CN110412514A - A kind of linear frequency modulation continuous wave waveform optimization method under MIMO system - Google Patents
A kind of linear frequency modulation continuous wave waveform optimization method under MIMO system Download PDFInfo
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- CN110412514A CN110412514A CN201910711214.2A CN201910711214A CN110412514A CN 110412514 A CN110412514 A CN 110412514A CN 201910711214 A CN201910711214 A CN 201910711214A CN 110412514 A CN110412514 A CN 110412514A
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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
- G01S13/91—Radar or analogous systems specially adapted for specific applications for traffic control
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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
- G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays
-
- 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
- G01S7/295—Means for transforming co-ordinates or for evaluating data, e.g. using computers
-
- 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
Abstract
The invention discloses a kind of linear frequency modulation continuous wave waveform optimization methods under MIMO system, the present invention is first on the basis of emitting linear frequency modulation continuous wave, a random phase is added in each pulse for issuing waveform to each transmitting terminal, separate transmitted waveform in Doppler's dimension, secondly waveform is optimized as evaluation index using main lobe gain, main-side lobe ratio, main lobe width of waveform etc., the phase sequence that evaluation index of sening as an envoy to is optimal is calculated by pattern search method, it is updated in transmitted waveform, completes optimization.The object of the present invention is to provide it is a kind of with preferable interference free performance, uniform system gain, preferable main-side lobe ratio, lesser main lobe width waveform；The invention proposes a kind of new radar waveform design and optimization methods based on application feature, so that the radar waveform designed, which has, preferably applies index.
Description
Technical field
The invention discloses a kind of linear frequency modulation continuous wave waveform optimization methods under MIMO system, are related to traffic radar letter
Number processing technology field.
Background technique
The key factor of MIMO radar operation is that multiple orthogonal waveforms can use simultaneously.LFMCW signal is applied to more
The design of kind orthogonal waveforms, corresponding design method have also obtained extensive research.
The most straightforward procedure for obtaining orthogonal waveforms is time division multiple acess (TDMA), but is not suitable for the side of high operation requirements PRF
Case；Doppler's multiple access (DDMA) MIMO waveform can be only applied to Low-frequency radar (for example, HF radar) or the thunder for short distance detection
It reaches.The present invention is based on the shortcomings of the above waveform design method, using CDMA (CDMA) MIMO waveform design method.
Since the measurement accuracy of CDMA waveform design method is limited, it is therefore desirable to carried out on the basis of original waveform it is excellent
Change.Main pass through constructs suitable cost function, and optimal signal waveform is obtained using suitable optimization algorithm.In construction generation
In terms of valence function, YANG Y is in document " MIMO radar waveform design basedon mutual information
The method that and minimum meansquare error estimation " utilizes information theory, by the mutual information of echo and
Minimum mean square error criterion optimizes waveform, and Jin Ming is mentioned in document " the class zero correlation polyphase code design based on genetic algorithm "
The concept in zero correlation region out, it is concerned about the secondary lobe in the region, ignores the secondary lobe outside region, so that closing on distance unit echo
Between interference effectively eliminated.
The present invention is using the ambiguity function of distance, speed, azimuth and the pitch angle four-dimension as Waveform Design criterion, comprehensive main lobe
The factors such as gain, main-side lobe ratio and main lobe width construct cost function.Ambiguity function can be used as simple target distance and speed
The precision and resolution ratio of degree assess scale, and how to be dependably distinguished multiple targets, ambiguity function according to the solution of these parameters
It is also the effective tool of radar signal Waveform Design.Which depict systems to use which type of transmitted waveform, what will have
The Potential performances such as resolving power, fuzziness, measurement accuracy and clutter suppression capability, therefore, the design of radar waveform can pass through
The optimization of its autoambiguity function is realized.
In terms of optimization algorithm, DENG H is in document " Polyphase code design for orthogonal
Netted radar systems " proposes to design Polyphase Orthogonal Code signal using simulated annealing, obtained it is relatively low from
Correlation side lobes, LIU B is at document " Polyphase orthogonal code design for MIMO radar systems "
Polyphase Orthogonal Code is designed with genetic algorithm, reduces the autocorrelation sidelobe peak and cross-correlation peak of transmitting signal, Wang Wei is in document
" the MIMO radar MIMO Radar Polyphase Code Design based on hybrid algorithm " is optimized with genetic tabu hybrid algorithm, by the auto-correlation made
Valve peak value and cross-correlation peak further decrease.
But current technology and optimization algorithm lack the optimization to application feature, cause unsatisfactory using characteristic effect.
Summary of the invention
The present invention provides the linear frequency modulation continuous wave waveform under a kind of MIMO system the defects of for above-mentioned background technique
Optimization method, the present invention optimize evaluation index using pattern search method, have obtained higher system gain, higher master
Minor lobe ratio, relatively narrow main lobe width.
To achieve the above object, The technical solution adopted by the invention is as follows: the linear frequency modulation under a kind of MIMO system is continuous
Wave waveform optimization method, which comprises the following steps:
Step 1: by MIMO radar to objective emission linear frequency modulation continuous wave, target is believed to MIMO radar back echo
Number；Random phase, the random phase are added in different transmitted waveforms between each pulse of the linear frequency modulation continuous wave
Constitute random phase matrix H；
Step 2: handling target echo signal, and each characteristic point in the target echo signal is one point
It distinguishes unit, multiple dimensional informations of resolution cell is obtained after echo signal processing, according to dimensional information, construction evaluation waveform superiority and inferiority
Evaluation index；
Step 3: according to evaluation index, cost function F is constructed, the cost function F is all resolution cell evaluation indexes
Weighted value；
Step 4: bound, the cycle-index of given random initial phase give one at random just in each circulation
It is worth phase, concurrently sets the termination condition of optimization, i.e. function maximum evaluation number, maximum number of iterations and termination tolerance etc.；
Retrieve random phase matrix H's when sening as an envoy to overall target cost function F acquirement minimum value by pattern search method
Respective value, and replaced into the random phase of step 1 transmitted waveform, the transmitted waveform after being optimized.
Further, in step 1, the matrix size of the random phase matrix is N*M；Wherein, N is MIMO radar
Transmitting antenna number, M be a transmitting antenna transmitted waveform umber of pulse；The signal that different transmitting antennas are sent is by not homology
The modulation of column quadrature phase codes, or modulated with rapid time or Slow time.
Further, in step 2, the method that constructs evaluation index specifically:
It extracts single dimensional information two-by-two from multiple dimensional informations and combines multiple two-dimensional signal waves that echo-signal is made
Shape fuzzy graph；
According to the basic index of target dimension information in multiple two-dimensional signal waveform fuzzy graphs, construction evaluates waveform superiority and inferiority
Evaluation index；The evaluation index is the weighted value of all dimensional information basic index corresponding index values of a resolution cell:
Fi=Fs+Fk+Ft
Wherein, FsFor the index value of main lobe gain；FkFor the weighted value of the index value of main-side lobe ratio；FtFor main lobe width
Index value, FiFor the evaluation index of i-th of resolution cell；
Wherein,
Fs=lsδs
δsFor the absolute value of the difference of main lobe gain measurements and theoretical value；
lsFor the flexible strategy of main lobe gain；
Fk=l1δ2+l2δ2+l3δ3+…+lkδk
δkFor the absolute value of the difference of k-th dimensional information main lobe width measured value and theoretical value；
lkFor the flexible strategy of k-th of dimensional information main lobe width；
Ft=ltδt
δtFor the absolute value of the difference of main-side lobe ratio minimum measured value and theoretical value；
ltFor the flexible strategy of main-side lobe ratio.
Further, in step 2, the dimensional information include: target with respect to the transmitting antenna of MIMO radar away from
From dimension, speed dimension, azimuth, pitch angle etc..
Further, in step 3, the cost function F is the weighted value of the evaluation index of all resolution cells；
Wherein, i is the number of resolution cell.
Further, in step 2, the basic index of the dimensional information includes main lobe width, main lobe gain and major-minor
Valve ratio.
Further, in step 4, pattern search method specifically: using random phase matrix H as independent variable, overall merit
Index F is dependent variable, the respective value of random phase matrix H when retrieving the minimum value for overall target cost function F acquirement of sening as an envoy to；
By pattern search method find a series of point X0, X1, X2 ..., these point be all increasingly closer to optimal value point, when search for into
Then by the last one solution of the point as this search, i.e. optimal stochastic phase sequence when row arrives termination condition, specifically include following
Step:
S1: initial random phasing matrix H is set0, step delta0> 0, the number of iterations k=0, ε > 0；
According to the direction of search of pattern search method, mode P is chosenkAny one column；
Pk=BCk
Wherein: B is basic matrix, is constant in every single-step iteration；
CkFor generator matrix, it is denoted as:
Ck=[Mk -Mk Lk]=[Γk Lk]
MkIt is the set for the n rank nonsingular square matrix being made of integer member, LkIt is arranged including at least a null vector,
Mode PkAfter the direction of search determines, exploration movement is carried out, for step deltakStep is soundd out in > 0, definition
Wherein:For CkI-th column；
S2: in kth iteration step, fromMiddle determination meets the step-length S of following two conditionk:
(1)Sk∈ΔkPk≡Δk[BΓk BLk]
(2) if min { F (Hk+y),y∈ΔkBΓk< F (Hk), then F (Hk+sk) < F (Hk)
It enables:
ρk=F (Hk)-F(Hk+sk)
S3: C is updatedk, Δk, k=k+1 turns S2；
S4: if ρk> 0, then Hk+1=Hk+Sk, otherwise Hk+1=Hk；
If Δk< ε and | | Sk| | < ε meets, then algorithm terminates；
Further, CkUpdate rule are as follows:
Ck=[Mk -Mk Lk]=[Γk Lk]
ΔkUpdate rule are as follows:
ω0< 0, ω1..., ωL≥0
If ρk≤ 0, then Δk+1=θ Δk, otherwise Δk+1=λ Δk。
By θ, the form of λ is it is found that 0 < θ < 1, λ >=1；Wherein θ is score and rational.
The utility model has the advantages that 1, using multidimensional fuzzy graph as design criteria, it is complete to extract main lobe gain, main-side lobe ratio, main lobe width etc.
The indication information in face, and effective optimization has all been carried out to all indication informations.
2, target points all in space are all optimized.
3, it is optimized using pattern search method, it is relatively simple compared to other optimization algorithms without carrying out derivative operation
It is easy.
Detailed description of the invention
The flow chart that Fig. 1 present invention realizes；
Fig. 2 waveform distance-velocity ambiguity functional arrangement；
Fig. 3 waveform distance-orientation angles ambiguity function figure；
Fig. 4 waveform speed-orientation angles ambiguity function figure；
Fig. 5 target range optimization front and back compares gain diagram；
Fig. 6 target velocity optimization front and back compares gain diagram；
The target bearing Fig. 7 angle optimization front and back compares gain diagram；
Specific embodiment
The implementation of technical solution is described in further detail with reference to the accompanying drawing.Following embodiment is only used for more clear
Illustrate to Chu technical solution of the present invention, and not intended to limit the protection scope of the present invention.
As shown in Figure 1, a kind of embodiment provided by the invention:
A kind of linear frequency modulation continuous wave waveform optimization method under MIMO system, comprising the following steps:
Step 1: by MIMO radar to objective emission linear frequency modulation continuous wave, target is believed to MIMO radar back echo
Number；Random phase, the random phase are added in different transmitted waveforms between each pulse of the linear frequency modulation continuous wave
Form the random phase matrix H of target；The matrix size of the random phase matrix H is N*M；Wherein, N is MIMO radar
Transmitting antenna number, M be a transmitting antenna transmitted waveform umber of pulse；The signal that different transmitting antennas are sent is by not homology
The modulation of column quadrature phase codes, or modulated with rapid time or Slow time.
Step 2: as shown in figs. 2 to 4, being handled target echo signal, each spy in the target echo signal
Sign point is a resolution cell, obtains the three of resolution cell and radar antenna relative distance, relative velocity and relative azimuth angle
Dimension data information, information extraction is gone out three two-dimensional data sets and is drawn with two-dimensional data sets corresponding from above-mentioned three-dimensional data
Fuzzy graph, the corresponding fuzzy graph of the 2-D data are distance-velocity ambiguity figure, range-azimuth direction ambiguity figure and speed-side
Parallactic angle degree fuzzy graph；
The present invention in other cases, can extract other dimensional informations, such as pitch angle, carry out waveform optimization；
As shown in Fig. 5~7, the distance of target, speed, azimuthal main lobe gain, main-side lobe ratio are extracted from fuzzy graph
The evaluation index of construction evaluation waveform superiority and inferiority is carried out with main lobe width, wherein main lobe gain is maxgain value, only one is total
Maximum gain, main-side lobe ratio is the difference of main lobe gain and maximum minor lobe gain, and main lobe width is that mainboard gain declines 3dB pairs
The transaxial width answered；The evaluation index is the weighting of all dimension multi information basic index corresponding index values of a resolution cell
Value:
Fi=lsδs+l1δ1+l2δ2+l3δ3+ltδt
Wherein, δsFor the absolute value of the difference of main lobe gain measurements and theoretical value, lsFor the flexible strategy of main lobe gain；
δ1For the absolute value of the difference of range dimension main lobe width measured value and theoretical value, l1For range dimension main lobe width
Flexible strategy；
δ2For the absolute value of the difference of speed dimension main lobe width measured value and theoretical value, l2For speed dimension main lobe width
Flexible strategy；
δ3For the absolute value of the difference of azimuth dimension main lobe width measured value and theoretical value, l3It is wide for azimuth dimension main lobe
The flexible strategy of degree；
δtFor the absolute value of the difference of minimum measured value and theoretical value in the main-side lobe ratio of each dimensional information, ltFor principal subsidiary lobe
The flexible strategy of ratio；
Step 3: according to evaluation index, cost function F is constructed, the cost function F is all resolution cell evaluation indexes
Weighted value:
Step 4: upper limit lb, lower limit ub, the cycle-index k of a given random initial phase give in each circulation
A fixed random initial value phase, concurrently sets the termination condition of optimization, i.e., function maximum evaluate number, maximum number of iterations and
Termination tolerance etc.；
Random phase matrix H when retrieving the minimum value for overall target cost function F acquirement of sening as an envoy to by pattern search method
Respective value, and replaced into the random phase of step 1 transmitted waveform, the transmitted waveform after being optimized.
The pattern search method principle: using random phase matrix H as independent variable, comprehensive evaluation index F is dependent variable, retrieval
The respective value of random phase matrix H when the minimum value that overall target of sening as an envoy to cost function F is obtained；One is found by pattern search method
The point X0, X1, X2 of series ..., these points are all increasingly closer to optimal value point, then will most when search proceeds to termination condition
The solution that the latter point is searched for as this, i.e. optimal stochastic phase sequence, specifically includes the following steps:
S1: initial random phasing matrix H is set0, step delta0> 0, the number of iterations k=0, ε > 0；
According to the direction of search of pattern search method, mode P is chosenkAny one column；
Pk=BCk
Wherein: B is basic matrix, is constant in every single-step iteration；
CkFor generator matrix, it is denoted as:
Ck=[Mk -Mk Lk]=[Γk Lk]
MkIt is the set for the n rank nonsingular square matrix being made of integer member, LkIt is arranged including at least a null vector,
Mode PkAfter the direction of search determines, exploration movement is carried out, for step deltakStep is soundd out in > 0, definition
Wherein:For CkI-th column；
S2: in kth iteration step, fromMiddle determination meets the step-length S of following two conditionk:
(1)Sk∈ΔkPk≡Δk[BΓk BLk]
(2) if min { F (Hk+y),y∈ΔkBΓk< F (Hk), then F (Hk+sk) < F (Hk)
It enables:
ρk=F (Hk)-F(Hk+sk)
S3: C is updatedk, Δk, k=k+1 turns S2；
S4: if ρk> 0, then Hk+1=Hk+Sk, otherwise Hk+1=Hk；
If Δk< ε and | | Sk| | < ε meets, then algorithm terminates；
Further, CkUpdate rule are as follows:
Ck=[Mk -Mk Lk]=[Γk Lk]
ΔkUpdate rule are as follows:
ω0< 0, ω1..., ωL≥0
If ρk≤ 0, then Δk+1=θ Δk, otherwise Δk+1=λ Δk。
By θ, the form of λ is it is found that 0 < θ < 1, λ >=1；Wherein θ is score and rational.
The present invention extracts main lobe gain, main-side lobe ratio, main lobe width etc. and comprehensively refers to using multidimensional fuzzy graph as design criteria
Information is marked, and effective optimization has all been carried out to all indication informations.
Target points all in space are optimized in the present invention.
The present invention is optimized using pattern search method, without carrying out derivative operation, more compared to other optimization algorithms
It is simple and easy.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, several improvement and deformations can also be made, these improvement and deformations
Also it should be regarded as protection scope of the present invention.
Claims (7)
1. a kind of linear frequency modulation continuous wave waveform optimization method under MIMO system, which comprises the following steps:
Step 1: by MIMO radar to objective emission linear frequency modulation continuous wave, target is to MIMO radar return echo signal；Institute
State and add random phase in the different transmitted waveforms between each pulse of linear frequency modulation continuous wave, the random phase constitute with
Machine phasing matrix H；
Step 2: handling target echo signal, and each characteristic point in the target echo signal is that a resolution is single
Member obtains multiple dimensional informations of resolution cell after echo signal processing, and according to dimensional information, construction evaluation waveform superiority and inferiority is commented
Valence index；
Step 3: according to evaluation index, cost function F is constructed, the cost function F is adding for all resolution cell evaluation indexes
Weight；
Step 4: random phase matrix H when retrieving the minimum value for overall target cost function F acquirement of sening as an envoy to by pattern search method
Respective value, and replaced into the random phase of step 1 transmitted waveform, the transmitted waveform after being optimized.
2. the linear frequency modulation continuous wave waveform optimization method under a kind of MIMO system according to claim 1, feature exist
In in step 1, the matrix size of the random phase matrix is N*M；Wherein, N is the transmitting antenna number of MIMO radar,
M is the umber of pulse of a transmitting antenna transmitted waveform.
3. the linear frequency modulation continuous wave waveform optimization method under a kind of MIMO system according to claim 1, feature exist
In, in step 2, the method that constructs evaluation index specifically:
It extracts single dimensional information two-by-two from multiple dimensional informations and combines multiple two-dimensional signal fluted moulds that echo-signal is made
Paste figure；
According to the basic index of target dimension information in multiple two-dimensional signal waveform fuzzy graphs, the evaluation of construction evaluation waveform superiority and inferiority
Index；The evaluation index is the weighted value of all dimensional information basic index corresponding index values of a resolution cell
Fi=Fs+Fk+Ft
Wherein, FsFor the index value of main lobe gain；FkFor the weighted value of the index value of main-side lobe ratio；FtFor the index of main lobe width
Value；FiFor the evaluation index of i-th of resolution cell；
Wherein,
Fs=lsδs
δsFor the absolute value of the difference of main lobe gain measurements and theoretical value；
lsFor the flexible strategy of main lobe gain；
Fk=l1δ2+l2δ2+l3δ3+…+lkδk
δkFor the absolute value of the difference of k-th dimensional information main lobe width measured value and theoretical value；
lkFor the flexible strategy of k-th of dimensional information main lobe width；
Ft=ltδt
δtFor the absolute value of the difference of main-side lobe ratio minimum measured value and theoretical value；
ltFor the flexible strategy of main-side lobe ratio.
4. the linear frequency modulation continuous wave waveform optimization method under a kind of MIMO system according to claim 1, feature exist
In in step 2, the dimensional information includes: distance dimension of the target with respect to the transmitting antenna of MIMO radar, speed dimension, orientation
Angle, pitch angle.
5. the linear frequency modulation continuous wave waveform optimization method under a kind of MIMO system according to claim 3, feature exist
In in step 3, the cost function F is the weighted value of the evaluation index of all resolution cells；
Wherein, i is the number of resolution cell.
6. the linear frequency modulation continuous wave waveform optimization method under a kind of MIMO system according to claim 3, feature exist
In in step 2, the basic index of the dimensional information includes main lobe width, main lobe gain and main-side lobe ratio.
7. the linear frequency modulation continuous wave waveform optimization method under a kind of MIMO system according to claim 1, feature exist
In, in step 4, pattern search method specifically: using random phase matrix H as independent variable, comprehensive evaluation index F is dependent variable, inspection
Rope send as an envoy to overall target cost function F acquirement minimum value when random phase matrix H respective value.
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| CN111308437A (en) * | 2020-02-27 | 2020-06-19 | 南京慧尔视智能科技有限公司 | Entropy-solving and speed-ambiguity-solving method for millimeter wave MIMO traffic radar |
| CN112578345A (en) * | 2020-11-20 | 2021-03-30 | 福瑞泰克智能系统有限公司 | Radar blocking detection method, device, equipment and storage medium |
| CN116256743A (en) * | 2023-05-16 | 2023-06-13 | 南京慧尔视智能科技有限公司 | Method and device for detecting moving object, electronic equipment and storage medium |
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| CN113204017B (en) * | 2021-03-16 | 2022-11-04 | 西安电子科技大学 | LFMCW-based MIMO radar signal processing method |
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| CN113325382B (en) * | 2021-05-26 | 2024-04-16 | 北京理工大学重庆创新中心 | DDMA MIMO radar speed disambiguation method based on global optimization phase modulation |
| CN115792822B (en) * | 2022-11-06 | 2023-09-05 | 中国人民解放军国防科技大学 | Radar embedded communication waveform design method for power exponent optimization water injection molding |
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| CN116256743B (en) * | 2023-05-16 | 2023-08-04 | 南京慧尔视智能科技有限公司 | Method and device for detecting moving object, electronic equipment and storage medium |
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| WO2021022683A1 (en) | 2021-02-11 |
| CN110412514B (en) | 2023-05-23 |
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