CN202433521U - Wind profile radar turbulence target detection processing plate - Google Patents
Wind profile radar turbulence target detection processing plate Download PDFInfo
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- CN202433521U CN202433521U CN2011203946303U CN201120394630U CN202433521U CN 202433521 U CN202433521 U CN 202433521U CN 2011203946303 U CN2011203946303 U CN 2011203946303U CN 201120394630 U CN201120394630 U CN 201120394630U CN 202433521 U CN202433521 U CN 202433521U
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Abstract
The utility model relates to a wind profile radar turbulence target detection processing plate including a signal pre-processor, a noise calculator, a spectral line detector, a velocity detector, a continuity detector and a spectrum moment calculator. A power spectrum of a wind profile radar is input into the signal pre-processor and the input power spectrum is pre-processed. Noise is calculated in the noise calculator and noise level is determined by using a segmentation average method. Initial survey and classified detection of the power spectrum are realized in the spectral line detector. The initial survey includes amplitude detection, spectral width detection and envelope detection. And the classified detection includes exploratory resection of spectral lines, classified judgment according to a resection result and spectrum-peak separation according to classifications. Velocity measurement fog-level is detected in the velocity detector and the velocity of a turbulence target power spectrum is corrected. The continuity of the turbulence target power spectrum is detected in the continuity detector and the continuity of the turbulence target power spectrum is corrected. Spectrum moment calculation is realized in the spectrum moment calculator and a result is output. The wind profile radar turbulence target detection processing plate provided by the utility model can improve the quality of wind profile radar target detection.
Description
Technical field
The utility model relates to a kind of wind profile radar turbulent flow object detection process plate, is used for the target detection of wind profile radar.
Background technology
Wind profile radar (wind profiling radar/wind profiler radar) is a kind of novel windfinding radar; Can the distribution of meteorological elements such as atmospheric level wind field, uprush, air index textural constant with height be provided unmanned continuously in 24 hours; Have the good characteristics of spatial and temporal resolution height, continuity and real-time; It is the visual plant that carries out aerological sounding; Being the important supplement of current conventional pilot balloon observation system, is the new tool of carrying out weather forecast and meteorological support.
In the echoed signal that radar receives, echo signal is arranged not only, also have various undesired signals such as noise and clutter, the target detection of radar just is meant under the situation of various interference, goes for out real target.Therefore Radar Targets'Detection is to improve an important ring of the data confidence level and the quality of data.
The target that radar will be surveyed is body in motion normally; The theoretical foundation that detects moving target and fixed clutter is their difference on translational speed; Cause that owing to movement velocity is different the Doppler frequency of echoed signal is unequal; Thereby can distinguish different objects, this is the basic thought that adopts moving-target demonstration and moving target detection technique in the radar.
The target detection of wind profile radar and other radar have different characteristics.At present, the simplest way of wind profile radar target detection is to the peaked detection method of power spectrum amplitude, and this method thinks that signal is always the strongest, therefore on power spectrum, finds out the position at maximal value place, and to be taken as be turbulent flow target spectrum peak.But when strong noise jamming was arranged, this method can cause very mistake.
Owing to a little less than the turbulent flow echoed signal, mix when wind profile radar is surveyed with very easily receiving, the pollution of bird etc.The multiple method of from the wind profile radar spectrum, removing clutter has been proposed at present, for example, main NIMA (the NCAR Improved Moment Algorithm) method of using.The NIMA method is mainly used in rejects the land clutter influence, and it thinks that whether certain point is that the principal character of land clutter is symmetry and curvature, in composite formula of these eigenwert substitutions, according to the size of output valve, judges signal or clutter.Parameter in the NIMA algorithm needs to be configured according to different equipment, different measurement places, and is more loaded down with trivial details.
General in the current operation wind transmission profile radar is " method objectifies " disposable plates." method objectifies " thinks that spectral density value all is a signal greater than the frequency of noise level, carries out integrating meter to whole spectrum then and calculates spectral moment.When on interference makes power spectrum, a plurality of spectrums peak occurring, this method is actually the weighting of spectrum peak and shared width, and what the result reflected is total effect of signal and various interference.More intense when echoed signal, when spectrum peak envelope was apparent in view, the detection of target was to be relatively easy to; But the echoed signal of wind profile radar is all more weak usually, and noise jamming is usually arranged, and a lot of clutters can both be covered real echo.In this case, adopt " method objectifies " to carry out target detection and calculate with each rank square, effect is relatively poor.
Therefore, need a kind of new wind profile radar turbulent flow object detection process plate of research, can satisfy real-time of handling and the requirement that detects effect two aspects simultaneously, to improve the quality of wind profile radar target detection.
The utility model content
The purpose of the utility model is to provide a kind of wind profile radar turbulent flow object detection process plate, and this method is treated to target with real time business, does not carry out loaded down with trivial details calculating, has eliminated the influence of noise jamming simultaneously again preferably.
According to the main aspect of the utility model, this wind profile radar turbulent flow object detection process plate comprises signal preprocessor, be connected the noise calculation device in signal preprocessor downstream, be connected noise calculation device downstream the spectral line detector, be connected the speed detector in spectral line detector downstream, the spectral moment counter that is connected the continuity detector in speed detector downstream and is connected continuity detector downstream; In signal preprocessor, import the power spectrum of wind profile radar and the power spectrum of being imported is carried out pre-service; Calculating noise and confirm noise level in the noise calculation device with the segmental averaging method; In the spectral line detector, power spectrum is carried out Preliminary detection and classification and Detection; Preliminary detection comprises that amplitude detection, spectrum width detect and envelope detected, and classification and Detection comprises spectral line is carried out exploratory excision, classifies according to the excision result and judge and compose the peak according to classification and separate; Fog-level and turbulent flow target power spectrum is carried out speed correct tests the speed in the speed detector; In the continuity detector, detect the continuity of turbulent flow target power spectrum and turbulent flow target power spectrum is carried out the continuity correction; In the spectral moment counter, carry out spectral moment and calculate and export the result.
According to an aspect of the utility model, said signal preprocessor comprises the interpolation processing module.
According to an aspect of the utility model, said signal preprocessor comprises the running mean processing module.
According to an aspect of the utility model, said interpolation processing module is a zero velocity point interpolation processing module.
According to an aspect of the utility model, said interpolation processing module adopts the mean value of the spectral density value of zero velocity point the right and left to replace the zero velocity point value when carrying out interpolation processing.
According to an aspect of the utility model, said running mean processing module is 3 running mean processing modules.
Will be appreciated that, the characteristic in the above each side of the utility model can be in the scope of the utility model independent assortment, and do not receive the restriction of its order---as long as the technical scheme after the combination drops in the connotation of the utility model.
Description of drawings
In order to be illustrated more clearly in the technical scheme in the utility model, will do to introduce simply to the accompanying drawing of the utility model below, wherein:
Fig. 1 has shown the synoptic diagram according to the wind profile radar turbulent flow object detection process plate of the utility model;
Fig. 2 is for carrying out the synoptic diagram of exploratory excision front and back to spectral line according to the utility model;
Fig. 3-Fig. 8 has shown several kinds of situation after the spectral line according to the utility model carries out exploratory excision.
Embodiment
The preferred embodiment that hereinafter will combine the utility model is elaborated to the technical scheme of the utility model.
Need to understand that the description of hereinafter (comprising accompanying drawing) only is exemplary, but not to the restricted description of the utility model.Can relate to the concrete quantity of parts in the following description, yet also need should be appreciated that, these quantity also only are exemplary, and those skilled in the art can choose the parts of right quantity with reference to the utility model arbitrarily.
First embodiment according to the utility model; Wind profile radar turbulent flow object detection process plate 10 comprises signal preprocessor 1, noise calculation device 2, spectral line detector 3, speed detector 4, continuity detector 5 and spectral moment counter 6, the signal flow above instrument of preferably flowing through successively.
At first, the power spectrum that wind profile radar is surveyed is input in the signal preprocessor 1, carries out pre-service then.Pre-service preferably mainly comprises interpolation processing and running mean and handles.
Interpolation processing generally is that the zero velocity point interpolation is handled.In zero velocity point interpolation processing procedure; When wind speed hour; Even the turbulence signal spectrum envelope has just comprised the zero velocity point near zero velocity point; Can make Power Spectrum Distribution fracture occur at zero velocity point place like this, therefore preferably adopt the alternative zero velocity point value of mean value of 2 spectral density value about zero velocity point to carry out interpolation processing.
The main effect that running mean is handled is to reject for some " flying spot data ".In the spectrum data, exist some to be worth king-sized data point sometimes, this belongs to interference once in a while, and their distribution is general more scattered, and spectral line is very narrow, promptly only occurs in some individual point.Spectrum is carried out running mean handle, preferably 3 running means are handled and can be removed these spike points.
Then, calculating noise and confirm noise level in noise calculation device 2 with the segmental averaging method.Be not arranged under the too little situation in maximum Doppler speed; In the whole long power spectrum chart of wind profile radar output; The spectrum of signal and various noise jamming generally all only accounts for the sub-fraction of spectrum on horizontal ordinate spectrum axle, therefore can whole spectrum be divided into plurality of sections, calculates the mean value of each section; Because in stronger signal spectrum and disturbance spectrum coexistence a certain section in plurality of sections, so can be with the minimum value in the mean value of all the other sections as noise level.In a preferred embodiment of the utility model, whole spectrum is divided into eight sections.Noise level is employed in subsequent step after confirming.
Follow again, in spectral line detector 3, power spectrum is carried out Preliminary detection.Preliminary detection comprises that amplitude detection, spectrum width detect and envelope detected.No matter how faint the atmospheric turbulence echoed signal is, on Power Spectrum Distribution figure, turbulent flow echoed signal spectrum peak all should be higher than cogongrass, and its spectral density value can not be a maximal value, but must be the maximum point with certain spectrum width.Therefore; On power spectrum, at first detect the spectrum peak maximum, search for respectively toward both sides then, find first point (or power spectral value is by the turning point that progressively reduces to begin to increase) less than the noise level value; Promptly think to have hunted out whole spectrum peak envelope, in envelope, calculate the spectrum width value.If the spectrum width value not in certain presetting range, then thinks not to be turbulence signal, should compose the peak and envelope all is set to the noise level value, remove to seek next polarographic maximum point then, up to finding the spectrum peak envelope that meets the demands.If the whole piece spectral line all fails to search out, seek again after then suitably enlarging the threshold range of spectrum width.
After Preliminary detection, need in spectral line detector 3, proceed classification and Detection.This is because the spectrum peak that Preliminary detection goes out is positioned at the zero velocity point sometimes, and a little spectrum peak envelope is arranged near zero velocity point, and the position and the detected spectrum of a last height layer (or next height layer) peak at this place, little spectrum peak have better height continuity.Human eye can think intuitively that this little spectrum peak should be only turbulent flow echoed signal spectrum peak, and just because the turbulent flow echoed signal of place height is weaker than land clutter, so computing machine has detected the land clutter position of zero velocity point when composing the peak Preliminary detection.If can cut away near the one section spectrum of Power Spectrum Distribution zero velocity point on these height, computing machine just can detect this little spectrum peak.But, for the automatic time of being born by computer program detects, be to let the people which specify highly can excise near one section spectrum of zero velocity point, therefore must after Preliminary detection, proceed classification and Detection.
Classification and Detection is one step of key of rejecting the land clutter influence, and main thought is near the assorted different shape that zero velocity point, is mingled in signal in base area, the judgement of classifying.Its key step comprises: judge whether the spectrum peak envelope that Preliminary detection goes out has crossed over curve of zero velocity, if do not cross over curve of zero velocity, think that the turbulence signal of this height is more intense, and not disturbed by land clutter, be labeled as credible; If spectrum peak envelope has been crossed over the height layer of curve of zero velocity, will detect as follows according to spectrum peak and the distance of zero line, the concrete shape of envelope:
Near one section spectral line to the Power Spectrum Distribution curve of zero velocity of this height layer carries out exploratory excision, according to " otch " shape that cuts out, the judgement of classifying.The width of exploratory spectral line excision will confirm that generally selected wide than the width of all land clutters around the curve of zero velocity both sides, still a width narrower than general turbulent flow Echo width excises according to the situation of local land clutter spectrum.Preferably, the excision width is about 1m/s, also is about each 0.5m/s of curve of zero velocity both sides.
When carrying out the excision of exploratory land clutter interference spectral line, replace being excised spectrum value a little with the noise level value of this height layer.
Fig. 2 is the synoptic diagram before and after the exploratory spectral line excision, the Far Left and the farthest right position of one section spectrum of left and right sides straight line representative excision among the figure, and middle straight line is represented the position of curve of zero velocity.First row's expression original spectrum, it possibly exist land clutter to disturb, and the spectrum after the exploratory spectral line excision is carried out in second row's expression, and the 3rd row's expression is to the otch both sides value of composing gradient calculation.The leftmost Grad of otch is that A point spectrum value deducts the spectrum value that B is ordered, and the rightmost Grad of otch is that the spectrum value that C is ordered deducts the spectrum value that D is ordered.Obtain after these two gradients, utilize them to judge that otch is precipitous or relaxes that the precipitous representative of otch has the influence of turbulent flow echo here, otch relaxes representative and does not exist the influence of turbulent flow echo or the influence of turbulent flow echo to ignore here.
Can know that referring to Fig. 3-Fig. 8 after carrying out the exploratory excision of spectral line, according to otch both sides Grad size, can be divided into following three kinds of situation, every kind of situation all possibly comprise different land clutters and turbulent flow echo mixed type, so will carry out following classification and Detection.
First kind of situation is that both sides Grad all very little (less than certain prevalue) at this moment possibly exist two kinds of situations again.A kind of is as shown in Figure 3, and what cut away is the land clutter peak really, has found the secondary maximum value peak with certain spectrum width in all the other positions of spectral line, can be used as turbulent flow target spectrum peak.Another kind of as shown in Figure 4, in this case, exploratory excision be the stack echo of turbulent flow echo and land clutter, what the excision back was left all is the very little values in original both sides, can not find the spectrum peak with turbulent flow target property.This explanation target and land clutter are excised simultaneously, should recover the data of being excised this moment, compose the peak as the turbulent flow target.
Second kind of situation be, both sides otch Grad is very big (greater than certain prevalue) all, at this moment also possibly have two kinds of situations.A kind of is because the land clutter spectrum is wide unusually, and causes otch both sides Grad all very big, but the secondary maximum value peak with certain spectrum width has been found in all the other positions of the spectral line after excision, can be used as turbulent flow target spectrum peak, like Fig. 5.Another kind is to can not find the spectrum peak with turbulent flow target property in the spectral line remaining after excision, and this explanation target is excised with land clutter simultaneously, should recover the data of being excised this moment, composes the peak as the turbulent flow target, like Fig. 6.
The third situation is that otch both sides Grad is big on one side little on one side, at this moment still possibly have two kinds of situations.A kind of is that the turbulent flow echo separates with the spectrum peak of land clutter, and distance is also far away, and preferably at least greater than 0.5m/s, but the spectral pattern envelope is not overlapping, as shown in Figure 7.Can be in original spectrum for this situation; Through finding in this side otch first smaller or equal to the spectrum point position of noise level value; Separation as land clutter and turbulent flow echo spectrum; Left side straight line adjusted to carry out the land clutter excision behind the separation again, and then hunt out target spectrum peak and envelope (referring to the following row of Fig. 7) thereof.Second kind of situation is that the turbulent flow echo separates with the spectrum peak of land clutter, but the spectral pattern envelope overlaps, and be as shown in Figure 8.For this situation; Can in original spectrum, find the position of minimum spectrum value point in this side otch; (can not find the minimal noise point when overlapping as the separation of land clutter and turbulent flow echo spectrum; So can only look for minimum spectrum value point), also be to carry out the land clutter excision again after this side straight line is adjusted to separation, detect target spectrum peak and envelope thereof (referring to the following row of Fig. 8) again.
After classification and Detection, detection speed fog-level and turbulent flow target power spectrum is carried out speed correct in speed detector 4.The all corresponding maximal rate that velocity ambiguity does not take place of each mode of operation of wind profile radar; If the actual radial velocity of target surpasses this maximal rate; It is fuzzy then can to test the speed; Thereby on the spectral density image, produce folding phenomenon, therefore need from the low layer to the high level, carry out the velocity ambiguity detection one by one and move back Fuzzy Processing, promptly carry out speed and correct.
Then, in continuity detector 5, detect the continuity of turbulent flow target power spectrum and turbulent flow target power spectrum carried out the continuity correction.Because wind field has certain continuity on the determined space scale of detection volume with on the determined time scale of time sense; If the difference of therefore searching the spectrum peak position that comes out between the height layer up and down is within certain threshold value; Then this data fit continuity requirement does not meet the continuity requirement otherwise should be identified as.According to this principle the radial velocity value between each height layer of each beam position detection being carried out continuity detects.Detect if all pass through continuity between all height layers, that is optimal.But because the intermittence of turbulent flow perhaps is interfered, usually there are some height layers spectrum distribution image cogongrass the centre, and the confidence level at the target spectrum peak of detection is poor, can't through and other height layer between continuity detect.For this situation; Can utilize the radial velocity value of the height layer that has passed through the continuity detection; Produce a radial velocity variation range; On the power spectrum of the height layer that does not detect, search the spectrum peak,, thereby accomplish continuity reparation tomography as the new target peak position of this height layer through continuity.
At last, in spectral moment counter 6, carry out spectral moment and calculate and export the result.After identifying turbulent flow target spectrum peak position, only within turbulent flow target spectrum peak envelope, calculate, in the hope of data such as signal to noise ratio (S/N ratio), doppler velocity and speed spectrum widths.The formula that calculates is following:
Wherein, P
rBe the power of echoed signal,
ψ (v) be the power spectrum density distribution function,
ψ (v) dv is the echo power of the particle of doppler velocity in v arrives the v+dv interval,
V
rBe average doppler velocity, and
σ
vIt is the doppler velocity spectrum width.
In computation process, other spectral line beyond the turbulent flow target spectrum peak envelope is not calculated, be higher than of the influence of the clutter spike of noise level to overcome other spectrum point place to each rank square result of calculation.After the doppler velocity of trying to achieve each beam position detection, just can calculate the air-out profile.
Above basis has preferred embodiment been done detailed description to the utility model; But it will be appreciated that; The scope of the utility model is not limited to these concrete embodiments, but comprises any change and the change that openly can make of those skilled in the art according to the utility model.
Claims (5)
1. wind profile radar turbulent flow object detection process plate, it comprises signal preprocessor, be connected the noise calculation device in signal preprocessor downstream, be connected noise calculation device downstream the spectral line detector, be connected the speed detector in spectral line detector downstream, the spectral moment counter that is connected the continuity detector in speed detector downstream and is connected continuity detector downstream; In signal preprocessor, import the power spectrum of wind profile radar and the power spectrum of being imported is carried out pre-service; Calculating noise and confirm noise level in the noise calculation device with the segmental averaging method; In the spectral line detector, power spectrum is carried out Preliminary detection and classification and Detection; Preliminary detection comprises that amplitude detection, spectrum width detect and envelope detected, and classification and Detection comprises spectral line is carried out exploratory excision, classifies according to the excision result and judge and compose the peak according to classification and separate; Fog-level and turbulent flow target power spectrum is carried out speed correct tests the speed in the speed detector; In the continuity detector, detect the continuity of turbulent flow target power spectrum and turbulent flow target power spectrum is carried out the continuity correction; In the spectral moment counter, carry out spectral moment and calculate and export the result.
2. wind profile radar turbulent flow object detection process plate according to claim 1 is characterized in that said signal preprocessor comprises the interpolation processing module.
3. wind profile radar turbulent flow object detection process plate according to claim 1 is characterized in that said signal preprocessor comprises running mean place module.
4. wind profile radar turbulent flow object detection process plate according to claim 2 is characterized in that said interpolation processing module is a zero velocity point interpolation processing module.
5. wind profile radar turbulent flow object detection process plate according to claim 3 is characterized in that said running mean processing module is 3 running mean processing modules.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104316929A (en) * | 2014-09-12 | 2015-01-28 | 何平 | Power spectrum identification method and apparatus |
| CN105022036A (en) * | 2015-08-26 | 2015-11-04 | 成都信息工程大学 | Wind profile radar wind speed determination method |
| CN108089166A (en) * | 2017-12-07 | 2018-05-29 | 北京无线电测量研究所 | A kind of adaptive frequency domain detection method based on millimeter wave cloud detection radar |
| CN110531337A (en) * | 2019-09-29 | 2019-12-03 | 北京润科通用技术有限公司 | Target confidence level calculation method and device based on degree of membership analysis |
| CN113376623A (en) * | 2020-02-25 | 2021-09-10 | 光宝科技股份有限公司 | Radar device, operation device for object detection and object detection method |
| CN114114273A (en) * | 2021-12-08 | 2022-03-01 | 天津市气象台 | Wind profile radar signal processing method |
-
2011
- 2011-10-17 CN CN2011203946303U patent/CN202433521U/en not_active Expired - Fee Related
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104316929A (en) * | 2014-09-12 | 2015-01-28 | 何平 | Power spectrum identification method and apparatus |
| CN105022036A (en) * | 2015-08-26 | 2015-11-04 | 成都信息工程大学 | Wind profile radar wind speed determination method |
| CN108089166A (en) * | 2017-12-07 | 2018-05-29 | 北京无线电测量研究所 | A kind of adaptive frequency domain detection method based on millimeter wave cloud detection radar |
| CN108089166B (en) * | 2017-12-07 | 2020-06-02 | 北京无线电测量研究所 | Adaptive frequency domain detection method based on millimeter wave cloud detection radar |
| CN110531337A (en) * | 2019-09-29 | 2019-12-03 | 北京润科通用技术有限公司 | Target confidence level calculation method and device based on degree of membership analysis |
| CN110531337B (en) * | 2019-09-29 | 2021-06-29 | 北京润科通用技术有限公司 | Target reliability calculation method and device based on membership analysis |
| CN113376623A (en) * | 2020-02-25 | 2021-09-10 | 光宝科技股份有限公司 | Radar device, operation device for object detection and object detection method |
| CN114114273A (en) * | 2021-12-08 | 2022-03-01 | 天津市气象台 | Wind profile radar signal processing method |
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