CN109509209B - Analysis method for detecting air moving target in sea-air environment by utilizing hyperspectral technology - Google Patents
Analysis method for detecting air moving target in sea-air environment by utilizing hyperspectral technology Download PDFInfo
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Abstract
The invention provides an analysis method for detecting an air moving target in a sea-air environment by utilizing a hyperspectral technology.
Description
Technical Field
The invention relates to an analysis method for detecting an air moving target in a sea-air environment by utilizing a hyperspectral technology.
Background
The aerial target has the characteristics of high time sensitivity, strong maneuverability, difficult track prediction, convenient burst prevention and the like, and the aerial target can be continuously monitored in a large range and high frequency only by a high-orbit satellite, and the conventional optical means takes the geometric shape of the aerial target as a recognition basis, requires an ultra-large optical caliber and greatly limits the development of the satellite and the formation of continuous detection capability.
The hyperspectral detection technology is to discover and identify the target by adopting a fine continuous spectrum through the difference of the spectrum characteristics of the target, and has the capabilities of disguising and stealth detection. When the air moving target of the sea-air background is detected, the continuous fine spectrum of the target can be obtained with high precision by utilizing the uniform and single characteristic of the sea-air background, and the detection and identification of the air moving target can be realized by utilizing the fingerprint characteristic of the target spectrum.
The air moving target detectability is a comprehensive problem related to a plurality of satellite-ground systems, how to explain the feasibility of detecting the air moving target by adopting a hyperspectral technology, and how to determine a core detection index all need to develop analysis method research in the aspect of feasibility demonstration.
Disclosure of Invention
The invention aims to provide an analysis method for detecting an air moving target in a sea-air environment by utilizing a hyperspectral technology.
In order to solve the above problems, the present invention provides an analysis method for detecting a moving object in the air in a sea-air environment by using a hyperspectral technology, comprising:
step A: according to the characteristic information of the object and the background which are researched and actually measured, designing parameters including observation angle, sun illumination and flying height when detecting the moving object in the air, and carrying out spectral characteristic simulation of the object and the background;
and (B) step (B): initializing the spatial resolution of a camera and the signal to noise ratio of the camera according to the satellite orbit height, and completing the design of a hyperspectral camera;
step C: mixing a target with a background according to the relation between the spatial resolution of the camera and the size of the target, superposing noise, simulating hyperspectral data output by the camera when imaging an aerial moving target, and simulating to obtain a hyperspectral image;
step D: adopting an anomaly detection method and a mixed pixel spectrum unmixing method, and analyzing the detection effect and spectrum extraction precision of an air moving target by utilizing a hyperspectral simulation image;
step E: and (C) modifying the spatial resolution of the camera and the signal-to-noise ratio index of the camera, and repeating the steps B to D until the detection effect and the spectrum extraction precision meet the satellite task requirements.
Further, in the above method, in the step a, the effect of the observation angle, the sun light and the flying height on the spectral characteristics of the target is considered when the spectral characteristics of the target and the background are simulated.
Furthermore, in the method, the spatial resolution and the signal to noise ratio of the camera are used as main variables, and then the hyperspectral camera design is completed.
Further, in the above method, the hyperspectral camera adopts a mechanical light splitting system, and the mechanical light splitting system includes grating light splitting.
Further, in the above method, when the object and the background are mixed in step C, the corresponding area ratio is analyzed in consideration of the position of the object in the field of view of the camera and the visual condition of the plurality of pixels, and the linear mixing of the object and the background is performed.
Further, in the above method, the superimposed noise in step C includes: a superposition of background heave noise, camera noise and scaled residual noise.
Further, in the above method, in the relationship between the spatial resolution of the camera and the target size, the target size is smaller than or equal to the spatial resolution of the camera.
Compared with the prior art, the method has the advantages that through the relation between the target size and the spatial resolution of the camera in the step C, the target and the background are linearly mixed and then analyzed, in the step D, the detection probability and the spectral extraction precision of the air moving target are used as the detectability evaluation index, in the step E, the detection probability and the spectral extraction precision of the air moving target under the condition of different parameters are analyzed by taking the spatial resolution of the camera and the signal to noise ratio as variable parameters, and the iteration is circulated until the task requirements of the satellite are met, the feasibility of detecting the air moving target by adopting a hyperspectral technology can be analyzed, and the core detection index is determined.
Drawings
FIG. 1 is a schematic diagram of a feasibility analysis method for detecting airborne moving targets using hyperspectral techniques according to an embodiment of the invention;
FIG. 2 is a schematic diagram of target spectral characteristics analysis according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a mixture of objects and background when the object size is much smaller than the spatial resolution of the camera in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of object and background mixing when the object size is close to the spatial resolution of the camera according to an embodiment of the present invention;
FIG. 5 is a flow chart of object detection and object recognition according to an embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the present invention provides an analysis method for detecting an air moving object in an air-sea environment by using a hyperspectral technology, comprising:
step A: according to the characteristic information of the object and the background which are researched and actually measured, designing parameters including observation angle, sun illumination and flying height when detecting the moving object in the air, and carrying out spectral characteristic simulation of the object and the background;
and (B) step (B): initializing the spatial resolution of a camera and the signal to noise ratio of the camera according to the satellite orbit height, and completing the design of a hyperspectral camera;
step C: mixing a target with a background according to the relation between the spatial resolution of the camera and the size of the target, superposing noise, simulating hyperspectral data output by the camera when imaging an aerial moving target, and simulating to obtain a hyperspectral image;
step D: adopting an anomaly detection method and a mixed pixel spectrum unmixing method, and analyzing the detection effect and spectrum extraction precision of an air moving target by utilizing a hyperspectral simulation image;
step E: and (C) modifying the spatial resolution of the camera and the signal-to-noise ratio index of the camera, and repeating the steps B to D until the detection effect and the spectrum extraction precision meet the satellite task requirements.
In the method, the detection probability and the spectrum extraction precision of the air moving target are used as the detectability evaluation indexes in the step D, the spatial resolution and the signal to noise ratio of a camera are used as variable parameters in the step E, the detection probability and the spectrum extraction precision of the air moving target under the condition of different parameters are analyzed, and the iteration is circulated until the task requirements of satellites are met, so that the feasibility of detecting the air moving target by using a hyperspectral technology can be analyzed, and the core detection indexes are determined.
In an embodiment of the feasibility analysis method for detecting the air moving target in the sea-air environment by utilizing the hyperspectral technology, the influence of the observation angle, the sun illumination and the flying height on the spectral characteristics of the target is considered when the spectral characteristics of the target and the background are simulated in the step A.
In an embodiment of the feasibility analysis method for detecting the air moving target in the sea-air environment by utilizing the hyperspectral technology, when the hyperspectral camera in the step B is designed, the space resolution and the signal-to-noise ratio of the camera are used as main variables, and then the hyperspectral camera is designed.
In an embodiment of the feasibility analysis method for detecting the air moving target in the sea-air environment by utilizing the hyperspectral technology, the hyperspectral camera adopts a mechanical light splitting system, and the mechanical light splitting system comprises grating light splitting.
In one embodiment of the feasibility analysis method for detecting the air moving target in the sea-sky environment by utilizing the hyperspectral technology, when the target and the background are mixed in the step C, the positions of the target in the field of view of a camera and the visible condition of a plurality of pixels are considered, the corresponding area ratio is analyzed, and the linear mixing of the target and the background is carried out.
In an embodiment of the feasibility analysis method for detecting an air moving target in a sea-air environment by using hyperspectral technology, the superimposed noise in the step C includes: a superposition of background heave noise, camera noise and scaled residual noise.
In an embodiment of the feasibility analysis method for detecting the air moving target in the sea-air environment by utilizing the hyperspectral technology, the target size is far smaller than the camera spatial resolution in the relation between the camera spatial resolution and the target size.
Here, when the target size is far smaller than the camera spatial resolution, the anomaly detection and spectrum extraction of the air target are feasible in the air-sea environment.
Specifically, models such as the appearance, the temperature field, the skin, the tail flame and the like of the air moving object to be detected can be established, and the spectral characteristic curves of the object under different flying heights, different flying speeds and different detection angles can be analyzed. As shown in fig. 2, the spectral characteristics of the moving object and the background in the air at the entrance pupil of the hyperspectral camera are calculated by analyzing the influence of atmospheric scattering, ground reflection and direct solar radiation on the spectral characteristics of the object and the background by using MODTRAN radiation transmission software.
The hyperspectral camera needs to adopt a mechanical light splitting system such as grating light splitting, so that when the aerial target flies at a high speed, hundreds of spectrum sections can acquire the target spectrum simultaneously, and when the target spans pixels, spectrum aliasing can not occur. When designing the hyperspectral camera, taking the spatial resolution and the signal to noise ratio of the camera as main variables to finish the design of the camera.
As shown in fig. 3, when the spectrum image of the aerial target is simulated, the relation between the size of the aerial target and the spatial resolution of the camera is considered, and when the size of the target is far smaller than the spatial resolution of the camera, the target and the background are linearly mixed according to the area ratio; as shown in fig. 4, when the size of the target is close to the spatial resolution of the camera, the position of the target in the field of view of the camera and the visual condition of a plurality of pixels are considered, the corresponding area ratio is analyzed, and linear mixing of the target and the background is performed.
The energy obtained by mixing the aerial target with the background is input into a camera imaging model, and after background fluctuation noise, camera noise and calibration residual noise are overlapped, the hyperspectral camera is simulated to detect spectral image data of the aerial target. In the hyperspectral image, a detection spectrum band with high signal to noise ratio is optimized, and for the selected band data, an abnormal target is detected from the hyperspectral image through an abnormal target detection algorithm; on the basis, extracting an unknown target spectrum in the abnormal pixel by combining a linear spectrum mixed model and a mixed pixel decomposition technology; finally, the target spectrum analysis is performed in combination with the spectrum library, as shown in fig. 5, to further define the target type.
And taking the air moving target detection probability and the spectrum extraction precision as the detectability evaluation index, changing the spatial resolution and the signal to noise ratio of the camera, analyzing the air moving target detection probability and the spectrum extraction precision under different parameter conditions, and performing loop iteration until the task requirements of satellites are met.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (4)
1. An analysis method for detecting an air moving target in a sea-air environment by utilizing a hyperspectral technology is characterized by comprising the following steps:
step A: according to the characteristic information of the object and the background which are researched and actually measured, designing parameters including observation angle, sun illumination and flying height when detecting the moving object in the air, and carrying out spectral characteristic simulation of the object and the background;
and (B) step (B): initializing the spatial resolution of a camera and the signal to noise ratio of the camera according to the satellite orbit height, and completing the design of a hyperspectral camera;
the hyperspectral camera adopts a mechanical light splitting system;
step C: mixing a target with a background according to the relation between the spatial resolution of the camera and the size of the target, superposing noise, simulating hyperspectral data output by the camera when imaging an aerial moving target, and simulating to obtain a hyperspectral image;
considering the relation between the size of an aerial target and the spatial resolution of a camera, and linearly mixing the target and the background according to the area ratio when the size of the target is far smaller than the spatial resolution of the camera; when the size of the target is close to the spatial resolution of the camera, the position of the target in the field of view of the camera and the visual condition of a plurality of pixels are considered, the corresponding area ratio is analyzed, and the linear mixing of the target and the background is carried out;
the energy obtained by mixing the aerial target with the background is input into a camera imaging model, and after background fluctuation noise, camera noise and calibration residual noise are overlapped, the spectrum image data of the aerial target is detected by a simulated hyperspectral camera;
step D: adopting an anomaly detection method and a mixed pixel spectrum unmixing method, and analyzing the detection effect and spectrum extraction precision of an air moving target by utilizing a hyperspectral simulation image;
selecting a detection spectrum band with high signal-to-noise ratio from the hyperspectral image, and detecting an abnormal target from the hyperspectral image by an abnormal target detection algorithm for the selected band data; on the basis, extracting an unknown target spectrum in the abnormal pixel by combining a linear spectrum mixed model and a mixed pixel decomposition technology; finally, combining a spectrum library to perform target spectrum analysis, and further defining the target type;
step E: and (C) modifying the spatial resolution of the camera and the signal-to-noise ratio index of the camera, and repeating the steps B to D until the detection effect and the spectrum extraction precision meet the satellite task requirements.
2. The method of claim 1, wherein the spectral characteristics of the object and the background are simulated in step a taking into account the effects of observation angle, solar illumination, altitude on the spectral characteristics of the object.
3. The method of claim 1, wherein the hyperspectral camera design in step B is completed with spatial resolution and camera signal to noise ratio as main variables.
4. The method of claim 1, wherein the hyperspectral camera employs a mechanical spectroscopy regime, the mechanical spectroscopy regime comprising grating spectroscopy.
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