CN108710127B - Target detection and identification method and system under low-altitude and sea surface environments - Google Patents
Target detection and identification method and system under low-altitude and sea surface environments Download PDFInfo
- Publication number
- CN108710127B CN108710127B CN201810354980.3A CN201810354980A CN108710127B CN 108710127 B CN108710127 B CN 108710127B CN 201810354980 A CN201810354980 A CN 201810354980A CN 108710127 B CN108710127 B CN 108710127B
- Authority
- CN
- China
- Prior art keywords
- target
- calibration
- tracking
- self
- establishing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000005259 measurement Methods 0.000 claims abstract description 28
- 238000007499 fusion processing Methods 0.000 claims abstract description 11
- 238000011426 transformation method Methods 0.000 claims abstract description 9
- 230000009466 transformation Effects 0.000 claims description 25
- 238000004422 calculation algorithm Methods 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 12
- 238000001914 filtration Methods 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000000354 decomposition reaction Methods 0.000 claims description 6
- 238000009499 grossing Methods 0.000 claims description 6
- 230000003993 interaction Effects 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 6
- 238000013519 translation Methods 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 3
- 230000000875 corresponding effect Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 5
- 230000014616 translation Effects 0.000 description 5
- 230000002596 correlated effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention provides a target detection and identification method and a system under low-altitude and sea surface environments, which comprise the following steps: establishing a spatial virtual reference coordinate system and performing self-calibration; aiming at different measurement conditions, establishing data of a measurement point and a target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method; calculating all geometric parameters of each target and coordinates of the targets; self-calibration and blind-repairing are carried out through two radars with different heights; radar signals processed by adopting a denoising method of interframe correlation; and carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking. The invention adopts a dynamic self-calibration technology and a self-adaptive detection and identification technology, inhibits strong sea clutter and improves the target positioning precision and the identification rate; the target detection capability of observing the sea area in a day and night under a severe meteorological environment is improved. The sea surface small target and the low-altitude small targets such as unmanned aerial vehicles and the like can be effectively detected, tracked, identified and monitored by law enforcement for evidence collection.
Description
Technical Field
The invention relates to the technical field of radar detection and identification, in particular to a target detection and identification method and system under low-altitude and sea surface environments.
Background
It is known that radars operating in the sea and low-altitude environment face more serious influence of the low-altitude and sea-surface environment, for example, ground and ocean clutter cause low detection and identification accuracy for targets. Especially for small sea targets such as periscopes, mine drifters, frogmans and eight-claw ships and small low-altitude targets such as unmanned aerial vehicles, the moving speed of the targets is fast or slow, the size of the targets is small, the radar reflection area is small, the radar short-range weak visual area problem is solved, and the targets are difficult to find, track and identify due to the influence of the low altitude and sea surface environments.
Interpretation of terms:
AIS: automatic Identification System, Automatic Identification System of ship.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a target detection and identification method and a target detection and identification system under low altitude and sea surface environments.
The invention provides a target detection and identification method under low-altitude and sea surface environments, which comprises the following steps:
self-calibration step: establishing a spatial virtual reference coordinate system and performing self-calibration;
and (3) coordinate transformation: aiming at different measurement conditions, establishing data of a measurement point and a target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method;
and a target calculation step: calculating all geometric parameters of each target and coordinates of the targets;
radar calibration: self-calibration and blind-repairing are carried out through two radars with different heights;
a signal processing step: radar signals processed by adopting a denoising method of interframe correlation;
target detection and tracking: and carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking.
Preferably, the self-calibration step includes:
step 11: establishing a space virtual reference coordinate system and a virtual measurement benchmark;
step 12: establishing a relation and a transformation relation among all coordinate systems;
step 13: and carrying out self-calibration to obtain the initial point and the initial distance of each measurement in the space virtual reference coordinate system.
Preferably, the step of calculating the objects comprises solving a system of nonlinear least squares equations by a Gauss-Newton method to calculate all geometric parameters of each object and coordinates of the object.
Preferably, the coordinate transformation method includes:
the coordinate transformation based on any plane is just regarded as the mapping of two or more linear spaces, and the transformation matrix is as follows:
wherein Δ X, Δ Y, Δ Z are coordinate translations, R (ω) is a rotation matrix, and (1+ m) is a scale factor;
the coordinate transformation between different coordinate systems is realized by establishing a one-to-one correspondence relationship between the two coordinate systems, and the dimension space is determined by relative reference of the coordinates.
Preferably, the radar calibration step includes: self-calibration and blind-fill are carried out through the two radars with different heights, and the data of the two radars are fused.
Preferably, the method for denoising the inter-frame correlation comprises: based on a two-dimensional complex wavelet transform and on a three-dimensional complex wavelet transform.
Preferably, the three-dimensional complex wavelet transform comprises: the signal is taken as a three-dimensional signal, namely, the signal comprises two space directions and one time direction, and the three-dimensional signal is subjected to wavelet decomposition.
Preferably, the target detecting and tracking step includes: carrying out target detection and tracking by adopting a tracking algorithm and an alpha-beta-gamma filtering algorithm;
the alpha-beta-gamma filtering algorithm comprises:
α＝1-ξ3；
β＝1.5(1-ξ2)(1-ξ)；
γ＝O.5(1-ξ)3；
the values of alpha, beta and gamma are determined by utilizing the smoothing coefficient xi, and the best values of the smoothing coefficient xi, namely the best values of the alpha, beta and gamma can be obtained by utilizing a fuzzy system to automatically adjust according to the mobility of a time-varying target before each tracking task under the premise of ensuring the precision.
Preferably, the target detecting and tracking step includes:
the method comprises the steps of performing information fusion processing on multi-source target data including radar, AIS and photoelectric equipment, capturing and tracking various targets in an area, establishing a target track, displaying target information in real time in an all-around and full-range mode, and providing a marine comprehensive target situation map;
providing target indication for the photoelectric equipment, and finishing the interaction of equipment state, attitude information and tracking information;
the position information of the target is continuously provided for the photoelectric equipment, the photoelectric equipment images the image of the target, and the tracking and the identification of the target are realized according to the characteristic attribute of the target.
The invention provides a target detection and identification system under low altitude and sea surface environment, which comprises:
a self-calibration module: establishing a spatial virtual reference coordinate system and performing self-calibration;
a coordinate transformation module: aiming at different measurement conditions, establishing data of a measurement point and a target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method;
a target calculation module: calculating all geometric parameters of each target and coordinates of the targets;
a radar calibration module: self-calibration and blind-repairing are carried out through two radars with different heights;
the signal processing module: radar signals processed by adopting a denoising method of interframe correlation;
a target detection tracking module: and carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking.
Compared with the prior art, the invention has the following beneficial effects:
the invention adopts a dynamic self-calibration technology and a self-adaptive detection and identification technology, inhibits strong sea clutter and improves the target positioning precision and the identification rate; the target detection capability of observing the sea area in a day and night under a severe meteorological environment is improved. Particularly, the low-altitude small targets such as sea surface small targets and unmanned planes are effectively detected, tracked, identified and monitored by law enforcement for evidence collection.
Meanwhile, the target detection and identification system has the advantages of simple structure and low cost, can realize the fusion of the radar and various target signals, has obvious effect, effectively realizes tracking, reduces the influence of complex weather on the radar and photoelectric equipment working in the marine environment, improves the performance of the radar and optical equipment in the marine environment, and improves the comprehensive detection and identification capabilities of the radar, the optical equipment and the like.
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 flow chart of the present invention;
fig. 2 is a schematic diagram of an application in 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 fig. 1 and fig. 2, the method for detecting and identifying an object in a low altitude and sea surface environment provided by the present invention includes:
self-calibration step: and establishing a spatial virtual reference coordinate system and performing self-calibration. The method specifically comprises the following steps:
step 11: a space virtual reference coordinate system and a virtual measurement benchmark are established, because a target moving in space freely moves in a three-dimensional space and an orthogonal object reference coordinate system does not exist.
Step 12: the relation and transformation relation between each coordinate system is established, the reference coordinate system is usually established on the tracking station, and a spherical coordinate system is adopted.
Step 13: and carrying out self-calibration to obtain the initial point and the initial distance of each measurement in the space virtual reference coordinate system.
And (3) coordinate transformation: and aiming at different measurement conditions, establishing the data of the measurement points and the target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method. The dynamic measurement system needs a uniform measurement reference coordinate system, and in order to improve the measurement efficiency, the data acquisition of the measurement point and the measured target usually takes the measured rotation center or the target attitude adjustment center as a base point. The coordinate transformation of the data needs to be established on the basis of establishing a virtual measurement reference coordinate system from calibration.
Coordinate transformation is the description of the location of a spatial entity, a process of transforming from one coordinate system to another. By establishing a one-to-one correspondence between the two coordinate systems. The dimensional space is determined by the coordinates relative to a reference during the transformation of two or more coordinates.
Due to the use of different coordinate systems, coordinate transformations between different coordinate systems are required. There is translation and rotation in rectangular coordinates, and also interconversion between polar and rectangular coordinates.
In the rectangular coordinate system, a relative coordinate and an absolute coordinate are described. The translation of the coordinates is caused by the translation and rotation of the coordinate axes. The distance moved, the direction moved, and the angle rotated (before moving relative to the original coordinates) of the original coordinates are clarified. Then the required coordinates are transformed in the same way as the original coordinates, so that the corresponding position can be found in the new coordinates.
The coordinate transformation of the measuring system is from the geodetic coordinate system to the map coordinate system, the digitizer coordinate system, the plotter coordinate system or the display coordinate system.
The coordinate transformation based on any plane is just regarded as the mapping of two or more linear spaces, and the transformation matrix is as follows:
wherein Δ X, Δ Y, Δ Z are coordinate translations, R (ω) is a rotation matrix, and (1+ m) is a scale factor;
and a target calculation step: all geometric parameters of each object are calculated, as well as the coordinates of the object. The following system of nonlinear least squares equations can be solved by the Gauss-Newton method to calculate all the geometric parameters of each tracked object and the coordinates of the moving object.
Radar calibration: self-calibration and blind-repairing are carried out through two radars with different heights. The radar adopts two X-band radars with different heights, has strong detection and tracking capabilities on low and slow small targets, is improved by more than 50% compared with a conventional navigation radar, and particularly has certain rain resistance under heavy rain environment conditions. The height of one radar is 15m, the height of the other radar is 10m, the problem of a point target short-range weak sight area caused by a multipath effect can be effectively solved, and short-range blind compensation is realized.
A signal processing step: and (3) processing the radar signal by adopting a denoising method of interframe correlation. The denoising method of the interframe correlation comprises the following steps: based on a two-dimensional complex wavelet transform and on a three-dimensional complex wavelet transform. Denoising based on three-dimensional complex wavelet transform and threshold processing considers a video signal as a three-dimensional signal, i.e. a signal including two spatial directions and one temporal direction. The wavelet decomposition is carried out on the three-dimensional signal, since the wavelet basis function is a three-dimensional function highly correlated in space and time, the correlation between frames is automatically taken into consideration, and the obtained wavelet coefficient is a decorrelation result. For different wavelet decomposition modes, if the characteristics of wavelet basis functions and signals are more similar, the decorrelation effect is better, and the signal processing result after the obtained coefficients are independently processed is better.
Target detection and tracking: and carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking. Common algorithms for target tracking are: the invention discloses a contrast tracking algorithm, a correlation tracking algorithm, a cepstrum tracking algorithm and the like, and aims at the contradiction between the tracking precision and the convergence speed of the traditional alpha-beta-gamma filtering and the limitation that a strong maneuverability target is difficult to track due to fixed coefficients. Providing a marine comprehensive target situation map; providing target indication for the photoelectric equipment, and finishing the interaction of equipment state, attitude information and tracking information; the system can continuously provide the position information of the attention target for the photoelectric equipment and display the real-time video image information acquired by the photoelectric equipment.
Improved alpha-beta-gamma filtering algorithm of the invention
Because the coefficients of the alpha-beta-gamma filter are fixed values which must be preset, the coefficients are preset, so that the necessary mobility of the target before tracking needs to have a priori knowledge, and if the mobility of the target changes, the value of alpha beta gamma needs to be changed. This is very cumbersome and cannot be used at all in time-varying systems, and therefore, the coefficients are fixed to the disadvantages of the alpha-beta-gamma filter.
The invention provides a self-adaptive alpha-beta-gamma filtering tracking algorithm,
the smoothing coefficient xi and alpha, beta and gamma satisfy the following relations:
α＝1-ξ3(1)
β＝1.5(1-ξ2)(1-ξ) (2)
γ＝O.5(1-ξ)3(3)
therefore, the values of α, β, γ can be determined using the smoothing coefficient ξ. The value of xi determines the convergence speed of the filter and the tracking precision of the filter, but the convergence speed and the tracking precision are a set of contradictions, if the convergence speed is required to be higher, the tracking error is larger, the precision is poorer, and vice versa. In engineering, before each tracking task, the best smooth coefficient xi value, namely the best alpha, beta and gamma values can be obtained by utilizing a fuzzy system to automatically adjust according to the formula (1), the formula (2) and the formula (3) and the actual requirement and the maneuverability of a time-varying target on the premise of ensuring the precision.
The target comprehensive processor completes target detection and tracking, and improves the comprehensive detection and tracking capability of the target; the system automatically performs information fusion processing on multi-source target data such as radar, AIS (automatic identification system) and photoelectric equipment, captures and tracks various targets in an area, establishes a target track, displays target information in real time in an all-around and full-range manner, and provides a marine comprehensive target situation map; providing target indication for the photoelectric equipment, and finishing the interaction of equipment state, attitude information and tracking information; the system can continuously provide the position information of the concerned target for the photoelectric equipment, the photoelectric equipment images the image of the target object, and the real-time video image information acquired by the photoelectric equipment is displayed for the purpose of tracking and identifying the target object according to the characteristic attribute of the target.
On the basis of the target detection and identification method under the low-altitude and sea-surface environments, the invention also provides a target detection and identification system under the low-altitude and sea-surface environments, which comprises the following steps:
a self-calibration module: and establishing a spatial virtual reference coordinate system and performing self-calibration. The method specifically comprises the following steps:
a space virtual reference coordinate system and a virtual measurement benchmark are established, because a target moving in space freely moves in a three-dimensional space and an orthogonal object reference coordinate system does not exist.
The relation and transformation relation between each coordinate system is established, the reference coordinate system is usually established on the tracking station, and a spherical coordinate system is adopted.
And carrying out self-calibration to obtain the initial point and the initial distance of each measurement in the space virtual reference coordinate system.
A coordinate transformation module: and aiming at different measurement conditions, establishing the data of the measurement points and the target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method. The dynamic measurement system needs a uniform measurement reference coordinate system, and in order to improve the measurement efficiency, the data acquisition of the measurement point and the measured target usually takes a measurement rotation center or a target attitude adjustment center as a base point. The coordinate transformation of the data needs to be established on the basis of establishing a virtual measurement reference coordinate system from calibration.
A target calculation module: all geometric parameters of each object are calculated, as well as the coordinates of the object. The following system of nonlinear least squares equations can be solved by the Gauss-Newton method to calculate all the geometric parameters of each tracked object and the coordinates of the moving object.
A radar calibration module: self-calibration and blind-repairing are carried out through two radars with different heights. The radar adopts two X-band radars with different heights, has strong detection and tracking capabilities on low and slow small targets, is improved by more than 50% compared with a conventional navigation radar, and particularly has certain rain resistance under heavy rain environment conditions. The height of one radar is 15m, the height of the other radar is 10m, the problem of a point target short-range weak sight area caused by a multipath effect can be effectively solved, and short-range blind compensation is realized.
The signal processing module: and (3) processing the radar signal by adopting a denoising method of interframe correlation. The denoising method of the interframe correlation comprises the following steps: based on a two-dimensional complex wavelet transform and on a three-dimensional complex wavelet transform. Denoising based on three-dimensional complex wavelet transform and threshold processing considers a video signal as a three-dimensional signal, i.e. a signal including two spatial directions and one temporal direction. The wavelet decomposition is carried out on the three-dimensional signal, since the wavelet basis function is a three-dimensional function highly correlated in space and time, the correlation between frames is automatically taken into consideration, and the obtained wavelet coefficient is a decorrelation result. For different wavelet decomposition modes, if the characteristics of wavelet basis functions and signals are more similar, the decorrelation effect is better, and the signal processing result after the obtained coefficients are independently processed is better.
A target detection tracking module: and carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking. Common algorithms for target tracking are: the invention discloses a contrast tracking algorithm, a correlation tracking algorithm, a cepstrum tracking algorithm and the like, and aims at the contradiction between the tracking precision and the convergence speed of the traditional alpha-beta-gamma filtering and the limitation that a strong maneuverability target is difficult to track due to fixed coefficients. Providing a marine comprehensive target situation map; providing target indication for the photoelectric equipment, and finishing the interaction of equipment state, attitude information and tracking information; the system can continuously provide the position information of the attention target for the photoelectric equipment and display the real-time video image information acquired by the photoelectric equipment.
The target comprehensive processor completes target detection and tracking, and improves the comprehensive detection and tracking capability of the target; the system automatically performs information fusion processing on multi-source target data such as radar, AIS (automatic identification system) and photoelectric equipment, captures and tracks various targets in an area, establishes a target track, displays target information in real time in an all-around and full-range manner, and provides a marine comprehensive target situation map; providing target indication for the photoelectric equipment, and finishing the interaction of equipment state, attitude information and tracking information; the system can continuously provide the position information of the concerned target for the photoelectric equipment, the photoelectric equipment images the image of the target object, and the real-time video image information acquired by the photoelectric equipment is displayed for the purpose of tracking and identifying the target object according to the characteristic attribute of the target.
Those skilled in the art will appreciate that, in addition to implementing the system and its various devices, modules, units provided by the present invention as pure computer readable program code, the system and its various devices, modules, units provided by the present invention can be fully implemented by logically programming method steps in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units included in the system for realizing various functions can also be regarded as structures in the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.
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 (8)
1. A target detection and identification method under low altitude and sea surface environments is characterized by comprising the following steps:
self-calibration step: establishing a spatial virtual reference coordinate system and performing self-calibration;
and (3) coordinate transformation: aiming at different measurement conditions, establishing data of a measurement point and a target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method;
and a target calculation step: calculating all geometric parameters of each target and coordinates of the targets;
radar calibration: self-calibration and blind-repairing are carried out through two radars with different heights;
a signal processing step: radar signals processed by adopting a denoising method of interframe correlation;
target detection and tracking: carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking;
the self-calibration step comprises:
step 11: establishing a space virtual reference coordinate system and a virtual measurement benchmark;
step 12: establishing a relation and a transformation relation among all coordinate systems;
step 13: and carrying out self-calibration to obtain the initial point and the initial distance of each measurement in the space virtual reference coordinate system.
2. The method for detecting and identifying the target in the low altitude and sea surface environment according to claim 1, wherein the coordinate transformation method comprises:
the coordinate transformation based on any plane is just regarded as the mapping of two or more linear spaces, and the transformation matrix is as follows:
wherein XA、YA、ZAAre respectively the coordinates of point A, XB、YB、ZBRespectively, the coordinates, DeltaX, of point B0，△Y0，△Z0Is the coordinate translation, R (ω) is the rotation matrix, and (1+ m) is the scale factor;
coordinate transformation between different coordinate systems is realized by establishing one-to-one correspondence relationship between the two coordinate systems, and the dimension space is determined by relative reference of the coordinates;
the target detection tracking step comprises: carrying out target detection and tracking by adopting a tracking algorithm and an alpha-beta-gamma filtering algorithm;
the alpha-beta-gamma filtering algorithm comprises:
α＝1-ξ3；
β＝1.5(1-ξ2)(1-ξ)；
γ＝O.5(1-ξ)3；
the values of alpha, beta and gamma are determined by utilizing the smoothing coefficient xi, and the best values of the smoothing coefficient xi, namely the best values of the alpha, beta and gamma can be obtained by utilizing a fuzzy system to automatically adjust according to the mobility of a time-varying target before each tracking task under the premise of ensuring the precision.
3. The method for detecting and identifying the target in the low altitude and sea surface environment according to claim 1, wherein the target calculating step includes solving a nonlinear least square equation system by a Gauss-Newton method to calculate all geometric parameters of each target and coordinates of the target.
4. The method for detecting and identifying the target in the low altitude and sea surface environment according to claim 1, wherein the radar calibration step comprises: self-calibration and blind-repairing are carried out through two radars with different heights, and data of the two radars are fused firstly.
5. The method for detecting and identifying the target in the low altitude and sea surface environment according to claim 1, wherein the method for denoising the inter-frame correlation comprises: based on a two-dimensional complex wavelet transform and on a three-dimensional complex wavelet transform.
6. The method for detecting and identifying the target in the low altitude and sea surface environment according to claim 5, wherein the three-dimensional complex wavelet transform comprises: the signal is taken as a three-dimensional signal, namely, the signal comprises two space directions and one time direction, and the three-dimensional signal is subjected to wavelet decomposition.
7. The method for detecting and identifying the target in the low altitude and sea surface environment according to claim 1, wherein the target detecting and tracking step comprises:
the method comprises the steps of performing information fusion processing on multi-source target data including radar, AIS and photoelectric equipment, capturing and tracking various targets in an area, establishing a target track, displaying target information in real time in an all-around and full-range mode, and providing a marine comprehensive target situation map;
providing target indication for the photoelectric equipment, and finishing the interaction of equipment state, attitude information and tracking information;
the position information of the target is continuously provided for the photoelectric equipment, the photoelectric equipment images the image of the target, and the tracking and the identification of the target are realized according to the characteristic attribute of the target.
8. A target detection and identification system under low altitude and sea surface environment is characterized by comprising:
a self-calibration module: establishing a spatial virtual reference coordinate system and performing self-calibration;
a coordinate transformation module: aiming at different measurement conditions, establishing data of a measurement point and a target in a space virtual reference coordinate system by adopting a corresponding coordinate transformation method;
a target calculation module: calculating all geometric parameters of each target and coordinates of the targets;
a radar calibration module: self-calibration and blind-repairing are carried out through two radars with different heights;
the signal processing module: radar signals processed by adopting a denoising method of interframe correlation;
a target detection tracking module: carrying out information fusion processing on multi-source target data including radar, and carrying out target detection and tracking;
the self-calibration module comprises:
establishing a space virtual reference coordinate system and a virtual measurement benchmark;
establishing a relation and a transformation relation among all coordinate systems;
and carrying out self-calibration to obtain the initial point and the initial distance of each measurement in the space virtual reference coordinate system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810354980.3A CN108710127B (en) | 2018-04-19 | 2018-04-19 | Target detection and identification method and system under low-altitude and sea surface environments |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810354980.3A CN108710127B (en) | 2018-04-19 | 2018-04-19 | Target detection and identification method and system under low-altitude and sea surface environments |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108710127A CN108710127A (en) | 2018-10-26 |
| CN108710127B true CN108710127B (en) | 2020-10-30 |
Family
ID=63866717
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810354980.3A Active CN108710127B (en) | 2018-04-19 | 2018-04-19 | Target detection and identification method and system under low-altitude and sea surface environments |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108710127B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| IT202200005390A1 (en) * | 2022-03-18 | 2023-09-18 | Univ Degli Studi Padova | Method for self-calibrating millimeter wave (mmWave) radar sensor networks starting from motion trajectories of targets in the environment |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111308463B (en) * | 2020-01-20 | 2022-06-07 | 京东方科技集团股份有限公司 | Human body detection method and device, terminal equipment, storage medium and electronic equipment |
| CN111860215B (en) * | 2020-06-30 | 2021-11-30 | 江苏云洲智能科技有限公司 | Target object position determining method, terminal device and navigation system |
| CN113075937B (en) * | 2021-03-17 | 2022-12-02 | 北京理工大学 | Control method for capturing target by unmanned aerial vehicle based on target acceleration estimation |
| CN117192528A (en) * | 2023-08-28 | 2023-12-08 | 河北德冠隆电子科技有限公司 | Linear scanning angle adjustable data dynamic fusion radar integrated machine |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160069987A1 (en) * | 2014-09-10 | 2016-03-10 | Furuno Electric Co., Ltd. | Method and device for displaying ship vicinity information |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102042835B (en) * | 2010-11-05 | 2012-10-24 | 中国海洋大学 | Autonomous underwater vehicle combined navigation system |
| CN106101590B (en) * | 2016-06-23 | 2019-07-19 | 上海无线电设备研究所 | The detection of radar video complex data and processing system and detection and processing method |
| CN106405540A (en) * | 2016-08-31 | 2017-02-15 | 上海鹰觉科技有限公司 | Radar and photoelectric device complementation-based detection and identification device and method |
| CN107219520A (en) * | 2017-05-31 | 2017-09-29 | 成都新越科技有限公司 | A kind of anti-unmanned plane distributed networking detection method and its device |
-
2018
- 2018-04-19 CN CN201810354980.3A patent/CN108710127B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160069987A1 (en) * | 2014-09-10 | 2016-03-10 | Furuno Electric Co., Ltd. | Method and device for displaying ship vicinity information |
Non-Patent Citations (1)
| Title |
|---|
| Application of Maritime AIS (Automatic Identification System) to ADS-B (Automatic Dependent Surveillance-Broadcast) Transceiver;Jae-Hoon Song et al.;《International Conference on Control, Automation and Systems 2010》;20101031;第2233-2237页 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| IT202200005390A1 (en) * | 2022-03-18 | 2023-09-18 | Univ Degli Studi Padova | Method for self-calibrating millimeter wave (mmWave) radar sensor networks starting from motion trajectories of targets in the environment |
| WO2023175487A1 (en) * | 2022-03-18 | 2023-09-21 | Università Degli Studi Di Padova | Method for self-calibration of mmwave radar networks |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108710127A (en) | 2018-10-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108710127B (en) | Target detection and identification method and system under low-altitude and sea surface environments | |
| CN111326023B (en) | Unmanned aerial vehicle route early warning method, device, equipment and storage medium | |
| CN104197928B (en) | Multi-camera collaboration-based method for detecting, positioning and tracking unmanned aerial vehicle | |
| CN113359097B (en) | Millimeter wave radar and camera combined calibration method | |
| CN107390704B (en) | IMU attitude compensation-based multi-rotor unmanned aerial vehicle optical flow hovering method | |
| CN109115173A (en) | Machine body of boring machine pose monocular vision measurement method based on straight line location model | |
| CN103411621A (en) | Indoor-mobile-robot-oriented optical flow field vision/inertial navigation system (INS) combined navigation method | |
| CN111025283A (en) | Method and device for linking radar and dome camera | |
| CN111027496A (en) | Infrared dim target detection method based on space-time joint local contrast | |
| Du et al. | Visual measurement system for roadheaders pose detection in mines | |
| CN111780716A (en) | Monocular real-time distance measurement method based on target pixel area and aspect ratio | |
| CN104063863A (en) | Pitch-down type binocular vision system for watercourse monitoring and image processing method | |
| CN114923477A (en) | Multi-dimensional space-ground collaborative map building system and method based on vision and laser SLAM technology | |
| JP2017524932A (en) | Video-assisted landing guidance system and method | |
| Jiang et al. | Bridge Deformation Measurement Using Unmanned Aerial Dual Camera and Learning‐Based Tracking Method | |
| CN117451054A (en) | Unmanned aerial vehicle high-precision indoor positioning method based on monocular camera, IMU and UWB multi-sensor fusion | |
| CN112945233A (en) | Global drift-free autonomous robot simultaneous positioning and map building method | |
| CN108646760A (en) | Based on the target following of monocular vision mobile robot and platform control system and method | |
| CN109903309A (en) | A kind of robot motion's information estimating method based on angle optical flow method | |
| CN115294210A (en) | Camera attitude calibration method based on single vanishing point | |
| Ren | An improved binocular LSD_SLAM method for object localization | |
| Yu et al. | Camera external self-calibration for intelligent vehicles | |
| CN111061273A (en) | Autonomous obstacle avoidance fusion method and system for unmanned ship | |
| CN114754743B (en) | Target positioning method for carrying multiple PTZ cameras on ground intelligent unmanned platform | |
| CN117268404B (en) | Unmanned aerial vehicle indoor and outdoor autonomous navigation method utilizing multi-sensor fusion |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Target detection and recognition method and system in low altitude and sea environment Effective date of registration: 20220624 Granted publication date: 20201030 Pledgee: China Minsheng Banking Corp Shanghai branch Pledgor: SHANGHAI YINGJUE TECHNOLOGY CO.,LTD. Registration number: Y2022310000083 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PC01 | Cancellation of the registration of the contract for pledge of patent right | ||
| PC01 | Cancellation of the registration of the contract for pledge of patent right |
Date of cancellation: 20230728 Granted publication date: 20201030 Pledgee: China Minsheng Banking Corp Shanghai branch Pledgor: SHANGHAI YINGJUE TECHNOLOGY CO.,LTD. Registration number: Y2022310000083 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Target Detection and Recognition Methods and Systems in Low Altitude and Sea Environment Effective date of registration: 20230801 Granted publication date: 20201030 Pledgee: China Minsheng Banking Corp Shanghai branch Pledgor: SHANGHAI YINGJUE TECHNOLOGY CO.,LTD. Registration number: Y2023310000419 |
|
| PC01 | Cancellation of the registration of the contract for pledge of patent right | ||
| PC01 | Cancellation of the registration of the contract for pledge of patent right |
Granted publication date: 20201030 Pledgee: China Minsheng Banking Corp Shanghai branch Pledgor: SHANGHAI YINGJUE TECHNOLOGY CO.,LTD. Registration number: Y2023310000419 |