CN106291588A - A kind of cloud layer signal automatic-identifying method based on finite state machine - Google Patents
A kind of cloud layer signal automatic-identifying method based on finite state machine Download PDFInfo
- Publication number
- CN106291588A CN106291588A CN201610632797.6A CN201610632797A CN106291588A CN 106291588 A CN106291588 A CN 106291588A CN 201610632797 A CN201610632797 A CN 201610632797A CN 106291588 A CN106291588 A CN 106291588A
- Authority
- CN
- China
- Prior art keywords
- cloud
- signal
- peak
- ceilometer
- value
- 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
- 238000000034 method Methods 0.000 title claims abstract description 23
- 230000003595 spectral effect Effects 0.000 claims description 6
- 238000012790 confirmation Methods 0.000 claims description 3
- 238000001228 spectrum Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 abstract description 3
- 239000003595 mist Substances 0.000 abstract description 2
- 230000008033 biological extinction Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000001556 precipitation Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/95—Lidar systems specially adapted for specific applications for meteorological use
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Electromagnetism (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
- Length Measuring Devices With Unspecified Measuring Means (AREA)
Abstract
The invention discloses a kind of cloud layer signal automatic-identifying method based on finite state machine, the method is set about according to the global feature of cloud layer signal, the basic feature of cloud layer signal is summarised as cloud base, Yun Feng, cloud top and the public boundary of two clouds, by ceilometer echo-signal being encoded to cloud layer signal description statement, then ceilometer signal is selected respectively.First the present invention has carried out smothing filtering to cloud signal and relevant inverted parameters and has asked for echo-signal first derivative, then the public boundary to cloud base, Yun Feng, cloud top and two clouds is encoded to cloud layer signal description statement, by to the feature identification of cloud layer signal and logical analysis, avoid the situation that the signals such as rain, mist and spike interference are mistaken for cloud signal, and provide the position on the cloud base in cloud layer, Yun Feng, cloud top, at most can meet the situation identifying three stratus, improve cloud layer signal recognition success rate.
Description
Technical field
The invention belongs to field of spectral analysis technology, be specifically related to a kind of cloud layer signal based on finite state machine and automatically know
Other method, is mainly used in automatically identifying and the automatic output of cloud base, Yun Feng and position, cloud top of air medium cloud signal.
Background technology
In current weather service observation, the observation of cloud is an important project, and observed pattern is seen mainly by artificial
Surveying, but artificial observation exists again the shortcomings such as strong, the accurate rate variance of subjectivity, therefore, China Meteorological Administration has been contemplated that use laser cloud
High instrument replaces artificial observation.Existing ceiling of clouds inversion algorithm based on ceilometer or laser radar mainly has differential zero crossing
Method, Klett method, sliding window integration method etc., but these several inversion algorithms are the most more complicated, and algorithm operation quantity is bigger.Differential
Zero crossing there is problems of the zero crossing of echo-signal differential and there may be a lot, and the noise in radar echo signal also can
Producing the most extra zero crossing, extracting effective zero point from numerous zero points is an extremely complex job.Klett
Method has the most hypothetical precondition when calculating extinction coefficient, brings certain error to the calculating of extinction coefficient, because of
And cloud level inversion algorithm of based on extinction coefficient also certainly exists certain error.Sliding window integration method there is problems of window
Separation results can be produced a very large impact by the selection of mouth size, and window too conference brings certain difficulty to the determination of position, cloud base,
Window is the least, is difficult to selected threshold, and the signal of some superposition noise may will not effectively be got rid of.Based on background above feelings
Condition, the present invention proposes a kind of cloud signal automatic identification algorithm based on finite state machine, and algorithm is the most popular, cloud signal identification
Success rate is high.
Summary of the invention:
It is an object of the invention to provide a kind of cloud layer signal automatic-identifying method based on finite state machine, it is achieved that cloud layer is believed
Cloud base in number, Yun Feng, accurately the finding and output of cloud level position, solve existing seeking and seek in cloud method that cloud precision is low, operand
Big problem.
The technical solution used in the present invention is:
A kind of cloud layer signal automatic-identifying method based on finite state machine, it is characterised in that mainly comprise the steps that
(1) gathering original signal data by ceilometer, described ceilometer original signal data includes the distance value of series increase
Each apart from upper signal intensity with corresponding；
(2) using the meansigma methods of primary signal more than ceilometer certain height as the background value of ceilometer primary signal, by cloud
The primary signal subtracting background of Gao Yi is worth to the echo-signal of ceilometer；
(3) use slip Savitzky-Golay method that ceilometer echo-signal is asked for first derivative and obtain the slope of echo-signal
Profile；
(4) increase suddenly when the slope value in ceilometer echo-signal somewhere and the slope of following continuous several points is both greater than one
When determining threshold value, algorithm is detected by cloud signal, and in this case, algorithm starts the bottom down searching for cloud and upwards searches for cloud
Top；
(5) with the catastrophe point in step (4) as starting point, in a suitable window, the maximum of echo-signal is upwards found also
Compare the relation of this maximum and next value simultaneously, when next one value is more than this maximum, next one value is assigned to this
Maximum, until loop ends, exports the position that this maximum is corresponding simultaneously；When next one value is much smaller than this maximum, defeated
Go out this maximum value position, simultaneously loop ends；
(6) maximum value position in step (5) is temporarily labeled as cloud peak position；
(7) it is set to starting point with cloud peak position, in the range of a certain distance, searches for downwards cloud layer bottom position, when echo-signal somewhere
Slope suddenly from signal to noise ratio when just becoming negative or at this less than certain threshold value time, it is judged that be position, cloud base at this, with
Time loop ends；
(8) with the position at cloud peak as starting point, upwards search for the top of cloud, when the signal intensity in somewhere much smaller than cloud peak at signal strong
When the size of degree or the signal to noise ratio at this are less than certain threshold value, it is judged that be position, cloud top, simultaneously loop ends at this；
(9) after cloud base, Yun Feng, cloud top location confirmation, use the mode of full width at half maximum to ask for cloud thick, only work as cloud thickness
During more than certain threshold value, it is judged that this signal meets cloud signal thickness condition；
(10) when the signal intensity of cloud being carried out threshold value and limiting, mainly by the end with this respectively of the signal intensity at cloud peak
Lower section carry out size with the signal of the top on cloud top and compare and judge whether to meet at certain threshold condition, only cloud peak
Intensity more than the signal below the cloud base of certain multiple or the signal above cloud top, thinks this in the range of a certain distance just now
Signal meets cloud signal strength conditions；
(11) if the width of spectral peak signal and intensity all meet requirement, confirm that this spectral peak signal is cloud layer signal, and from cloud top
Position begins look for next cloud layer position；If the peak width of cloud and peak height thresholding have one to be unsatisfactory for requirement, then judge this spectrum
Peak is pseudo-cloud layer signal, and then from step (4), the position of next signal point continues up searching cloud layer information；
(12) after the searching of cloud signal terminates, it is sequentially output the height and position on cloud base, Yun Feng, cloud top.
The invention have the advantage that
1. ceilometer echo-signal is asked for using slip Savitzky-Golay method during first derivative by the present invention, and the method can
It is prevented effectively from signal fluctuation and the impact of spike interference in cloud layer signal identification, more remains cloud layer signal characteristic；
2., when filtering cloud, mist and spike interference signal, cloud signal is used gate-width (cloud is thick) to limit and the high (cloud of door by the present invention
Signal intensity) limit, by cloud thickness is set certain threshold value, it is to avoid spike interference signal is mistaken for the situation of cloud signal；
By the signal intensity of cloud is carried out threshold restriction, it is to avoid fog and precipitation signal to be mistaken for the situation of cloud signal；
3. when cloud thickness is limited, use the mode of full width at half maximum to ask for cloud thick, effectively prevent cloud base and position, cloud top
Uncertainty bring cloud signal erroneous judgement situation；
4. first the present invention has carried out smothing filtering to cloud signal and relevant inverted parameters and has asked for echo-signal first derivative,
Then the public boundary to cloud base, Yun Feng, cloud top and two clouds is encoded to cloud layer signal description statement, by cloud layer signal
Feature identification and logical analysis, then use mode based on finite state machine to list the possible situation of cloud layer signal one by one also
Each self-identifying, final the output cloud base of cloud signal, Yun Feng, position, cloud top, at most can meet the situation identifying three stratus, carry
High cloud layer signal recognition success rate.
Accompanying drawing explanation
Fig. 1 is Laser Measuring cloud system schematic diagram.
Fig. 2 is cloud layer signal schematic representation.
Fig. 3 is ceilometer echo-signal figure.
Fig. 4 is the first derivative figure of ceilometer echo-signal.
Fig. 5 is that ceilometer seeks cloud algorithm flow chart.
Detailed description of the invention:
For making the object, technical solutions and advantages of the present invention more clear distinct, below in conjunction with being embodied as case, and with reference to attached
Figure, the present invention is described in more detail.
If Fig. 1 is Laser Measuring cloud system schematic diagram, include laser emission element, detecting signal unit, signal reception list
Unit.
Such as Fig. 2-5, a kind of cloud layer signal automatic-identifying method based on finite state machine, mainly comprise the steps that
(1) gathering original signal data by ceilometer, described ceilometer original signal data includes the distance value of series increase
Each apart from upper signal intensity with corresponding；
(2) using the meansigma methods of primary signal more than ceilometer certain height as the background value of ceilometer primary signal, by cloud
The primary signal subtracting background of Gao Yi is worth to the echo-signal of ceilometer；
(3) use slip Savitzky-Golay method that ceilometer echo-signal is asked for first derivative and obtain the slope of echo-signal
Profile；
(4) increase suddenly when the slope value in ceilometer echo-signal somewhere and the slope of following continuous several points is both greater than one
When determining threshold value, algorithm is detected by cloud signal, and in this case, algorithm starts the bottom down searching for cloud and upwards searches for cloud
Top；
(5) with the catastrophe point in step (4) as starting point, in a suitable window, the maximum of echo-signal is upwards found also
Compare the relation of this maximum and next value simultaneously, when next one value is more than this maximum, next one value is assigned to this
Maximum, until loop ends, exports the position that this maximum is corresponding simultaneously；When next one value is much smaller than this maximum, defeated
Go out this maximum value position, simultaneously loop ends；
(6) maximum value position in step (5) is temporarily labeled as cloud peak position；
(7) it is set to starting point with cloud peak position, in the range of a certain distance, searches for downwards cloud layer bottom position, when echo-signal somewhere
Slope suddenly from signal to noise ratio when just becoming negative or at this less than certain threshold value time, it is judged that be position, cloud base at this, with
Time loop ends；
(8) with the position at cloud peak as starting point, upwards search for the top of cloud, when the signal intensity in somewhere much smaller than cloud peak at signal strong
When the size of degree or the signal to noise ratio at this are less than certain threshold value, it is judged that be position, cloud top, simultaneously loop ends at this；
(9) after cloud base, Yun Feng, cloud top location confirmation, use the mode of full width at half maximum to ask for cloud thick, only work as cloud thickness
During more than certain threshold value, it is judged that this signal meets cloud signal thickness condition；
(10) when the signal intensity of cloud being carried out threshold value and limiting, mainly by the end with this respectively of the signal intensity at cloud peak
Lower section carry out size with the signal of the top on cloud top and compare and judge whether to meet at certain threshold condition, only cloud peak
Intensity more than the signal below the cloud base of certain multiple or the signal above cloud top, thinks this in the range of a certain distance just now
Signal meets cloud signal strength conditions；
(11) if the width of spectral peak signal and intensity all meet requirement, confirm that this spectral peak signal is cloud layer signal, and from cloud top
Position begins look for next cloud layer position；If the peak width of cloud and peak height thresholding have one to be unsatisfactory for requirement, then judge this spectrum
Peak is pseudo-cloud layer signal, and then from step (4), the position of next signal point continues up searching cloud layer information；
(12) after the searching of cloud signal terminates, it is sequentially output the height and position on cloud base, Yun Feng, cloud top.
Claims (1)
1. a cloud layer signal automatic-identifying method based on finite state machine, it is characterised in that mainly comprise the steps that
(1) gathering original signal data by ceilometer, described ceilometer original signal data includes the distance value of series increase
Each apart from upper signal intensity with corresponding；
(2) using the meansigma methods of primary signal more than ceilometer certain height as the background value of ceilometer primary signal, by cloud
The primary signal subtracting background of Gao Yi is worth to the echo-signal of ceilometer；
(3) use slip Savitzky-Golay method that ceilometer echo-signal is asked for first derivative and obtain the slope of echo-signal
Profile；
(4) increase suddenly when the slope value in ceilometer echo-signal somewhere and the slope of following continuous several points is both greater than one
When determining threshold value, algorithm is detected by cloud signal, and in this case, algorithm starts the bottom down searching for cloud and upwards searches for cloud
Top；
(5) with the catastrophe point in step (4) as starting point, in a suitable window, the maximum of echo-signal is upwards found also
Compare the relation of this maximum and next value simultaneously, when next one value is more than this maximum, next one value is assigned to this
Maximum, until loop ends, exports the position that this maximum is corresponding simultaneously；When next one value is much smaller than this maximum, defeated
Go out this maximum value position, simultaneously loop ends；
(6) maximum value position in step (5) is temporarily labeled as cloud peak position；
(7) it is set to starting point with cloud peak position, in the range of a certain distance, searches for downwards cloud layer bottom position, when echo-signal somewhere
Slope suddenly from signal to noise ratio when just becoming negative or at this less than certain threshold value time, it is judged that be position, cloud base at this, with
Time loop ends；
(8) with the position at cloud peak as starting point, upwards search for the top of cloud, when the signal intensity in somewhere much smaller than cloud peak at signal strong
When the size of degree or the signal to noise ratio at this are less than certain threshold value, it is judged that be position, cloud top, simultaneously loop ends at this；
(9) after cloud base, Yun Feng, cloud top location confirmation, use the mode of full width at half maximum to ask for cloud thick, only work as cloud thickness
During more than certain threshold value, it is judged that this signal meets cloud signal thickness condition；
(10) when the signal intensity of cloud being carried out threshold value and limiting, mainly by the end with this respectively of the signal intensity at cloud peak
Lower section carry out size with the signal of the top on cloud top and compare and judge whether to meet at certain threshold condition, only cloud peak
Intensity more than the signal below the cloud base of certain multiple or the signal above cloud top, thinks this in the range of a certain distance just now
Signal meets cloud signal strength conditions；
(11) if the width of spectral peak signal and intensity all meet requirement, confirm that this spectral peak signal is cloud layer signal, and from cloud top
Position begins look for next cloud layer position；If the peak width of cloud and peak height thresholding have one to be unsatisfactory for requirement, then judge this spectrum
Peak is pseudo-cloud layer signal, and then from step (4), the position of next signal point continues up searching cloud layer information；
(12) after the searching of cloud signal terminates, it is sequentially output the height and position on cloud base, Yun Feng, cloud top.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610632797.6A CN106291588A (en) | 2016-08-04 | 2016-08-04 | A kind of cloud layer signal automatic-identifying method based on finite state machine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610632797.6A CN106291588A (en) | 2016-08-04 | 2016-08-04 | A kind of cloud layer signal automatic-identifying method based on finite state machine |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106291588A true CN106291588A (en) | 2017-01-04 |
Family
ID=57664681
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610632797.6A Pending CN106291588A (en) | 2016-08-04 | 2016-08-04 | A kind of cloud layer signal automatic-identifying method based on finite state machine |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106291588A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106897998A (en) * | 2017-02-24 | 2017-06-27 | 深圳市昊睿智控科技服务有限公司 | Solar energy direct solar radiation strength information Forecasting Methodology and system |
| CN118393509A (en) * | 2024-06-28 | 2024-07-26 | 中电建(洛阳)绿色建筑科技有限公司 | Atmospheric correction method and system in complex environment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103901505A (en) * | 2014-03-11 | 2014-07-02 | 中国气象科学研究院 | Cloud top height detection method and device based on wet bulb effect |
| CN104316480A (en) * | 2014-11-06 | 2015-01-28 | 中国科学院合肥物质科学研究院 | Laser in-situ detection system for oxygen concentration in arsenic-bearing gold concentrate roasting furnace |
| CN104408770A (en) * | 2014-12-03 | 2015-03-11 | 北京航空航天大学 | Method for modeling cumulus cloud scene based on Landsat8 satellite image |
| CN104991260A (en) * | 2015-06-24 | 2015-10-21 | 中国科学院合肥物质科学研究院 | Semiconductor laser ceilometer-based cloud height automatic inversion method |
| CN105136021A (en) * | 2015-07-24 | 2015-12-09 | 哈尔滨工业大学 | Laser frequency scanning interferometer dispersion phase compensation method based on focusing definition evaluation function |
| CN105158770A (en) * | 2015-10-10 | 2015-12-16 | 中国科学技术大学 | Coherent wind measurement laser radar system with adjustable range resolution |
-
2016
- 2016-08-04 CN CN201610632797.6A patent/CN106291588A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103901505A (en) * | 2014-03-11 | 2014-07-02 | 中国气象科学研究院 | Cloud top height detection method and device based on wet bulb effect |
| CN104316480A (en) * | 2014-11-06 | 2015-01-28 | 中国科学院合肥物质科学研究院 | Laser in-situ detection system for oxygen concentration in arsenic-bearing gold concentrate roasting furnace |
| CN104408770A (en) * | 2014-12-03 | 2015-03-11 | 北京航空航天大学 | Method for modeling cumulus cloud scene based on Landsat8 satellite image |
| CN104991260A (en) * | 2015-06-24 | 2015-10-21 | 中国科学院合肥物质科学研究院 | Semiconductor laser ceilometer-based cloud height automatic inversion method |
| CN105136021A (en) * | 2015-07-24 | 2015-12-09 | 哈尔滨工业大学 | Laser frequency scanning interferometer dispersion phase compensation method based on focusing definition evaluation function |
| CN105158770A (en) * | 2015-10-10 | 2015-12-16 | 中国科学技术大学 | Coherent wind measurement laser radar system with adjustable range resolution |
Non-Patent Citations (1)
| Title |
|---|
| 毛飞跃等: "基于改进微分零交叉法的米氏散射激光雷达云检测与参数反演", 《光学学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106897998A (en) * | 2017-02-24 | 2017-06-27 | 深圳市昊睿智控科技服务有限公司 | Solar energy direct solar radiation strength information Forecasting Methodology and system |
| CN106897998B (en) * | 2017-02-24 | 2020-09-04 | 深圳市微埃智能科技有限公司 | Method and system for predicting information of direct solar radiation intensity |
| CN118393509A (en) * | 2024-06-28 | 2024-07-26 | 中电建(洛阳)绿色建筑科技有限公司 | Atmospheric correction method and system in complex environment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP5838901B2 (en) | Object identification device and object identification method | |
| CN114488194B (en) | A method for target detection and recognition on structured roads for intelligent driving vehicles | |
| US9507052B2 (en) | Automatic recognition method of continental slope foot point based on terrain grid | |
| Zhao et al. | Improvement of canny algorithm based on pavement edge detection | |
| CN109636829A (en) | A kind of multi-object tracking method based on semantic information and scene information | |
| CN114299417A (en) | Multi-target tracking method based on radar-vision fusion | |
| CN106679633B (en) | A vehicle ranging system and method | |
| CN109737976A (en) | Map road section and lane line automatic Generation | |
| CN108519587B (en) | Real-time aerial target motion mode identification and parameter estimation method | |
| CN114353817B (en) | Multi-source sensor lane line determination method, system, vehicle and computer readable storage medium | |
| CN109298414A (en) | A real-time tracking method for radar multi-moving targets | |
| CN106291588A (en) | A kind of cloud layer signal automatic-identifying method based on finite state machine | |
| JP6600615B2 (en) | Clustering device, artifact identification device, trunk detection device, method, and program | |
| CN113514848A (en) | A railway crossing locomotive detection system based on laser scanning | |
| KR102154589B1 (en) | METHOD FOR CLUSTERING MULTI-LAYER DATE OF LiDAR, AND COMPUTING DEVICE USING THE SAME | |
| CN108226890B (en) | Airport foreign matter radar detection method based on time direction statistics | |
| CN109543498A (en) | A kind of method for detecting lane lines based on multitask network | |
| CN109979194A (en) | Heavy vehicle ramp based on Markov chain is creeped Activity recognition method | |
| KR102283053B1 (en) | Real-Time Multi-Class Multi-Object Tracking Method Using Image Based Object Detection Information | |
| CN110992375B (en) | String-angle discriminative clustering single-tree segmentation method for layer-by-layer LiDAR point cloud | |
| CN105911553B (en) | A kind of road feasible zone determines method and system | |
| CN108020838A (en) | A kind of processing method of MMW RADAR SIGNAL USING in adaptive cruise | |
| CN108961288A (en) | A kind of web of the rail plug pin pin and lead detection image intelligent identification Method | |
| CN100513996C (en) | Method for detecting field water obstacle detection based on polarizing information | |
| CN116430336B (en) | Convection monomer identification method based on self-adaptive threshold |
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: 20170104 |