CN102508219B - Turbulent current target detection method of wind profiler radar - Google Patents
Turbulent current target detection method of wind profiler radar Download PDFInfo
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Abstract
The invention relates to a turbulent current target detection method of a wind profiler radar. The method comprises the following steps of inputting a power spectrum of the wind profiler radar; performing pretreatment on the input power spectrum; determining noise level by a segmental averaging method; performing preliminary detection on the power spectrum, wherein the preliminary detection comprises amplitude detection, spectrum width detection and envelope detection; performing classification detection on the power spectrum, wherein the classification detection comprises exploratory excision of a spectral line, classification judgment according to the excision result and spectral peak separation according to categories; performing speed correction on a turbulent current target power spectrum; performing continuous modification on the turbulent current target power spectrum; and performing spectral moment calculation and outputting a result. According to the method disclosed by the invention, the target detection quality of the wind profiler radar can be improved.
Description
Technical field
The present invention relates to a kind of wind profile radar turbulent flow object detection method, be 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 provide the distribution of meteorological elements such as atmospheric level wind field, uprush, air index textural constant with height in 24 hours continuously by unmanned, 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 refers under the situation of various interference, goes for out real target.Therefore Radar Targets'Detection is to improve an important ring of 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.Therefore 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, finds out the position at maximal value place at power spectrum, 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 being subjected to, the pollution of bird etc.The multiple method of removing clutter from the wind profile radar spectrum has been proposed at present, for example, main NIMA method (the NCAR Improved Moment Algorithm) method of using.The NIMA method is mainly used in rejecting 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 "." method objectifies " thinks that spectral density value all is signal greater than the frequency of noise level, carries out integrating meter to whole spectrum then and calculates spectral moment.When a plurality of spectrums peak occurring on interference makes power spectrum, 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 each rank square calculating, effect is relatively poor.
Therefore, need a kind of new wind profile radar turbulent flow object detection method of research, can satisfy the real-time of handling and the requirement that detects effect two aspects simultaneously, to improve the quality of wind profile radar target detection.
Summary of the invention
The object of the present invention is to provide a kind of wind profile radar turbulent flow object detection method, 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 main aspect of the present invention, this wind profile radar turbulent flow object detection method may further comprise the steps:
The power spectrum of a, input wind profile radar;
B, the power spectrum of importing is carried out pre-service;
C, determine noise level with the segmental averaging method;
D, power spectrum is carried out Preliminary detection, detect and envelope detected comprising amplitude detection, spectrum width;
E, power spectrum is carried out classification and Detection, 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 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, according to the concrete shape of the distance of spectrum peak and zero line, envelope spectral line is carried out exploratory excision, classifies according to the excision result and judge and compose the peak according to classification and separate;
F, turbulent flow target power spectrum is carried out speed correct;
G, turbulent flow target power spectrum is carried out the continuity correction; And
H, carry out spectral moment and calculate, and the output result.
According to an aspect of the present invention, pre-service comprises interpolation processing.
According to an aspect of the present invention, pre-service also comprises the running mean processing.
According to an aspect of the present invention, interpolation processing is that the zero velocity point interpolation is handled.
According to an aspect of the present invention, adopt during interpolation processing about zero velocity point the mean value of 2 spectral density value to replace the zero velocity point value.
According to an aspect of the present invention, the running mean processing is that 3 running means are handled.
Will be appreciated that the feature in the above each side of the present invention is independent assortment within the scope of the invention, and be not subjected to the restriction of its order---as long as the technical scheme after the combination drops in the connotation of the present invention.
Description of drawings
In order to be illustrated more clearly in the technical scheme among the present invention, will do to introduce simply to accompanying drawing of the present invention below, wherein:
Fig. 1 has shown the process flow diagram according to wind profile radar turbulent flow object detection method of the present invention;
Fig. 2 is for carrying out the synoptic diagram of exploratory excision front and back to spectral line according to the present invention;
Fig. 3 (a)-3(f) has shown according to spectral line of the present invention and has carried out several situations after the exploratory excision.
Embodiment
Hereinafter will be elaborated to technical scheme of the present invention in conjunction with the preferred embodiments of the present invention.
Need to understand that following description (comprising accompanying drawing) only is exemplary, but not the limitation of the present invention description.Can relate to the concrete quantity of parts in the following description, yet also it is to be understood that, these quantity also only are exemplary, and those skilled in the art can choose the parts of right quantity with reference to the present invention arbitrarily.
According to the first embodiment of the present invention, the power spectrum that wind profile radar is surveyed is input in the signal processor, 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 ".Exist some to be worth king-sized data point sometimes in the spectrum data, this belongs to interference once in a while, and their distribution is general more scattered, and spectral line is very narrow, namely only in some indivedual some appearance.Spectrum is carried out running mean handle, preferably 3 running means are handled and can be removed these spike points.
Then, determine noise level 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 whole spectrum can be divided into some sections, calculate the mean value of each section, because in the stronger signal spectrum and disturbance spectrum coexistence a certain section in some 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 invention, whole spectrum is divided into eight sections.Noise level is employed in subsequent step after determining.
Follow, power spectrum is carried out Preliminary detection, this detects and envelope detected comprising amplitude detection, spectrum width.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 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 less than the noise level value (or power spectral value is by the turning point that progressively reduces to begin to increase), namely think to have hunted out whole spectrum peak envelope, in the envelope scope, 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 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 at this place, little spectrum peak and the detected spectrum of a last height layer (or next height layer) 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 detection of being born by computer program in real time automatically, be to allow the people which specifies 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, main thought be the base area assorted with near signal different shape mixed in together zero velocity point, 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 carry out following detection according to spectrum peak and the distance of zero line, the concrete shape of envelope:
Near one section spectral line the Power Spectrum Distribution curve of zero velocity of this height layer is carried out exploratory excision, according to " otch " shape that cuts out, the judgement of classifying.The width of exploratory spectral line excision will determine 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 the spectrum value of cut point with the noise level value of this height layer.
Fig. 2 is the synoptic diagram before and after the exploratory spectral line excision, 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 represents the position of curve of zero velocity.First row's expression original spectrum, it may 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 herein, otch relaxes representative and does not exist the influence of turbulent flow echo or the influence of turbulent flow echo to ignore herein.
Referring to Fig. 3 (a)-3(f) as can be known, after carrying out the exploratory excision of spectral line, according to otch both sides Grad size, can be divided into following three kinds of situations, every kind of situation all may comprise different land clutters and turbulent flow echo mixed type, so will carry out following classification and Detection.
First kind of situation is that the both sides Grad is very little (less than certain prevalue) all, at this moment may have two kinds of situations again.A kind of is shown in Fig. 3 (a), 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 Fig. 3 (b) shown in, 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 simultaneously cut, and should recover cut data this moment, as turbulent flow target spectrum peak.
Second kind of situation is that both sides otch Grad is very big (greater than certain prevalue) all, at this moment also may 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, as Fig. 3 (c).Another kind is to can not find the spectrum peak with turbulent flow target property in the spectral line that is left after excision, and this explanation target and land clutter are simultaneously cut, and should recover cut data this moment, as turbulent flow target spectrum peak, as Fig. 3 (d).
The third situation is that otch both sides Grad is big little on one side on one side, at this moment still may 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, shown in Fig. 3 (e).Can be in original spectrum for this situation, by 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. 3 (e)) 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, shown in Fig. 3 (f).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. 3 (e)) again.
After classification and Detection, turbulent flow target radar spectrum is carried out speed correct.Each mode of operation of wind profile radar is corresponding maximal rate that velocity ambiguity does not take place all, if the actual radial velocity of target surpasses this maximal rate, it is fuzzy then can to test the speed, thereby produce folding phenomenon at the spectral density image, therefore need from the low layer to the high level, carry out the velocity ambiguity detection one by one and move back Fuzzy Processing, namely carry out speed and correct.
Then, turbulent flow target power spectrum is carried out the continuity correction.Because wind field has certain continuity with the determined time scale of time sense on the determined space scale of detection volume, if therefore search the difference of the spectrum peak position that comes out up and down between the height layer 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.If all detect by 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 by 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, power spectrum at the height layer that does not detect by continuity is searched the spectrum peak, as the new target peak position of this height layer, thereby finish continuity reparation to tomography.
At last, carry out spectral moment and calculate, and the output 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 as follows:
Wherein, P
rBe the power of echoed signal,
ψ (v) be the power spectrum density distribution function,
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 the clutter spike of noise level to the influence of each rank square result of calculation to overcome other spectrum point place.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 present invention, but it will be appreciated that, scope of the present invention is not limited to these concrete embodiments, but comprises that those skilled in the art are according to any modifications and changes that openly can make of the present invention.
Claims (6)
1. wind profile radar turbulent flow object detection method said method comprising the steps of:
The power spectrum of a, input wind profile radar;
B, the power spectrum of importing is carried out pre-service;
C, determine noise level with the segmental averaging method;
D, power spectrum is carried out Preliminary detection, detect and envelope detected comprising amplitude detection, spectrum width;
E, power spectrum is carried out classification and Detection, 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 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, according to the concrete shape of the distance of spectrum peak and zero line, envelope spectral line is carried out exploratory excision, classifies according to the excision result and judge and compose the peak according to classification and separate;
F, turbulent flow target power spectrum is carried out speed correct;
G, turbulent flow target power spectrum is carried out the continuity correction; And
H, carry out spectral moment and calculate, and the output result.
2. wind profile radar turbulent flow object detection method according to claim 1 is characterized in that described pre-service comprises interpolation processing.
3. wind profile radar turbulent flow object detection method according to claim 1 is characterized in that, described pre-service comprises the running mean processing.
4. wind profile radar turbulent flow object detection method according to claim 2 is characterized in that, interpolation processing is that the zero velocity point interpolation is handled.
5. wind profile radar turbulent flow object detection method according to claim 4 is characterized in that, adopts about zero velocity point the mean value of 2 spectral density value to replace the zero velocity point value during interpolation processing.
6. wind profile radar turbulent flow object detection method according to claim 3 is characterized in that, it is that 3 running means are handled that described running mean is handled.
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