CN113092382A - Fourier transform spectrometer on-satellite data lossless compression method and system - Google Patents
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Abstract
The invention provides a lossless compression method and a lossless compression system for satellite data of a Fourier transform spectrometer, wherein the lossless compression method comprises the following steps: step S1: performing complex finite-length unit impulse response band-pass filtering on the on-orbit pair interferogram, and synchronously performing down-sampling; step S2: carrying out segmented bit truncation on the down-sampled complex interference image; step S3: packing the truncated interferogram and transmitting the packed interferogram to the ground; step S4: analyzing the received compressed data on the ground, and carrying out phase modulation on the interferogram; step S5: and calculating a plurality of spectrograms and corresponding to the actual spectral channels to obtain the information of the lossless compression result of the satellite data of the Fourier transform spectrometer. According to the method for lossless compression of the satellite data, the satellite performs band-pass filtering, down-sampling and bit truncation on the interference pattern, so that the data volume of a Fourier transform spectrometer is effectively reduced, phase modulation and spectrum correspondence of the interference pattern are performed on the ground, and spectrum information is restored.
Description
Technical Field
The invention relates to the technical field of remote sensing data processing, in particular to a Fourier transform spectrometer on-satellite data lossless compression method and system.
Background
The Fourier transform spectrometer has the characteristics of multiple spectrum channels, high spectral resolution, high signal-to-noise ratio and the like, can be used for fine spectrum detection and imaging, and can be used for measuring the radiation values of the earth surface or the atmosphere in different spectrum channels and acquiring cubic data of two dimensions of space and one dimension of spectrum. The Fourier transform spectrometer has great difficulty in satellite-to-ground transmission due to large on-track data acquisition amount, and the Fourier transform spectrometer has certain information redundancy in a data cube, so that the data amount and the code rate can be reduced in an on-satellite compression processing mode.
A lossy compression method based on wavelet transform for a static interference imaging spectrometer is given in the document 'application of self-adaptive lifting wavelet in interference hyperspectral compression'. In order not to affect the high-precision and quantitative application of the fourier transform spectrometer, a lossless compression method needs to be researched. The existing lossless compression methods are all segmented processing methods, data near zero optical path difference are not compressed, and only interference signals with large optical path difference are compressed.
The literature, interference type hyperspectral imager data compression method, samples DPCM (differential pulse code modulation) on a part with large optical path difference. Patent document, "lossless real-time compression method of satellite-borne hyperspectral interference fringe image", compresses interference signals with large optical path difference, and performs decorrelation difference calculation first and then lossless quantization or non-uniform quantization compression. In the literature, "study on lossless compression based on single-frame interferograms", entropy encoding compression is performed on interference signals having large optical path differences. The segmentation processing method cannot achieve a high compression ratio, and the data volume is increased rapidly with the further improvement of the spatial resolution and the spectral resolution of the Fourier transform spectrometer, so that a satellite data compression method with a larger compression ratio needs to be sought.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a lossless compression method and system for satellite data of a Fourier transform spectrometer.
The invention provides a Fourier transform spectrometer satellite data lossless compression method, which comprises the following steps:
step S1: performing complex finite-length unit impulse response (FIR) band-pass filtering on the on-track pair interferogram, synchronously performing down-sampling, and acquiring complex interferogram information with the sampling rate smaller than a set threshold value;
step S2: according to the complex interference image information with the sampling rate smaller than the set threshold, carrying out segmented bit truncation on the down-sampled complex interference image to obtain segmented bit truncation result information;
step S3: packing and downloading the truncated interferogram to the ground according to the segmentation bit truncation result information to obtain packed and downloaded ground result information;
step S4: analyzing the received compressed data on the ground according to the packed and downloaded ground result information, and carrying out phase modulation on the interferogram to obtain phase modulation result information;
step S5: and calculating a plurality of spectrograms according to the phase modulation result information and corresponding to the actual spectrum channel to obtain the on-satellite data lossless compression result information of the Fourier transform spectrometer.
Preferably, the step S1 includes:
step S1.1: the down-sampling factor D is calculated by the following formula:
wherein the effective spectral range of the Fourier transform spectrometer is sigma1～σ2The original sampling frequency is σs，
Representing a floor function.
Step S1.2: the low end cut-off frequency σ of the FIR band-pass filter is determined by the following formulac1And high end cut-off frequency sigmac2：
Preferably, the step S1 further includes:
step S1.3: for the FIR band-pass filter, a weighted Chebyshev ripple approximation criterion is adopted, and if the order of the band-pass filter is N, N +1 filter coefficients bi(i-0, 1,2, …, N) is stored on the satellite storage medium and the following calculations are performed on the satellite:
where I is the original interferogram and B is the filter coefficient matrix, i.e. B ═ B0,b1,b2,…,bN],
Convolution is represented, but convolution operation does not need to be calculated according to an original sampling interval, calculation is carried out only by taking a down-sampling factor D as an interval, and the on-satellite operation times are reduced; f is the filtered and down-sampled complex interferogram.
Preferably, the step S2 includes:
step S2.1: the truncation mode is set according to the characteristics of the observed target, generally, the number of bits needed by the sampling point near the zero optical path difference is large, and the number of bits needed by the sampling point far away from the zero optical path difference is small. And the on-track adjustment of the truncation setting value can be performed through an instruction.
Preferably, the step S4 includes:
step S4.1: the phase modulation is performed as follows:
wherein F (n) represents the nth point in the interference pattern F, j is an imaginary unit, j2The symbol "G" (n) denotes the nth point in the phase-modulated interferogram "G".
The invention provides a Fourier transform spectrometer on-satellite data lossless compression system, which comprises:
module M1: performing complex finite-length unit impulse response (FIR) band-pass filtering on the on-track pair interferogram, synchronously performing down-sampling, and acquiring complex interferogram information with the sampling rate smaller than a set threshold value;
module M2: according to the complex interference image information with the sampling rate smaller than the set threshold, carrying out segmented bit truncation on the down-sampled complex interference image to obtain segmented bit truncation result information;
module M3: packing and downloading the truncated interferogram to the ground according to the segmentation bit truncation result information to obtain packed and downloaded ground result information;
module M4: analyzing the received compressed data on the ground according to the packed and downloaded ground result information, and carrying out phase modulation on the interferogram to obtain phase modulation result information;
module M5: and calculating a plurality of spectrograms according to the phase modulation result information and corresponding to the actual spectrum channel to obtain the on-satellite data lossless compression result information of the Fourier transform spectrometer.
Preferably, said module M1 comprises:
module M1.1: the down-sampling factor D is calculated by the following formula:
wherein the effective spectral range of the Fourier transform spectrometer is sigma1～σ2The original sampling frequency is σs，
Representing a floor function.
Module M1.2: the low end cut-off frequency σ of the FIR band-pass filter is determined by the following formulac1And high end cut-off frequency sigmac2：
Preferably, the module M1 further includes:
module M1.3: for the FIR band-pass filter, a weighted Chebyshev ripple approximation criterion is adopted, and if the order of the band-pass filter is N, N +1 filter coefficients bi(i-0, 1,2, …, N) is stored on the satellite storage medium and the following calculations are performed on the satellite:
where I is the original interferogram and B is the filter coefficient matrix, i.e. B ═ B0,b1,b2,…,bN],
Representing convolution, but the convolution operation does not need to be calculated according to the original sampling interval, only needs to be calculated according to a down-sampling factorD is interval calculation, and the on-satellite operation times are reduced; f is the filtered and down-sampled complex interferogram.
Preferably, said module M2 comprises:
module M2.1: the truncation mode is set according to the characteristics of the observed target, generally, the number of bits needed by the sampling point near the zero optical path difference is large, and the number of bits needed by the sampling point far away from the zero optical path difference is small. And the on-track adjustment of the truncation setting value can be performed through an instruction.
Preferably, said module M4 comprises:
module M4.1: the phase modulation is performed as follows:
wherein F (n) represents the nth point in the interference pattern F, j is an imaginary unit, j2The symbol "G" (n) denotes the nth point in the phase-modulated interferogram "G".
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method for lossless compression of the satellite data, the satellite performs band-pass filtering, down-sampling and bit truncation on the interference pattern, so that the data volume of a Fourier transform spectrometer is effectively reduced, phase modulation and spectrum correspondence of the interference pattern are performed on the ground, and spectrum information is restored.
2. The method is reasonable, simple and easy to implement, can obtain a better compression ratio than the prior art, and has wide application prospect.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic flow diagram of the overall process of the present invention;
FIG. 2 is a schematic diagram of the amplitude-frequency response of a band-pass filter used for on-satellite compression of a Fourier transform spectrometer in an embodiment of the invention;
FIG. 3 is a schematic diagram of a comparison between a complex interferogram after satellite down-sampling and an original interferogram of a Fourier transform spectrometer according to an embodiment of the invention;
FIG. 4 is a schematic diagram of a bit-truncation setting on a satellite of a Fourier transform spectrometer in an embodiment of the invention;
fig. 5 is a schematic diagram showing a comparison between a spectrum restored by an interference pattern compressed on a satellite and an original spectrum in a fourier transform spectrometer according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
As shown in FIGS. 1-5, a theoretical analysis basis introduction applicable to the on-board data lossless compression method of Fourier transform spectrometer is as follows: generally, Fourier transform spectrometers are all systems with limited spectral bandwidth (if the effective spectral range is σ)1～σ2) In the sampling process, in order to satisfy the Nyquist sampling law, the sampling frequency σ is requiredsSatisfies the following conditions: sigmas≥2σ2. For systems where the signal itself has a bandpass characteristic, a low sampling frequency can be used without spectral aliasing.
The minimum sampling frequency can be set to (σ)2-σ1) I.e. the down-sampling factor D is maximum:
because the actual fourier transform spectrometer is outside the effective spectral range, there may still be some noise, and in order to avoid the noise being amplified during the down-sampling process, prior to the down-sampling, the bandpass filtering is performed according to the effective spectral range. Low end cut-off frequency sigma of band-pass filterc1And high end cut-off frequency sigmac2Is determined by the following formulaDetermining:
according to cut-off frequency, calculating the coefficient of the band-pass filter by adopting a weighted Chebyshev and other ripple approximation criteria in advance, and if the order of the band-pass filter is N, then N +1 filter coefficients bi(I ═ 0,1,2, …, N) is stored in the on-board storage medium, and the raw interferogram I acquired on-track pair is subjected to the following calculation:
where I is the original interferogram and B is the filter coefficient matrix, i.e. B ═ B0,b1,b2,…,bN],
The convolution is represented, but the convolution operation does not need to be calculated according to the original sampling interval, and only needs to be calculated by taking the down-sampling factor D as the interval, so that the on-satellite operation times are reduced. F is the filtered and down-sampled complex interferogram.
Compared with the original interferogram I, the data volume of the filtered and down-sampled complex interferogram F is reduced to original D/2. Generally, in a common Fourier transform spectrometer, D is about 10-30, so that the data rate can be effectively compressed.
For the filtered and down-sampled complex interferogram F, the signal still has the characteristics of large amplitude of the zero-optical-path-difference accessory signal and small amplitude of the signal at the position with large optical-path difference, so that the characteristic can be utilized for further compression.
In order to ensure that the final spectrogram is not distorted, a bit truncation mode is adopted, namely, the data with smaller signals adopt low quantization bits, the data with larger signals adopt high quantization bits, and the highest quantization bits are adopted near zero optical path difference. By bit-truncated compression, the data can be compressed by a factor of about 2.
Due to the fixed filter coefficients, ripple effects on the effective spectral range can be eliminated by radiometric calibration.
Since in the down-sampling process the original spectrum is being sampled at the new sampling frequency σsthe/D folding causes a frequency shift in the calculated spectrogram from the complex interferogram F. To avoid this effect, the interferogram F may be phase modulated, and according to the nature of discrete fourier transform, the calculation method is as follows:
wherein F (n) represents the nth point in the interference pattern F, and j is an imaginary unit (j)2G (n) is the nth point in the phase-modulated interferogram G (1).
Spectral range 0-sigma of modulated interferogram GsD is corresponding to σc1～σc2。
The implementation process of the invention is described below with reference to an interference diagram of a Fourier transform spectrometer, wherein the effective spectral range of a Fourier transform spectrometer is 596-1222 cm-1Original sampling frequency 11737cm-1The down-sampling factor D is 18.
The original interferogram 18972 sampling points are quantized by 16 bits, and the data volume of the single-frame interferogram is 37944 Byte. The equivalent response of the bandpass filter in step 1 is shown in fig. 2, according to the method of the invention. After down-sampling in step 1, the complex interferogram is shown in fig. 3. The data in fig. 3 is segmented and bit-truncated, the truncation is set as shown in fig. 4, and for the vicinity of zero optical path difference, 16-bit quantization is still reserved, i.e. it can represent that there is a coincidence signal range of-215～215-1. And the positions far away from the zero optical path difference are respectively quantized by 12 bits, 11 bits and 10 bits. After compression, the data size of the single-frame interferogram on the satellite is compressed from 37944Byte to 2999Byte, and the compression ratio is larger than 12.
The spectrum of the compressed data is restored according to the method of the invention, and the spectrum comparison result of the discrete Fourier transform of the restored spectrum and the original 18972 sample point interferogram is shown in FIG. 5. As can be seen from fig. 5, the compressed data can faithfully reflect the spectral information of the original interferogram.
In the description of the present application, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present application.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. A Fourier transform spectrometer on-satellite data lossless compression method is characterized by comprising the following steps:
step S1: performing complex finite-length unit impulse response band-pass filtering on the on-track pair interferogram, synchronously performing down-sampling, and acquiring complex interferogram information with the sampling rate smaller than a set threshold value;
step S2: according to the complex interference image information with the sampling rate smaller than the set threshold, carrying out segmented bit truncation on the down-sampled complex interference image to obtain segmented bit truncation result information;
step S3: packing and downloading the truncated interferogram to the ground according to the segmentation bit truncation result information to obtain packed and downloaded ground result information;
step S4: analyzing the received compressed data on the ground according to the packed and downloaded ground result information, and carrying out phase modulation on the interferogram to obtain phase modulation result information;
step S5: and calculating a plurality of spectrograms according to the phase modulation result information and corresponding to the actual spectrum channel to obtain the on-satellite data lossless compression result information of the Fourier transform spectrometer.
2. The method for lossless compression of data on a fourier transform spectrometer satellite as claimed in claim 1, wherein the step S1 comprises:
step S1.1: the down-sampling factor D is calculated by the following formula:
wherein the effective spectral range of the Fourier transform spectrometer is sigma1～σ2The original sampling frequency is σs，
Represents a floor function;
step S1.2: the low end cut-off frequency σ of the FIR band-pass filter is determined by the following formulac1And high end cut-off frequency sigmac2：
Wherein the effective spectral range of the Fourier transform spectrometer is sigma1～σ2The original sampling frequency is σs(ii) a The down-sampling factor is D.
3. The method for lossless compression of data on a fourier transform spectrometer satellite as claimed in claim 2, wherein the step S1 further comprises:
step S1.3: for the FIR band-pass filter, a weighted Chebyshev ripple approximation criterion is adopted, and if the order of the band-pass filter is N, N +1 filter coefficients bi(ii) a i is 0,1,2, …, N; stored in an on-board storage medium, the following calculations are performed on the board:
where I is the original interferogram and B is the filter coefficient matrix, i.e. B ═ B0,b1,b2,…,bN],
Convolution is represented, but convolution operation does not need to be calculated according to an original sampling interval, calculation is carried out only by taking a down-sampling factor D as an interval, and the on-satellite operation times are reduced; f is the filtered and down-sampled complex interferogram.
4. The method for lossless compression of data on a fourier transform spectrometer satellite as claimed in claim 1, wherein the step S2 comprises:
step S2.1: and setting an interception mode according to the characteristics of the observation target.
5. The method for lossless compression of data on a fourier transform spectrometer satellite as claimed in claim 1, wherein the step S4 comprises:
step S4.1: the phase modulation is performed as follows:
wherein F (n) represents the nth point in the interference pattern F, j is an imaginary unit, j2The symbol "G" (n) denotes the nth point in the phase-modulated interferogram "G".
6. A Fourier transform spectrometer on-satellite data lossless compression system is characterized by comprising:
module M1: performing complex finite-length unit impulse response band-pass filtering on the on-track pair interferogram, synchronously performing down-sampling, and acquiring complex interferogram information with the sampling rate smaller than a set threshold value;
module M2: according to the complex interference image information with the sampling rate smaller than the set threshold, carrying out segmented bit truncation on the down-sampled complex interference image to obtain segmented bit truncation result information;
module M3: packing and downloading the truncated interferogram to the ground according to the segmentation bit truncation result information to obtain packed and downloaded ground result information;
module M4: analyzing the received compressed data on the ground according to the packed and downloaded ground result information, and carrying out phase modulation on the interferogram to obtain phase modulation result information;
module M5: and calculating a plurality of spectrograms according to the phase modulation result information and corresponding to the actual spectrum channel to obtain the on-satellite data lossless compression result information of the Fourier transform spectrometer.
7. The Fourier transform spectrometer on-board data lossless compression system of claim 1, wherein the module M1 includes:
module M1.1: the down-sampling factor D is calculated by the following formula:
wherein the effective spectral range of the Fourier transform spectrometer is sigma1～σ2The original sampling frequency is σs，
Represents a floor function;
module M1.2: the low end cut-off frequency σ of the FIR band-pass filter is determined by the following formulac1And high end cut-off frequency sigmac2：
Wherein the effective spectral range of the Fourier transform spectrometer is sigma1～σ2The original sampling frequency is σs(ii) a The down-sampling factor is D.
8. The Fourier transform spectrometer on-satellite data lossless compression system of claim 7, wherein the module M1 further comprises:
module M1.3: for the FIR band-pass filter, a weighted Chebyshev ripple approximation criterion is adopted, and if the order of the band-pass filter is N, N +1 filter coefficients bi(ii) a i is 0,1,2, …, N; stored in an on-board storage medium, the following calculations are performed on the board:
where I is the original interferogram and B is the filter coefficient matrix, i.e. B ═ B0,b1,b2,…,bN],
Convolution is represented, but convolution operation does not need to be calculated according to an original sampling interval, calculation is carried out only by taking a down-sampling factor D as an interval, and the on-satellite operation times are reduced; f is the filtered and down-sampled complex interferogram.
9. The Fourier transform spectrometer on-board data lossless compression system of claim 6, wherein the module M2 includes:
module M2.1: and setting an interception mode according to the characteristics of the observation target.
10. The Fourier transform spectrometer on-board data lossless compression system of claim 6, wherein the module M4 includes:
module M4.1: the phase modulation is performed as follows:
wherein F (n) represents the nth point in the interference pattern F, j is an imaginary unit, j2The symbol "G" (n) denotes the nth point in the phase-modulated interferogram "G".
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