CN106569188B - Based on the ionosphere phase perturbation correction algorithm for improving PGA - Google Patents
Based on the ionosphere phase perturbation correction algorithm for improving PGA Download PDFInfo
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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
- G01S7/40—Means for monitoring or calibrating
-
- 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
- G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
- G01S7/2927—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods by deriving and controlling a threshold value
-
- 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
- G01S7/35—Details of non-pulse systems
- G01S7/352—Receivers
- G01S7/354—Extracting wanted echo-signals
Abstract
The invention discloses a kind of based on the ionosphere phase perturbation correction algorithm for improving PGA, FFT calculating is carried out to the echo data of a certain range-azimuth resolution cell first, obtain its frequency spectrum, the strong peak Bragg of broadening is filtered out using adaptive sliding window bandpass filter, and then IFFT is carried out to the frequency domain data of filter output, then this Data correction echo data is utilized, thresholding is arranged according to the mean value of this data at the same time, record the position that amplitude in this data is lower than this threshold value, the data that the position is corresponded in echo data are rejected, finally echo data is reconstructed using CS algorithm, acquire its frequency spectrum, ionosphere phase pollution at this time has corrected, sea/land clutter spectral peak sharpens, noise floor reduces.Simulation result shows compared with PGA algorithm, and after the improved PGA algorithm ionosphere corrections of radar echo signal, radar noise substrate reduces about 10dB, consistent with the radar echo signal noise floor that phase pollution is not added.
Description
Technical field
The invention belongs to algorithm of target detection in Radar Technology, and in particular to a kind of based on the ionosphere phase for improving PGA
Pollute correcting algorithm.
Background technique
Sky-wave OTH radar (OTHR) works in high frequency band, is the reflex using ionosphere to high frequency band signal
And realize to the radar system of target acquisition other than sighting distance, it has been applied to military field.However ionosphere is the shakiness of time-varying
Determine transmission medium, certain phase perturbation can be brought to the echo-signal of OTHR, causes the Doppler's spectral peak exhibition of sea/land clutter
Width covers the Weak target near it.Therefore, for improving OTHR target detection capabilities, ionosphere phase perturbation correction
It is particularly significant.
Phase gradient algorithm (PGA) is filtered out the positive/negative peak Bragg of broadening using bandpass filter, carries out IFFT to it
And the time domain data at the peak Bragg is obtained, it is then assumed that the phase difference between consecutive number strong point is Δ φ, time interval is Δ t, then
It is f (t)=π Δ t of Δ φ/2 that its instantaneous frequency, which can be calculated, can finally be carried out to ionosphere phase using this Instantaneous frequency variations
Correction.Although the method is very simple and intuitive, and can calculate the variation of the peak Bragg instantaneous frequency in the short time, real
Border is found when applying, for the peak the Bragg time domain data filtered out, if the amplitude in a certain data point is lower,
Calculated instantaneous frequency will appear a mutation relative to the point of surrounding on the aspect, increases and calculates error, thereby reduces PGA
Solution phase pollutant performance.
Based on the above analysis, PGA algorithm is in the peak Bragg miscellaneous noise ratio (CNR) lower situation, calculated instantaneous pollution
Between phase and true value have relatively large deviation, it would be desirable to seek a kind of more effective approach, i.e., searching the peak Bragg CNR compared with
Low position, and solution phase pollution is carried out to this position data using more efficient way.
Summary of the invention
The purpose of the present invention is to provide a kind of based on the ionosphere phase perturbation correction algorithm for improving PGA, overcomes PGA
Algorithm is in the lower situation of the peak Bragg CNR, asking with relatively large deviation between calculated instantaneous pollution phase and true value
Topic.
The technical solution for realizing the aim of the invention is as follows: a kind of to be calculated based on the ionosphere phase perturbation correction for improving PGA
Method, method and step are as follows:
Step 1: extracting the peak sea clutter Bragg that energy is strong in echo-signal using sliding window bandpass filter, obtain Bragg
The time domain data s (n) at peak calculates the peak the Bragg frequency f according to radar transmitter frequencyb, so that s (n) is moved to zero-frequency,
Calculate phase errorn。
Step 2: echo data phase is corrected according to formula (5), and calculates adaptive magnitude threshold T:
X '=Ψ x (5)
Wherein, in a CIT, the echo data of a certain range-azimuth resolution cell, after the pollution of ionosphere phase
It is indicated with the vector x that N × 1 is tieed up；Echo data after the n dimensional vector n x ' expression phasing of N × 1；N × N-dimensional matrix Ψ indicates ionization
Layer phasing matrix, and phase calibration is in the diagonal positions of matrix；
Adaptive magnitude threshold T=meanamη, meanamThe mean value of s (n) amplitude of expression, η expression meet a certain specific mistake
Difference and the scale factor set, are usually arranged as 0.6.
Step 3: the data y according to formula (6) and adaptive magnitude threshold T, after being rejected.
Step 4: the data y after rejecting being reconstructed according to formula (7) and formula (8), obtains reconstruct data spectrum
Calculated value θ 'y。
Compared with prior art, the present invention its remarkable advantage is:
(1) the positive/negative peak Bragg of sea clutter is more accurately extracted.
(2) in the lower situation of the peak Bragg CNR, pollution echo data can be also corrected.
Detailed description of the invention
Fig. 1 is frequency-amplitude figure of sliding window bandpass filter of the invention.
Fig. 2 is the calculation flow chart for the adaptive sliding window bandpass filter that the present invention uses.
Fig. 3 is simulation result diagram, wherein figure (a) is that ionosphere phase pollutes front and back comparison diagram, figure (b) is adaptive threshold
Detection data figure, figure (c) PGA calculate phase and true value comparison diagram, and figure (d) is PGA and improves Frequency spectrum ratio after PGA phase calibration
Compared with figure.
Fig. 4 is that the present invention is based on the algorithm flow charts for the ionosphere phase perturbation correction algorithm for improving PGA.
Specific embodiment
Present invention is further described in detail with reference to the accompanying drawing.
In a CIT, the echo data of a certain range-azimuth resolution cell, by ionosphere phase pollution after with N ×
The vector x of 1 dimension indicates that wherein N indicates the umber of pulse in a CIT.It include sea/land clutter, target and noise in x, wherein sea
The Bragg peak energy amount of clutter is strongest.Assuming that P (f) indicates the FFT of x, due to being polluted by ionosphere phase, clutter spectrum is tight
It broadens again.Below with reference to Fig. 4, introduce based on the ionosphere phase perturbation correction algorithm for improving PGA, method and step is as follows:
Step 1: extracting the positive/negative peak Bragg that energy is strong in echo-signal using sliding window bandpass filter, obtain Bragg
The time domain data s (n) at peak calculates the peak the Bragg frequency f according to radar transmitter frequencyb, so that s (n) is moved to zero-frequency,
Calculate phase errorn:
Positive/negative Bragg is extracted according to maximum value position judgement in the position for determining maximum value in echo data frequency spectrum first
The peak Bragg that broadening how is extracted using adaptive sliding window bandpass filter is described below in peak, it is assumed that extracts the negative Bragg in left side
Peak.
1. calculating echo data noise power mean value using following formula.
WhereinIndicate noise power mean value；The frequency spectrum of P (f) expression echo data；[fu,fd] indicate that Frequency Domain Integration calculates
Section, generally select front end without clutter and target area.
2. designing one group of rectangular filter.The center frequency points of first filter are f1, starting and cutoff frequency are distinguished
For f1- m Δ f and f1+ m Δ f, wherein m is a positive integer, indicates the size of filter window, and Δ f indicates frequency domain sample interval.It adopts
The frequency spectrum for extracting echo data since the negative frequency section leftmost side with this filter, extracts the general power P of portions of the spectrum1For
And then in the clutter general power P ' of this frequency range1It can be calculated by following formula
The centre frequency of second filter is f2=f1+ Δ f, starting and cutoff frequency are respectively f2- m Δ f and f2+mΔ
F can obtain P ' using formula (2) and the identical calculation method of formula (3)2, and then others P 'i(i=3,4 ..., N/2-2m) with same
Mode can be calculated, wherein N is the total sampling number of echo data (umber of pulse in a CIT).Window sliding is cut
Only Frequency point is spectral centroid point 0Hz, and concrete condition is as shown in Figure 1.One group of clutter general power can be obtained by the sliding of window,
The maximum value in this group of clutter general power is searched, and uses L1It is represented, and records the corresponding center frequency points of maximum value, is denoted as
fmid1。
3. converting sliding window width, if m=m+ λ, wherein λ is positive integer, and then calculates clutter general power maximum value L2, and remember
The corresponding center frequency points of maximum value are recorded, f is denoted asmid2。
4. if L2/L1(δ is a decision threshold to≤δ satisfaction, and usually less than 1.1), the window width m of filtering is optimal
, i.e., this window width is suitable with the peak sea clutter Bragg of extension, on the contrary, if L2/L1> δ, then L1=L2, repeat the above-mentioned 3rd
Step calculates, and the calculation process of adaptive sliding window bandpass filter is as shown in Figure 2.
The peak Bragg is extracted according to the above-mentioned peak Bragg extracting method, and then the time domain data for extracting the peak Bragg is expressed as
Wherein s (n) indicates the time domain data at the peak Bragg；J indicates imaginary unit；εnIndicate phase error；κn, φ and fbPoint
It Biao Shi not amplitude, initial phase and the peak Bragg frequency；Indicate that sliding window bandpass filter filters out the peak Bragg in left side ,+indicate to slide
Curtain heading tape bandpass filter filters out the right side peak Bragg；Δ t indicates time-domain sampling interval；V (n) indicates noise, and assumes that such noise is
White Gaussian noise；N indicates n-ththA hits, N indicate total sampling number (i.e. umber of pulse in a CIT).
From formula (4) as can be seen that only including the single peak Bragg in s (n), therefore the phase in s (n) is calculated using PGA
Error, and phasing is carried out to x with calculated phase error, i.e., the frequency f at the peak Bragg is calculated according to transmitting carrier frequencyb,
To move s (n) to zero-frequency, phase error can be calculatedn。
Step 2: correcting echo data phase according to formula (5), calculate adaptive magnitude threshold T.
Calculate phase errornPhasing can be carried out to x, specific updating formula is as follows
X '=Ψ x (5)
The wherein echo data after the n dimensional vector n of N × 1 x ' expression phasing；N × N-dimensional matrix Ψ indicates ionosphere phase school
Positive matrices, and phase calibration is in the diagonal positions of matrix.When the CNR at the peak Bragg is larger, influence of the noise to PGA can
To ignore, to accurately calculate phase errorn, and when the CNR at the peak Bragg is smaller, influence of the noise to PGA can not
Ignore, phase errornIt can not accurately calculate, and then clutter spectral peak is caused to extend, noise floor is raised.Therefore, it is asked for above-mentioned
Topic proposes adaptive magnitude threshold T, searches the peak the Bragg lesser position CNR (the i.e. lesser position of Bragg peak amplitude in s (n)
Set), wherein adaptive magnitude threshold T=meanamη, meanamThe mean value of s (n) amplitude of expression, η expression meet a certain specific mistake
Difference and the scale factor (being usually arranged as 0.6) set.
Step 3: the data y after being rejected according to formula (6) and adaptive magnitude threshold T.
Data Position of the amplitude lower than adaptive magnitude threshold T will be recorded in s (n), and by the number of this position in x '
According to rejecting, the data after rejecting are represented by
Y=Fx '=F Ψ x (6)
Wherein y is M × 1 (M < N) n dimensional vector n, indicates the remaining data for rejecting the middle amplitude smaller portions of x '；F indicates M × N
Dimension rejects matrix, is to extract M row by row from N × N-dimensional diagonal matrix, the line number of extraction is opposite with data point is not rejected in x '
It answers.X=Φ θ can be obtained by carrying out FFT to xx, wherein Φ indicates that N × N-dimensional IFFT matrix, i.e. Φ=IFFT [I], I indicate N × N-dimensional pair
Angular moment battle array, θxIndicate that N × 1 ties up the spectral vector of x.
Step 4: data y being reconstructed according to formula (7) and formula (8), obtains the calculated value θ of reconstruct data spectrum
′y。
CS theory shows when some condition is fulfilled, by solving l1Norm optimization problem, can be by unknown sparse letter
It number is accurately recovered from the data of limited quantity.After the phase perturbation correction of ionosphere, the peak Bragg, land clutter and target
Sparse form is shown as in the entire frequency spectrum of y.Therefore, y is sparse in Doppler domain, and then meets CS theory to recovery number
According in some domain can rarefaction representation requirement, formula (6) is rewritable to be
Y=F Φ θy (7)
Wherein F and Φ respectively indicates M × N (M < N) dimension perception matrix (rejecting matrix) and N × N-dimensional basis matrix (IFFT
Matrix)；θyComplete Doppler frequency spectrum is indicated, including sea/land clutter, target and noise.Sparse signal U-shaped for one
(a special aobvious point number U meets U < < N i.e. in frequency spectrum), if dictionary matrix Θ=F Φ meet limited equidistant characteristics (RIP) and M >=
Ο (UlogN), by solving following convex problem, θyCan from finite data y precise restoration
min(||θ′y||1),subject to||Θθ′y-y||2≤τ (8)
Wherein θ 'yIndicate θyCalculated value；||·||pIt indicates to calculate lpNorm；Minimum value is sought in min () expression.Perception
Matrix F and basis matrix Φ are respectively to reject matrix and IFFT matrix.Any two column usually in perception matrix F and basis matrix Φ
Between correlation it is smaller, therefore dictionary matrix Θ meet RIP requirement.τ indicates that radar noise substrate, this value can only be received in radar
It is accurately calculated when noise.It follows that CS algorithm primary condition has met, data spectrum can be reconstructed by CS algorithm.
Embodiment 1
Using the validity of ground wave OTHR measured data verifying this patent algorithm, wherein ground wave OTHR is returned
Wave number includes sea, land clutter and target in.Emission signal frequency is 7.5MHz, emits signal period Δ t=0.7264, individually
Umber of pulse in CIT is N=128, and scale factor η=0.6 when thresholding selects, phase pollutes function of εn=1.2exp (0.01n
Δt)sin(0.15nΔt)。
In conjunction with Fig. 3, sea/land clutter spectral contrast result such as Fig. 3 a of ionosphere phase pollution front and back) shown in, wherein solid line
Indicate that the sea/land clutter frequency spectrum for being not added with the pollution of ionosphere phase, corresponding dotted line indicate that addition ionosphere phase is dirty
Sea/land clutter frequency spectrum after dye, land clutter frequency spectrum is near zero-frequency, and the peak sea clutter Bragg is respectively in the position ± 0.3Hz, target
In the position -0.6Hz.Fig. 3 a) display phase pollution can lead to sea/land clutter and target spectral peak broadening, radar noise substrate from
60dB is lifted to 70dB, and then leads to the reduction of SOTHR target detection performance.In Fig. 3 b), solid line expression is filtered by sliding window band logical
Wave device filters out the time domain waveform at the stronger peak Bragg, and dotted line indicates adaptive threshold value T, illustrates the peak Bragg lower than this threshold value
CNR is lower.Comparison result such as Fig. 3 c between the instantaneous pollution phase that PGA is calculated and true value) shown in, start bit is shown in figure
The difference set between the calculated value and true value in middle position is larger, and such situation is consistent with position below thresholding in Fig. 3 b),
Therefore illustrate that adaptive threshold can determine BraggThe lower position CNR in peak, and then reject the echo data of this position.Figure
3d) it is PGA algorithm and the echo-signal frequency spectrum after improvement PGA algorithm solution pollution, shows PGA algorithm in figure and improve PGA algorithm
The pollution of ionosphere phase can be corrected, but the solution pollutant performance for improving PGA algorithm is better than PGA algorithm, echo-signal frequency spectrum
Make an uproar bottom of making an uproar (70dB) the about 10dB of bottom (60dB) lower than PGA algorithm solution pollution back echo signal spectrum, with pollution pre-echo signal
Frequency spectrum bottom (60dB) of making an uproar is consistent.This is because the lower position CNR in the peak Bragg, the calculated phase of PGA algorithm is dirty
Dye inaccuracy thereby reduces it and solves phase pollutant performance, and improves PGA algorithm and the above problem is not present, and is answered the door using adaptive
Limit finds the lower position CNR in the peak Bragg, and is rejected, and is restored using CS algorithm by data are rejected well, is increased with this
It is strong to understand phase pollution capacity, to effectively improve SOTHR target detection performance.
This project is not suitable for ionosphere phase perturbation correction problem under the conditions of low CNR for PGA algorithm, has carried out algorithm
Research proposes and improves PGA algorithm, breaches the limitation of the high miscellaneous noise ratio scope of application.Added using actual measurement higher-frequency radar data
The mode of applying aspect pollution verifies the validity for improving PGA algorithm, and simulation result shows that improving PGA algorithm can effectively mention
The peak sea clutter Bragg is taken, accurately detection, rejecting and the position for repairing low CNR in echo-signal, compared with PGA algorithm, radar
After the improved PGA algorithm ionosphere corrections of echo-signal, radar noise substrate reduces about 10dB, with the thunder that phase pollution is not added
It is consistent up to echo-signal noise floor.
Claims (1)
1. a kind of based on the ionosphere phase perturbation correction algorithm for improving PGA, which is characterized in that method and step is as follows:
Step 1: extracting the peak sea clutter Bragg that energy is strong in echo-signal using sliding window bandpass filter, obtain the peak Bragg
Time domain data s (n) calculates the peak the Bragg frequency f according to radar transmitter frequencyb, to moving s (n) to zero-frequency, calculate
Phase error outn；
Step 2: echo data phase is corrected according to formula (5), and calculates adaptive magnitude threshold T:
X '=Ψ x (5)
Wherein, in a CIT, the echo data of a certain range-azimuth resolution cell is used N by after the pollution of ionosphere phase
The vector x of × 1 dimension is indicated；Echo data after the n dimensional vector n x ' expression phasing of N × 1；N × N-dimensional matrix Ψ indicates ionosphere
Phasing matrix, and phase calibration is in the diagonal positions of matrix；
Adaptive magnitude threshold T=meanamη, meanamThe mean value of s (n) amplitude of expression, η expression meet a certain certain errors value and
The scale factor of setting, is set as 0.6；
Step 3: according to formula (6) and adaptive magnitude threshold T, data y after being rejected, steps are as follows:
Data Position of the amplitude lower than adaptive magnitude threshold T will be recorded in s (n), and pick the data of this position in x '
It removes, the data y after rejecting is expressed as
Y=Fx '=F Ψ x (6)
Wherein y indicates the n dimensional vector n of M × 1, wherein M < N, indicates to reject the remaining data that the middle amplitude of x ' is less than T；F indicates that M × N-dimensional is picked
It is to extract M row by row from N × N-dimensional diagonal matrix Ψ, the line number of extraction is corresponding with data point is not rejected in x ' except matrix；
Step 4: the data y after rejecting being reconstructed according to formula (7) and formula (8), obtains the calculating of reconstruct data spectrum
Value θ 'y, steps are as follows:
Y=F Φ θy (7)
Wherein F indicates that M × N-dimensional rejects matrix, and Φ indicates that N × N-dimensional IFFT matrix, i.e. Φ=IFFT [I], I indicate N × N-dimensional pair
Angular moment battle array；θyComplete Doppler frequency spectrum is indicated, including sea/land clutter, target and noise；Sparse letter U-shaped for one
Number, if special aobvious point number U meets U<limited equidistant characteristics of<N dictionary matrix Θ=F Φ satisfaction and M>=O that is, in frequency spectrum
(UlogN), by solving following convex problem, θyThe precise restoration from the finite data y after rejecting
min(||θ′y||1),subject to||Θθ′y-y||2≤τ (8)
Wherein θ 'yIndicate θyCalculated value；||·||pIt indicates to calculate lpNorm, p=1,2；Minimum value, τ are sought in min () expression
Indicate radar noise substrate.
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| CN112824927B (en) * | 2019-11-20 | 2022-10-28 | 中国人民解放军空军预警学院 | Sky wave over-the-horizon radar ionospheric phase pollution correction method based on sparse filtering |
| CN112130138B (en) * | 2020-07-06 | 2022-10-14 | 电子科技大学 | Ionized layer phase pollution correction method for over-the-horizon radar |
| CN112014813B (en) * | 2020-09-03 | 2024-01-02 | 中国人民解放军海军航空大学 | Method and system for correcting ionosphere pollution of sky wave radar |
| CN112272066B (en) * | 2020-09-15 | 2022-08-26 | 中国民用航空飞行学院 | Frequency spectrum data cleaning method used in airport terminal area very high frequency communication |
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