CN111289948B - Pulse weather radar echo weak signal detection method and electronic equipment - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
- G01S7/2921—Extracting wanted echo-signals based on data belonging to one radar period
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention relates to a pulse weather radar echo weak signal detection method and electronic equipment, wherein the method comprises the following steps: a noise suppression step of receiving a first echo signal, and sequentially performing AD oversampling processing, multi-band-pass filtering processing and distance-pulse matrix operation on the first echo signal to obtain a second echo signal subjected to noise suppression; clutter suppression, namely performing adaptive spectrum correction on the second echo signal based on a static clutter map to obtain a third echo signal; and a weak signal extraction step, namely extracting effective weak signals based on constant false alarm rate detection and priori knowledge judgment. Compared with the prior art, the invention has the advantages of effectively inhibiting noise, better keeping the integrity of the original signal and the like.
Description
Technical Field
The invention relates to the technical field of radar signal processing, in particular to a pulse weather radar echo weak signal detection method and electronic equipment.
Background
The clutter in the echo of the existing pulse weather radar is mainly ground clutter and sea clutter, the characteristics of the two clutter are that the two clutter are generally near zero frequency, and sea clutter caused by wave fluctuation on the sea surface can contain a certain Doppler frequency shift and a certain bandwidth due to the influence of an observation environment, and the bandwidth is generally smaller than 200Hz. The clutter suppression methods at the present stage are mainly three methods: pulse cancellation MTI technique, CLEAN algorithm, generalized Matched Filter (GMF). The MTI technology can realize complete suppression of zero frequency ground clutter, and has simple engineering application and low calculated amount. But useful information around zero frequency is also attenuated due to the nonlinear modulation of the amplitude-frequency response of the MTI technique. As in patent CN103885044B, a method for suppressing noise of a narrowband radar echo based on the CLEAN algorithm is disclosed, but the CLEAN algorithm is only suitable for removing single-frequency clutter at zero frequency, and clutter with a certain bandwidth cannot be suppressed, such as weather clutter, sea clutter, and the like. The effect of ground clutter, sea clutter and the like in Doppler spectrum is equivalent to colored noise, which can treat clutter suppression as a problem of detecting a definite signal in a colored noise background, a Generalized Matched Filter (GMF) is an effective method for detecting signals in the background, clutter can be well removed and complete information of an original waveform can be kept, but GMF technology generally needs priori information, estimation of a clutter autocorrelation matrix is needed, and the estimation calculation amount is large, so that the change of Doppler line amplitude outside a clutter component range can be caused.
Noise in clutter in pulse weather radar echo is mainly phase noise of local oscillation signals, thermal noise of a system, shot noise of electronic devices and thermal noise of the atmosphere. These three types of noise are all characterized as white noise and are distributed over the entire frequency band. The conventional clutter removal method cannot well remove noise in echo, and the noise cannot be well removed by a single filter. The weak signal in the pulse weather radar echo is a turbulent echo signal of clear sky, the signal is characterized in that the echo intensity is weak, the frequency spectrum has a certain skirt band and time-varying characteristics, and if the noise and clutter processing effect is poor, the accurate and effective weak signal is difficult to extract.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a pulse weather radar echo weak signal detection method and electronic equipment which can effectively inhibit noise and well keep the integrity of the original signal.
The aim of the invention can be achieved by the following technical scheme:
a pulse weather radar echo weak signal detection method comprises the following steps:
a noise suppression step, namely receiving a first echo signal, and sequentially carrying out AD oversampling processing, multi-band-pass filtering processing and distance-pulse matrix operation on the first echo signal to realize noise suppression of a pulse weather radar echo and obtain a second echo signal, wherein the noise of the pulse weather radar echo is usually system thermal noise, phase noise of a local oscillator signal and atmospheric background noise;
clutter suppression, namely performing adaptive spectrum correction on the second echo signal based on a static clutter map, and removing environmental clutter to obtain a third echo signal;
and a weak signal extraction step, namely extracting effective weak signals based on constant false alarm rate detection and priori knowledge judgment.
Further, the AD oversampling processing specifically includes M times of oversampling AD conversion, an ideal digital low-pass filter filtering processing and a decimation processing, so as to realize reduction and quantization of radar echo noise.
Further, the multi-bandpass filtering process is implemented based on a multi-bandpass filter bank.
Further, the distance-pulse matrix operation is specifically:
and carrying out FFT operation on the same distance points of different pulses on the distance-pulse matrix to obtain frequency spectrums of different distances, and carrying out coherent accumulation and averaging operation on the frequency spectrums of the same distance.
Further, the distance-pulse matrix is a pulse complex matrix, each behavior is different pulse sampling point set, and each column is the sampling point set of the same distance in different pulse periods.
Further, accumulation and statistics are carried out on the trace point data containing the clutter, discrimination and identification are carried out on the clutter area, and the static clutter map is built.
Further, the adaptive spectrum correction specifically includes:
dividing a two-dimensional plane around the radar into a plurality of azimuth distance units, averaging the second echo signals in distance according to the number of distance gates contained in each divided azimuth distance unit based on the static clutter map, updating signals stored in each azimuth unit through a recursive filter, and distinguishing clutter based on the signals.
Further, the constant false alarm rate detection is based on a CFAR detector implementation.
Further, the a priori knowledge decision obtains an effective weak signal through existing knowledge and range estimation of the measurement target.
The invention also provides an electronic device for pulse weather radar echo weak signal detection, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the one processor to cause the at least one processor to perform the steps of the method.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention adopts the multi-band-pass filter group to inhibit noise, well keeps the integrity of the original signal, improves the signal-to-noise ratio of the echo signal by coherent accumulation and further inhibits the noise.
2. According to the invention, the static clutter map and the radar echo are added to carry out self-adaptive spectrum correction to filter the environmental clutter, so that the effect is good.
3. And after noise suppression based on radar echo, constant false alarm rate detection and judgment are carried out so as to detect and obtain an echo weak signal, and an accurate weak signal can be effectively obtained.
Drawings
FIG. 1 is a flow chart of the overall method architecture of the present invention;
FIG. 2 is a schematic diagram of quantization noise reduction by AD oversampling in noise suppression in accordance with the present invention;
FIG. 3 is a schematic diagram of out-of-band noise suppression by multiple bandpass filters in noise suppression in accordance with the present invention;
FIG. 4 is a diagram of the results of a matlab simulation of a noisy radar echo signal of the present invention;
FIG. 5 is a matlab simulation result diagram of the multi-band filter of the present invention suppressing out-of-band noise;
FIG. 6 is a flow chart of clutter map processing for clutter suppression according to the present invention;
fig. 7 is a block diagram of a unit average CFAR detector according to the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
Example 1
The embodiment provides a pulse weather radar echo weak signal detection method, the principle framework of which is shown in fig. 1, and the method comprises the following steps:
a noise suppression step, namely receiving a first echo signal, and sequentially carrying out AD oversampling processing, multi-band-pass filtering processing and distance-pulse matrix operation on the first echo signal to realize noise suppression on the pulse weather radar echo and obtain a second echo signal;
clutter suppression, namely performing adaptive spectrum correction on the second echo signal based on a static clutter map, and removing environmental clutter to obtain a third echo signal;
and a weak signal extraction step, namely extracting effective weak signals based on constant false alarm rate detection and priori knowledge judgment.
Noise from pulsed weather radar echoes is typically system thermal noise, phase noise of local oscillator signals, and atmospheric background noise, which can be considered white noise within a limited signal bandwidth. The noise suppression of the pulse weather radar echo is comprehensively realized through three steps of AD oversampling technology, a multi-band-pass filter bank and distance-pulse matrix operation.
(1) AD oversampling
The AD oversampling processing specifically comprises M times of oversampling AD conversion, ideal digital low-pass filter filtering processing and extraction processing, so as to realize reduction and quantification of radar echo noise. Specifically:
as shown in fig. 2, after the radar echo is subjected to the oversampling AD conversion by M times, the noise of the radar echo is quantized, and the larger M is, the less the spectrum aliasing part of the echo signal and the noise is; then the over-sampled echo signal passes through an ideal digital low-pass filter of pi/M, the signal power is not affected at this time, and quantization noise outside pi/M is filtered; and then the modulation information is reserved through a sampling module. Considering the distance accuracy requirement and the hardware parameters of the ADC, M is generally between 2 and 10.
(2) Multi-bandpass filtering process
As shown in fig. 3, after the radar echo signal is subjected to sampling AD conversion, the signal bandwidth of the radar echo signal still has more noise, which mainly comes from system noise and environmental noise. The time domain expression of the radar intermediate frequency echo is as follows:
the echo signal has a period ofSquare wave signal f pluse For the sampling frequency, the signal can be written as the sum of multiple harmonic trigonometric functions after a triangular transformation. The expression is as follows:
wherein the method comprises the steps of
Since the full frequency band contains noise, it is necessary that the combination of multiple band pass filters suppress the out-of-band noise as much as possible while preserving the modulation information of the original echo.
In this embodiment, 8 band-pass filters are used to form a multi-band-pass filter bank for filtering. According to spectrum analysis, 8 band-pass filters can suppress noise outside the pass band, and more than 90% of original information of echo signals can be reserved.
As shown in fig. 4, the denoising effect of the multi-band filter can be verified by the following simulation experiment: simulating a radar signal with a repetition frequency of 1MHz, and using f s The echo signal is sampled by 12.5MHz, zero-mean complex Gaussian white noise is added to form an echo signal containing noise, and the signal-to-noise ratio is 0dB; is provided withAnd designing a 10kHz passband at the frequency points of 500kHz,1MHz,1.5MHz and … MHz respectively, and passing the echo signals containing Gaussian white noise through the multi-bandpass filter.
As shown in the simulation results of fig. 5, the out-of-band noise is well suppressed, and only a small amount of noise in the passband is contained.
(3) Distance-pulse matrix operation
The radar echo signals passing through the multi-band-pass filter bank are subjected to FFT operation on the same distance points of different pulses on a distance-pulse matrix to obtain frequency spectrums of different distances, and based on the characteristic that the noise correlation degree of white noise is zero at different moments, the signal to noise ratio of the radar echo signals is improved by performing coherent accumulation and averaging operation on the frequency spectrums of the same distance.
In this embodiment, the distance-pulse matrix is a 2048×25 pulse complex matrix, each of which has a different set of pulse sampling points, and is a fast time dimension sampling, and the sampling frequency in this embodiment is f ADC =25 MHz; each column is a set of sampling points at the same distance in different pulse periods, and is slow time dimension sampling, and the sampling frequency in the embodiment is f pulse ＝500KHz。
The clutter of the pulse weather radar echo is usually ground clutter and sea clutter, the sea clutter is fluctuant, and particularly some clutter with higher energy are often regarded as targets, so that the false alarm probability is increased. In the method, noise is suppressed by forming a static noise map and performing adaptive spectrum correction on the radar echo after noise removal to remove environmental noise, as shown in fig. 6. Accumulating and counting the spot data containing clutter, judging and identifying the clutter area, establishing the static clutter map, and further adopting corresponding clutter suppression processing.
The adaptive spectrum correction of the static clutter map and the second echo signal after noise removal specifically comprises the following steps:
dividing a two-dimensional plane around the radar into a plurality of azimuth distance units, averaging the second echo signals in distance according to the number of distance gates contained in each divided azimuth distance unit based on the static clutter map, updating signals stored in each azimuth unit through a recursive filter, and distinguishing clutter based on the signals.
The echo signal for each azimuth distance cell is stored in a memory, the amplitude of the clutter for each azimuth distance cell is averaged, and the signal stored for each azimuth cell is updated by a recursive filter as the antenna scans. Wherein the expression of the recursive filter is Y n ＝(1-K)Y n-1 +KX n K is a factor less than 1, X n For echo signals of each azimuth distance unit, Y n Is a signal stored in the memory cell after recursive updating.
Judging the information in the clutter map through a detection threshold H, wherein H=C×lambda, C is a threshold factor, lambda is a noise mean value, and if the detected signal X n And if the noise is less than or equal to H, judging that the echo signal is out of the noise, selecting a normal branch output result by the system, otherwise, selecting a cancellation branch output result by the system, and removing the noise, thereby greatly reducing the processing capacity of the signal and data processing unit on useless echoes.
In the weak signal extraction step, the weak signal extraction of the pulse weather radar echo is realized by carrying out constant false alarm rate detection on the third echo signal after removing the noise through combining distance-speed matrix operation, and carrying out judgment on priori knowledge of a detection target.
Constant false alarm rate detection of a signal is thresholded by determining the statistical properties of noise or clutter by estimating some samples in a reference cell in a CFAR detector (CFAR processing circuit). In the unit average constant false alarm rate detection in this embodiment, the distance units l=8 on both sides of the unit average constant false alarm rate detection are taken as reference units, the reference unit number n=16, and the estimation of the background clutter power is the arithmetic average of N clutter sample powers. The distribution of the envelope of the clutter can be regarded as Rayleigh distribution, and is subjected to exponential distribution after square rate detection, and the probability density function and the constant false alarm rate are respectively as follows:
where λ is the statistical mean of the random variable x, let s=tλ, then P f ＝e -T It can be seen that the constant false alarm rate depends only on the threshold factor T, and echo signals below the threshold are filtered out according to the threshold, so that clutter is eliminated.
As shown in fig. 7, a CFAR detector is used to take 8 distance units on both sides of a certain detection unit as reference units, average the 16 reference units, and multiply the obtained value by a threshold factor to obtain a threshold level. This threshold level continuously changes as background clutter or noise within a distance segment around the target changes. The units on the left side and the right side of the detection unit are protection units and are not calculated into the detection unit, so that the influence on the average background value can be avoided.
According to priori knowledge, interference signals are eliminated through the existing cognition and range estimation of the measurement target, and finally all effective echo signals are extracted.
Example 2
The embodiment provides an electronic device for pulse weather radar echo weak signal detection, which comprises at least one processor and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the one processor, the instructions being executable by the at least one processor to cause the at least one processor to perform steps of a method as in embodiment 1.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the technical personnel in the field according to the inventive concept are within the protection scope determined by the present invention.
Claims (7)
1. The pulse weather radar echo weak signal detection method is characterized by comprising the following steps of:
a noise suppression step of receiving a first echo signal, and sequentially performing AD oversampling processing, multi-band-pass filtering processing and distance-pulse matrix operation on the first echo signal to obtain a second echo signal subjected to noise suppression;
clutter suppression, namely performing adaptive spectrum correction on the second echo signal based on a static clutter map to obtain a third echo signal;
a weak signal extraction step, namely extracting effective weak signals based on constant false alarm rate detection and priori knowledge judgment;
the distance-pulse matrix operation is specifically as follows: performing FFT operation on the same distance points of different pulses on the distance-pulse matrix to obtain frequency spectrums of different distances, and performing coherent accumulation and averaging operation on the frequency spectrums of the same distance;
accumulating and counting the spot data containing clutter, judging and identifying clutter areas, and establishing the static clutter map, wherein the self-adaptive frequency spectrum correction specifically comprises the following steps:
dividing a two-dimensional plane around the radar into a plurality of azimuth distance units, averaging the second echo signals in distance according to the number of distance gates contained in each divided azimuth distance unit based on the static clutter map, updating signals stored in each azimuth unit through a recursive filter, and distinguishing clutter based on the signals.
2. The method for detecting the echo weak signal of the pulse weather radar according to claim 1, wherein the AD oversampling process specifically includes M-times oversampling AD conversion, ideal digital low-pass filter filtering process and decimation process.
3. The pulsed weather radar echo weak signal detection method of claim 1, wherein the multi-bandpass filtering process is implemented based on a multi-bandpass filter bank.
4. The method of claim 1, wherein the distance-pulse matrix is a pulse complex matrix, each of the pulse sampling point sets having different behaviors, and each of the pulse sampling point sets having the same distance in different pulse periods.
5. The pulsed weather radar echo weak signal detection method of claim 1, wherein the constant false alarm rate detection is implemented based on CFAR detectors.
6. The pulsed weather radar echo weak signal detection method of claim 1, wherein the a priori knowledge decision obtains an effective weak signal by existing knowledge and range estimation of a measurement target.
7. An electronic device for pulsed weather radar echo weak signal detection, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the one processor to cause the at least one processor to perform the steps of the method of any one of claims 1-6.
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