CN111580068A - Remote sensing data processing method based on satellite laser radar technology - Google Patents
Remote sensing data processing method based on satellite laser radar technology Download PDFInfo
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- 238000005516 engineering process Methods 0.000 title claims abstract description 26
- 238000003672 processing method Methods 0.000 title claims abstract description 8
- 238000001514 detection method Methods 0.000 claims abstract description 30
- 238000010835 comparative analysis Methods 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 18
- 238000000354 decomposition reaction Methods 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 4
- 238000002790 cross-validation Methods 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 238000012706 support-vector machine Methods 0.000 claims description 3
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
- G06F18/24147—Distances to closest patterns, e.g. nearest neighbour classification
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Abstract
The invention provides a remote sensing data processing method based on a satellite laser radar technology, which is characterized in that the satellite laser radar technology is utilized to carry out remote sensing detection on a target detection area to obtain remote sensing data; converting the amplitude of the waveform from an original intensity value counting mode to a voltage value, and then amplifying and filtering the voltage value signal to improve the intensity of waveform data; selecting all parameters to obtain optimal parameters, obtaining a waveform result under the optimal parameters, and extracting the characteristics of the decomposed waveform; and acquiring historical data of the target detection area, and performing comparative analysis. According to the invention, the amplifier is used for amplifying and the high-low pass filter is used for filtering, so that a frequency point with a specific frequency or frequencies except the frequency point can be effectively filtered, a voltage signal with the specific frequency is obtained, or the voltage signal with the specific frequency is eliminated, the output voltage ripple coefficient is reduced, the waveform becomes smoother, and the remote sensing detection accuracy is improved.
Description
Technical Field
The invention relates to the technical field of remote sensing data processing, in particular to a remote sensing data processing method based on a satellite laser radar technology.
Background
The remote sensing is understood as remote sensing, which means that a sensor acquires electromagnetic wave information of a target object in a non-contact manner, and spatial distribution characteristics and a temporal-spatial change rule of each element on the earth surface are qualitatively and quantitatively revealed through transmission, transformation and processing of the electromagnetic wave information. According to the different signal modes obtained by remote sensing, namely the difference of electromagnetic radiation energy, the remote sensing can be divided into passive remote sensing and active remote sensing, wherein an active remote sensing system is provided with an artificial radiation source for emitting electromagnetic waves in a certain form to a target object, and then a sensor receives and records reflected waves of the electromagnetic waves. The existing synthetic aperture radar, ground penetrating radar, laser radar and the like belong to active remote sensing systems.
The active remote sensing technology has the advantages of being independent of solar radiation, capable of working day and night, capable of selecting the wavelength and the emission mode of electromagnetic waves according to different detection targets and the like, and is developed rapidly in the field of remote sensing technology. The laser radar technology is a main branch of the active remote sensing technology, and can analyze information such as the size of reflection energy on the surface of a target ground object, the amplitude, the frequency, the phase and the like of a reflection spectrum by measuring the propagation distance of laser emitted by a sensor between the sensor and the target object, accurately resolve target positioning information, and present accurate three-dimensional structure information of the target object.
In the prior art, the remote sensing data is easily interfered by the outside and the signal intensity is unstable in the processing process, so that the accuracy of remote sensing detection is not high. The time-frequency analysis method can reduce the influence on the accuracy of data caused by the external interference of the waveform signals to the maximum extent, effectively obtains more reliable and more effective test data, and is widely applied to remote sensing data processing based on the satellite laser radar technology. However, when the time-frequency analysis method is applied to remote sensing data processing based on the satellite laser radar technology, frequency points with part of frequencies or frequencies except the frequency points cannot be effectively filtered, so that the result of remote sensing detection is influenced; in addition, some weak but critical signals are easily ignored, resulting in the loss of signals.
Disclosure of Invention
The invention provides a remote sensing data processing method based on a satellite laser radar technology, which aims to solve the problems that a certain part of frequency points cannot be effectively filtered and weak key signals are ignored, so that a remote sensing detection result is influenced.
The invention relates to a remote sensing data processing method based on a satellite laser radar technology, which specifically comprises the following steps:
s101, establishing a satellite remote communication system;
s102, acquiring coordinates of a detection area, and performing remote sensing detection on the detection area based on a satellite laser radar technology;
s103, realizing data transmission by using the satellite telecommunication system, and acquiring a plurality of original waveforms of the detection area;
s104, preprocessing the original waveforms, and converting the amplitudes of the original waveforms into voltage values to count;
s105, amplifying and processing the electrical frequency of the original waveforms;
s106, normalizing the original waveforms processed in S104 and S105, and performing comparative analysis;
s107, respectively carrying out histogram statistics on the voltage values of the original waveforms after the normalization processing, and carrying out optimal Gaussian function fitting to obtain real and effective signals;
s108, performing convolution operation on the planar standard echo waveform and the original waveforms processed in the S107 respectively;
s109, carrying out Gaussian decomposition on a plurality of original waveforms processed in the S108, and fitting the waveforms subjected to Gaussian decomposition by adopting a nonlinear least square method;
s110, initially estimating parameters of a standard Gaussian function, selecting optimal parameters, and acquiring waveform data under the optimal parameters;
s111, performing feature extraction on the waveform data under the optimal parameters by adopting a classifier, and analyzing the terrain features in the corresponding light spots;
and S112, acquiring historical waveform data in the detection area, and performing comparative analysis.
By adopting the technical scheme, in S108, because the original waveform is easily influenced by the terrain and greatly influences the actual waveform signal effect, the standard waveform data of the plane is required to be used as a template, and then convolution operation is performed on the standard waveform data and the original waveform processed in S107 to delete the waveform with saturated signal and excessive noise, and the obtained data is more comprehensive and has a wider range.
Optionally, in S105, a programmable gain amplifier is used to amplify the electrical frequency, and a high-low pass filter is used to process the electrical signal.
By adopting the technical scheme, the frequency points of a certain part of frequencies or frequencies except the frequency points can be effectively filtered through the amplifier, and the condition that weak key signals can be ignored is avoided by processing the electric signals through the high-low pass filter.
Optionally, in S107, acquiring the real and effective signal specifically includes:
taking the expectation and the variance after the optimal Gaussian function fitting as the mean and the variance of the background noise;
estimating and eliminating the background noise signal;
and acquiring a real effective signal.
By adopting the technical scheme, because the sensor and factors such as atmospheric scattering can cause noise influence, the background noise needs to be estimated and removed to obtain the effective signal.
Optionally, in S110, the parameters of the standard gaussian function include an amplitude, a gaussian position, and a pulse width, and an optimal parameter is selected through a cross-validation method.
Optionally, in S111, the classifier includes a nearest neighbor classifier or a support vector machine classifier.
Optionally, a plurality of the original waveforms are all composed of 544 frames of data, where each frame of data stores an echo intensity count value received at a corresponding time.
Optionally, the coordinates of the detection area are composed of longitude and latitude.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, original waveform data is preprocessed and converted into a voltage value, an amplifier is used for amplifying an electric signal, and meanwhile, a high-low pass filter is used for filtering, so that a frequency point with a specific frequency or an unexpected frequency of the frequency point can be effectively filtered, a voltage signal with the specific frequency is obtained, or the voltage signal with the specific frequency is eliminated, the output voltage ripple coefficient is reduced, the waveform becomes smoother, and the signal intensity is enhanced and the accuracy of remote sensing detection is improved through amplification and filtering.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of a method for processing remote sensing data according to the present invention.
Detailed Description
The invention provides a remote sensing data processing method based on a satellite laser radar technology, which comprises the steps of firstly, carrying out remote sensing detection on a target detection area by utilizing the satellite laser radar technology, and acquiring remote sensing data through a satellite communication technology; then, through preprocessing, the amplitude of the waveform is converted into a voltage value from an original intensity value counting mode, and then the voltage value signal is amplified and filtered to improve the intensity of waveform data; secondly, selecting all parameters by adopting a cross validation method to obtain optimal parameters, taking a waveform result under the optimal parameters as a final result, and extracting the characteristics of the decomposed waveform by adopting a classifier so as to analyze the topographic characteristics in the corresponding light spots; and finally, acquiring historical data of the target detection area, and performing comparative analysis.
Referring to fig. 1, the method for processing remote sensing data based on the satellite laser radar technology specifically comprises the following steps:
s101, establishing a satellite remote communication system;
s102, acquiring coordinates of a detection area, and performing remote sensing detection on the detection area based on a satellite laser radar technology;
s103, realizing data transmission by using the satellite telecommunication system, and acquiring a plurality of original waveforms of the detection area;
s104, preprocessing the original waveforms, and converting the amplitudes of the original waveforms into voltage values to count;
s105, amplifying and processing the electrical frequency of the original waveforms;
s106, normalizing the original waveforms processed in S104 and S105, and performing comparative analysis;
s107, respectively carrying out histogram statistics on the voltage values of the original waveforms after the normalization processing, and carrying out optimal Gaussian function fitting to obtain real and effective signals;
s108, performing convolution operation on the planar standard echo waveform and the original waveforms processed in the S107 respectively;
s109, carrying out Gaussian decomposition on a plurality of original waveforms processed in the S108, and fitting the waveforms subjected to Gaussian decomposition by adopting a nonlinear least square method;
s110, initially estimating parameters of a standard Gaussian function, selecting optimal parameters, and acquiring waveform data under the optimal parameters;
s111, performing feature extraction on the waveform data under the optimal parameters by adopting a classifier, and analyzing the terrain features in the corresponding light spots;
and S112, acquiring historical waveform data in the detection area, and performing comparative analysis.
By adopting the technical scheme, in S108, because the original waveform is easily influenced by the terrain and greatly influences the actual waveform signal effect, the standard waveform data of the plane is required to be used as a template, and then convolution operation is performed on the standard waveform data and the original waveform processed in S107 to delete the waveform with saturated signal and excessive noise, and the obtained data is more comprehensive and has a wider range.
In addition to the above-mentioned specific embodiments, in step S105, a programmable gain amplifier is used to amplify the electrical frequency, and a high-low pass filter is used to process the electrical signal.
By adopting the technical scheme, the frequency points of a certain part of frequencies or frequencies except the frequency points can be effectively filtered through the amplifier, and the condition that weak key signals can be ignored is avoided by processing the electric signals through the high-low pass filter.
On the basis of the foregoing specific embodiment, further, in S107, acquiring the real and valid signal specifically includes:
taking the expectation and the variance after the optimal Gaussian function fitting as the mean and the variance of the background noise;
estimating and eliminating the background noise signal;
and acquiring a real effective signal.
By adopting the technical scheme, because the sensor and factors such as atmospheric scattering can cause noise influence, the background noise needs to be estimated and removed to obtain the effective signal.
Based on the foregoing specific embodiment, further in S110, the parameters of the standard gaussian function include an amplitude, a gaussian position, and a pulse width, and an optimal parameter is selected through a cross-validation method.
Based on the foregoing specific embodiment, further in S111, the classifier includes a nearest neighbor classifier or a support vector machine classifier.
On the basis of the above specific embodiment, further, several of the original waveforms are composed of 544 frames of data.
On the basis of the above specific embodiment, further, the coordinates of the detection area are composed of longitude and latitude.
The specific embodiments provided in the present invention are only examples of the general inventive concept, and do not limit the scope of the present invention. Any other embodiments extended by the solution according to the invention without inventive step will be within the scope of protection of the invention for a person skilled in the art.
Claims (7)
1. A remote sensing data processing method based on a satellite laser radar technology is characterized by comprising the following steps:
s101, establishing a satellite remote communication system;
s102, acquiring coordinates of a detection area, and performing remote sensing detection on the detection area based on a satellite laser radar technology;
s103, realizing data transmission by using the satellite telecommunication system, and acquiring a plurality of original waveforms of the detection area;
s104, preprocessing the original waveforms, and converting the amplitudes of the original waveforms into voltage values to count;
s105, amplifying and processing the electrical frequency of the original waveforms;
s106, normalizing the original waveforms processed in S104 and S105, and performing comparative analysis;
s107, respectively carrying out histogram statistics on the voltage values of the original waveforms after the normalization processing, and carrying out optimal Gaussian function fitting to obtain real and effective signals;
s108, performing convolution operation on the planar standard echo waveform and the original waveforms processed in the S107 respectively;
s109, carrying out Gaussian decomposition on a plurality of original waveforms processed in the S108, and fitting the waveforms subjected to Gaussian decomposition by adopting a nonlinear least square method;
s110, initially estimating parameters of a standard Gaussian function, selecting optimal parameters, and acquiring waveform data under the optimal parameters;
s111, performing feature extraction on the waveform data under the optimal parameters by adopting a classifier, and analyzing the terrain features in the corresponding light spots;
and S112, acquiring historical waveform data in the detection area, and performing comparative analysis.
2. A method for processing remote sensing data based on satellite lidar technology according to claim 1, wherein in S105, a programmable gain amplifier is used to amplify the electrical frequency, and a high-low pass filter is used to process the electrical signal.
3. The method for processing remote sensing data based on the satellite lidar technology according to claim 1, wherein in S107, the acquiring of the real and valid signal specifically comprises:
taking the expectation and the variance after the optimal Gaussian function fitting as the mean and the variance of the background noise;
estimating and eliminating the background noise signal;
and acquiring a real effective signal.
4. The method for processing remote sensing data based on satellite lidar technology of claim 1, wherein in S110, the parameters of the standard gaussian function comprise amplitude, gaussian position and pulse width, and the optimal parameters are selected by cross validation.
5. The method for processing remote sensing data based on satellite lidar technology of claim 1, wherein in S111, the classifier comprises a nearest neighbor classifier or a support vector machine classifier.
6. A method as claimed in claim 1, wherein the plurality of original waveforms are composed of 544 frames of data.
7. A method for remote sensing data processing based on satellite lidar technology according to claim 1, wherein the coordinates of the detection area consist of longitude and latitude.
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- 2020-05-28 CN CN202010465994.XA patent/CN111580068A/en active Pending
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| CN101051085A (en) * | 2007-04-27 | 2007-10-10 | 中国科学院上海光学精密机械研究所 | Coherent laser height measurement frequency demodulation circuit |
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