CN110488227A - Sourceless seism suppressing method under complex environment based on cognition radar waveform design - Google Patents
Sourceless seism suppressing method under complex environment based on cognition radar waveform design Download PDFInfo
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- CN110488227A CN110488227A CN201910892894.2A CN201910892894A CN110488227A CN 110488227 A CN110488227 A CN 110488227A CN 201910892894 A CN201910892894 A CN 201910892894A CN 110488227 A CN110488227 A CN 110488227A
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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
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/0209—Systems with very large relative bandwidth, i.e. larger than 10 %, e.g. baseband, pulse, carrier-free, ultrawideband
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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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Abstract
The present invention provide it is a kind of based on cognition radar waveform design complex environment under sourceless seism suppressing method, include following procedure: determine radar emission receipt signal model；Determine the response prior information of target, clutter, sourceless seism and noise；It determines detector and obtains detector performance；Waveform Design is carried out according to bandwidth, emitted energy, calculates transmitting signal frequency domain Energy distribution；The signal frequency domain energy spectrum of acquisition is for emitting signal.The present invention passes through the Waveform Design towards clutter and sourceless seism confrontation, it being capable of the prior information based on clutter and sourceless seism, the Energy distribution mode towards AF panel is designed in ultra wide band frequency domain, to inhibit disturbance response, target acquisition recognition capability of the radar under complicated environmental condition is improved.
Description
Technical field
The present invention relates to radar waveforms to design anti-interference field, and in particular to a kind of answering based on cognition radar waveform design
Sourceless seism suppressing method under heterocycle border.
Background technique
The complex electromagnetic environment that radar faces mainly from radar by various interference environments influenced.These interference are main
It is made of natural environment interference and human interference, wherein natural environment interference mainly includes land clutter, sea clutter, cloud and mist sleet gas
As interference etc., human interference mainly includes artificial sourceless seism and artificial active interference, wherein artificial sourceless seism mainly includes
Chaff, corner reflector, passive decoy etc..Currently, Anti-jamming Ability for Radar is weak under complex electromagnetic environment, Electro Magnetic Compatibility is poor,
The outstanding problems such as skill performance of fighting decline, it has also become restrict one of radar performance performance and the bottleneck promoted.Wherein, anti-ly, sea it is miscellaneous
Wave and various sourceless seisms are an important rings for Anti-jamming Ability for Radar.
Existing phased array system, pulse Doppler radar pass through space-time adaptive processing, doppler processing, micro- how general
The signal processing modes such as Le processing carry out clutter reduction；To improve next pair of the methods of radar resolution, polarization identification, doppler filtering
Anti- sourceless seism.Although these processing techniques improve the energy that radar clutter inhibits and sourceless seism is fought to a certain extent
Power, but current radar is usually according to preset mode of operation, when practical application, faces clutter, interference spectrum characteristic becomes
The severe challenge for changing the problems such as indefinite, can not play maximum ability, this is for increasingly complicated clutter, more sourceless seism conditions
Under target detection cause very big difficulty.
Patent CN106443595A (a kind of cognition radar waveform design method of anti-instantaneous forwarding slice reconstruct interference) is mentioned
A kind of cognition radar waveform design method of anti-instantaneous forwarding slice reconstruct interference out, the priori obtained using cognition radar
Information therefrom extracts the relevant parameter of slice reconstruct interference, improves the signal interference ratio near real goal, reaching real goal just
The purpose really detected.What this method considered is slice reconstruct interference signal, for sourceless seism signal and is not suitable for.
Patent CN107102300A (the cognition radar waveform design method inhibited based on interference and secondary lobe equilibrium) is disclosed
A kind of cognition radar waveform design method inhibited based on interference and secondary lobe equilibrium, on the basis of adaptive framework, compacting noise
In interference model, the cognition radar waveform Optimized model of interference inhibition balanced with secondary lobe is introduced and constructed.What it fought is active
Compacting interference in interference, can not fight sourceless seism and clutter.
Patent CN104267379A (a kind of active radar and passive radar collaboration anti-interference method based on Waveform Design) uses main quilt
Dynamic radar cooperative work mode detects interference and is identified using the echo information of passive radar detecting real-time, and estimates
The relevant parameter of interference, the interference information that Active Radar utilizes passive radar to provide, designs optimal transmitted waveform, and to echo
Information is handled.It does not use corresponding interference and clutter prior information, and is not to carry out Waveform Design for sourceless seism.
Article [1] " the intelligent chaff countermeasure system based on interference cognition ", electronic information countermeasure techniques, 2018-
11-15. Wang Xin, Qin Kun, Qin Yiwei study the counter-measure strategy dispatching technique based on game theory, propose one kind
Interfere the appraisal procedure and a kind of intelligent chaff countermeasure system of countermeasure effectiveness.
Article [2] " the adaptive waveform design method under clutter environment towards extension target detection " Tsinghua University's journal:
Natural science edition 51.11 (2011): 1742-1746. public affairs threads China proposes under a kind of clutter environment towards extension target detection
Adaptive waveform design method.
Article [3] " a kind of cognition waveform design method of anti-velocity gate deception interference ", radar science and technology, 2015-04-
15. Wu Jian, Cui Guolong, hole enable and saying, for the ability for improving the anti-velocity gate deception interference of radar, guarantee radar to real goal Doppler
Correct detection, propose a kind of inter-pulsed phase-coded waveform design method.
Article [4] " the retransmitted jamming cognitive algorithm based on transform domain time-frequency slice ", electric wave science journal, 2014-04-
15, Wang Feng, Lei Zhiyong, Chen Qing, for the radar for using linear FM signal, propose based on Fourier Transform of Fractional Order with it is short
When Fourier transformation slice Differential Characteristics extraction algorithm, the detection and identification of intensive repeating jamming can be efficiently accomplished.These
Article from different perspectives, different purpose radar waveform is designed, but its either active interference for being related to, or special
Determine sourceless seism, not according to prior information, row Waveform Design is integrally taken into account to clutter, sourceless seism.
Summary of the invention
The present invention provide it is a kind of based on cognition radar waveform design complex environment under sourceless seism suppressing method, pass through face
The Waveform Design fought to clutter and sourceless seism, can the prior information based on clutter and sourceless seism, in ultra wide band frequency domain
Interior Energy distribution mode of the design towards AF panel improves radar under complicated environmental condition to inhibit disturbance response
Target acquisition recognition capability.
In order to achieve the above object, the technical solution of the present invention is to provide a kind of complexity based on cognition radar waveform design
Sourceless seism suppressing method under environment, it includes following procedure:
Step 1, radar emission receipt signal model is determined；
Step 2, the response prior information of target, clutter, sourceless seism and noise is determined；
Step 3, it determines detector and obtains detector performance；
Step 4, Waveform Design is carried out according to bandwidth, emitted energy, calculates transmitting signal frequency domain Energy distribution；
Step 5, the signal frequency domain energy spectrum of acquisition is for emitting signal.
In step 1, the signal that radar emission goes out is s (t), has motivated target, sourceless seism and clutter and has returned to reception
Machine, echo have been mixed into noise signal in receiver end；
The signal y (t) received is expressed as
Wherein,Represent convolution algorithm, h (t), c (t), j (t) be respectively the response of target, the response of clutter, passive
Disturbance response, Fourier transformation are respectively Ht(f)、Hc(f) and Hj(f)；N (t) is white Gauss noise, Fourier transformation N
(f)。
In step 2, the response model of clutter, interference and noise is determined；
The frequency-region signal of clutter is expressed asThe power spectral density P of clutterc(f),
Indicate multiple Gauss distribution；
The frequency-region signal of interference is expressed asThe power spectral density P of interferencej(f)；
The frequency-region signal of noise is expressed asThe power spectral density of noise is Pn(f)。
In step 3, detector is determined according to Neyman-Pearson criterion:
X (Y)=YHΓ-1T
Wherein, T, C, J, N are respectively target response, clutter response, disturbance response, noise response；Y=[Y
(F-M/2),...,Y(FM/2)]；Γ is the covariance matrix of C+J+N, and Γ is pair of horns matrix, diagonal element [Γ]mm=Pc
(Fm)+Pn(Fm)；Sample frequency Fm=m/T, m=-M/2 ..., M/2.
In step 3, the detection performance of detector X () is with biasing coefficient d2Monotone increasing；
Bias coefficient d2Are as follows:
Wherein, H0The case where to be free of clutter and interference in scene；H1The case where to include clutter and interference in echo；H0
And H1In the case of detector square:
E(X；H0)=0
E(X；H1)=E [YHΓ-1T]=THΓ-1T
In step 3, as X (Y) > γ, detector is judged to H1；
Calculate PFAAnd PD:
Wherein, Pr { } indicates probability distribution；γ is threshold value；
Q () is right tail probabilities function, is defined as
In step 4, the process of optimum waveform design includes:
Selection transmitting signal S (f), under conditions of emitting gross energy limitation:
So that d2It is maximum；Wherein E is signal single emission gross energy.
In step 4, if ε (f)=| S (f) |2For the power spectral density function for emitting signal；By lagrange's method of multipliers institute
, so that biasing coefficient d2Maximum transmitting signal energy spectrum density is expressed as
Wherein max (x, 0) is that biggish one is selected in x and 0；Parameter lambda determines by total signal emitted energy E, i.e.,
By
To determine λ.
The present invention is based on ultra wideband radar system, is recognized using interference and waveform generation technique is recognized based on etection theory,
Realize the sourceless seisms active suppression such as anti-to ground and sea clutter, chaff, angle.Cognitive techniques are introduced, priori knowledge library is based on, using super
The technological means such as identification, actively perceive are passively scouted in broadband, realize interference cognition；It is raw using the cognition waveform based on etection theory
At technology, interference active suppression is realized.
Detailed description of the invention
Fig. 1 is radar schematic diagram of a scenario.
Fig. 2 is radar emission receipt signal model figure.
Fig. 3 is the flow chart of the method for the present invention.
Fig. 4 is clutter PSD and interference PSD schematic diagram.
Fig. 5 is Optimal Signals energy spectrum schematic diagram.
Fig. 6 is the present invention relative to the linear FM signal routinely emitted, believes the schematic diagram that miscellaneous noise ratio improves.
Specific embodiment
As shown in figure 3, the present invention provide it is a kind of based on cognition radar waveform design complex environment under sourceless seism inhibit
Method comprising the steps of:
Step 1, radar emission receipt signal model is determined.The signal that radar emission goes out is s (t), has motivated target, passive
Interference and clutter simultaneously return to receiver, and echo has been mixed into noise signal in receiver end, as shown in Figure 2.The signal y received
(t) it can be expressed as
WhereinRepresent convolution algorithm, h (t), c (t), j (t) is respectively the response of target, the response of clutter, passive dry
Response is disturbed, Fourier transformation is respectively Ht(f)、Hc(f) and Hj(f).N (t) is white Gauss noise, Fourier transformation N
(f)。
Step 2, the response model of signal, clutter, interference and noise is determined.Assuming that the response c (t) of clutter is extended stationary
(Wide Sense Stationary, WSS) Gaussian random process simultaneously has zero-mean, power spectral density (Power
Spectrum Density, PSD) it is Pc(f), i.e.,WhereinIndicate multiple Gauss distribution.
Similarly, the PSD of interference:The frequency-region signal of noise can be expressed asWherein PnIt (f) is the PSD of noise signal.
Step 3, detector (NP detector) is determined according to Neyman-Pearson criterion and obtains detector performance.NP detection
Device can indicate are as follows:
H0:
H1:
Wherein H0The case where to be free of clutter and interference in scene；H1The case where to include clutter and interference in echo.Its frequency
Domain form NP detector can be written as:
H0: Y (f)=S (f) Hc(f)+N(f)
H1: Y (f)=S (f) Ht(f)+S(f)Hc(f)+S(f)Hj(f)+N(f)
According to frequency domain snapshot model, for WT >=16 time-bandwidth product (Time-Bandwidth Product, TBP), I
Can be with sample frequency FmIt is sampled, wherein Fm=m/T, m=-M/2 ..., M/2.By Fourier transformation and adopt
After sample, the vector model of our available (M+1) length.It is as follows to rewrite vector hypothesis testing:
H0:
H1:
Wherein, T, C, J are respectively target response, clutter response, disturbance response.
Y=[Y (F-M/2),...,Y(FM/2)], it can similarly obtain T, C, J and N.Γ is the covariance matrix of C+J+N.Above formula
Probability density function (Probability Density Function, PDF) can be written as:
Its log-likelihood ratio are as follows:
Constant term is neglected, we can obtain test statistics are as follows:
X (Y)=YHΓ-1T
Wherein Γ is diagonal matrix, diagonal element [Γ]mm=Pc(Fm)+Pn(Fm)。
Neyman-Pearson theorem are as follows: the P given for oneFA=α, so that PDMaximum judgement are as follows:
Wherein threshold value γ is by PFA=∫{ x:L (x) > γ }P(x；H0) dx=α finds out.Function L (x) is known as likelihood ratio, it is described
For each x value, H1Possibility and H0The ratio of possibility.
In the present invention, as X (Y) > γ, detector is judged to H1.P is calculated belowFAAnd PD:
Wherein Pr { } is the abbreviation of probability distribution (Probability)；Q () is right tail probabilities (Right-tail
Probability) function is defined asDefinition biasing coefficient d2Are as follows:
Then detection probability PDIt can indicate are as follows:
From the above equation, we can see that the detection performance of detector X () and biasing coefficient d2It is related.In order to calculate d2, first find out in H1
And H0In the case of detector square:
E(X；H0)=0
E(X；H1)=E [YHΓ-1T]=THΓ-1T
var(X；H0)=var (X；H1)
=E { [YHΓ-1T]2}
=THΓ-1T
Then bias coefficient d2Are as follows:
By being analyzed above it is found that the detection performance of detector X () is with d2Monotone increasing.
Step 4, Waveform Design is carried out according to conditional parameter, such as transmitting signal is calculated according to bandwidth, emitted energy parameter
Frequency domain energy distribution.Optimum waveform design problem is reduced to selection transmitting signal S (f), under conditions of emitting gross energy limitation:
So that d2It is maximum.Wherein E is signal single emission gross energy.
If ε (f)=| S (f) |2For energy spectral density (ESD) function for emitting signal.Obtained by lagrange's method of multipliers,
So that biasing coefficient d2Maximum transmitting signal ESD can be expressed as
Wherein max (x, 0) is that biggish one is selected in x and 0.Parameter lambda determines by total signal emitted energy E, i.e.,
By
To determine λ.
Step 5, it is used for the signal frequency domain energy spectrum of acquisition to emit signal.
A specific embodiment presented below:
Determine radar emission receipt signal model.Radar emission go out signal be s (t), motivated target, sourceless seism with
And clutter and receiver being returned to, echo has been mixed into noise signal in receiver end, as shown in Figure 2.The signal y (t) received can
To be expressed as
WhereinRepresent convolution algorithm, h (t), c (t), j (t) is respectively the response of target, the response of clutter, passive dry
Disturb response.
Determine the response prior information of signal, clutter, interference and noise.In the present example it is assumed that target response is composed | Ht(f)|2
=1 × 10-4W/Hz is constant, noise Pn(f)=1 × 10-3W/Hz is constant, and clutter spectrum Pc(f), disturbance spectrum Pj(f) in frequency
Domain response is different, and clutter spectrum, disturbance spectrum such as following formula indicate.Its figure is as shown in Figure 4.
Determine transmission signal parameters.In this example, emission peak energy is 10W, bandwidth 300MHz.Emit the energy of signal
Spectrum density ε (f)=| S (f) |2It can indicate are as follows:
Wherein max (x, 0) is that biggish one is selected in x and 0.Parameter lambda determines by total signal emitted energy E, i.e.,
By
To determine λ.The energy spectral density for emitting signal is as shown in Figure 5.Relative to the linear FM signal routinely emitted,
Letter miscellaneous noise ratio improves about 6.7dB, as shown in Figure 6.
It is discussed in detail although the contents of the present invention have passed through above preferred embodiment, but it should be appreciated that above-mentioned
Description is not considered as limitation of the present invention.After those skilled in the art have read above content, for of the invention
A variety of modifications and substitutions all will be apparent.Therefore, protection scope of the present invention should be limited to the appended claims.
Claims (8)
1. it is a kind of based on cognition radar waveform design complex environment under sourceless seism suppressing method, which is characterized in that comprising with
Lower process:
Step 1, radar emission receipt signal model is determined；
Step 2, the response prior information of target, clutter, sourceless seism and noise is determined；
Step 3, it determines detector and obtains detector performance；
Step 4, Waveform Design is carried out according to bandwidth, emitted energy, calculates transmitting signal frequency domain Energy distribution；
Step 5, the signal frequency domain energy spectrum of acquisition is for emitting signal.
2. sourceless seism suppressing method as described in claim 1, which is characterized in that
In step 1, the signal that radar emission goes out is s (t), has motivated target, sourceless seism and clutter and has returned to receiver, is returned
Wave has been mixed into noise signal in receiver end；
The signal y (t) received is expressed as
Wherein,Convolution algorithm is represented, h (t), c (t), j (t) are respectively the response of target, the response of clutter, sourceless seism
Response, Fourier transformation is respectively Ht(f)、Hc(f) and Hj(f)；N (t) is white Gauss noise, and Fourier transformation is N (f).
3. sourceless seism suppressing method as claimed in claim 2, which is characterized in that
In step 2, the response model of clutter, interference and noise is determined；
The frequency-region signal of clutter is expressed as Hc(f)~CN (0, Pc(f)), the power spectral density P of clutterc(f), CN indicates multiple Gauss
Distribution；
The frequency-region signal of interference is expressed as Hj(f)~CN (0, Pj(f)), the power spectral density P of interferencej(f)；
The frequency-region signal of noise is expressed as N (f)~CN (0, Pn(f)), the power spectral density of noise is Pn(f)。
4. sourceless seism suppressing method as claimed in claim 3, which is characterized in that
In step 3, detector is determined according to Neyman-Pearson criterion:
X (Y)=YHΓ-1T
Wherein, T, C, J, N are respectively target response, clutter response, disturbance response, noise response；Y=[Y (F-M/2),...,Y
(FM/2)]；Γ is the covariance matrix of C+J+N, and Γ is pair of horns matrix, diagonal element [Γ]mm=Pc(Fm)+Pn(Fm)；It adopts
Sample frequency Fm=m/T, m=-M/2 ..., M/2.
5. sourceless seism suppressing method as claimed in claim 4, which is characterized in that
In step 3, the detection performance of detector X () is with biasing coefficient d2Monotone increasing；
Bias coefficient d2Are as follows:
Wherein, H0The case where to be free of clutter and interference in scene；H1The case where to include clutter and interference in echo；H1And H0Feelings
The square of detector under condition:
E(X；H0)=0
E(X；H1)=E [YHΓ-1T]=THΓ-1T
6. sourceless seism suppressing method as claimed in claim 5, which is characterized in that
In step 3, as X (Y) > γ, detector is judged to H1；
Calculate PFAAnd PD:
Wherein, Pr { } indicates probability distribution；γ is threshold value；
Q () is right tail probabilities function, is defined as
7. sourceless seism suppressing method as claimed in claim 5, which is characterized in that
In step 4, the process of optimum waveform design includes:
Selection transmitting signal S (f), under conditions of emitting gross energy limitation:
So that d2It is maximum；Wherein E is signal single emission gross energy.
8. sourceless seism suppressing method as claimed in claim 7, which is characterized in that
In step 4, if ε (f)=| S (f) |2For the power spectral density function for emitting signal；Obtained by lagrange's method of multipliers, make
Coefficient d must be biased2Maximum transmitting signal energy spectrum density is expressed as
Wherein max (x, 0) is that biggish one is selected in x and 0；Parameter lambda determines by total signal emitted energy E, i.e., by
To determine λ.
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| CN113238194A (en) * | 2021-07-13 | 2021-08-10 | 中国人民解放军火箭军工程大学 | Broadband phased array radar anti-decoy interference method based on fractional domain-frequency domain processing |
| CN113238194B (en) * | 2021-07-13 | 2021-10-08 | 中国人民解放军火箭军工程大学 | Broadband phased array radar anti-decoy interference method based on fractional domain-frequency domain processing |
| CN114137483A (en) * | 2021-11-03 | 2022-03-04 | 广州辰创科技发展有限公司 | Adaptive interference suppression method and medium for one-dimensional phase-scanning radar and one-dimensional phase-scanning radar |
| CN114594425A (en) * | 2022-03-14 | 2022-06-07 | 电子科技大学 | Clutter interference resistant short-time pulse train waveform design method |
| CN114594425B (en) * | 2022-03-14 | 2023-05-16 | 电子科技大学 | Short-time pulse train waveform design method for resisting clutter interference |
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