CN102540156A - Wind profile radar signal and data processing method based on two channels - Google Patents

Abstract

The invention discloses a wind profile radar signal and data processing method based on two channels. The wind profile radar signal and data processing method is implemented by a signal processor and a data terminal, and comprises the specific steps that: the signal processor sets two groups of processing parameters; 2, the signal processor generates two groups of power spectrum data; 3, the data terminal processes the two groups of power spectrum data respectively; and 4, the data terminal selects a processing result. Therefore, wind profile radar signal and data processing based on the two channels is implemented. The method has the advantages that: the data output rate of a wind profile radar system is not changed; the new increased processing load is relatively small; the method is easily implemented; and the extraction capacity and the estimation precision of a wind profile radar to weak signals are improved effectively.

Description

A kind of based on twin-channel wind profile radar signal and data processing method

Technical field

The present invention relates to a kind of radar signal and data processing method, particularly a kind of based on twin-channel wind profile radar signal and data processing method.

Background technology

Present wind profile radar signal and data processing method are based on signal processor and data terminal realization, and the key step of signal Processing is: coherent accumulation, and with N _CIThe individual echoed signal of returning is in succession carried out coherent accumulation, wherein, and N _CIBe called the coherent accumulation number; Spectral transformation is with N _FFTEchoed signal behind the individual coherent accumulation is carried out fast Fourier transform (FFT), obtains a power spectral density function, N _FFTBeing called FFT counts; Spectrum is average, with N _SPCIndividual power spectral density function averages, and obtains a new average power spectral density function (being designated hereinafter simply as power spectrum), N _SPCBe called spectral average.Afterwards, data terminal is composed data processing to power spectrum, obtains echo power Pr, Doppler shift f _d, speed spectrum width σ and signal to noise ratio snr.

In above signal Processing and spectrum data processing, coherent accumulation is that wind profile radar is realized the committed step that feeble signal is extracted, and its major function is to improve signal to noise ratio (S/N ratio), in theory, and N _CIInferior relevant accumulation can improve signal to noise ratio (S/N ratio) N _CIDoubly.The limit that coherent accumulation improves signal to noise ratio (S/N ratio) depends primarily on the auto-correlation time of return signal in phase stability and the atmosphere of wind profile radar system itself; When the system phase degree of stability met the demands, the number of times that carries out coherent accumulation was main relevant with the auto-correlation time and the recurrent interval of atmosphere return signal.The wavelength that the auto-correlation time of return signal and atmospheric condition and wind profile radar are selected for use in the atmosphere is relevant, and for troposphere wind profile radar (pattern-band), the auto-correlation time selected for use 0.15～0.45 second, and boundary layer wind profile radar (L-band) was selected for use 0.05～0.15 second.

Because atmospheric condition is ever-changing, the coherent accumulation time of adopting when system, greatly the time, theory and practice all showed, can influence the effect of coherent accumulation, is unfavorable for the extraction of feeble signal with the auto-correlation time difference of return signal.Though in the wind profile radar system design; The coherent accumulation number has certain optional to select scope; Supply to carry out in the actual detection preferred; But present most of wind profile radar all take one group fixedly processing parameter move automatically, though the part wind profile radar that is used to study from the research needs and often change processing parameter, can not adapt to different atmospheric conditions automatically.

Summary of the invention

The object of the present invention is to provide a kind of based on twin-channel wind profile radar signal and data processing method; When solving traditional wind profile radar signal Processing; The coherent accumulation time and the return signal auto-correlation time that exist can not mate automatically, are unfavorable for the problem that feeble signal is extracted.

A kind of based on twin-channel wind profile radar signal and data processing method, be based on that signal processor and data terminal realize, its concrete steps are:

First step signal processor is provided with two groups of processing parameters

For the auto-correlation time, the troposphere wind profile radar was selected for use respectively 0.15～0.225,0.3～0.45 second, and the boundary layer wind profile radar was selected for use respectively 0.05～0.075,0.1～0.15 second.Auto-correlation time and wave beam residence time are respectively:

τ＝PRT×N _CI×N _FFT (1)

T _BEAM＝PRT×N _CI×N _FFT×N _SPC (2)

In the formula, τ is the auto-correlation time, T _BEAMBe the wave beam residence time, PRT is the pulse repetition time, N _CIBe coherent accumulation number, N _FFTFor FFT counts, N _SPCBe spectral average.

After confirming the wave beam residence time, according to two groups of auto-correlation times of selecting for use, it is constant to keep pulse repetition time, FFT to count, and calculates two groups of different processing parameters.Wherein, the coherent accumulation number of first group of parameter is two times of second group of parameter, and spectral average is 1/2nd of second group of parameter.

The second step signal processor generates two groups of power spectrum datas

Signal processor according to two groups of processing parameters, carries out coherent accumulation, spectral transformation, spectrum average treatment to identical echoed signal respectively successively, generates two groups of power spectrum datas.Two groups of power spectrum datas have different not fuzzy speed and velocity resolution, are respectively:

V _MAX＝λ/(4×PRT×N _CI) (3)

V _MIN＝λ/(2×PRT×N _CI×N _FFT) (4)

In the formula, V _MAXBe not fuzzy speed, V _MINBe velocity resolution, λ is a radar wavelength.

The processing of two groups of power spectrum datas is carried out at the 3rd step data terminal respectively

Data terminal is used identical processing parameter to carry out square respectively and is estimated two groups of power spectrum datas, obtains echo power, Doppler shift, speed spectrum width and signal to noise ratio (S/N ratio).Formula is:

$\mathrm{Pr}=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(5\right)$

$f_d=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f}_i{p}_i/\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(6\right)$

$\mathrm{\σ}=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f_i}^2{p}_i/\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(7\right)$

$\mathrm{SNR}=10\log \left(\frac{\underset{i=1}{\overset{h}{\mathrm{\Σ}}}{p}_i}{P_n}\right)---\left(8\right)$

In the formula, Pr is an echo power, f _dBe Doppler shift, σ speed spectrum width, SNR are signal to noise ratio (S/N ratio), P _nBe noise power, p _iBe i point performance number, f _iIt is i point Doppler shift value.

The 4th step data terminal is carried out result and is chosen

Data terminal is the result of two groups of power spectrum datas relatively, according to the high person's priority principle of signal to noise ratio (S/N ratio), chooses the wind spectrum discrimination and the estimated result of high s/n ratio.Formula is:

SNR1≥SNR2，Pr＝Pr1，f _d＝f _d1，σ＝σ1，SNR＝SNR1

SNR1＜SNR2，Pr＝Pr2，f _d＝f _d2，σ＝σ2，SNR＝SNR2 (9)

So far, realized based on twin-channel wind profile radar signal and data processing.

This method adopts two kinds of different coherent accumulations and incoherent accumulation number, solves coherent accumulation and real atmosphere situation and does not match, and causes signal and data processing weak echo signal to be extracted the problem of difficulty.The advantage of this method is not change wind profile radar system output data rate, newly-increased processing load is less, realization is simple, can effectively strengthen extractability and the estimated accuracy of wind profile radar to feeble signal.

Embodiment

A kind of based on twin-channel wind profile radar signal and data processing method, be based on that signal processor and data terminal realize, its concrete steps are:

First step signal processor is provided with two groups of processing parameters

For the auto-correlation time, the troposphere wind profile radar was selected for use respectively 0.2,0.4 second, and the boundary layer wind profile radar was selected for use respectively 0.065,0.13 second.Auto-correlation time and wave beam residence time are respectively:

τ＝PRT×N _CI×N _FFT (1)

T _BEAM＝PRT×N _CI×N _FFT×N _SPC (2)

In the formula, τ is the auto-correlation time, T _BEAMBe the wave beam residence time, PRT is the pulse repetition time, N _CIBe coherent accumulation number, N _FFTFor FFT counts, N _SPCBe spectral average.

After confirming the wave beam residence time, according to two groups of auto-correlation times of selecting for use, it is constant to keep pulse repetition time, FFT to count, and calculates two groups of different processing parameters.Wherein, the coherent accumulation number of first group of parameter is two times of second group of parameter, and spectral average is 1/2nd of second group of parameter.

The second step signal processor generates two groups of power spectrum datas

Signal processor according to two groups of processing parameters, carries out coherent accumulation, spectral transformation, spectrum average treatment to identical echoed signal respectively successively, generates two groups of power spectrum datas.Two groups of power spectrum datas have different not fuzzy speed and velocity resolution, are respectively:

V _MAX＝λ/(4×PRT×N _CI) (3)

V _MIN＝λ/(2×PRT×N _CI×N _FFT) (4)

In the formula, V _MAXBe not fuzzy speed, V _MINBe velocity resolution, λ is a radar wavelength.

The processing of two groups of power spectrum datas is carried out at the 3rd step data terminal respectively

Data terminal is used identical processing parameter to carry out square respectively and is estimated two groups of power spectrum datas, obtains echo power, Doppler shift, speed spectrum width and signal to noise ratio (S/N ratio).Formula is:

$\mathrm{Pr}=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(5\right)$

$f_d=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f}_i{p}_i/\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(6\right)$

$\mathrm{\σ}=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f_i}^2{p}_i/\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(7\right)$

$\mathrm{SNR}=10\log \left(\frac{\underset{i=1}{\overset{h}{\mathrm{\Σ}}}{p}_i}{P_n}\right)---\left(8\right)$

In the formula, Pr is an echo power, f _dBe Doppler shift, σ speed spectrum width, SNR are signal to noise ratio (S/N ratio), P _nBe noise power, p _iBe i point performance number, f _iIt is i point Doppler shift value.

The 4th step data terminal is carried out result and is chosen

Data terminal is the result of two groups of power spectrum datas relatively, according to the high person's priority principle of signal to noise ratio (S/N ratio), chooses the wind spectrum discrimination and the estimated result of high s/n ratio.Formula is:

SNR1≥SNR2，Pr＝Pr1，f _d＝f _d1，σ＝σ1，SNR＝SNR1

SNR1＜SNR2，Pr＝Pr2，f _d＝f _d2，σ＝σ2，SNR＝SNR2 (9)

So far, realized based on twin-channel wind profile radar signal and data processing.

Claims (1)

1. one kind based on twin-channel wind profile radar signal and data processing method, is based on that signal processor and data terminal realize, it is characterized in that concrete steps are:

First step signal processor is provided with two groups of processing parameters

For the auto-correlation time, the troposphere wind profile radar was selected for use respectively 0.15～0.225,0.3～0.45 second, and the boundary layer wind profile radar was selected for use respectively 0.05～0.075,0.1～0.15 second; Auto-correlation time and wave beam residence time are respectively:

τ＝PRT×N _CI×N _FFT (1)

T _BEAM＝PRT×N _CI×N _FFT×N _SPC (2)

In the formula, τ is the auto-correlation time, T _BEAMBe the wave beam residence time, PRT is the pulse repetition time, N _CIBe coherent accumulation number, N _FFTFor FFT counts, N _SPCBe spectral average;

After confirming the wave beam residence time, according to two groups of auto-correlation times of selecting for use, it is constant to keep pulse repetition time, FFT to count, and calculates two groups of different processing parameters; Wherein, the coherent accumulation number of first group of parameter is two times of second group of parameter, and spectral average is 1/2nd of second group of parameter;

The second step signal processor generates two groups of power spectrum datas

Signal processor according to two groups of processing parameters, carries out coherent accumulation, spectral transformation, spectrum average treatment to identical echoed signal respectively successively, generates two groups of power spectrum datas; Two groups of power spectrum datas have different not fuzzy speed and velocity resolution, are respectively:

V _MAX＝λ/(4×PRT×N _CI) (3)

V _MIN＝λ/(2×PRT×N _CI×N _FFT) (4)

In the formula, V _MAXBe not fuzzy speed, V _MINBe velocity resolution, λ is a radar wavelength;

The processing of two groups of power spectrum datas is carried out at the 3rd step data terminal respectively

Data terminal is used identical processing parameter to carry out square respectively and is estimated two groups of power spectrum datas, obtains echo power, Doppler shift, speed spectrum width and signal to noise ratio (S/N ratio); Formula is:

$\mathrm{Pr}=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(5\right)$

$f_d=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f}_i{p}_i/\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(6\right)$

$\mathrm{\σ}=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f_i}^2{p}_i/\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{p}_i---\left(7\right)$

$\mathrm{SNR}=10\log \left(\frac{\underset{i=1}{\overset{h}{\mathrm{\Σ}}}{p}_i}{P_n}\right)---\left(8\right)$

In the formula, Pr is an echo power, f _dBe Doppler shift, σ speed spectrum width, SNR are signal to noise ratio (S/N ratio), P _nBe noise power, p _iBe i point performance number, f _iIt is i point Doppler shift value;

The 4th step data terminal is carried out result and is chosen

Data terminal is the result of two groups of power spectrum datas relatively, according to the high person's priority principle of signal to noise ratio (S/N ratio), chooses the wind spectrum discrimination and the estimated result of high s/n ratio; Formula is:

SNR1≥SNR2，Pr＝Pr1，f _d＝f _d1，σ＝σ1，SNR＝SNR1

SNR1＜SNR2，Pr＝Pr2，f _d＝f _d2，σ＝σ2，SNR＝SNR2 (9)

So far, realized based on twin-channel wind profile radar signal and data processing.