CN114564684B - Method for compressing detection signal data of missile-borne detector - Google Patents

Method for compressing detection signal data of missile-borne detector Download PDF

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CN114564684B
CN114564684B CN202210182954.3A CN202210182954A CN114564684B CN 114564684 B CN114564684 B CN 114564684B CN 202210182954 A CN202210182954 A CN 202210182954A CN 114564684 B CN114564684 B CN 114564684B
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武军安
董志豪
郭锐
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Nanjing University of Science and Technology
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Abstract

The invention discloses a method for compressing signal data detected by a missile-borne detector. And then, carrying out low-bit-width quantization on the high-frequency and low-frequency coefficients obtained by decomposition to obtain quantized wavelet coefficients and scale coefficients. And using the quantized wavelet coefficients and scale coefficients for storage and transmission of the missile-borne transmission system. And finally, the receiving end uses the quantized wavelet coefficient and the quantized scale coefficient to carry out wavelet reconstruction, and a reconstructed signal subjected to data compression is obtained. The invention can realize effective data compression under the condition that the basic information is not lost by the signal acquired by the missile-borne detector, and reduces the resource expenditure of data storage and transmission.

Description

Method for compressing detection signal data of missile-borne detector
Technical Field
The invention belongs to the signal processing technology, and particularly relates to a method for compressing signal data detected by a missile-borne detector.
Background
The missile-borne detector generates an analog signal in the detection stage, and one-dimensional waveform data is acquired through a 16-bit ADC of the missile-borne computer. Because the shot detection time is long and the ADC sampling rate of the missile-borne computer is high, the obtained one-dimensional waveform data is large in quantity, and the data storage and the data transmission are inconvenient. The hardware resources are limited in the missile-borne environment, and complex algorithms are inconvenient to compress and process signals with large data size.
Ke Xingli in the text of "design and implementation of a certain type of missile-borne data acquisition system", the data acquired by the missile-borne detector is compressed based on an LZW compression algorithm, the LZW algorithm needs to dynamically create a dictionary according to the input data, and for waveform signals with large amplitude ranges, the compression effect is limited by the capacity of a memory in a chip, the complexity of the algorithm and the instantaneity.
Disclosure of Invention
The invention aims to provide a method for compressing detection signal data of a missile-borne detector, which can realize effective compression of data volume under the condition of ensuring that original information is not basically lost.
The technical solution for realizing the purpose of the invention is as follows: a method for compressing signal data detected by a missile-borne detector, comprising the steps of:
step 1, a one-dimensional waveform signal is detected by the missile-borne detector and is converted into a 16-bit digital signal A 0, and the step 2 is carried out.
And step 2, carrying out 6-layer wavelet decomposition on the 16-bit digital signal to obtain a 6-level wavelet coefficient D x and a 1-level scale coefficient A 6, wherein the wavelet coefficient serial number x=1 and 2 … …. Wherein, the 'db 4' wavelet is selected as the wavelet base. The data bit width of the digital signal A 0 is 16 bits; the bit width of each level of coefficients obtained through decomposition is the same as the bit width of the data point of the digital signal A 0, and is 16 bits, the sum of the points of each level of coefficients obtained through decomposition is equal to the number of the data points of the digital signal A 0, and the step 3 is carried out.
And 3, respectively carrying out low-order width quantization on the 6-level wavelet coefficient D x and the 1-level scale coefficient A 6, namely, representing a 16-bit data point by 12 bits, 8 bits or 4 bits to obtain a quantized wavelet coefficient D 'x and a quantized scale coefficient A' 6 and obtain a quantized wavelet coefficient D 'x and a quantized scale coefficient A' 6.
And 4, splicing the quantized wavelet coefficient D 'x and the quantized scale coefficient A' 6 to obtain spliced data, and transferring to the step 5.
And 5, performing wavelet reconstruction on the spliced data to obtain a reconstructed signal A' 0, namely a compressed signal.
Compared with the prior art, the invention has the remarkable advantages that:
According to the invention, original detection data is decomposed into 6-level wavelet coefficients and 1-level scale coefficients through wavelet transformation, and the sum of the points of each level of coefficients in the decomposition process is equal to the number of the undecomposed data; and the quantized coefficients are spliced and then subjected to data transmission and storage, so that the bus bandwidth of the missile-borne computer is improved. And carrying out wavelet reconstruction on each level of coefficients after splicing to obtain reconstruction data. Under the condition that the original data information is kept basically not lost, the data quantity of the reconstructed data is reduced, and storage and transmission resources are saved.
Drawings
FIG. 1 is a flow chart of a method for compressing signal data detected by a missile-borne detector in accordance with the present invention.
Fig. 2 is a schematic diagram of original data and 6 th layer scale factor and wavelet coefficient obtained by wavelet decomposition in step 2.
Fig. 3 shows the result of the different low bit-width representation of the scale factor a 6 in step 3.
Fig. 4 is a waveform comparison diagram of the reconstructed signal and the original signal in step 5.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, a method for compressing signal data detected by a missile-borne probe includes the steps of:
Step 1, the missile-borne detector detects a one-dimensional waveform signal (the signal has the characteristics that the targeted waveform is bell-shaped pulse, the non-targeted waveform is small fluctuation at a fixed voltage, as shown in fig. 2), and the signal is converted into a 16-bit (data point) digital signal A 0 through an ADC (analog to digital converter) of the missile-borne computer, and the step 2 is carried out.
Step 2, performing 6-layer wavelet decomposition on the 16-bit digital signal A 0 to obtain a 6-level wavelet coefficient D x and a 1-level scale coefficient A 6, wherein the wavelet coefficient serial number x=1, 2 … … 6, and the wavelet decomposition is preferably that the wavelet base is db4 wavelet.
And (3) switching to step 3.
Step 3, performing low-order width quantization on the wavelet coefficient D x and the 1-level scale coefficient A 6 respectively, namely, representing a 16-bit data point by 12 bits, 8 bits or 4 bits to obtain a quantized wavelet coefficient D 'x and a quantized scale coefficient A' 6, which are specifically as follows:
Step 3-1, respectively calculating the information entropy Q Dx of the wavelet coefficient D x and the information entropy Q A6 of the level 1 scale coefficient a 6:
wherein, L Dx、LA6 is the total number of possible values in the wavelet coefficient or scale coefficient, and the values are related to the waveform amplitude range; p i is the ratio of the number of data points of the wavelet coefficient or scale coefficient with a value equal to i to the total number of data points.
Step 3-2, respectively carrying out low-order width quantization on the 6-level wavelet coefficient D x and the 1-level scale coefficient A 6 to obtain a wavelet coefficient D 'x and a scale coefficient A' 6 which are expressed by the low-order width:
Wherein y Dx is the low-order width selected by the wavelet coefficient of the x-th layer, y 6 is the low-order width selected by the scale coefficient of the 6-th layer, and different low-order widths of the scale coefficient A 6 represent the results shown in FIG. 3.
Step 3-3, respectively calculating the information entropy Q 'Dx of the wavelet coefficient D' x represented by the low-order width and the information entropy Q 'A6 of the scale coefficient a' 6 represented by the low-order width:
where L Dx′ is the total number of values that may occur in the x-th layer wavelet coefficient represented by the low-order width, and L A6′ is the total number of values that may occur in the 6-th layer scale coefficient represented by the low-order width.
Step 3-4, calculating the loss amount loss Dx of the information entropy Q Dx of the wavelet coefficient and the information entropy Q 'Dx of the wavelet coefficient represented by the low-order width, and the loss amount loss A6 of the information entropy Q A6 of the scale coefficient and the information entropy Q' A6 of the scale coefficient represented by the low-order width under different low-order width representations:
in order to ensure that the reconstructed waveform is not severely distorted, the quantized information entropy loss should satisfy loss <40%.
Step 3-5, introducing a compression ratio CPR to measure the compression effect, and measuring the compression condition meeting the information entropy loss less than 40 percent:
In the above formula, N is the data amount which is not represented by the low bit width, and K is the data amount which is represented by the low bit width; wherein:
In the above formula, N Dx is the storage space occupied by the x-th layer wavelet coefficient after wavelet decomposition of the data not represented by the low-order width, and N A6 is the storage space occupied by the 6-th layer scale coefficient after wavelet decomposition of the data not represented by the low-order width; k Dx is the storage space occupied by the x-th layer wavelet coefficient after low-bit width representation, K A6 is the storage space occupied by the 6-th layer scale coefficient after low-bit width representation, and N Dx、NA6 and K Dx、KA6 satisfy:
KDx＝yDxNDx
KA6＝yA6NA6
Wherein y Dx and y A6 are respectively the low-order width selected by the wavelet coefficient of the x-th layer and the low-order width selected by the scale coefficient of the 6-th layer.
Step 3-6, selecting a low bit width representation combination with the maximum compression ratio and meeting less than 40%, and quantizing the 6-level wavelet coefficient D X obtained in step 2, wherein x=1, 2 … … 6 and the 1-level scale coefficient A 6 to obtain quantized wavelet coefficients D 'x and scale coefficient A' 6. And (4) switching to step 4.
And 4, splicing the quantized wavelet coefficient D 'x and the quantized scale coefficient A' 6 to obtain spliced data, and transferring to the step 5.
Since the bus width of the missile-borne computer is 32 bits, the number of bits written in each time of the missile-borne computer is 32 bits when the data is written. When the data bits of the written data are less than the bus width, the computer still writes 32 bits, but specifies the number of valid bits. Splicing the quantized wavelet coefficients and scale coefficients of each level obtained in the step 3, splicing a plurality of data into one data, so that the data bit is equal to the bus width of a computer, and writing the plurality of data once when the computer writes each time, thereby improving the bus bandwidth and increasing the data transmission rate:
newWord＝12a0+8a1+4a2
In the above formula, a 0、a1、a2 is the data number after 12bit, 8bit and 4bit quantization respectively, satisfies:
12a0+8a1+4a2＝32
at this time, the bus bandwidth can be increased by a 0+a1+a2 times as much as the original one.
And 5, performing wavelet reconstruction on the spliced data to obtain a reconstructed signal A' 0, namely a compressed signal.
Example 1
Referring to fig. 1, a method for compressing signal data detected by a missile-borne probe includes the steps of:
Step 1, a missile-borne detector obtains a one-dimensional waveform signal; the signal has a targeted waveform in the form of a bell pulse, and the non-targeted waveform is a small fluctuation at a fixed voltage, as shown in fig. 2; it is converted to a 16bit (data point) digital signal a 0 by the ADC of the missile-borne computer, and the process proceeds to step 2.
And 2, carrying out 6-layer wavelet decomposition on the digital signal A 0 to obtain a 6-level wavelet coefficient D 1～D6 and a 1-level scale coefficient A 6, wherein 'db 4' wavelet is selected as a wavelet base when the wavelet decomposition is carried out, and the number of decomposition layers is 6. The sixth layer wavelet coefficient and scale coefficient obtained by decomposition are shown in fig. 2. The data bit width of the digital signal A 0 is 16 bits; the bit width of each level of coefficients obtained through decomposition is the same as the bit width of the data point of the digital signal A 0, and is 16 bits, and the sum of the points of each level of coefficients obtained through decomposition is equal to the number of the data points of the digital signal A 0; and (3) switching to step 3.
Step 3, performing low-order width quantization on the wavelet coefficient D 1～D6 and the scale coefficient a 6 obtained in step 2, to obtain a quantized wavelet coefficient D "1～D″6 and a quantized scale coefficient a" 6, which are specifically as follows:
Step 3-1, respectively calculating the information entropy Q Dx of the wavelet coefficient D x and the information entropy Q A6 of the level 1 scale coefficient a 6:
wherein, L Dx、LA6 is the total number of possible values in the wavelet coefficient or scale coefficient, and the values are related to the waveform amplitude range; p i is the ratio of the number of data points of the wavelet coefficient or scale coefficient with a value equal to i to the total number of data points.
Step 3-2, respectively carrying out low-order width quantization on the 6-level wavelet coefficient D x and the 1-level scale coefficient A 6 to obtain a wavelet coefficient D 'x and a scale coefficient A' 6 which are expressed by the low-order width:
Wherein y Dx is the low-order width selected by the wavelet coefficient of the x-th layer, y 6 is the low-order width selected by the scale coefficient of the 6-th layer, and different low-order widths of the scale coefficient A 6 represent the results shown in FIG. 3.
Step 3-3, respectively calculating the information entropy Q 'Dx of the wavelet coefficient D' x represented by the low-order width and the information entropy Q 'A6 of the scale coefficient a' 6 represented by the low-order width:
where L Dx′ is the total number of values that may occur in the x-th layer wavelet coefficient represented by the low-order width, and L A6′ is the total number of values that may occur in the 6-th layer scale coefficient represented by the low-order width.
Step 3-4, calculating the loss amount loss Dx of the information entropy Q Dx of the wavelet coefficient and the information entropy Q 'Dx of the wavelet coefficient represented by the low-order width, and the loss amount loss A6 of the information entropy Q A6 of the scale coefficient and the information entropy Q' A6 of the scale coefficient represented by the low-order width under different low-order width representations:
in order to ensure that the reconstructed waveform is not severely distorted, the quantized information entropy loss should satisfy loss <40%.
Step 3-5, introducing a compression ratio CPR to measure the compression effect, and measuring the compression condition meeting the information entropy loss less than 40 percent:
In the above formula, N is the data amount which is not represented by the low bit width, and K is the data amount which is represented by the low bit width; wherein:
In the above formula, N Dx is the storage space occupied by the x-th layer wavelet coefficient after wavelet decomposition of the data not represented by the low-order width, and N A6 is the storage space occupied by the 6-th layer scale coefficient after wavelet decomposition of the data not represented by the low-order width; k Dx is the storage space occupied by the x-th layer wavelet coefficient after low-bit width representation, K A6 is the storage space occupied by the 6-th layer scale coefficient after low-bit width representation, and N Dx、NA6 and K Dx、KA6 satisfy:
KDx＝yDxNDx
KA6＝yA6NA6
Wherein y Dx and y A6 are respectively the low-order width selected by the wavelet coefficient of the x-th layer and the low-order width selected by the scale coefficient of the 6-th layer.
Step 3-6, selecting a low bit width representation combination with the maximum compression ratio and meeting less than 40%, and quantizing the 6-level wavelet coefficient D x obtained in step 2, wherein x=1, 2 … … 6 and the 1-level scale coefficient A 6 to obtain quantized wavelet coefficients D 'x and scale coefficient A' 6.
Through the above steps, the wavelet coefficient D 1、D2 is selected for 4-bit quantization, the wavelet coefficient D 3、D4 is 8-bit quantized, and the wavelet coefficient D 5、D6 and the scale coefficient a 6 are 12-bit quantized. Because the original data bit width is 16 bits, the quantized data bit width is reduced under the condition of the same number of points, the data volume is wholly reduced, and the data compression is realized; and (4) switching to step 4.
And 4, splicing the quantized wavelet coefficient D '1～D″6 and the quantized scale coefficient A' 6 to obtain spliced data, wherein the spliced data are used for transmitting and storing data of a missile-borne detection system, and the method comprises the following steps of:
since the bus width of the missile-borne computer is 32 bits, the number of bits written in each time of the missile-borne computer is 32 bits when the data is written. When the data bits of the written data are less than the bus width, the computer still writes 32 bits, but specifies the number of valid bits. Splicing the quantized wavelet coefficients and scale coefficients of each level obtained in the step 3, splicing a plurality of data into one data, so that the data bit is equal to the bus width of a computer, and writing the plurality of data once when the computer writes each time, thereby improving the bus bandwidth and increasing the data transmission rate:
newWord＝12a0+8a1+4a2
In the above formula, a 0、a1、a2 is the data number after 12bit, 8bit and 4bit quantization respectively, satisfies:
12a0+8a1+4a2＝32
at this time, the bus bandwidth can be improved to a 0+a1+a2 times of the original bandwidth; turning to step 5;
And 5, receiving the transmission data in the step 4 by the data receiving end, and performing wavelet reconstruction to obtain a reconstructed signal A' 0. Data compression is carried out on the data acquired by the missile-borne detector, and three target waveforms are intercepted as analysis objects for convenience of description. Comparing the original data waveform with the reconstructed waveform obtained after compression, the result is shown in fig. 4, and the waveform can be found to be undistorted. The distortion degree and the compression effect are measured by introducing a Mean Square Error (MSE) and a compression ratio (CPR), after compression, CPR=3.0476 and MES=2.15×10 -8, the compression effect is good, and the distortion degree is low.

Claims (1)

1. A method for compressing signal data detected by a missile-borne detector, comprising the steps of:
Step 1, a one-dimensional waveform signal is detected by a missile-borne detector and is converted into a 16-bit digital signal A 0, and the step 2 is carried out;
Step 2, performing 6-layer wavelet decomposition on the 16-bit digital signal to obtain a 6-level wavelet coefficient D x and a 1-level scale coefficient A 6, wherein the wavelet coefficient serial number x=1, 2 … … 6, and turning to step 3;
Step 3, respectively carrying out low-order width quantization on the wavelet coefficient D x and the 1-level scale coefficient A 6, namely, representing a 16-bit data point by 12 bits, 8 bits or 4 bits to obtain a quantized wavelet coefficient D 'x and a quantized scale coefficient A' 6; turning to step 4;
Step 4, splicing the quantized wavelet coefficient D 'x and the quantized scale coefficient A' 6 to obtain spliced data, and transferring to step 5;
Step 5, carrying out wavelet reconstruction on the spliced data to obtain a reconstructed signal A' 0, namely a compressed signal;
the wavelet base of the wavelet decomposition in the step 2 is db4 wavelet;
In the step 3, the 6-level wavelet coefficient D x and the 1-level scale coefficient a 6 are quantized in low-level width, that is, the 16-bit data point is represented by 12bit, 8bit or 4bit, so as to obtain the quantized wavelet coefficient D "x and scale coefficient a" 6, which are specifically as follows:
Step 3-1, respectively calculating the information entropy Q Dx of the wavelet coefficient D x and the information entropy Q A6 of the level 1 scale coefficient a 6:
Wherein, L Dx、LA6 is the total number of possible values in the wavelet coefficient or scale coefficient, and the values are related to the waveform amplitude range; p i is the ratio of the number of data points with the value equal to i in the wavelet coefficient or the scale coefficient to the total number of data points;
Step 3-2, respectively carrying out low-order width quantization on the 6-level wavelet coefficient D x and the 1-level scale coefficient A 6 to obtain a wavelet coefficient D 'x and a scale coefficient A' 6 which are expressed by the low-order width:
Wherein y Dx is the low-order width selected by the x-th layer wavelet coefficient, and y 6 is the low-order width selected by the 6-th layer scale coefficient;
Step 3-3, respectively calculating the information entropy Q 'Dx of the wavelet coefficient D' x represented by the low-order width and the information entropy Q 'A6 of the scale coefficient a' 6 represented by the low-order width:
Where L Dx' is the total number of values that may occur in the x-th layer wavelet coefficient represented by the low-order width, and L A6' is the total number of values that may occur in the 6-th layer scale coefficient represented by the low-order width;
Step 3-4, calculating the loss amount loss Dx of the information entropy Q Dx of the wavelet coefficient and the information entropy Q 'Dx of the wavelet coefficient represented by the low-order width, and the loss amount loss A6 of the information entropy Q A6 of the scale coefficient and the information entropy Q' A6 of the scale coefficient represented by the low-order width under different low-order width representations:
in order to ensure that the reconstructed waveform is not severely distorted, the quantized information entropy loss should satisfy loss <40%;
Step 3-5, introducing a compression ratio CPR to measure the compression effect, and measuring the compression condition meeting the information entropy loss less than 40 percent:
In the above formula, N is the data amount which is not represented by the low bit width, and K is the data amount which is represented by the low bit width; wherein:
In the above formula, N Dx is the storage space occupied by the x-th layer wavelet coefficient after wavelet decomposition of the data not represented by the low-order width, and N A6 is the storage space occupied by the 6-th layer scale coefficient after wavelet decomposition of the data not represented by the low-order width; k Dx is the storage space occupied by the x-th layer wavelet coefficient after low-bit width representation, K A6 is the storage space occupied by the 6-th layer scale coefficient after low-bit width representation, and N Dx、NA6 and K Dx、KA6 satisfy:
KDx＝yDxNDx
KA6＝yA6NA6
Wherein y Dx and y A6 are respectively the low-order width selected by the x-th layer wavelet coefficient and the low-order width selected by the 6-th layer scale coefficient;
And 3-6, selecting a low-bit-width representation combination with the maximum compression ratio and meeting less than 40% to quantize the 6-level wavelet coefficient D x and the 1-level scale coefficient A 6 obtained in the step 2, and obtaining a quantized wavelet coefficient D 'x and a quantized scale coefficient A' 6.
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