CN109358331B - Real-time dynamic noise power detection method for meteorological radar - Google Patents
Real-time dynamic noise power detection method for meteorological radar Download PDFInfo
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Abstract
The invention provides a meteorological radar real-time dynamic noise power detection method, which is used for improving the signal-to-noise ratio of radar echo data and increasing the observation area range; meanwhile, the radar detection data quality is improved, the reflectivity factor estimation deviation is reduced, the velocity spectrum width estimation is improved, and the polarization radar correlation coefficient and the effectiveness of differential reflectivity estimation are improved. The method is suitable for the noise fluctuation situation of the pulse radar caused by the element parameter change, the signal channel characteristic drift, the antenna rotation, the sun and the cosmic radiation, and the like, compared with the static noise level setting method, the method can dynamically improve the signal-to-noise ratio of the echo corresponding to each transmitted pulse, only radiates the noise by the sun, and can adapt to the noise change of more than 20dB in real time for the weather radar of X and below wave bands.
Description
Technical Field
The invention belongs to the field of electronic information, and particularly relates to a real-time dynamic noise power detection method for a meteorological radar.
Background
The meteorological radar is used for finding meteorological targets, namely atmosphere and precipitation objects, measuring the position and the speed of the targets, and inverting the reflectivity factor, the average radial speed, the velocity spectrum width, the differential reflectivity, the differential propagation phase shift rate, related directly-measured basic physical quantities according to the radar system and the characteristics of the echoes on the phase, the frequency and the amplitude so as to further invert the meteorological parameters such as precipitation types, particle spectrums, precipitation rates and the like.
As shown in fig. 2-3, due to the target distance and its radar cross-section, the echo power is in many cases not very high and the signal-to-noise ratio is low, when the noise power level is relative to the above-mentioned basic physical quantityThe estimation of (2) will have a large influence, especially on the reflectivity factor Zh, the velocity spectrum width σ v Correlation | ρ hv (0) The estimated deviation of parameters such as | and the differential reflectivity Zdr increases, which affects the data quality of target measurement.
At present, some radar manufacturers adopt a method for periodically measuring the noise of a radar receiver and periodically setting a noise power threshold, or a method for performing noise power measurement once before each radar observation and scanning required by a meteorological department, which is measured on the premise that a transmitter does not work and no echo exists. The method has certain effect, but the requirements of the meteorological radar for measuring strong and weak targets to certain data quality are basically difficult to meet.
The main reason is that the generation of radar noise includes three aspects, firstly, noise fluctuation caused by the change of the working temperature of a receiver; second, noise fluctuations caused by feed line channels, particularly rotary joints; third, the broad-spectrum radiation received by the antenna from the sun and universe fluctuates with time and antenna position. These noise variations cannot be predicted, and current noise methods cannot be estimated accurately and in time.
If a statistical method is adopted, the maximum noise power is used as the noise threshold value for radar operation, which can cause serious reduction of radar sensitivity.
Therefore, a method or a technique for accurately, dynamically detecting the noise power of the weather radar in real time is needed.
Disclosure of Invention
The invention aims to solve the defects of the prior art and provides a real-time dynamic noise power detection method for meteorological radars, which is used for accurately, real-time and dynamically detecting the noise power of the meteorological radars so as to automatically adapt to the change of the noise power of the radar, improve the sensitivity of the radar to the maximum extent and improve the measurement parameters of the radar.
The invention adopts the following technical scheme:
the real-time dynamic noise power detection method for the meteorological radar is characterized by comprising the following steps:
step 1, detecting range scan echo signals corresponding to emission pulses output by a radar digital receiver one by using a continuous weak power detection module, and estimating noise power;
the continuous weak power detection module detects the power of a baseband signal in a continuous weak signal area according to a distance/time sequence and a certain distance range/time length to obtain a continuous weak power echo time period containing noise power;
step 2, using 4 detection modules of a short-time power standard deviation module, a short-time phase standard deviation module, a short-time average normalized coherent power module and a short-time 0-order correlation coefficient module to perform parameter estimation of the short-time power standard deviation, the short-time phase standard deviation, the short-time average normalized coherent power and the short-time 0-order correlation coefficient on the continuous weak power echo time segment data in the step 1 according to a relatively short certain time segment;
and 3, fuzzifying and reasoning the parameters in the step 2 by using a comprehensive judgment module, determining the positioning of a pure noise area, and calculating the noise power level.
The further technical scheme of the invention is that the step 1 of continuous weak signal power detection comprises the following steps:
1) Calculating the echo power P of each range gate Gi Hi And P Vi ；
A. In the case of a Doppler radar, the echo power P at each range gate Gi can be directly calculated by using the output H (I, Q) of the linear digital receiver Hi As shown in the following formula:
h (I, Q) is a digital signal of a horizontal polarization echo of the meteorological radar, and the in-phase component of the digital signal is H I The value of the Gi-th range gate is H Ii With orthogonal component H Q The value of the Gi-th range gate is H Qi ；
B. If the Doppler radar is a dual-polarization Doppler radar, the horizontal polarization echo on each range gate Gi can be directly calculated by using the digital signals H (I, Q) of the horizontal polarization echo output by the linear digital receiver of the Doppler radarPower P Hi As shown in the following formula:
by using the vertical polarization echo digital signals V (I, Q), the vertical polarization echo power P on each range gate Gi can be directly calculated Vi As shown in the following formula:
wherein the in-phase component of the vertical polarization echo is V I The value of the Gi-th range gate is V Ii (ii) a With a quadrature component of V Q The value of the Gi-th range gate is V Qi 。
2) Confirming and marking weak echo signals in range scanning
Determining the noise level of the radar according to the working parameters of the radar, wherein the noise level mainly comprises two parts, namely receiver noise and antenna noise, the receiver noise is calculated by a receiver theory, and the noise power level of the receiver is estimated according to the following formula:
P RNoise ＝-114dB+10·log 10 (B n [MHz])+10·log 10 (F 0 )(dBm)------------(3)
wherein, B n For the receiver bandwidth, in MHz, F 0 Calculating the noise coefficient of the radar system by using the measured value under the room temperature condition;
the antenna noise is obtained by estimating the maximum solar radiation power P of the antenna under the conditions of corresponding working frequency band, bandwidth and antenna gain according to the height, longitude and latitude of the radar station and through the solar ephemeris and the spectral density thereof Solar 。
3. Finding weak echo signal section in range scan
Finding out a section of a continuous range gate with relatively small signal power on a scanning surface through power comparison, and respectively obtaining weak echo sections of a horizontal receiving channel and a vertical receiving channel according to the following formula;
m is the number of the continuous distance doors.
The preferred technical scheme of the invention is that the number of the M continuous distance gates is 50-100 points.
The further technical scheme of the invention is that the short-time phase standard deviation parameter, the short-time power standard parameter, the short-time average normalized coherent power parameter and the short-time 0-order correlation coefficient parameter estimation method in step 2 are as follows:
and (3) short-time phase standard deviation parameter estimation, which adopts the following formula to detect and calculate:
wherein N is the number of continuous distance points, x phi The phase of the echo signal of the Gi-th range gate; mu.s ph Is the average of the phases of the N points over the continuous distance, i.e.
And short-time power standard deviation parameter estimation, which adopts the following formula to detect and calculate:
wherein x is Pi The power of echo signals for Gi range gates; mu.s P Is the average of the power of N points over the continuous distance, i.e.
Short-time average normalized coherent power parameter estimation, and detecting and calculating the single repetition frequency by adopting the following formula:
Or the staggered repetition frequency is detected and calculated by adopting the following formula:
for the 1 st pulse interval of the pulse,
1 st order correlation of the Gi th range gate echo signal;
is the power of the echo signal of the Gi-th range gate, and
for the 2 nd pulse interval,
1 st order correlation of the Gi th range gate echo signal;
is the power of the echo signal of the Gi-th range gate, and
estimating short-time 0-order correlation coefficient parameters, and detecting and calculating according to the following formula
Wherein, the first and the second end of the pipe are connected with each other,
and
is the 0 th order autocorrelation function, i.e., power, of the horizontally polarized echo and the vertically polarized echo, respectively, and
is the 0 th order correlation function, i.e. the cross power, of the horizontally polarized echo and the vertically polarized echo.
The preferred technical scheme of the invention is that the number N of the continuous distance points is 9.
The further technical scheme of the invention is that the step 3 specifically comprises the following steps:
1) Fuzzy quantization, namely judging 4 parameter estimates of noise to be quantized to a numerical value between 0 and 1;
2) Weighted summation, i.e. weighted summation of fuzzy quantized parameter estimation, calculated according to the following formula
N Sign ＝K Pi ·σ Pi +K PH ·σ phase +K NCP ·NCP+K ρHV ·ρ hv (0)-------------(11)
N Sign Is a mark for judging the noise area;
3) Judging noise region, and weighting and summing the result N in step 2) with a comparison threshold Sign Comparing, if not less than the threshold, judging the noise area, otherwise, not;
4) And 3, noise power calculation, namely averaging the power of the noise area in the step 3) to obtain the noise level under the distance scanning.
The preferred technical scheme of the invention is that the comparison threshold value is 0.85.
The invention has the beneficial effects that:
(1) The method improves the poor detection (the alarm-missing rate is increased or the false alarm rate is increased) which takes the fixed noise level or the fixed noise level in an observation period as the standard of radar signal-to-noise ratio judgment and can cause the signal-to-noise ratio to be greatly reduced (taking the maximum noise as the standard) or the noise is mistakenly taken as a signal (taking the maximum noise as the standard).
(2) The method is suitable for noise fluctuation conditions of the pulse radar caused by element parameter change, signal channel characteristic drift, antenna rotation, sun and cosmic radiation and the like.
(3) Compared with a static noise level setting method, the signal-to-noise ratio of the echo corresponding to each transmitted pulse can be dynamically improved, only one item of solar radiation noise is needed, and the method can adapt to noise change exceeding 20dB in real time for the weather radar of X and below wave bands.
Drawings
FIG. 1 is a block diagram of a real-time dynamic noise power detector for a weather radar according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating statistics of noise power variation conditions in radar echoes according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a change in power of an echo of a range scan according to an embodiment of the present invention;
fig. 4 (a), fig. 4 (b), fig. 4 (c), and fig. 4 (d) are schematic diagrams of the membership degree of the noise criterion according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention are described below clearly and completely, and it is obvious that the described embodiments are some, not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
The invention is suitable for the complex baseband signal processing without pulse accumulation output by a digital receiver. The same processing is still valid for the complex baseband signal which has been pulse-accumulated, but the threshold parameter needs to be modified accordingly, and the noise estimation power is slightly increased, but still more effective than the conventional noise threshold setting method.
The processed result of the invention is shown in fig. 2-3, fig. 2 shows a schematic diagram of the echo power change in a range scan, and the continuous low level part with bold mark bit gray is a noise signal or a signal with small power; after the judgment processing, the single range scan pulse has been integrated, and the condition that the noise power variation of the radar azimuth scan echo fluctuates is obtained as shown in fig. 3.
The specific principle is as follows:
1. continuous weak power detection per range sweep
And carrying out continuous weak signal power detection on range scan echo signals corresponding to the transmitted pulses one by one.
First, the echo power P of each range gate Gi is calculated Hi And P Vi 。
In the case of a doppler radar, the output H (I,
q), the echo power P at each range gate Gi can be directly calculated Hi As shown in equation (1).
Here, H (I, Q) is a digital signal of a horizontal polarization echo of the meteorological radar, and the in-phase component of the digital signal is H I The value of the Gi-th range gate is H Ii (ii) a Its orthogonal component is H Q The value of the Gi-th range gate is H Qi 。
If the Doppler radar is a dual-polarization Doppler radar, the horizontal polarization echo power P on each range gate Gi can be directly calculated by using the digital signals H (I, Q) of the horizontal polarization echo output by the linear digital receiver of the Doppler radar Hi As shown in equation (1). To utilize itThe vertical polarization echo digital signal V (I, Q) can be directly calculated to obtain the vertical polarization echo power P on each range gate Gi Vi As shown in equation (2).
Wherein the in-phase component of the vertical polarization echo is V I The value of the Gi-th range gate is V Ii (ii) a With a quadrature component of V Q The value of the Gi-th range gate is V Qi 。
Second, weak echo signals in range scans are confirmed and flagged.
The possible noise level of the radar is determined according to the working parameters of the radar, such as the working frequency band, the bandwidth, the antenna gain, the receiver gain, the height and the longitude and the latitude of a radar station, and the possible noise level mainly comprises two parts, namely the receiver noise and the antenna noise.
Receiver noise is calculated by receiver theory, and the receiver noise power level can be estimated according to formula (3):
P RNoise ＝-114dB+10·log 10 (B n [MHz])+10·log 10 (F 0 )(dBm)------------(3)
wherein, B n Is the receiver bandwidth in MHz; f 0 The noise figure of the radar system can be calculated using the measured value at room temperature.
The antenna noise is obtained by estimating the maximum solar radiation power P of the antenna under the conditions of corresponding working frequency band, bandwidth and antenna gain according to the height, longitude and latitude of the radar station and through the solar ephemeris and the spectral density thereof Solar . For solar radiation, its horizontally polarized power and vertically polarized power can be considered equal.
Receiver noise power P RNoise With solar radiation power P Solar And the sum is reserved with a margin of 1dB, and can be used as the rough noise power of the radar and used as a power threshold value P for judging the weak echo N0 I.e. P N0 ＝P RNoise +P Solar +1. For a horizontally polarized channel, the receiver noise power isP HNoise For a vertically polarized channel, the receiver noise power is P VNoise Judging that the power threshold values of the weak echoes of the horizontal receiving channel and the vertical receiving channel are respectively P HN0 ＝P HNoise +P Solar +1 and P VN0 ＝P VNoise +P Solar +1。
Third, find the weak echo signal section in range scan
By comparing the power, the section of the continuous range gate with relatively small signal power on the range scan can be found out, and the weak echo sections of the horizontal receiving channel and the vertical receiving channel can be obtained according to the formulas (4) and (5).
In the above two formulas, M is the number of the continuous distance gates. The number M of points in the weak echo section cannot be too small, and generally 50 to 100 points can be adopted to obtain better effect. Because the value is small, the echo power value and the threshold value can be logarithmically processed for convenience of calculation and comparison.
2. 4 parameter estimation for noise discrimination
The method comprises 3 Doppler radar judgment parameters, namely short-time phase standard deviation, short-time power standard deviation and short-time average normalized coherent power, and 1 dual-polarization radar judgment parameter, namely a short-time 0-order correlation coefficient.
Standard deviation of phase of successive N points in distance
The phase range of the radar echo signal is-180 degrees to +180 degrees. In the pure noise region, the phase is random. It can be considered that the random phase follows a uniform distribution with a standard deviation of
(degree).
In contrast, in the non-noise region, there is a difference in signal intensity but the phases have a certain uniformity. Therefore, the phase standard deviation is calculated and can be used as a judgment basis of the noise signal.
The phase standard deviation can be calculated according to equation (6). Wherein, N is the number of continuous distance points, and N is small, so the method is called short time, and N =9 can be generally taken; x is the number of phi For the phase, μ, of the Gi-th range-gate echo signal ph Is the average of the phases of the N points over the continuous distance, i.e.
The calculation of the short-time phase standard deviation is performed based on the aforementioned processing of item 1. And in a plurality of continuous weak echo areas of M points scanned at a distance, calculating the phase standard deviation of the N points one by one, and storing the calculation results. Note that in the case of dual polarization radar, the horizontal and vertical receive channels are processed separately. This process can be done with only a single range scan (i.e. 1 measurement pulse).
3. Comprehensive decision module and noise power estimation
And the comprehensive noise judgment module performs comprehensive judgment processing on the 4 parameter estimation results for judging the noise so as to obtain the actual noise level on each distance scan.
1) Fuzzy quantization
In most cases, the 4 parameter estimation results for noise estimation are distributed on both the large and small values, so the problem of fuzzification becomes simple and the fuzzy quantization process is easily implemented according to the fuzzy membership function as shown in fig. 4.
To fit all cases, the fuzzy membership functions shown in FIG. 4 can easily implement the fuzzy quantization process.
In order to adapt to all cases, the transition curve in fig. 4 is subjected to a simplification process, and the transition region is simplified to be replaced by three-value transition, so that the membership function of each parameter variable shown in table 1 can be obtained. An example of the actual value space of the parameter variation is shown in table 2.
TABLE 1 membership function
TABLE 2 practical value space example for parameter variation
By this processing, it is judged that 4 kinds of parameters of the noise are quantized to a value between 0 and 1.
2) Weighted summation
As shown in fig. 1, the parameters are weighted and summed. It should be noted that, for the dual-polarization radar, a short-time phase relation parameter is needed, otherwise, the short-time phase relation parameter is not needed; and the average normalized coherent power of the continuous N points on the distance needs to use the previous or subsequent detection pulse data, and the processing can be carried out only by buffering.
The weighted sum can be performed using the calculation formula (11), resulting in N Sign Is a flag for noise region determination. The values of the weighting coefficients are shown in table 3, for example, according to the operating system of the radar.
N Sign ＝K Pi ·σ Pi +K PH ·σ phase +K NCP ·NCP+K ρHV ·ρ hv (0)-------------(11)
Table 3 example weighting factor values for each parameter variable
3) Noise region decision
Using a comparison threshold (which may be 0.85) and the above calculation result N Sign And comparing, if not less than the threshold, judging the noise area, otherwise, not judging the noise area.
4) Noise power calculation
5) For 1 or several noise regions identified as noise, as exemplified by the grey bold line in fig. 2, the power of the noise regions is averaged, i.e. the noise level at the distance scan is obtained. From this, it is natural that the signal-to-noise ratio of the echo signal can be calculated as a reference.
Subsequent signal processing and inversion of the detected physical quantity, both calculated as signal-to-noise ratio, will become convenient.
Example 1: implementation of dual-polarization Doppler weather radar noise level real-time detection
The dual-polarization (the weather world customarily changes dual polarization into dual polarization, generally, the polarization is called for electromagnetic waves, the polarization is called for light, and the polarization and the light can be used in general) Doppler weather radar has the characteristics of full airspace detection, dual channels work simultaneously, and cost factors are considered particularly during manufacturing, so that the performance instantaneous change of components such as azimuth/pitching rotary joints, circulators and the like in a feeder line is serious. For using only doppler parameters, the performance is not severely degraded. However, the performance is difficult to maintain stably by using dual polarization observation parameters.
Real-time detection of the noise level can solve this problem.
In step 1, horizontal complex baseband signals H (I, Q) and vertical complex baseband signals V (I, Q) output by the radar dual-channel receiver are converted into power levels, as shown in equations (1) and (2). For convenience, they were separately logarithmically transformed to yield 10logP Hi And 10logP Vi And (d) represents the echo power signal.
Step 2, echo power signal 10logP on range scan Hi And 10logP Vi Respectively carrying out continuous weak power detection, wherein the detection reference is the preliminary noise power obtained by calculation of a formula (3), and a plurality of signals are obtainedAnd (5) a weak echo section.
And 3, carrying out noise judgment 4 parameter detection on the weak echoes of the sections, namely detecting a short-time phase standard deviation, a short-time power standard deviation, a short-time average normalized coherent power and a short-time 0-order correlation coefficient.
And step 4, carrying out fuzzy quantization on the parameters in the step 3.
And 5, carrying out weighted summation on the parameters in the step 4.
And 6, judging the noise area of the summation result in the step 5.
And 7, calculating the noise level of the judged noise area.
Thus, the noise levels of the horizontal polarization channel and the vertical polarization channel are obtained respectively.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (4)
1. The real-time dynamic noise power detection method for the meteorological radar is characterized by comprising the following steps:
step 1, detecting range scan echo signals corresponding to transmitting pulses output by a radar digital receiver one by using a continuous weak power detection module, and estimating noise power;
the continuous weak power detection module detects the power of the baseband signal in a continuous weak signal area according to a distance/time sequence and a certain distance range/time length to obtain a continuous weak power echo time period containing noise power;
step 2, using 4 detection modules of a short-time power standard deviation module, a short-time phase standard deviation module, a short-time average normalized coherent power module and a short-time 0-order correlation coefficient module to perform parameter estimation of the short-time power standard deviation, the short-time phase standard deviation, the short-time average normalized coherent power and the short-time 0-order correlation coefficient on the continuous weak power echo time segment data in the step 1 according to a relatively short certain time segment;
step 3, fuzzifying and reasoning the parameters in the step 2 by using a comprehensive judgment module, determining the positioning of a pure noise area, and calculating a noise power level;
wherein, the step 1 of continuous weak signal power detection comprises:
1) Calculating the echo power P of each range gate Gi Hi And P Vi ；
A. In the case of a Doppler radar, the echo power P at each range gate Gi is directly calculated by using the output H (I, Q) of the linear digital receiver Hi As shown in the following formula:
h (I, Q) is a digital signal of a horizontal polarization echo of the meteorological radar, and the in-phase component of the digital signal is H I The value of the Gi-th range gate is H Ii With orthogonal component H Q The value of the Gi-th range gate is H Qi ；
B. If the Doppler radar is a dual-polarization Doppler radar, the power P of the horizontal polarization echo on each range gate Gi is directly calculated by using the digital signals H (I, Q) of the horizontal polarization echo output by a linear digital receiver of the Doppler radar Hi As shown in the following formula:
the vertical polarization echo power P on each range gate Gi is directly calculated by using the vertical polarization echo digital signal V (I, Q) Vi As shown in the following formula:
wherein the in-phase component of the vertically polarized echo is V I The value of the Gi-th range gate is V Ii (ii) a With a quadrature component of V Q The value of the Gi-th range gate is V Qi ；
2) Confirming and marking weak echo signals in range scanning
Determining the noise level of the radar according to the working parameters of the radar, wherein the noise level of the radar mainly comprises two parts, namely receiver noise and antenna noise, the receiver noise is calculated through a receiver theory, and the noise power level of the receiver is estimated according to the following formula:
P RNoise ＝-114dB+10·log 10 (B n [MHz])+10·log 10 (F 0 )(dBm)------------(3)
wherein, B n For the receiver bandwidth, in MHz, F 0 Calculating the noise coefficient of the radar system by using the measured value under the room temperature condition;
the antenna noise is obtained by estimating the maximum solar radiation power P of the antenna under the conditions of corresponding working frequency band, bandwidth and antenna gain according to the height, longitude and latitude of the radar station and through the solar ephemeris and the spectral density thereof Solar ；
3) Finding out the weak echo signal section in range scanning
Finding out a section of a continuous range gate with relatively small signal power on a scanning surface through power comparison, and respectively obtaining weak echo sections of a horizontal receiving channel and a vertical receiving channel according to the following formula;
m is the number of the continuous distance doors;
the number of the M continuous distance gates is 50-100 points;
the short-time phase standard deviation parameter, the short-time power standard parameter, the short-time average normalized coherent power parameter and the short-time 0-order correlation coefficient parameter estimation method in the step 2 are as follows:
and short-time phase standard deviation parameter estimation, which adopts the following formula to detect and calculate:
wherein N is the number of continuous distance points, x phi The phase of the echo signal of the Gi-th range gate;
μ ph is the average of the phases of the N points over the continuous distance, i.e.
And (3) estimating the short-time power standard deviation parameter, and detecting and calculating by adopting the following formula:
wherein x is Pi The power of echo signals for Gi range gates; mu.s P Is the average of the power of N points over the continuous distance, i.e.
Short-time average normalized coherent power parameter estimation, and detecting and calculating the single repetition frequency by adopting the following formula:
or the staggered repetition frequency is detected and calculated by adopting the following formula:
for the 1 st pulse interval of the pulse,
correlation of order 1 for the Gi-th range gate echo signal;
is the power of the echo signal of the Gi-th range gate, and
for the 2 nd pulse interval,
1 st order correlation of the Gi th range gate echo signal;
is the power of the echo signal of the Gi-th range gate, an
Estimating short-time 0-order correlation coefficient parameters, and detecting and calculating according to the following formula
Wherein the content of the first and second substances,
and
is the 0 th order autocorrelation function, i.e., power, of the horizontally polarized echo and the vertically polarized echo, respectively, and
is the 0 th order correlation function, i.e. the cross power, of the horizontally polarized echo and the vertically polarized echo.
2. The weather radar real-time dynamic noise power detection method as claimed in claim 1, wherein the number of consecutive distance points N is 9.
3. The weather radar real-time dynamic noise power detection method according to claim 1, wherein the step 3 specifically comprises:
1) Fuzzy quantization, namely judging 4 parameter estimates of noise to be quantized to a value between 0 and 1;
2) Weighted summation, i.e. weighted summation of fuzzy quantized parameter estimation, calculated according to the following formula
N Sign Is a mark for judging the noise area;
3) Judging the noise area, and weighting and summing the result N in step 2) by using a comparison threshold value Sign Comparing, if not less than the threshold, judging the noise area, otherwise, not;
4) And 3, noise power calculation, namely averaging the power of the noise area in the step 3) to obtain the noise level under the distance scanning.
4. The weather radar real-time dynamic noise power detection method according to claim 3, wherein the comparison threshold value is 0.85.
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