CN116258932A - Infrared fusion detection method and system for underwater moving target wake - Google Patents
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Abstract
The invention discloses an infrared fusion detection method and system for a trail of an underwater moving target, comprising the following steps: acquiring sea surface temperature disturbance caused by an underwater moving target by acquiring a sea surface wind field and a temperature fluctuation period based on a sea surface flow field caused by the underwater moving target; based on sea surface temperature disturbance, acquiring a sea surface background temperature field and a random sea wave background field corresponding to a wind field, and performing image fusion according to a thermal infrared spectrum segment and a middle infrared spectrum segment to generate an infrared image of a wake of an underwater moving object, and performing infrared image simulation on the underwater moving object, wherein the infrared image is used for representing an infrared radiation intensity change part caused by temperature disturbance of an inner wave wake of the underwater moving object; the method provides algorithm reference for reducing the detection difficulty of the underwater moving object in the infrared image, provides support for the design and development of the underwater object infrared detection equipment, and provides technical support for improving the infrared detection recognition probability.
Description
Technical Field
The invention relates to the technical field of ocean target detection, in particular to an infrared fusion detection method and system for underwater moving target wake.
Background
The underwater moving object can excite internal waves when sailing in the ocean water body with the density jump layer, the sea surface flow field generated by the internal waves causes the upper and lower convection mixing of the sea surface layer and the subsurface water body, the local sea surface temperature distribution change is caused, and the heat radiation distribution characteristic of the sea surface is changed, so that the infrared imager can be used for detecting the internal wave wake.
When the single infrared spectrum segment is adopted to detect the inner wave wake, the signal to noise ratio of the underwater moving object wake/the ocean background is weak due to the existence of ocean background waves, and the underwater moving object wake can be submerged in the ocean background wave noise, so that detection is difficult to realize. The different infrared spectral radiance changes respond differently to the same temperature disturbance, so that a certain sea surface can be imaged by using a thermal infrared-mid infrared imaging technology, and the influence of background sea wave noise is removed by using a dual-spectral image, so that the detection of inner wave wake is realized.
Disclosure of Invention
In order to solve the problems in the prior art, the invention aims to provide an infrared fusion detection method and an infrared fusion detection system for detecting the trail of an underwater moving target, so as to research the trail of the underwater moving target by infrared dual-spectrum fusion remote sensing imaging.
In order to achieve the technical purpose, the invention provides an infrared fusion detection method for the wake of an underwater moving target, which comprises the following steps:
acquiring sea surface temperature disturbance caused by an underwater moving target by acquiring a sea surface wind field and a temperature fluctuation period based on a sea surface flow field caused by the underwater moving target;
based on sea surface temperature disturbance, an infrared image of the trail of the underwater moving object is generated by acquiring a sea surface background temperature field and a random sea wave background field under a corresponding wind field and carrying out image fusion according to a thermal infrared spectrum segment and a middle infrared spectrum segment, and the infrared image simulation is carried out on the underwater moving object, wherein the infrared image is used for representing an infrared radiation intensity change part caused by the temperature disturbance of the inner wave trail of the underwater moving object.
Preferably, in the process of acquiring the sea surface temperature disturbance, acquiring the sea surface flow field divergence according to the sea surface flow field;
based on the sea surface flow field divergence, acquiring sea surface temperature disturbance according to the thickness of the cold skin corresponding to the sea surface wind speed condition and the fluctuation frequency corresponding to the temperature fluctuation period condition.
Preferably, in acquiring the sea-surface-flow-field divergence, the sea-surface-flow-field divergence is expressed as:
wherein the u component of the sea surface flow field is a component along the x direction, the v component is a component along the y direction, and alpha represents the divergence of the sea surface flow field.
Preferably, in the process of acquiring the fluctuation frequency, the fluctuation frequency is expressed as:
where T is the period of fluctuation of temperature, ω represents the fluctuation frequency.
Preferably, in the process of acquiring the sea surface temperature disturbance, the sea surface temperature disturbance is generated through an osborn unsteady state model based on sea surface flow field divergence, cold skin thickness and fluctuation frequency, wherein the osborn unsteady state model is expressed as:
wherein alpha is the divergence of the sea surface flow field, delta 0 For cold skin thickness, ω is the fluctuation frequency, g is the static surface gradient, sinh is the hyperbolic sine function, cosh is the hyperbolic cosine function, λ is the disturbance wavelength, where,
g＝(T ω -T sky )h，
T sky 243K, sunny day, T sky And 273K in cloudy days.
Preferably, in the process of acquiring the infrared image, sea surface background sea wave inclination is acquired according to a random sea wave background field, wherein the sea surface background sea wave inclination is expressed as:
wherein Deltax, deltay are the horizontal resolution in the x, y direction, k respectively x ,k y Respectively the slopes of the small cells in the x and y directions, cos theta represents sea background sea wave inclination, and theta represents zenith angle;
generating a sea surface temperature field according to sea surface temperature disturbance and a sea surface background temperature field, and performing image fusion according to a thermal infrared spectrum segment and a mid infrared spectrum segment through sea surface background sea wave inclination to generate an infrared image, wherein the sea surface temperature field is expressed as:
where T represents the sea surface temperature field,
representing the sea surface background temperature field.
Preferably, in the process of performing infrared image simulation on an underwater moving object, respectively integrating and calculating infrared radiance in two spectral bands when the sea surface background temperature is T according to a Planck formula, wherein the two general bands represent a thermal infrared spectral band and a middle infrared spectral band, and the infrared radiance is expressed as follows:
wherein c is the speed of light, L ab For infrared radiance, a is the beginning wavelength of the spectrum and b is the ending wavelength of the spectrum.
Dividing the sea surface into a plurality of small cells, regarding each small cell as a lambertian surface, acquiring the radiation intensity of each small cell on the unit area according to the infrared radiation brightness, adopting a vertical downward-looking condition, and carrying out infrared image simulation on an underwater moving target by using an observation zenith angle equal to the inclination angle of the background sea wave small cell, wherein the radiation intensity is expressed as follows:
wherein L represents infrared radiance, and A represents sea surface small surface element area.
Preferably, in the process of performing infrared image simulation on an underwater moving object, normalizing the infrared images of the two spectral bands by utilizing sea surface background infrared radiation intensity, performing fusion treatment, removing the change of the infrared radiation intensity caused by sea surface inclination, acquiring an infrared radiation intensity change part caused by temperature disturbance of an inner wave wake, generating an infrared image, and performing infrared image simulation on the underwater moving object.
The invention discloses an infrared fusion detection system for a trail of an underwater moving target, which comprises the following components:
the data processing module is used for acquiring sea surface temperature disturbance caused by the underwater moving target by collecting sea surface wind fields and temperature fluctuation periods based on the sea surface flow fields caused by the underwater moving target;
the simulation module is used for generating an infrared image of the trail of the underwater moving target by acquiring a sea surface background temperature field and a random sea wave background field corresponding to a wind field based on sea surface temperature disturbance and performing image fusion according to a thermal infrared spectrum segment and a middle infrared spectrum segment, and performing infrared image simulation on the underwater moving target, wherein the infrared image is used for representing an infrared radiation intensity change part caused by temperature disturbance of an inner wave trail of the underwater moving target.
Preferably, the data processing module is further used for obtaining the sea surface flow field according to the geometric parameters, the navigational speed, the navigational depth and the sea water density profile of the underwater moving object, wherein the geometric parameters represent the length and the diameter of the underwater moving object.
The invention discloses the following technical effects:
according to the invention, through acquiring the infrared characteristic data of the wake of the underwater moving object under the condition of two infrared spectral bands, the fusion image of the thermal infrared-middle infrared spectral band for removing the influence of the wave background is further acquired, so that algorithm reference is provided for reducing the detection difficulty of the underwater moving object in the infrared image, support is provided for the design and development of the infrared detection equipment of the underwater moving object, and technical support is provided for improving the infrared detection recognition probability.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an infrared fusion detection model of the wake of an underwater moving object;
FIG. 2 is a schematic flow chart of the method of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.
As shown in fig. 1-2, the infrared fusion detection method for the wake of the underwater moving target provided by the invention has the following infrared imaging remote sensing detection mechanism: in the stratified water body, the motion of the underwater moving object can excite internal waves, the internal waves are transmitted to the sea surface to modulate the thickness of the cold epidermis on the sea surface, the temperature difference change in the cold epidermis is caused, the weak change of the temperature can be detected by a high-precision infrared remote sensor, and therefore the motion of the underwater moving object can show the infrared trail of the underwater moving object by modulating the infrared radiation intensity distribution on the sea surface.
The thermal infrared-mid infrared fusion imaging remote sensing detection has the advantages that compared with single-spectrum infrared remote sensing detection, the thermal infrared-mid infrared fusion imaging remote sensing detection has the following advantages: the influence of inclination of a considerable part of sea background sea waves is removed, and the detection difficulty is reduced. The thermal infrared-mid infrared fusion imaging remote sensing detection mechanism is as follows: according to the Planck formula, the change of the infrared radiance change amount DeltaL along with the wavelength (namely the change of the sea surface background infrared radiance) caused by the temperature disturbance DeltaT is nonlinear, so that the sea surface background sea wave influence can be removed by using the thermal infrared-mid infrared two-spectrum image, and the inner wave wake part is reserved.
Based on the above analysis, as shown in fig. 1, the invention provides an infrared fusion detection method for the wake of an underwater moving target, which comprises the following steps:
s1, calculating a sea surface flow field caused by an underwater moving object according to the geometric parameters (length, diameter), navigational speed, navigational depth, ocean water density profile and other conditions of the underwater moving object;
the calculation method of the sea surface flow field caused by the underwater moving object has various existing models, and the existing models are directly used herein and are not repeated.
S2, calculating sea surface temperature disturbance caused by an underwater moving target by using a sea surface cold skin effect model and taking the sea surface flow field, a sea surface wind field (wind speed and wind direction) and a temperature fluctuation period as inputs;
the step S2 specifically comprises the following steps:
s21, calculating the divergence alpha of the sea surface flow field by using the sea surface flow field caused by the underwater moving object;
wherein the u component of the sea surface flow field is a component along the x direction, and the v component is a component along the y direction.
S22, utilizing a given sea surface wind speed condition, and finding out the thickness delta of the cold skin under the condition according to a relevant empirical formula 0 ；
S23, calculating fluctuation frequency omega under the condition of a given temperature fluctuation period;
wherein T is the fluctuation period of temperature.
S24, calculating an internal wave wake temperature disturbance delta T under given conditions according to a sea surface cold skin effect model;
the sea surface cold epidermis effect model adopts an Osborne unsteady state model, and is specifically as follows:
wherein alpha is the divergence of the sea surface flow field, delta 0 For cold skin thickness, ω is the fluctuation frequency;
g is the static surface gradient, g= (T ω -T sky )h，
T sky 243K, sunny day, T sky 273K, cloudy day;
s3, calculating a wake infrared image of the underwater moving target by using sea surface infrared radiation model and taking sea surface temperature disturbance, a sea surface background temperature field, a random sea wave background field corresponding to a wind field and a thermal infrared-mid infrared spectrum as inputs; the infrared image is the infrared radiation intensity at different positions (x, y) of the sea surface; the method comprises the following steps:
s31, calculating sea surface background sea wave inclination cos theta by taking a random sea wave background field as input;
Δx, Δy are the horizontal resolution in the x, y directions, k, respectively x ，k y The slopes of the facets in the x, y directions, respectively.
S32, disturbing delta T by using internal wave wake temperature and sea surface background temperature field
For input, calculate the sea surface temperature field T: />
S33, taking an inner wave wake sea surface temperature field, background sea wave inclination and a thermal infrared-middle infrared spectrum band as input, and calculating an inner wave wake infrared image by utilizing a sea surface infrared radiation model; the method comprises the following steps:
(1) Respectively integrating and calculating the infrared radiance in two spectral bands when the sea surface background temperature is T according to the Planck formula:
a, b are the end wavelengths of the integral band range.
(2) The sea surface is divided into a number of small cells, each of which is regarded as a lambertian surface (cosine scatterer), whose radiance L is equal in all directions and independent of the observed zenith angle θ, but whose radiance I (θ) is related to cos θ:
I(θ)＝LA cosθ；
the radiation intensity per unit area of each voxel is calculated as:
the simulation adopts a vertical downward-looking condition, and the zenith angle theta is equal to the inclination angle of the background sea wave small cell.
And S4, carrying out fusion processing on the two underwater moving object wake infrared images to obtain a two-spectrum fusion image with the sea wave background removed. The method comprises the following steps:
s41, normalizing the infrared images of the two spectral bands by utilizing sea surface background infrared radiation intensity I0;
the normalized infrared radiation intensity for the ith row and jth column facets of a certain band (a, b) is:
I 0 is the average value of the front 1/3 part of the sea surface background infrared radiation intensity.
S42, carrying out fusion treatment on the normalized two-spectrum infrared images, removing the change of the infrared radiation intensity caused by sea surface inclination, and retaining the infrared radiation intensity change part delta I (I, j) caused by the temperature disturbance of the inner wave wake;
the invention is further described below by using a double-spectrum infrared imaging remote sensing potential theory model example under typical conditions.
Setting input conditions:
(1) Sea water density profile, taking an actual measurement value of 10 months somewhere in the sea area of south China sea.
(2) Underwater moving object parameters: underwater moving objects (length 170.7m, width 12.8 m), depth 50m, speed 12 knots.
(3) Sea surface wind speed: 5m/s, wind direction 0 deg.
(4) Sea surface background temperature: 300K.
(5) Infrared parameters: the middle infrared band is 3-5 μm and the thermal infrared band is 8-10 μm.
And obtaining an underwater moving target wake thermal infrared-mid infrared fusion image by calculating the inner wave wake temperature disturbance field under the above conditions.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
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 (10)
1. An infrared fusion detection method for the wake of an underwater moving object is characterized by comprising the following steps:
acquiring sea surface temperature disturbance caused by an underwater moving target by acquiring a sea surface wind field and a temperature fluctuation period based on a sea surface flow field caused by the underwater moving target;
based on the sea surface temperature disturbance, an infrared image of the wake of the underwater moving object is generated by acquiring a sea surface background temperature field and a random sea wave background field corresponding to a wind field and performing image fusion according to a thermal infrared spectrum segment and a middle infrared spectrum segment, and the infrared image simulation is performed on the underwater moving object, wherein the infrared image is used for representing an infrared radiation intensity change part caused by the temperature disturbance of the inner wave wake of the underwater moving object.
2. The infrared fusion detection method for the wake of the underwater moving object according to claim 1, wherein the method comprises the following steps:
in the process of acquiring sea surface temperature disturbance, acquiring sea surface flow field divergence according to the sea surface flow field;
and acquiring the sea surface temperature disturbance according to the cold skin thickness corresponding to the sea surface wind speed condition and the fluctuation frequency corresponding to the temperature fluctuation period condition based on the sea surface flow field divergence.
3. An infrared fusion detection method for a wake of an underwater moving object according to claim 2, wherein:
in the process of acquiring the sea-surface flow field divergence, the sea-surface flow field divergence is expressed as:
wherein the u component of the sea surface flow field is a component along the x direction, the v component is a component along the y direction, and alpha represents the divergence of the sea surface flow field.
4. An infrared fusion detection method for a wake of an underwater moving object according to claim 3, wherein:
in the process of acquiring the fluctuation frequency, the fluctuation frequency is expressed as:
where T is the period of fluctuation of temperature, ω represents the fluctuation frequency.
5. The infrared fusion detection method for the wake of the underwater moving object according to claim 4, wherein the method comprises the following steps:
in the process of acquiring the sea surface temperature disturbance, generating the sea surface temperature disturbance through an osborn unsteady state model based on the sea surface flow field divergence, the cold skin thickness and the fluctuation frequency, wherein the osborn unsteady state model is expressed as:
wherein alpha is the divergence of the sea surface flow field, delta 0 For cold skin thickness, ω is the fluctuation frequency, g is the static surface gradient, sinh is the hyperbolic sine function, cosh is the hyperbolic cosine function, λ is the disturbance wavelength, where,
g＝(T ω -T sky )h，
T sky 243K, sunny day, T sky And 273K in cloudy days.
6. The infrared fusion detection method for the wake of the underwater moving object according to claim 5, wherein the method comprises the following steps:
in the process of acquiring the infrared image, acquiring sea surface background sea wave inclination according to the random sea wave background field, wherein the sea surface background sea wave inclination is expressed as:
wherein Deltax, deltay are the horizontal resolution in the x, y direction, k respectively x ,k y Respectively the slopes of the small cells in the x and y directions, cos theta represents sea background sea wave inclination, and theta represents zenith angle;
generating a sea surface temperature field according to the sea surface temperature disturbance and the sea surface background temperature field, and performing image fusion according to the thermal infrared spectrum segment and the mid infrared spectrum segment through sea surface background sea wave inclination to generate the infrared image, wherein the sea surface temperature field is expressed as:
where T represents the sea surface temperature field,
representing the sea surface background temperature field.
7. The infrared fusion detection method for the wake of the underwater moving object according to claim 6, wherein the method comprises the following steps:
in the process of carrying out infrared image simulation on an underwater moving target, respectively integrating and calculating infrared radiance in two spectral bands when the sea surface background temperature is T according to a Planck formula, wherein the two spectral bands represent the thermal infrared spectral band and the middle infrared spectral band, and the infrared radiance is expressed as follows:
wherein c is the speed of light, L ab For infrared radiance, a is the beginning wavelength of the spectrum and b is the ending wavelength of the spectrum.
Dividing the sea surface into a plurality of small cells, regarding each small cell as a lambertian surface, acquiring the radiation intensity of each small cell on the unit area according to the infrared radiation brightness, adopting a vertical downward-looking condition, enabling the observed zenith angle to be equal to the inclination angle of the background sea wave small cell, and carrying out infrared image simulation on the underwater moving target, wherein the radiation intensity is expressed as:
wherein L represents infrared radiance, and A represents sea surface small surface element area.
8. The infrared fusion detection method for the wake of the underwater moving object according to claim 7, wherein the method comprises the following steps:
in the process of carrying out infrared image simulation on an underwater moving object, normalizing the infrared images of the two spectral bands by utilizing sea surface background infrared radiation intensity, carrying out fusion treatment, removing the change of the infrared radiation intensity caused by sea surface inclination, acquiring an infrared radiation intensity change part caused by temperature disturbance of an inner wave trail, generating the infrared image, and carrying out infrared image simulation on the underwater moving object.
9. An infrared fusion detection system for a wake of an underwater moving object, comprising:
the data processing module is used for acquiring sea surface temperature disturbance caused by the underwater moving target by collecting sea surface wind fields and temperature fluctuation periods based on the sea surface flow fields caused by the underwater moving target;
the simulation module is used for generating an infrared image of the trail of the underwater moving target by acquiring a sea surface background temperature field and a random sea wave background field under a corresponding wind field based on the sea surface temperature disturbance and performing image fusion according to a thermal infrared spectrum segment and a middle infrared spectrum segment, and performing infrared image simulation on the underwater moving target, wherein the infrared image is used for representing an infrared radiation intensity change part caused by the temperature disturbance of the inner wave trail of the underwater moving target.
10. An infrared fusion detection system for a wake of an underwater moving object according to claim 9, wherein:
the data processing module is further used for obtaining the sea surface flow field according to the geometric parameters, the navigational speed, the navigational depth and the ocean water body density profile of the underwater moving object, wherein the geometric parameters represent the length and the diameter of the underwater moving object.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102077108A (en) * | 2008-04-28 | 2011-05-25 | 康奈尔大学 | Tool for accurate quantification in molecular mri |
| CN107545096A (en) * | 2017-07-14 | 2018-01-05 | 西安电子科技大学 | The real-time Dynamic IR emulation mode of surface vessel tail |
| CN108073865A (en) * | 2016-11-18 | 2018-05-25 | 南京信息工程大学 | A kind of aircraft trail cloud recognition methods based on satellite data |
| WO2018120444A1 (en) * | 2016-12-31 | 2018-07-05 | 华中科技大学 | Infrared radiation spectral characteristic simulation analysis method for moving target |
| CN108594230A (en) * | 2018-07-17 | 2018-09-28 | 电子科技大学 | A kind of diameter radar image emulation mode of seagoing vessel scene |
| CN109671111A (en) * | 2018-11-09 | 2019-04-23 | 西安电子科技大学 | Temperature field modulator approach based on visible remote sensing image |
| CN111273378A (en) * | 2020-05-07 | 2020-06-12 | 南京海气智绘信息技术有限公司 | Typhoon center positioning method based on wind stress disturbance |
| CN111289484A (en) * | 2020-03-11 | 2020-06-16 | 哈尔滨工业大学（威海） | Cold skin detection method based on rhodamine B fluorescence characteristic |
| CN113324656A (en) * | 2021-05-28 | 2021-08-31 | 中国地质科学院 | Unmanned aerial vehicle-mounted infrared remote sensing earth surface heat anomaly detection method and system |
| CN114169264A (en) * | 2021-11-30 | 2022-03-11 | 哈尔滨工程大学 | Infrared simulation method for ship wake |
| CN114758219A (en) * | 2022-06-13 | 2022-07-15 | 青岛国数信息科技有限公司 | Trace identification method based on spectral data and infrared temperature data fusion |
| CN114818385A (en) * | 2022-06-16 | 2022-07-29 | 自然资源部第一海洋研究所 | SAR ocean image simulation method, device and medium |
| CN115267770A (en) * | 2022-01-13 | 2022-11-01 | 中国科学院空天信息创新研究院 | SAR image ocean vortex detection method and system |
| RU2784788C1 (en) * | 2022-04-13 | 2022-11-29 | Российская Федерация, от имени которой выступает ФОНД ПЕРСПЕКТИВНЫХ ИССЛЕДОВАНИЙ | Method for determining sea surface anomalies from optical images |
| CN115421120A (en) * | 2022-08-04 | 2022-12-02 | 中国人民解放军91977部队 | Modeling method for real sea surface electromagnetic scattering environment |
| CN115507959A (en) * | 2022-10-19 | 2022-12-23 | 电子科技大学 | Infrared radiation characteristic analysis method for target detection |
-
2023
- 2023-03-09 CN CN202310223948.2A patent/CN116258932B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102077108A (en) * | 2008-04-28 | 2011-05-25 | 康奈尔大学 | Tool for accurate quantification in molecular mri |
| CN108073865A (en) * | 2016-11-18 | 2018-05-25 | 南京信息工程大学 | A kind of aircraft trail cloud recognition methods based on satellite data |
| WO2018120444A1 (en) * | 2016-12-31 | 2018-07-05 | 华中科技大学 | Infrared radiation spectral characteristic simulation analysis method for moving target |
| CN107545096A (en) * | 2017-07-14 | 2018-01-05 | 西安电子科技大学 | The real-time Dynamic IR emulation mode of surface vessel tail |
| CN108594230A (en) * | 2018-07-17 | 2018-09-28 | 电子科技大学 | A kind of diameter radar image emulation mode of seagoing vessel scene |
| CN109671111A (en) * | 2018-11-09 | 2019-04-23 | 西安电子科技大学 | Temperature field modulator approach based on visible remote sensing image |
| CN111289484A (en) * | 2020-03-11 | 2020-06-16 | 哈尔滨工业大学（威海） | Cold skin detection method based on rhodamine B fluorescence characteristic |
| CN111273378A (en) * | 2020-05-07 | 2020-06-12 | 南京海气智绘信息技术有限公司 | Typhoon center positioning method based on wind stress disturbance |
| CN113324656A (en) * | 2021-05-28 | 2021-08-31 | 中国地质科学院 | Unmanned aerial vehicle-mounted infrared remote sensing earth surface heat anomaly detection method and system |
| CN114169264A (en) * | 2021-11-30 | 2022-03-11 | 哈尔滨工程大学 | Infrared simulation method for ship wake |
| CN115267770A (en) * | 2022-01-13 | 2022-11-01 | 中国科学院空天信息创新研究院 | SAR image ocean vortex detection method and system |
| RU2784788C1 (en) * | 2022-04-13 | 2022-11-29 | Российская Федерация, от имени которой выступает ФОНД ПЕРСПЕКТИВНЫХ ИССЛЕДОВАНИЙ | Method for determining sea surface anomalies from optical images |
| CN114758219A (en) * | 2022-06-13 | 2022-07-15 | 青岛国数信息科技有限公司 | Trace identification method based on spectral data and infrared temperature data fusion |
| CN114818385A (en) * | 2022-06-16 | 2022-07-29 | 自然资源部第一海洋研究所 | SAR ocean image simulation method, device and medium |
| CN115421120A (en) * | 2022-08-04 | 2022-12-02 | 中国人民解放军91977部队 | Modeling method for real sea surface electromagnetic scattering environment |
| CN115507959A (en) * | 2022-10-19 | 2022-12-23 | 电子科技大学 | Infrared radiation characteristic analysis method for target detection |
Non-Patent Citations (5)
| Title |
|---|
| XUEQI CHEN等: "Infrared Ocean Image Simulation Algorithm Based on Pierson–Moskowitz Spectrum and Bidirectional Reflectance Distribution Function", 《PHOTONICS》, vol. 9, 9 March 2022 (2022-03-09), pages 1 - 16 * |
| 廖惟博等: "基于红外物理学和流体动力学的海面船只红外尾迹真实感绘制", 《计算机辅助设计与图形学学报》, vol. 29, no. 7, 31 July 2017 (2017-07-31), pages 1227 - 1234 * |
| 汪小君: "海面及舰船尾迹电磁散射的角度复合面元算法研究", 《中国优秀硕士学位论文全文数据库 基础科学辑》, no. 2021, 15 April 2021 (2021-04-15), pages 005 - 165 * |
| 阳海鹏等: "海洋内波的红外成像机理—冷表皮剪切模型", 《舰船电子工程》, vol. 32, no. 12, 31 December 2012 (2012-12-31), pages 155 - 157 * |
| 陈彬: "海面背景下舰船目标红外辐射特性研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》, no. 2016, 15 February 2016 (2016-02-15), pages 036 - 160 * |
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