CN106199555A - A kind of unmanned boat navigation radar for collision avoidance detection method - Google Patents
A kind of unmanned boat navigation radar for collision avoidance detection method Download PDFInfo
- Publication number
- CN106199555A CN106199555A CN201610792104.XA CN201610792104A CN106199555A CN 106199555 A CN106199555 A CN 106199555A CN 201610792104 A CN201610792104 A CN 201610792104A CN 106199555 A CN106199555 A CN 106199555A
- Authority
- CN
- China
- Prior art keywords
- target
- radar
- unmanned boat
- detection
- collision avoidance
- 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.)
- Pending
Links
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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/411—Identification of targets based on measurements of radar reflectivity
-
- 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
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/937—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of marine craft
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Ocean & Marine Engineering (AREA)
- Electromagnetism (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a kind of unmanned boat navigation radar for collision avoidance detection method, comprise the steps: that radar antenna and transceiver carry out comprehensive target search to observed marine site, receive the reflection echo of target, after amplified frequency conversion detection, obtain the target raw video signal of band clutter;Send signal acquisition module to carry out A/D conversion raw video signal by Signal interface module, obtain the target raw digital video signal of band clutter;By ruggedized computer, target raw digital video signal is carried out software implementation point mark extraction, signal processing, clutter recognition and target detection automatically and follow the tracks of data process, receive the gyro compass of this ship, log, GPS, AIS and optoelectronic device signal simultaneously, carry out moving platform motion compensation and subject fusion, all kinds of naval target of acquisition and tracking, set up targetpath, then tracing detection.Present invention achieves the unmanned boat under complicated sea condition to marine multi-batch targets comprehensive survey, follow the tracks of and identify.
Description
Technical field
The present invention relates to people's ship to naval target comprehensive survey, follow the tracks of and identify systems technology field, be specifically related to one
Unmanned boat navigation radar for collision avoidance detection method.
Background technology
The easy pathfinder detectivity that existing spitkit is used is weak, the most at most can only manually follow the tracks of 20 batches
Target, cannot detect Small object under clutter conditions, therefore can not meet unmanned boat navigation collision prevention requirement, to this, Wo Men
On the basis of spitkit pathfinder antenna and transceiver unit, the detect and track technology of small maneuvering target is carried out greatly
Quantifier elimination, improves emphatically signal processing technology, Clutter Rejection Technique and detecting and tracking algorithm, is greatly improved under clutter conditions little
Target detection capabilities, full-automatic target acquistion follow the tracks of ability, design and manufacture meet unmanned boat use require navigation collision prevention and
To naval target synthesis detection system.
Summary of the invention
Object of the present invention is to provide a kind of unmanned boat navigation radar for collision avoidance detection method, at spitkit navigation thunder
On the basis of reaching antenna and transceiver unit, use spitkit pathfinder antenna and the technology of transceiver integration, carry out
Software implementation radar system design, improves emphatically signal processing technology, Clutter Rejection Technique and detecting and tracking algorithm, is greatly improved miscellaneous
Under the conditions of ripple, ability is followed the tracks of in small target deteection ability, full-automatic target acquistion, simple with overcome existing spitkit to be used
Pathfinder detectivity weak, the most at most can only manually follow the tracks of 20 batches of targets, Small object under clutter conditions, cannot be detected,
Therefore the requirement of unmanned boat navigation collision prevention can not be met.
The purpose of the present invention is achieved through the following technical solutions:
The detection method of a kind of unmanned boat navigation radar for collision avoidance detection system, comprises the steps:
S1, radar antenna and transceiver carry out comprehensive target search to observed marine site, receive the reflection echo of target,
The target raw video signal of band clutter is obtained after amplified frequency conversion detection;
S2, send signal acquisition module to carry out A/D conversion raw video signal by Signal interface module, obtain band clutter
Target raw digital video signal;
S3, by ruggedized computer 1 target raw digital video signal carried out automatically software implementation point mark extract, at signal
Reason, clutter recognition and target detection are followed the tracks of data and are processed, and receive the gyro compass of this ship, log, GPS, AIS and photoelectricity simultaneously and set
Standby signal, carries out moving platform motion compensation and subject fusion, and targetpath set up by all kinds of naval target of acquisition and tracking, then with
Track detects;
S4, indication control board receive the digital radar video signal after the track data of target, status signal and compression;In aobvious control
On platform, radar is remotely controlled operation, real-time comprehensive gamut display digital radar video image, target component and target boat
The navigation information of anti-collision that mark etc. are necessary, integration objective situation map.
Preferably, radar completes no-coherence cumulating detection, i.e. TBD by the process of repeatedly search sweep, utilizes sky
Line scanning inter-frame information, when target interframe is independent, antenna turns over n circle, and the probability of detection occurred at least once is that Pm is
Wherein Pi is the probability of detection often enclosed.Obviously, utilize the resource of time to do long-time accumulation, detection can be improved
Energy.
Target in single frames scanning signal is had and invariably makes a decision by this technology, but tires out the energy of multiframe signal
Long-pending, due to pathfinder antenna rotation rate generally at about 24RPM, rotating speed is relatively slow, therefore when target maneuver or this ship are motor-driven,
Target location had within the time that antenna rotates a circle moves significantly, and therefore long-time cumulative process will can to target
The resolution cell that can occur is made estimation and calculates, anticipation target position on space plane, then associates between several observation
Every or resident period likely correspond to the resolution cell of target travel, TBD is to tire out in the interim of radar Multiple-Scan
Long-pending, improve small target deteection performance.
Preferably, target location is obtained by filtering algorithm for estimating based on target travel kinetics equation and observational equation
Precise information.In actual application, need to do a series of engineerings such as including model foundation, system noise, performance evaluation
Analyze.
Targets Dots data association is the premise realizing multiple target tracking.The correctness that data association processes directly affects
Tracking accuracy and flight path quality.The data association of mistake will cause the loss of correct flight path and the increase of false track.Preferably,
Radar uses JPDA method on the basis of Probabilistic Data Association Algorithm, concrete, uses optimum Bayesian Method, examines
That considers Bo Mennei is had a mark, according to different spread patterns, carries out joint hypothesis, calculates joint probability, and by probability with carry out
Target association;In mathematical analysis, i.e. solve n-th mark associate the probability problem corresponding to N+1 hypothesis of m-th flight path.
A kind of well method of multiple target tracking under dense clutter environment.Intersect or mesh adjacent to each other especially for following the tracks of
Mark has preferable performance.
Preferably, use multiple hypotheis tracking algorithm (being called for short MHT), binding site mark data intelligence corresponding technology, produce and assume
Flight path, each flight path carries out probability calculation, forms the concept of class;Assume not only to consider the probability of false-alarm each time, also examine
Consider the probability that fresh target occurs, and the hypothesis in k moment is considered a certain hypothesis and the current data set pass in k-1 moment
The result of connection.Consider the situations such as flight path overlapping, point row, merging simultaneously.
Preferably, use Classification and Identification, concrete, by for a long time for the observation of sea-surface target and substantial amounts of for various
The raw data acquisition analysis of typical case's sea-surface target (including buoy, skiff, Large Container Ship, general cargo carrier etc.), is formed
Divide with the detailed target that the various data such as RCS range value time series and shape, size and corresponding running orbit are characterized
Class identification storehouse;By data base, can be the most real-time the target of radar detection is carried out Classification and Identification, improve to target with
Track recognition performance.
Preferably, being adapted to the change of dbjective state by multi-mode tracking wave filter, multi-mode tracking (being called for short MMT) includes
Two wave filter, one is target maneuver kinetic model, and another is target non-maneuver kinetic model, and final valuation is logical
The weighting crossing two wave filter outputs obtains, and therefore weighting used is exactly that posteriority assumes probability;Maneuvering target is regarded as mesh
Mark the interior change of dynamic characteristic rather than regard addition or the correction of state-noise variance as, two models thus constructed
The mutual conversion of two models is realized by motor-driven detector.
In the present invention, continuous wave radar head is solid state microwave integrated design, and compact conformation, volume are little, lightweight, corrosion resistant
Erosion performance is strong, it is adaptable to the little unmanned boat of hull.Computer plays continuous wave radar capacity of resisting disturbance advantage and completes signal processing, miscellaneous
Ripple suppresses and detects, follows the tracks of and identify.Designing of Reinforced Computer has protection against the tide, Defend salt fog, mould proof, anti-vibration, shock proof energy
Power, it is adaptable to unmanned boat speed is fast, use bad environments, install lift-launch condition difference ring border.
The method have the advantages that
Use the signal processing and data processing algorithm improved, set up Objective extraction and tracking under strong sea clutter background
Mathematical model, carries out, across cycle digitized relevant treatment, putting forth effort to solve the target acquisition under complicated sea condition and tracking;Utilize real
Target characteristic data storehouse under the sea clutter background of border, carries out pattern recognition to the target under strong clutter background, relatively low in signal to noise ratio
In the case of can effectively distinguish target and clutter, the system that substantially increases target acquisition ability under strong sea clutter background, for letter
Make an uproar and can effectively distinguish target and clutter one new approach of offer in the case of relatively low.
Accompanying drawing explanation
Fig. 1 is the structural representation of embodiment of the present invention unmanned boat navigation radar for collision avoidance detection system;
Fig. 2 is the flow chart of embodiment of the present invention unmanned boat navigation radar for collision avoidance detection system detection method.
Detailed description of the invention
Below in conjunction with specific embodiment, the present invention is described in detail.Following example will assist in the technology of this area
Personnel are further appreciated by the present invention, but limit the present invention the most in any form.It should be pointed out that, the ordinary skill to this area
For personnel, without departing from the inventive concept of the premise, it is also possible to make some deformation and improvement.These broadly fall into the present invention
Protection domain.
As it is shown in figure 1, embodiments provide a kind of unmanned boat navigation radar for collision avoidance detection system, whole system master
Integrated treatment unit is researched and developed by radar, radar antenna, transceiver, servo Transmit-Receive Unit, servo Transmit-Receive Unit includes >=
40MHz signal acquisition module, Designing of Reinforced Computer, detecting and tracking module, clutter recognition module, research and development integrated treatment unit includes
One central control board display controls computer, can match equipment (gyro compass, log, GPS, AIS and optoelectronic device neatly
Deng), reserved information centre.
As in figure 2 it is shown, the embodiment of the present invention additionally provides the detection side of a kind of unmanned boat navigation radar for collision avoidance detection system
Method, comprises the steps:
S1, radar antenna and transceiver carry out comprehensive target search to observed marine site, receive the reflection echo of target,
The target raw video signal of band clutter is obtained after amplified frequency conversion detection;
S2, send signal acquisition module to carry out A/D conversion raw video signal by Signal interface module, obtain band clutter
Target raw digital video signal;
S3, by ruggedized computer 1 target raw digital video signal carried out automatically software implementation point mark extract, at signal
Reason, clutter recognition and target detection are followed the tracks of data and are processed, and receive the gyro compass of this ship, log, GPS, AIS and photoelectricity simultaneously and set
Standby signal, carries out moving platform motion compensation and subject fusion, and targetpath set up by all kinds of naval target of acquisition and tracking, then with
Track detects;
S4, indication control board receive the digital radar video signal after the track data of target, status signal and compression;In aobvious control
On platform, radar is remotely controlled operation, real-time comprehensive gamut display digital radar video image, target component and target boat
The navigation information of anti-collision that mark etc. are necessary, integration objective situation map.
Radar completes no-coherence cumulating detection, i.e. TBD by the process of repeatedly search sweep, utilizes antenna scanning frame
Between information, when target interframe is independent, antenna turns over n circle, and the probability of detection occurred at least once is that Pm is
Wherein Pi is the probability of detection often enclosed.Obviously, utilize the resource of time to do long-time accumulation, detection can be improved
Energy.
Target in single frames scanning signal is had and invariably makes a decision by this technology, but tires out the energy of multiframe signal
Long-pending, due to pathfinder antenna rotation rate generally at about 24RPM, rotating speed is relatively slow, therefore when target maneuver or this ship are motor-driven,
Target location had within the time that antenna rotates a circle moves significantly, and therefore long-time cumulative process will can to target
The resolution cell that can occur is made estimation and calculates, anticipation target position on space plane, then associates between several observation
Every or resident period likely correspond to the resolution cell of target travel, TBD is to tire out in the interim of radar Multiple-Scan
Long-pending, improve small target deteection performance.
The accurate of target location is obtained by filtering algorithm for estimating based on target travel kinetics equation and observational equation
Information.In actual application, need to do a series of project analysis such as including model foundation, system noise, performance evaluation.
Targets Dots data association is the premise realizing multiple target tracking.The correctness that data association processes directly affects
Tracking accuracy and flight path quality.The data association of mistake will cause the loss of correct flight path and the increase of false track.Preferably,
Radar uses JPDA method on the basis of Probabilistic Data Association Algorithm, concrete, uses optimum Bayesian Method, examines
That considers Bo Mennei is had a mark, according to different spread patterns, carries out joint hypothesis, calculates joint probability, and by probability with carry out
Target association;In mathematical analysis, i.e. solve n-th mark associate the probability problem corresponding to N+1 hypothesis of m-th flight path.
A kind of well method of multiple target tracking under dense clutter environment.Intersect or mesh adjacent to each other especially for following the tracks of
Mark has preferable performance.
Use multiple hypotheis tracking algorithm (being called for short MHT), binding site mark data intelligence corresponding technology, produce and assume flight path, often
One flight path carries out probability calculation, forms the concept of class;Assume not only to consider the probability of false-alarm each time, it is also considered that fresh target
The probability occurred, and the hypothesis in k moment is considered the knot that a certain hypothesis in k-1 moment associates with current data set
Really.Consider the situations such as flight path overlapping, point row, merging simultaneously.
Use Classification and Identification, concrete, by for a long time for the observation of sea-surface target and substantial amounts of for various typical case seas
The raw data acquisition analysis of Area Objects (including buoy, skiff, Large Container Ship, general cargo carrier etc.), is formed with RCS width
The detailed target classification identification that the various data such as angle value time series and shape, size and corresponding running orbit are characterized
Storehouse;By data base, can be the most real-time the target of radar detection is carried out Classification and Identification, improve the Tracking Recognition to target
Performance.
Adapted to the change of dbjective state by multi-mode tracking wave filter, multi-mode tracking (being called for short MMT) includes two filters
Ripple device, one is target maneuver kinetic model, and another is target non-maneuver kinetic model, and final valuation is by two
The weighting of wave filter output obtains, and therefore weighting used is exactly that posteriority assumes probability;Maneuvering target is regarded as target dynamic
The interior change of characteristic rather than regard addition or the correction of state-noise variance as, two models thus constructed pass through machine
Dynamic detector realizes the mutual conversion of two models
In the present invention, continuous wave radar head is solid state microwave integrated design, and compact conformation, volume are little, lightweight, corrosion resistant
Erosion performance is strong, it is adaptable to the little unmanned boat of hull.Computer plays continuous wave radar capacity of resisting disturbance advantage and completes signal processing, miscellaneous
Ripple suppresses and detects, follows the tracks of and identify.Designing of Reinforced Computer has protection against the tide, Defend salt fog, mould proof, anti-vibration, shock proof energy
Power, it is adaptable to unmanned boat speed is fast, use bad environments, install lift-launch condition difference ring border.
Above the specific embodiment of the present invention is described.It is to be appreciated that the invention is not limited in above-mentioned
Particular implementation, those skilled in the art can make various deformation or amendment within the scope of the claims, this not shadow
Ring the flesh and blood of the present invention.
Claims (7)
1. the detection method of a unmanned boat navigation radar for collision avoidance detection system, it is characterised in that comprise the steps:
S1, radar antenna and transceiver carry out comprehensive target search to observed marine site, receive the reflection echo of target, through putting
The target raw video signal of band clutter is obtained after big frequency conversion detection;
S2, send signal acquisition module to carry out A/D conversion raw video signal by Signal interface module, obtain the mesh of band clutter
Mark raw digital video signal;
S3, by ruggedized computer target raw digital video signal carried out automatically software implementation point mark extraction, signal processing, miscellaneous
Ripple suppression and target detection are followed the tracks of data and are processed, and receive the gyro compass of this ship, log, GPS, AIS and optoelectronic device letter simultaneously
Number, carry out moving platform motion compensation and subject fusion, all kinds of naval target of acquisition and tracking, set up targetpath, then follow the tracks of inspection
Survey;
S4, indication control board receive the digital radar video signal after the track data of target, status signal and compression;On indication control board
Radar is remotely controlled operation, real-time comprehensive gamut display digital radar video image, target component and targetpath etc.
Necessary navigation information of anti-collision, integration objective situation map.
The detection method of a kind of unmanned boat the most as claimed in claim 1 navigation radar for collision avoidance detection system, it is characterised in that thunder
Reach and complete no-coherence cumulating detection, i.e. TBD by the process of repeatedly search sweep.
The detection method of a kind of unmanned boat the most as claimed in claim 1 navigation radar for collision avoidance detection system, it is characterised in that logical
Cross filtering algorithm for estimating based on target travel kinetics equation and observational equation and obtain the precise information of target location.
The detection method of a kind of unmanned boat the most as claimed in claim 1 navigation radar for collision avoidance detection system, it is characterised in that thunder
Reach employing JPDA method on the basis of Probabilistic Data Association Algorithm, concrete, use optimum Bayesian Method, it is considered to
Bo Mennei is had a mark, according to different spread patterns, carries out joint hypothesis, calculates joint probability, and by probability with carry out mesh
Mark association.
The detection method of a kind of unmanned boat the most as claimed in claim 1 navigation radar for collision avoidance detection system, it is characterised in that adopt
Using multiple hypotheis tracking algorithm, binding site mark data intelligence corresponding technology, produce and assume flight path, each flight path carries out probability meter
Calculate, form the concept of class;Assume not only to consider the probability of false-alarm each time, it is also considered that the probability that fresh target occurs, and
The hypothesis in k moment is considered the result that a certain hypothesis in k-1 moment associates with current data set.
The detection method of a kind of unmanned boat the most as claimed in claim 1 navigation radar for collision avoidance detection system, it is characterised in that adopt
By Classification and Identification, concrete, by for a long time for observation and substantial amounts of former for various typical case's sea-surface targets of sea-surface target
Beginning data collection and analysis, formed with RCS range value time series and shape, size and corresponding running orbit be characterized detailed
Target classification identification storehouse;By data base, can be the most real-time the target of radar detection is carried out Classification and Identification, it is right to improve
The Tracking Recognition performance of target.
The detection method of a kind of unmanned boat the most as claimed in claim 1 navigation radar for collision avoidance detection system, it is characterised in that logical
Crossing multi-mode tracking wave filter and adapt to the change of dbjective state, multi-mode tracking (being called for short MMT) includes two wave filter, and one is
Target maneuver kinetic model, another is target non-maneuver kinetic model, and final valuation is to be exported by two wave filter
Weighting obtain, weighting used be therefore exactly posteriority assume probability;Maneuvering target is regarded as the inside of target dynamic characteristic
Change, two models thus constructed realize the mutual conversion of two models by motor-driven detector.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610792104.XA CN106199555A (en) | 2016-08-31 | 2016-08-31 | A kind of unmanned boat navigation radar for collision avoidance detection method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610792104.XA CN106199555A (en) | 2016-08-31 | 2016-08-31 | A kind of unmanned boat navigation radar for collision avoidance detection method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106199555A true CN106199555A (en) | 2016-12-07 |
Family
ID=58085381
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610792104.XA Pending CN106199555A (en) | 2016-08-31 | 2016-08-31 | A kind of unmanned boat navigation radar for collision avoidance detection method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106199555A (en) |
Cited By (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107040583A (en) * | 2017-02-20 | 2017-08-11 | 中国船舶重工集团公司第七0七研究所 | A kind of unmanned boat information interaction system |
CN107329477A (en) * | 2017-08-14 | 2017-11-07 | 河海大学常州校区 | A kind of unmanned boat navigation and autopilot facility and its method |
CN107748561A (en) * | 2017-09-25 | 2018-03-02 | 华南理工大学 | A kind of unmanned boat part obstacle avoidance system and method based on more parameter sensings |
CN107767668A (en) * | 2017-10-19 | 2018-03-06 | 深圳市置辰海信科技有限公司 | A kind of method based on the continuous real-time tracking of radar active probe vehicle |
CN108226930A (en) * | 2017-12-20 | 2018-06-29 | 扬州宇安电子科技有限公司 | A kind of carrier-borne small-size multifunction radar |
CN108241147A (en) * | 2018-02-06 | 2018-07-03 | 上海圆舟电子科技有限公司 | A kind of palm intelligent maritime affairs radar and its surface surveillance method |
CN109298708A (en) * | 2018-08-31 | 2019-02-01 | 中船重工鹏力(南京)大气海洋信息***有限公司 | A kind of unmanned boat automatic obstacle avoiding method merging radar and photoelectric information |
CN109782247A (en) * | 2019-01-28 | 2019-05-21 | 中船重工鹏力(南京)大气海洋信息***有限公司 | A method of utilizing track Information revision radar return |
CN109850092A (en) * | 2019-01-10 | 2019-06-07 | 安徽天帆智能科技有限责任公司 | A kind of unmanned lifeboat makes a return voyage system automatically |
CN109932701A (en) * | 2019-04-02 | 2019-06-25 | 哈尔滨工程大学 | A kind of object ship echo 2D imaging method for simulating marine radar |
WO2019119177A1 (en) * | 2017-12-18 | 2019-06-27 | 深圳市大疆创新科技有限公司 | Weak target detection method, microwave radar sensor and unmanned aerial vehicle |
CN110031816A (en) * | 2019-03-22 | 2019-07-19 | 中国民航科学技术研究院 | Based on the Flying Area in Airport noncooperative target classifying identification method for visiting bird radar |
CN111323757A (en) * | 2019-12-30 | 2020-06-23 | 北京海兰信数据科技股份有限公司 | Target detection method and device for marine radar |
CN111596269A (en) * | 2020-05-25 | 2020-08-28 | 中国人民解放军海军航空大学 | Method for detecting radar composite detection target capability |
CN111949034A (en) * | 2020-08-21 | 2020-11-17 | 闽江学院 | Unmanned ship autonomous navigation system |
CN112101158A (en) * | 2020-09-04 | 2020-12-18 | 四川智海联科技有限公司 | Ship navigation auxiliary system and method based on deep learning and visual SLAM |
CN112526507A (en) * | 2020-11-06 | 2021-03-19 | 广州辰创科技发展有限公司 | Radar and photoelectric scanning combined collision avoidance method and system |
CN113009470A (en) * | 2021-02-09 | 2021-06-22 | 北京理工大学 | Target situation characteristic data processing method, system, device and medium |
CN115342814A (en) * | 2022-07-26 | 2022-11-15 | 江苏科技大学 | Unmanned ship positioning method based on multi-sensor data fusion |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7016772B2 (en) * | 2001-08-03 | 2006-03-21 | Furuno Electric Company, Limited | Vehicle information display apparatus |
CN201314952Y (en) * | 2008-07-14 | 2009-09-23 | 上海智森航海电子科技有限公司 | Ship navigation radar with automatic plotting and tracking |
-
2016
- 2016-08-31 CN CN201610792104.XA patent/CN106199555A/en active Pending
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7016772B2 (en) * | 2001-08-03 | 2006-03-21 | Furuno Electric Company, Limited | Vehicle information display apparatus |
CN201314952Y (en) * | 2008-07-14 | 2009-09-23 | 上海智森航海电子科技有限公司 | Ship navigation radar with automatic plotting and tracking |
Non-Patent Citations (1)
Title |
---|
徐学发: ""嵌入式导航雷达显控终端的研究与设计"", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (29)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107040583A (en) * | 2017-02-20 | 2017-08-11 | 中国船舶重工集团公司第七0七研究所 | A kind of unmanned boat information interaction system |
CN107329477B (en) * | 2017-08-14 | 2020-05-15 | 河海大学常州校区 | Unmanned ship navigation and automatic driving equipment and method thereof |
CN107329477A (en) * | 2017-08-14 | 2017-11-07 | 河海大学常州校区 | A kind of unmanned boat navigation and autopilot facility and its method |
CN107748561A (en) * | 2017-09-25 | 2018-03-02 | 华南理工大学 | A kind of unmanned boat part obstacle avoidance system and method based on more parameter sensings |
CN107767668A (en) * | 2017-10-19 | 2018-03-06 | 深圳市置辰海信科技有限公司 | A kind of method based on the continuous real-time tracking of radar active probe vehicle |
US11105894B2 (en) | 2017-12-18 | 2021-08-31 | SZ DJI Technology Co., Ltd. | Weak target detection method, microwave radar sensor, and unmanned aerial vehicle |
WO2019119177A1 (en) * | 2017-12-18 | 2019-06-27 | 深圳市大疆创新科技有限公司 | Weak target detection method, microwave radar sensor and unmanned aerial vehicle |
CN108226930A (en) * | 2017-12-20 | 2018-06-29 | 扬州宇安电子科技有限公司 | A kind of carrier-borne small-size multifunction radar |
CN108241147A (en) * | 2018-02-06 | 2018-07-03 | 上海圆舟电子科技有限公司 | A kind of palm intelligent maritime affairs radar and its surface surveillance method |
CN109298708A (en) * | 2018-08-31 | 2019-02-01 | 中船重工鹏力(南京)大气海洋信息***有限公司 | A kind of unmanned boat automatic obstacle avoiding method merging radar and photoelectric information |
CN109298708B (en) * | 2018-08-31 | 2021-08-17 | 中船重工鹏力(南京)大气海洋信息***有限公司 | Unmanned ship autonomous obstacle avoidance method integrating radar and photoelectric information |
CN109850092A (en) * | 2019-01-10 | 2019-06-07 | 安徽天帆智能科技有限责任公司 | A kind of unmanned lifeboat makes a return voyage system automatically |
CN109782247A (en) * | 2019-01-28 | 2019-05-21 | 中船重工鹏力(南京)大气海洋信息***有限公司 | A method of utilizing track Information revision radar return |
CN109782247B (en) * | 2019-01-28 | 2020-09-22 | 中船重工鹏力(南京)大气海洋信息***有限公司 | Method for correcting radar echo by using track information |
CN110031816A (en) * | 2019-03-22 | 2019-07-19 | 中国民航科学技术研究院 | Based on the Flying Area in Airport noncooperative target classifying identification method for visiting bird radar |
CN110031816B (en) * | 2019-03-22 | 2021-04-27 | 中国民航科学技术研究院 | Airport flight area non-cooperative target classification and identification method based on bird detection radar |
CN109932701A (en) * | 2019-04-02 | 2019-06-25 | 哈尔滨工程大学 | A kind of object ship echo 2D imaging method for simulating marine radar |
CN111323757A (en) * | 2019-12-30 | 2020-06-23 | 北京海兰信数据科技股份有限公司 | Target detection method and device for marine radar |
CN111596269A (en) * | 2020-05-25 | 2020-08-28 | 中国人民解放军海军航空大学 | Method for detecting radar composite detection target capability |
CN111596269B (en) * | 2020-05-25 | 2022-04-19 | 中国人民解放军海军航空大学 | Method for detecting radar composite detection target capability |
CN111949034A (en) * | 2020-08-21 | 2020-11-17 | 闽江学院 | Unmanned ship autonomous navigation system |
CN112101158A (en) * | 2020-09-04 | 2020-12-18 | 四川智海联科技有限公司 | Ship navigation auxiliary system and method based on deep learning and visual SLAM |
CN112526507A (en) * | 2020-11-06 | 2021-03-19 | 广州辰创科技发展有限公司 | Radar and photoelectric scanning combined collision avoidance method and system |
CN112526507B (en) * | 2020-11-06 | 2024-01-16 | 广州辰创科技发展有限公司 | Collision prevention method and system combining radar and photoelectric scanning |
CN113009470A (en) * | 2021-02-09 | 2021-06-22 | 北京理工大学 | Target situation characteristic data processing method, system, device and medium |
CN113009470B (en) * | 2021-02-09 | 2023-04-21 | 北京理工大学 | Processing method, system, device and medium for target situation characteristic data |
CN115342814A (en) * | 2022-07-26 | 2022-11-15 | 江苏科技大学 | Unmanned ship positioning method based on multi-sensor data fusion |
WO2024021642A1 (en) * | 2022-07-26 | 2024-02-01 | 江苏科技大学 | Unmanned ship positioning method based on multi-sensor data fusion |
CN115342814B (en) * | 2022-07-26 | 2024-03-19 | 江苏科技大学 | Unmanned ship positioning method based on multi-sensor data fusion |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106199555A (en) | A kind of unmanned boat navigation radar for collision avoidance detection method | |
CN110414396B (en) | Unmanned ship perception fusion algorithm based on deep learning | |
CN110275153B (en) | Water surface target detection and tracking method based on laser radar | |
CN102081801B (en) | Multi-feature adaptive fused ship tracking and track detecting method | |
Neves et al. | Rotated object detection with forward-looking sonar in underwater applications | |
CN111157982A (en) | Intelligent ship and shore cooperative target tracking system and method based on shore-based radar | |
CN111899568B (en) | Bridge anti-collision early warning system, method and device and storage medium | |
CN105184816A (en) | Visual inspection and water surface target tracking system based on USV and detection tracking method thereof | |
CN102915650A (en) | Convergent photography-based ship navigation safety early-warning equipment for ships in water area of bridges | |
CN111123212A (en) | Signal processing method of scene surveillance radar based on complex clutter background | |
CN111323756B (en) | Marine radar target detection method and device based on deep learning | |
CN105022057A (en) | A target detection method based on improved Radon transformation and multi-frame jointed processing | |
EP2211200A1 (en) | Marine radar system with three-dimensional memory | |
CN111323757B (en) | Target detection method and device for marine radar | |
CN107945580A (en) | Marine traction system AIS virtually guards against mark designation system and method | |
CN102270394A (en) | Vessel traffic monitoring method based on laser sensor | |
CN112289004B (en) | River monitoring and early warning method and system | |
CN111289944B (en) | Unmanned ship position and course measuring method based on UWB positioning | |
Qin et al. | Research on information fusion structure of radar and AIS | |
CN115857520A (en) | Unmanned aerial vehicle carrier landing state monitoring method based on combination of vision and ship state | |
CN113484864B (en) | Unmanned ship-oriented navigation radar and photoelectric pod collaborative environment sensing method | |
Yan et al. | Clustering statistic Hough transform based estimation method for motion elements of multiple underwater targets | |
CN112731400B (en) | Method and system for estimating target vector speed of marine vessel | |
CN115032601A (en) | Marine radar target detection algorithm for inhibiting sea clutter in image sequence based on space-time combined filtering technology | |
JP2011185719A (en) | Tracking radar device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161207 |