CN108983209A - Clutter suppression method based on symmetrical covariance matrix - Google Patents
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- CN108983209A CN108983209A CN201810383727.0A CN201810383727A CN108983209A CN 108983209 A CN108983209 A CN 108983209A CN 201810383727 A CN201810383727 A CN 201810383727A CN 108983209 A CN108983209 A CN 108983209A
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- G—PHYSICS
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- 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
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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
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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
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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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
- G01S2013/0236—Special technical features
- G01S2013/0245—Radar with phased array antenna
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Abstract
The invention discloses a kind of calculation method of the covariance matrix of clutter plus noise signal and based on the clutter suppression method of symmetrical covariance matrix, wherein, the calculation method of the covariance matrix of clutter plus noise signal carries out doppler filtering to the corresponding echo-signal of each rang ring respectively, the echo-signal after respectively obtaining the doppler filtering under multiple Doppler channels；It is chosen in multiple rang rings and is in the rang ring in set distance range as estimated distance ring with rang ring to be detected；Covariance estimation is carried out to the echo-signal after the doppler filtering under the corresponding same Doppler channel of all estimated distance rings of selection, obtains the preliminary covariance matrix under the Doppler channel；Based on obtained preliminary covariance matrix, clutter plus noise covariance matrix is calculated.Above-mentioned technical proposal reduces sample number used in estimated matrix, and calculation amount is smaller.
Description
Technical field
The invention belongs to airborne radar signal processing technology fields, are related to a kind of clutter based on symmetrical covariance matrix
Suppressing method.
Background technique
Sample covariance matrix (SCM) is the actual estimated amount for calculating clutter covariance matrix, however, in dimension STAP entirely
(f-STAP) in, SCM needs a large amount of training sample, this is unapproachable in actual airborne radar environment.In addition,
F-STAP needs carry out matrix inversion operation in self-adaptive processing, this calculating is considerably complicated.It there is now and keep phase with f-STAP
With performance and it can solve dimensionality reduction/degradation STAP algorithm of the above problem, wherein rear Doppler's self-adaptive processing method extends
Factor algorithm (EFA and mDT) will be most effective and practical one of space-time adaptive Processing Algorithm.
The basic principle of EFA (Extended factored approach) is by the adaptive filter of N × K dimension of f-STAP
Wave problem is converted to K independent P × N-dimensional self-adaptive processing problems, and wherein N is antenna number, and K is umber of pulse, and P is integer, and
P>1.Therefore, according to RMB criterion, (RMB criterion has determined the data of estimation clutter plus noise covariance matrix, and Uniform Sample is got over
More estimate covariance matrix is better, we using covariance matrix calculate STAP weight vector performance it is also better),
Required uniform training samples number can be reduced to 2PN.In addition, the calculation amount of EFA can be reduced, practical application can also be improved.
But if uniformly number of training is inadequate, especially in the onboard radar system of large-scale antenna array, it will substantially reduce
The clutter suppression capability of EFA.
In fact, the full symmetric property of modern clutter covariance matrix increases accurately miscellaneous typically as priori knowledge
Wave covariance matrix number of training.It is initially applied to communicate, and Tong et al. is by the characteristic application extension of its symmetry
Into Per-EFA, the results showed that, required training samples number is reduced.In the limited scene of training sample, Per-
EFA is verified as a kind of effective algorithm.However, there is no reductions for the calculating cost of the Per-EFA in self-adaptive processing, and
And a large amount of training sample is still needed in there is large-scale airspace freedom degree (DoF) biggish onboard radar system.
Summary of the invention
For above-mentioned problems of the prior art or defect, the object of the present invention is to provide one kind based on symmetrical
The clutter suppression method of covariance matrix, this method, which can reduce, calculates training sample in cost and rear Doppler's self-adaptive processing
The requirement of this number, and there is centainly superior in terms of large-scale antenna onboard radar system training sample convergence rate and calculating
Property.
To achieve the goals above, the present invention adopts the following technical scheme:
A kind of calculation method of the covariance matrix of clutter plus noise signal, comprising the following steps:
Step 1, airborne phased array radar antenna emits signal, and signal is scattered by the clutter in rang rings multiple on ground
Point reflection, airborne phased array radar antenna receive multiple echo-signal y；Echo-signal y includes noise signal z and noise letter
Number n；
Step 2, doppler filtering is carried out to each echo-signal y respectively, is respectively obtained more under multiple Doppler channels
It is general to strangle filtered echo-signal；
Step 3, it is chosen in multiple rang rings and is in the rang ring conduct in set distance range with rang ring to be detected
Estimated distance ring；
Step 4, the doppler filtering under the corresponding same Doppler channel of all estimated distance rings chosen to step 3
Echo-signal afterwards carries out covariance estimation, obtains the preliminary covariance matrix under the Doppler channel；
Step 5, the preliminary covariance matrix under each Doppler channel obtained based on step 4 is counted using formula (1)
Calculate the covariance matrix of the clutter plus noise signal under each Doppler channel:
Wherein, RkIt is the covariance matrix of the clutter plus noise signal under k-th of Doppler channel,It is that how general kth is
Strangle the preliminary covariance matrix under channel, BsIt is space conversion matrices, BtIt is time change matrix, BstIt is spatial-temporal transform matrix.
Optionally, the space conversion matrices in the step 5Time change matrixIt is empty
When transformation matrixWherein, IpRepresentation dimension is the unit matrix of p, p=3, INRepresentation dimension is the unit matrix of N；
Js=fliplr (IN), wherein fliplr () is the MATLAB operator of left and right directions flip matrix, and N is airborne radar
The bay number of radar antenna；
Wherein, diag () indicates diagonal matrix, fk-1,fk,fk+1It is normalization Doppler's frequency in three neighboring Doppler channels
Rate.
The present invention also provides a kind of clutter suppression methods based on symmetrical covariance matrix, comprising the following steps:
Step 1, airborne phased array radar antenna emits signal, and signal is dissipated by the clutter in rang ring to be detected on ground
Exit point reflection, airborne phased array radar antenna receive echo-signal y；Echo-signal y includes noise signal z, noise signal n
With echo signal s, wherein noise signal z and noise signal n is referred to as clutter plus noise signal x；
Step 2, doppler filtering is carried out to clutter plus noise signal x and echo signal s, respectively obtained multiple how general
Clutter plus noise signal after strangling the doppler filtering under channelWith it is more under multiple Doppler channels
It is general to strangle filtered echo signalWherein,Indicate the doppler filtering under k-th of Doppler channel
Clutter plus noise signal afterwards,How general echo signal after indicating the doppler filtering under k-th of Doppler channel, K indicate
Strangle the sum in channel；
Step 3, generation is established using formula (2) for the echo signal after the doppler filtering under each Doppler channel
Valence function:
Wherein, ukAnd vkIndicate the weight vector under k-th of Doppler channel；RkIt is more under k-th of Doppler channel
The general covariance matrix for strangling filtered clutter plus noise signal；
Step 4, using each cost function obtained in double iterative method solution procedure 3, it is logical to obtain each Doppler
Weight vector under road；
Step 5, it for the weight vector under each Doppler channel, is calculated, is obtained each how general using formula (3)
Strangle the letter miscellaneous noise ratio under channel:
Wherein, SCNROut, kIndicate the letter miscellaneous noise ratio under k-th of Doppler channel；
Step 6, the corresponding weight vector conduct of maximum letter miscellaneous noise ratio in all letter miscellaneous noise ratios obtained in selecting step 5
The weight vector finally chosen；
Step 7, the weight vector finally chosen based on step 6 is to the Doppler under the corresponding Doppler channel of the weight vector
Filtered clutter plus noise signal is handled using formula (4), the echo-signal after obtaining clutter recognition
Wherein, umAnd vmFor the weight vector finally chosen,It is miscellaneous after the doppler filtering under m-th of Doppler channel
Wave plus noise signal.
The covariance of the clutter plus noise signal after the doppler filtering under k-th of Doppler channel in the step 3
Matrix RkThe calculation method of the covariance matrix of clutter plus noise signal according to claim 1 obtains.
Compared with prior art, the present invention has following technical effect that the meter of the covariance matrix of clutter plus noise signal
Calculation method reduces sample number used in estimated matrix, and calculation amount is smaller.Clutter recognition based on symmetrical covariance matrix
The covariance matrix that method uses equally has the above advantages for the covariance matrix of above-mentioned clutter plus noise signal.
Explanation and illustration in further detail is made to the solution of the present invention with reference to the accompanying drawings and examples.
Detailed description of the invention
Fig. 1 is the method figure of the calculation method of the covariance matrix of clutter plus noise signal of the invention；
Fig. 2 be Small Sample Size under EFA, Per-EFA, BiPer-EFA snr loss's curve comparison figure, wherein (a)
Indicate θcPositive side when=0 optionally, (b) indicates θcNon-working side situation when=π/6；
Fig. 3 is EFA in the case of large sample, Per-EFA and BiPer-EFA snr loss's curve, wherein (a) is indicated
θcPositive side when=0 optionally under Normalized Signal/Noise Ratio lose curve, (b) indicate in θcNon-working side situation when=π/6
Under Normalized Signal/Noise Ratio lose curve；
Fig. 4 is EFA, Per-EFA and BiPer-EFA convergence rate figure compared with number of training；
Fig. 5 is that the calculating cost of tri- kinds of methods of EFA, Per-EFA and BiPer-EFA compares figure.
Specific embodiment
The invention discloses the machines that a kind of calculation method of the covariance matrix of clutter plus noise signal, this method use
Load Phased Array Radar Antenna is even linear array, and the bay number of airborne phased array radar antenna is N, referring to Fig. 1, including
Following steps:
Step 1, airborne phased array radar antenna emits signal, and signal is scattered by the clutter in rang rings multiple on ground
Point reflection, airborne phased array radar antenna receive multiple echo-signal y；Echo-signal y includes noise signal z and noise letter
Number n.
Step 2, doppler filtering is carried out to each echo-signal y respectively, is respectively obtained more under multiple Doppler channels
It is general to strangle filtered echo-signal；
Step 3, it is chosen in multiple rang rings and is in the rang ring conduct in set distance range with rang ring to be detected
Estimated distance ring；
Step 4, the doppler filtering under the corresponding same Doppler channel of all estimated distance rings chosen to step 3
Echo-signal afterwards carries out covariance estimation, obtains the preliminary covariance matrix under the Doppler channel；
Step 5, the preliminary covariance matrix under each Doppler channel obtained based on step 4 is counted using formula (1)
Calculate the covariance matrix of the clutter plus noise signal under each Doppler channel:
Wherein, RkIt is the covariance matrix of the clutter plus noise signal under k-th of Doppler channel,It is that how general kth is
Strangle the preliminary covariance matrix under channel, BsIt is space conversion matrices, BtIt is time change matrix, BstIt is spatial-temporal transform matrix.
Specifically, in another embodiment, the space conversion matrices in the step 5Time change square
Battle arraySpatial-temporal transform matrixWherein, IpRepresentation dimension is the unit matrix of p, p=3, INIt indicates
Dimension is the unit matrix of N；Js=fliplr (IN), wherein fliplr () is the MATLAB operation of left and right directions flip matrix
Symbol, N are the bay number of airborne phased array radar antenna；
Wherein, diag () indicates diagonal matrix, fk-1,fk,fk+1It is normalization Doppler's frequency in three neighboring Doppler channels
Rate.In the present embodiment, in order to increase number of training, the normalization Doppler frequency of three neighboring Doppler signal boxs is utilized
The space-time data for constructing Conversion of Spatial Data and the data after space-time conversion.
The calculation method of the covariance matrix of clutter plus noise signal disclosed by the invention, reducing estimated matrix is made
Sample number.
Another aspect of the present invention discloses a kind of clutter suppression method based on symmetrical covariance matrix, this method
The following steps are included:
Step 1, airborne phased array radar antenna emits signal, and signal is dissipated by the clutter in rang ring to be detected on ground
Exit point reflection, airborne phased array radar antenna receive echo-signal y；Echo-signal y includes noise signal z, noise signal n
With echo signal s, wherein noise signal z and noise signal n is referred to as clutter plus noise signal x.
Step 2, doppler filtering is carried out to clutter plus noise signal x and echo signal s, respectively obtained multiple how general
Clutter plus noise signal after strangling the doppler filtering under channelWith it is more under multiple Doppler channels
It is general to strangle filtered echo signalWherein,Indicate Doppler's filter under k-th of Doppler channel
Clutter plus noise signal after wave,Echo signal after indicating the doppler filtering under k-th of Doppler channel, K indicate more
The general sum for strangling channel.
Step 3, generation is established using formula (2) for the echo signal after the doppler filtering under each Doppler channel
Valence function:
Wherein, ukAnd vkIndicate the weight vector under k-th of Doppler channel；RkIt is more under k-th of Doppler channel
The general covariance matrix for strangling filtered clutter plus noise signal；
Step 4, using each cost function obtained in double iterative method solution procedure 3, it is logical to obtain each Doppler
Weight vector under road；
Step 5, it for the weight vector under each Doppler channel, is calculated, is obtained each how general using formula (3)
Strangle the letter miscellaneous noise ratio under channel:
Wherein, SCNROut, kIndicate the letter miscellaneous noise ratio under k-th of Doppler channel；
Step 6, the corresponding weight vector conduct of maximum letter miscellaneous noise ratio in all letter miscellaneous noise ratios obtained in selecting step 5
The weight vector finally chosen；
Step 7, the weight vector finally chosen based on step 6 is to the Doppler under the corresponding Doppler channel of the weight vector
Filtered clutter plus noise signal is handled using formula (4), the echo-signal after obtaining clutter recognition
Wherein, umAnd vmFor the weight vector under the weight vector finally chosen, that is, m-th of Doppler channel,It is
Clutter plus noise signal after doppler filtering under m Doppler channel.
The clutter plus noise signal after the doppler filtering under k-th of Doppler channel in the step 3Association side
Poor matrix RkFor what is obtained according to the calculation method of the covariance matrix of above-mentioned clutter plus noise signal.
Embodiment
The bay that the present embodiment uses has 64, and equidistant and spacing is d=0.1m, the echo width of each noise source
Degree is a complicated Gaussian random variable, and is weighted by launching beam mode.Table 1 lists the other parameters of the present embodiment.
Experiment porch be on 2.4GHz core processor, i7-5500u, the laptop of 4GB memory, the algorithm coding
Matlab program is to operate in Matlab R2011a.
1 analog parameter of table
Measure clutter suppression capability an important indicator be its direct losses degree, i.e. actual processor and one most
Loss between excellent is poor.
(1) the letter miscellaneous noise ratio loss under small sample is compared
Fig. 2 shows EFA, the Normalized Signal/Noise Ratio loss of Per-EFA, BiPer-EFA (method of the invention) (
Normalization maximum signal to noise ratio loss in EFA, Per-EFA, BiPer-EFA) curve graph, it is shown that small sample training is to returning
One changes the influence of Doppler frequency.In order to estimate that clutter covariance matrix S's is reversible, the sample number that each method is chosen is respectively
30,50 and 192, the spacing distance of neighbor distance ring is 50m, for different sample numbers, chooses the set distance of estimated distance ring
It is followed successively by 1500m, 2500m and 9600m, set distance=sample number × neighbor distance ring spacing distance.In addition, in Fig. 2
(a) θc=0 indicates positive side optionally, the θ of (b) in Fig. 2c=π/6 indicates non-working side situation.Although this shows less
Training sample is BiPer-EFA exploitation, it is clear that Per-EFA and EFA has better in main clutter area and sidelobe clutter area
The performance of snr loss.
(2) the letter miscellaneous noise ratio loss under large sample is compared
Show EFA, Per-EFA and BiPer-EFA in the normalization big training sample (L=of Doppler frequency in Fig. 3
500) Normalized Signal/Noise Ratio in positive side view and non-working side loses curve under support and respectively, in such case
Under, the signal-to-noise performance of BiPer-EFA is slightly below Per-EFA and EFA.Obviously, it can be obtained when number of training is enough
Optimal signal-to-noise performance analysis.When sample number is 500, the set distance for choosing estimated distance ring is 25000m.
(3) convergence rate is compared with number of training
Fig. 4 shows that the training sample of BiPer-EFA, Per-EFA and EFA are 10,50 and 192 how general in normalization respectively
Frequency is strangled to be 0.3 and normalize the convergence rate under the conditions of spatial frequency is 0.Obviously, BiPer-EFA is in identical training sample
Lower convergence rate is faster than other two kinds.In other words, BiPer-EFA, which is compared, has lower instruction for Per-EFA and EFA
Practice sample requirement.
(4) cost is calculated to compare
It is more as shown in Figure 5 to calculate cost.Herein, using L1=30, L2=100 and L3=250 be due to each side
Method can obtain almost the same snr loss with the selection of number of training.According to BiPer-EFA, Per-EFA and
The comparison of EFA show that, as N > 10, the smallest calculation amount may be implemented in BiPer-EFA.According to analog result, when array number ratio
Example is almost the half of EFA to the calculation amount of BiPer-EFA when larger.
(5) the processing time for drawing the curve of each method in Fig. 2 is compared in table 2.Obviously, according to meter above-mentioned
The analysis of calculation amount, BiPer-EFA, which has, at least calculates the time in all methods.
The algorithm proposed by the present invention for reducing training sample demand and calculation amount.The sub-symmetry of clutter covariance matrix
Utilize the decomposition of the weight vectors of EFA.Then the weight vectors needed for being found using double iterative algorithm.The experimental results showed that should
Algorithm has superiority in terms of large-scale antenna onboard radar system training sample convergence rate and calculation amount.
The processing time under 2 small sample of table is supported compares
Claims (3)
1. a kind of calculation method of the covariance matrix of clutter plus noise signal, which comprises the following steps:
Step 1, airborne phased array radar antenna emits signal, and signal is anti-by the clutter scattering point in rang rings multiple on ground
It penetrates, airborne phased array radar antenna receives multiple echo-signal y；Echo-signal y includes noise signal z and noise signal n；
Step 2, doppler filtering is carried out to each echo-signal y respectively, respectively obtains the Doppler under multiple Doppler channels
Filtered echo-signal；
Step 3, it is chosen in multiple rang rings and is in the rang ring in set distance range as estimation with rang ring to be detected
Rang ring；
Step 4, returning after the doppler filtering under the corresponding same Doppler channel of all estimated distance rings chosen to step 3
Wave signal carries out covariance estimation, obtains the preliminary covariance matrix under the Doppler channel；
Step 5, the preliminary covariance matrix under each Doppler channel obtained based on step 4 is calculated each using formula (1)
The covariance matrix of clutter plus noise signal under Doppler channel:
Wherein, RkIt is the covariance matrix of the clutter plus noise signal under k-th of Doppler channel,It is that k-th of Doppler is logical
Preliminary covariance matrix under road, BsIt is space conversion matrices, BtIt is time change matrix, BstIt is spatial-temporal transform matrix.
2. the calculation method of the covariance matrix of clutter plus noise signal as described in claim 1, which is characterized in that the step
Space conversion matrices in rapid 5Time change matrixSpatial-temporal transform matrixWherein, IpRepresentation dimension is the unit matrix of p, p=3, INRepresentation dimension is the unit matrix of N；Js=fliplr
(IN), wherein fliplr () is the MATLAB operator of left and right directions flip matrix, and N is airborne phased array radar antenna
Bay number；
Wherein, diag () indicates diagonal matrix, fk-1,fk,fk+1It is the normalization Doppler frequency in three neighboring Doppler channels.
3. a kind of clutter suppression method based on symmetrical covariance matrix, which comprises the following steps:
Step 1, airborne phased array radar antenna emits signal, and signal is anti-by the clutter scattering point in rang ring to be detected on ground
It penetrates, airborne phased array radar antenna receives echo-signal y；Echo-signal y includes noise signal z, noise signal n and target letter
Number s, wherein noise signal z and noise signal n is referred to as clutter plus noise signal x；
Step 2, doppler filtering is carried out to clutter plus noise signal x and echo signal s, respectively obtains multiple Doppler channels
Under doppler filtering after clutter plus noise signalWith the doppler filtering under multiple Doppler channels
Echo signal afterwardsWherein,Clutter after indicating the doppler filtering under k-th of Doppler channel adds
Noise signal,Echo signal after indicating the doppler filtering under k-th of Doppler channel, K indicate the total of Doppler channel
Number；
Step 3, cost letter is established using formula (2) for the echo signal after the doppler filtering under each Doppler channel
Number:
Wherein, ukAnd vkIndicate the weight vector under k-th of Doppler channel；RkFor Doppler's filter under k-th of Doppler channel
The covariance matrix of clutter plus noise signal after wave；
Step 4, it using each cost function obtained in double iterative method solution procedure 3, obtains under each Doppler channel
Weight vector；
Step 5, it for the weight vector under each Doppler channel, is calculated using formula (3), obtains each Doppler channel
Under letter miscellaneous noise ratio:
Wherein, SCNROut, kIndicate the letter miscellaneous noise ratio under k-th of Doppler channel；
Step 6, in all letter miscellaneous noise ratios obtained in selecting step 5 the corresponding weight vector of maximum letter miscellaneous noise ratio as final choosing
The weight vector taken；
Step 7, after the weight vector finally chosen based on step 6 is to the doppler filtering under the corresponding Doppler channel of the weight vector
Clutter plus noise signal handled using formula (4), the echo-signal after obtaining clutter recognition
Wherein, umAnd vmFor the weight vector finally chosen,Add for the clutter after the doppler filtering under m-th of Doppler channel
Noise signal.
The covariance matrix R of the clutter plus noise signal after the doppler filtering under k-th of Doppler channel in the step 3k
The calculation method of the covariance matrix of clutter plus noise signal according to claim 1 obtains.
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| CN111308431A (en) * | 2020-02-27 | 2020-06-19 | 西北大学 | Two-dimensional two-pulse cancellation method based on estimation error |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111308431A (en) * | 2020-02-27 | 2020-06-19 | 西北大学 | Two-dimensional two-pulse cancellation method based on estimation error |
| CN111308431B (en) * | 2020-02-27 | 2022-02-18 | 西北大学 | Two-dimensional two-pulse cancellation method based on estimation error |
| CN113376607A (en) * | 2021-05-27 | 2021-09-10 | 西安理工大学 | Airborne distributed radar small sample space-time adaptive processing method |
| CN113376607B (en) * | 2021-05-27 | 2023-06-20 | 西安理工大学 | Airborne distributed radar small sample space-time self-adaptive processing method |
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Application publication date: 20181211 |