder SY to 0 for distinguishing differential data, and sequentially storing the differential data; i is accumulated to 1;

step S4, reading the ith data D _i First for D _i Performing integral multiple quantization, wherein the quantized value is SN, and calculating the differential value iE to be equal to SN-SO; judging whether the iE is in the threshold range, and returning to the step S2 if the iE exceeds the threshold; if iE does not exceed the threshold value, entering step S5;

step S5, converting the differential value iE into a non-zero differential value iEO; the highest position of iEO is set to 1, differential data is represented and stored, and CNT counting is started; and assigning SN to SO; meanwhile, i is accumulated by 1, and the step S6 is carried out;

step S6, starting a new cycle, and reading the ith data D _i For D _i Performing integer multiple quantization with SN as quantization value, and calculating differential value iE _i Equal to SN-SO, determine iE _i If not, entering step S4; assigning SN to if equalSO, accumulating the CNT count by 1, judging whether the CNT count exceeds a threshold or whether the CNT count exceeds SUM-1, if not, continuing to circulate in the step S6, otherwise, jumping out the circulation to enter the step S7;

step S7, carrying out six-bit quantization on the counted CNT count to obtain a quotient CS and a remainder CY, if CS is zero, the storage is not needed, if CS is not zero, the next-highest positions of CS and CY are 1, the next-highest positions are represented as counted differential data, the storage is carried out, and meanwhile CNT is cleared, and the step S2 is returned;

step S8, exiting the loop, processing the last data D _SUM First, for data D _SUM And (3) carrying out integral multiple quantization to obtain SO, carrying out eight-bit quantization, and storing the highest positions of the quotient and the remainder as 0.

Further, in the step S2, tolerance of the precision loss is set for the integer multiple quantization.

Further, the tolerance limit for the loss of precision is set to be one digit.

Further, the data in the text is a file in ascii format.

Further, the file storage format is row number, column number, upper left corner longitude, upper left corner latitude, grid resolution, and then the topographic data is arranged in sequence according to the row number and the column number, and the compressed data only comprises topographic data.

The invention also discloses a topographic data decompression algorithm based on the TAWS system, which comprises the following steps:

step 1, setting a circulation variable i to start from 0, and reading three data Di, di+1 and Di+2;

step 2, judging whether a circulation condition is satisfied: the number of the read data is smaller than the total number of the files, if the number of the read data is not satisfied, the loop is exited to enter the step 7, and if the number of the read data is satisfied, the next step is entered;

step 3, taking the highest level and the next highest level of Di to judge; if the highest bit of Di is 0, the data is represented as normal data, then Di and Di+1 are utilized to carry out eight-bit quantization recovery to obtain SO, and SO is further subjected to integral multiple quantization recovery to obtain original data, di+2 is assigned to Di, new Di+1 and Di+2 are read in, and the step 2 is returned; if the highest bit of Di is 1, the differential data is represented, and the step 4 is entered;

step 4, di is a nonzero differential value iEO, iEO is converted into a real differential value iE, the iE is added with SO to obtain SN, integral multiple quantization recovery is carried out on the SN to obtain original data, and the SN is assigned to the SO; next, judging the next higher order of Di+1 and Di+2, if the next higher order of Di+1 is 0, then, not repeating the data, assigning Di+1 to Di, assigning Di+2 to Di+1, and then re-reading Di+2, and returning to the step 2; if Di+1 is 1, the next high bit indicates that repeated data is next, if Di+2 is also 1, the repeated data is present for the second time, and the step 5 is entered, otherwise, the step 6 is entered;

step 5, for the secondary repeated data, performing six-bit quantization recovery on Di+1 and Di+2 to obtain CNT, wherein the repeated data recovery process is as follows: adding SO to iE to obtain SN, and carrying out integral multiple quantification recovery on the SN to obtain original data; assigning SN to SO, and exiting after circulating CNT-1 times; re-reading the new Di, di+1, di+2, and turning to step 2;

step 6, for one-time repeated data, performing six-bit quantitative recovery on Di+1 to obtain CNT, wherein the repeated data recovery process is as follows: adding SO to iE to obtain SN, and carrying out integral multiple quantification recovery on the SN to obtain original data; assigning SN to SO, and exiting after circulating CNT-1 times; di+2 is assigned to Di, di+1 and Di+2 are read in again, and the step 2 is carried out;

and 7, carrying out eight-bit quantization recovery on Di and Di+1 aiming at the last piece of data to obtain SO and SO, and carrying out integral multiple quantization recovery to obtain the original data.

Compared with the prior art, the beneficial effects of adopting the technical scheme are as follows: by adopting the technical scheme of the invention, a large amount of topographic data is compressed and stored in the storage space through the compression algorithm, so that a large amount of storage resources are saved. Based on the reduction in storage space requirements, there is an approach to even alternative available models for smaller capacity storage devices that are domestic. Secondly, a further index for the compression algorithm is compression time, since for a TAWS system, compression of data is not directly reflected in the TAWS system, but is reflected in the preprocessing of the data; when the TAWS system normally operates, all terrain data are not loaded at the same time, the terrain data in the range of the front and left and right covered by the current position are selected for processing and displaying, and are updated when crossing the area, so that a great amount of time is not consumed for decompression, and the stability of the system performance is achieved.

Drawings

Fig. 1 is a schematic flow chart of a terrain data compression algorithm based on a TAWS system according to the present invention.

Fig. 2 is a flow chart of a topographic data decompression algorithm based on a TAWS system according to the present invention.

Detailed Description

The invention is further described below with reference to the accompanying drawings.

The compression method is a lossy compression method (quantization method), and the topographic data is assumed to be preprocessed to form a file in an ascii format, wherein the storage format is row number, column number, upper left corner longitude, upper left corner latitude and grid resolution, and then the data are sequentially arranged according to the row number and the column number. The compressed data includes only real terrain data and no data header. First, a set of operations is defined:

integer times quantization: defining the quantization with ten, hundred and thousand as quantization units as integer multiple quantization;

eight-bit quantization: defining quantization in 256 quantization units as eight-bit quantization;

six-digit quantization: defining quantization with 64 as quantization unit as six-bit quantization;

the specific implementation of compression is as follows:

as shown in fig. 1, a terrain data compression algorithm based on a TAWS system includes:

step S1, compression is started, a circulation variable i is set to be from 0, the circulation times are the total number SUM of data in the text minus 1, and step S2 is entered;

step S2, if i exceeds SUM-1, the loop exits to step S8; otherwise, the ith data Di is read, integral multiple quantization is carried out on the data, the quantization process brings precision loss, tolerance limit on the precision loss is selected according to actual requirements, and the precision loss is acceptable to a single digit (meter) level for a TAWS system; storing the integer multiple quantification result as SO, and entering step S3;

step S3, performing eight-bit quantization on SO to obtain quotient SS and remainder SY, setting the highest bit of the quotient SS and the remainder SY to 0 for distinguishing differential data, and sequentially storing the differential data; i is accumulated to 1, and the step S4 is carried out;

step S4, reading the ith data Di, firstly carrying out integral multiple quantization on the Di, wherein the quantized value is SN, and calculating the differential value iE to be equal to SN-SO; judging whether the iE is in the threshold range, and returning to the step S2 if the iE exceeds the threshold; if iE does not exceed the threshold value, entering step S5;

step S6, starting a new cycle, reading the ith data Di, carrying out integral multiple quantization on the Di, calculating a differential value iEi equal to SN-SO, judging iEi whether the differential value is equal to iE, and if not, entering step S4; if SO, assigning SN to SO, accumulating CNT count by 1, judging whether CNT count exceeds a threshold or whether i exceeds SUM-1, if not, continuing to circulate in step S6, otherwise, jumping out the circulation to enter step S7; ( It should be noted that there is only one i, i that will only be incremented, and that i will not fall back when jumping to other steps after incrementing, or i is current. The data corresponding to the previous sequence i has been processed. )

and S8, circularly exiting, processing the last data DSUM, performing integral multiple quantization on the data DSUM to obtain SO, performing eight-bit quantization, and storing the highest positions of the quotient and the remainder as 0.

This compression ends.

The decompression algorithm and the compression algorithm are exactly the inverse process and are in one-to-one correspondence, and a group of operations are defined:

and (3) integer multiple quantification recovery: the inverse process of integer multiple quantification;

eight-bit quantization recovery: an inverse of the eight-bit quantization;

six-digit quantization recovery: an inverse process of six-digit quantization;

the decompression is realized as follows:

as shown in fig. 2, a terrain data decompression algorithm based on a TAWS system includes:

step 1, setting a circulation variable i to start from 0, reading three data Di, di+1 and Di+2, and entering step 2;

step 2, judging whether a circulation condition is satisfied: the number of the read data is smaller than the total number of the files, if the number of the read data is not satisfied, the loop is exited to enter the step 7, and if the number of the read data is satisfied, the loop enters the step 3;

step 4, di is a non-zero differential value iEO (the highest bit is not used), iEO is converted into a real differential value iE, the iE is added with SO to obtain SN, the SN is subjected to integral multiple quantization and recovery to obtain original data, and the SN is assigned to the SO; next, judging the next higher order of Di+1 and Di+2, if the next higher order of Di+1 is 0, then, not repeating the data, assigning Di+1 to Di, assigning Di+2 to Di+1, and then re-reading Di+2, and returning to the step 2; if Di+1 is 1, the next high bit indicates that repeated data is next, if Di+2 is also 1, the repeated data is present for the second time, and the step 5 is entered, otherwise, the step 6 is entered;

This decompression ends.

The embodiment provides a terrain data compression and decompression algorithm based on a TAWS system. The topographical data itself is not in the research category herein. By means of the compression algorithm, a large amount of topographic data is compressed and stored in the storage space, a large amount of storage resources are saved, and the purpose that even for domestic storage devices, the available model is selected is achieved. For example: the method covers the topographic data with the precision of 90m in Sichuan and Shaanxi areas, and has 1200 files, the size of 826MB before compression and the size of 316MB after compression, and the compression rate of 38% by adopting the algorithm. Saving a large part of memory space resources. Also, the decompression algorithm can enable 1200 files to be decompressed correctly. The compression algorithm has more obvious effect on plain areas or areas with gentle change of topography.

The invention is not limited to the specific embodiments described above. The invention extends to any novel one, or any novel combination, of the features disclosed in this specification, as well as to any novel one, or any novel combination, of the steps of the method or process disclosed. It is intended that insubstantial changes or modifications from the invention as described herein be covered by the claims below, as viewed by a person skilled in the art, without departing from the true spirit of the invention.

Claims

1. A TAWS system-based terrain data compression algorithm, comprising:

step S2, if i exceeds SUM-1, the loop exits to step S8; otherwise, reading the ith data Di, carrying out integral multiple quantification on the data, and storing an integral multiple quantification result as SO;

step S4, reading the ith data Di, firstly, carrying out integral multiple quantization on D i, wherein the quantized value is SN, and calculating the differential value iE to be equal to SN-SO; judging whether the iE is in the threshold range, and returning to the step S2 if the iE exceeds the threshold; if iE does not exceed the threshold value, entering step S5;

step S6, starting a new cycle, reading the ith data Di, carrying out integral multiple quantization on the Di, calculating a differential value iEi equal to SN-SO, judging iEi whether the differential value is equal to iE, and if not, entering step S4; if SO, assigning SN to SO, accumulating CNT count by 1, judging whether CNT count exceeds a threshold or whether i exceeds SUM-1, if not, continuing to circulate in step S6, otherwise, jumping out the circulation to enter step S7;

step S8, exiting the loop, processing the last data D _SUM First, for data D _SUM Carrying out integral multiple quantization to obtain SO, carrying out eight-bit quantization, and storing the highest positions of quotient and remainder as 0;

six-digit quantization: quantization in units of quantization of 64 is defined as six-bit quantization.

2. The TAWS system-based terrain data compression algorithm according to claim 1, characterized in that in the step S2, tolerance of loss of accuracy is set for integer quantization.

3. The TAWS system-based terrain data compression algorithm according to claim 2, characterized in that tolerance of accuracy loss is set to be single digit.

4. The TAWS system-based terrain data compression algorithm according to claim 1, wherein the data in the text is a file in ascii format.

5. The method of claim 4, wherein the file storage format is row number, column number, upper left longitude, upper left latitude, grid resolution, and then the topographic data is arranged in sequence according to the row number and the column number, and the compressed data only includes topographic data.

6. A TAWS system-based terrain data decompression algorithm, comprising:

step 7, carrying out eight-bit quantization recovery on Di and Di+1 aiming at the last piece of data to obtain SO and SO, and carrying out integral multiple quantization recovery to obtain original data;

eight-bit quantization recovery: an inverse of the eight-bit quantization;

six-digit quantization recovery: inverse of six-bit quantization.