CN110426670A - External illuminators-based radar super-resolution DOA estimation method based on TLS-CS - Google Patents
External illuminators-based radar super-resolution DOA estimation method based on TLS-CS 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
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
- G01S3/04—Details
- G01S3/06—Means for increasing effective directivity, e.g. by combining signals having differently oriented directivity characteristics or by sharpening the envelope waveform of the signal derived from a rotating or oscillating beam antenna
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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
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
- G01S3/04—Details
- G01S3/12—Means for determining sense of direction, e.g. by combining signals from directional antenna or goniometer search coil with those from non-directional antenna
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Abstract
The external illuminators-based radar super-resolution DOA estimation method based on TLS-CS that the invention discloses a kind of.Mainly solve the problems, such as that the prior art does not consider that compressed sensing super-resolution DOA estimation angle measurement accuracy and target resolution is caused to reduce by array amplitude phase error.Comprising: obtain the echo and the received direct wave of reference antenna of array antenna received；Inhibit direct wave and multipath interference signal in echo using direct wave and its time delay, the processing of distance-Doppler two-dimensional correlation is made to the echo-signal after clutter recognition, obtains complex vector signal S；Width is added to S again mutually to disturb to obtain the complex vector signal there are amplitude phase errorThe steering vector D of entire observation space is constructed, and it is solved to obtain the steering vector after amendment amplitude phase errorIt utilizesWithSparse reconstruct is carried out to the azimuth information of multiple targets, obtains the orientation of target.Influence present invention decreases array amplitude phase error to steering vector improves the angle measurement accuracy and resolution performance of target, can be used for target positioning.
Description
Technical field
The invention belongs to Radar Signal Processing Technology field more particularly to external illuminators-based radar super-resolution DOA estimation method,
It can be used for target positioning.
Background technique
External illuminators-based radar refers to and does not emit electromagnetic wave actively, by the non-cooperation of third party existing in target reflection environment
It irradiates source signal to implement, the radar for detecting target such as frequency modulation broadcasting FM, TV signal, mobile phone signal, being positioned and being tracked
System.The emitter Signals frequency range that the radar utilizes is low, irradiates towards ground, with stealthy and detecting low-altitude objective energy
Power, therefore have received widespread attention.
In external radiation source radar system, the direction of arrival DOA of array signal estimation be in target position fixing process one it is non-
Often important link.In general, array antenna received is far below to the echo-signal energy reflected from target from radiation source
Strong direct wave and the multipath clutter reflected through ground and building and noise signal, are difficult to realize the direct direction finding to target.
In order to estimate in external illuminators-based radar the DOA of target, inhibit array antenna received first with clutter cancellation algorithm
Echo-signal in strong direct wave and multipath clutter signal；Then it is improved and is received using the processing of distance-Doppler two-dimensional correlation
The signal-to-noise ratio of target echo signal；Finally on the distance-Doppler unit locating for target to the azimuth information of multiple targets into
Super-resolution DOA estimation is realized in the sparse reconstruct of row compressed sensing.However, error bars only are not present in array using compressed sensing
Good performance could be obtained under part.In practical external radiation source radar system, the amplitude and phase gain of each interchannel of array
Usually inconsistent, i.e., there are amplitude phase errors for array, can cause steering vector mismatch, and compressed sensing based super-resolution DOA estimates
In meter method, perception matrix is made of steering vector, and the mismatch of steering vector will lead to super-resolution performance and decline rapidly.
In conclusion when in array there are when amplitude phase error, the angle measurement accuracy and target resolution performance of above-mentioned existing method
Sharply decline, cannot effectively realize the super-resolution DOA estimation of target.
Summary of the invention
It is an object of the invention in view of the above shortcomings of the prior art, propose that it is a kind of based on overall minimum that one kind proposes
Two multiply the-external illuminators-based radar super-resolution DOA estimation method of compressed sensing TLS-CS, to improve target super-resolution DOA estimation
Angle measurement accuracy and target resolution performance effectively realize the super-resolution DOA estimation of target.
Realizing the thinking of the object of the invention is, solves the overall minimum two there are amplitude phase error by singular value decomposition method
Multiply TLS signal model, the steering vector after obtaining amendment amplitude phase error, by revised steering vector perceptually matrix, benefit
The sparse reconstruct of compressed sensing is carried out to the azimuth information of target with iteration tracking matching algorithm is hated to leave, realizes super-resolution DOA estimation.
According to above-mentioned thinking, implementation of the invention includes the following:
(1) the echo-signal S of array antenna received is obtained respectivelyechThe direct wave in radiation source direction is received with reference antenna
Signal Sref；
(2) direct-path signal that radiation source direction is received using reference antenna, using extension cancellation algorithm to echo-signal
In direct wave and multipath interference inhibited, the echo-signal S after obtaining clutter recognitionsur；
(3) to the echo-signal S after clutter recognitionsurThe processing of distance-Doppler two-dimensional correlation is carried out, complex vector letter is obtained
Number S；
S=A*Star+Z <1>
StarIndicate that target echo signal, A indicate that the corresponding steering vector of target, Z indicate noise signal；
(4) width is added to complex vector signal S and mutually disturbs parameter, Δ A, obtain the TLS signal model there are amplitude phase error,For
There are the complex vector signals of amplitude phase error:
(5) line number of entire observation space steering vector is set as element number of array M, columns is the division number N of observation space,
A M × N-dimensional matrix is constructed, the steering vector D as observation section；
(6) using the steering vector D in entire observation section as there are the steering vector that width mutually disturbs, substitution complex vector signalsIn, and it is solved using singular value decomposition method, the steering vector after obtaining amendment amplitude phase error
(7) by complex vector signalSteering vector as measurement vector, after correcting amplitude phase errorPerceptually matrix,
Compressed sensing is carried out to the azimuth information of multiple targets in same distance-Doppler unit using iteration tracing algorithm is hated to leave
Sparse reconstruct obtains the azimuth information of multiple targets.
Compared with the prior art, the present invention has the following advantages:
1. the present invention due to considering influence of the amplitude phase error to echo-signal, is added width in echo signal model and mutually misses
Difference solves amendment amplitude phase error using singular value decomposition method, and recycling hates to leave iterative matching pursuit algorithm to multiple targets
Azimuth information carries out sparse reconstruct, obtains the orientation of target, improves the angle measurement accuracy and resolution performance of target.
2. not needed present invention only requires the reference antenna of the array antenna of receives echo-signal and reception direct-path signal
Additional calibration antenna is realized simple.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is the application scenarios schematic diagram of external illuminators-based radar；
Fig. 2 is implementation flow chart of the invention；
Fig. 3 is that there is no the simulation experiment result figures of conventional method when amplitude phase error and the method for the present invention；
Fig. 4 is the simulation experiment result figure there are conventional method when amplitude phase error and the method for the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Firstly, for ease of understanding, below all by the application scenarios based on external illuminators-based radar shown in FIG. 1, external sort algorithm
Radar application scene is described below:
As shown in Figure 1, third party's non-cooperative illuminator is placed on the far field of external illuminators-based radar receiving station as hair
Station is penetrated, electromagnetic signals are come with this, the target that electromagnetic wave signal is radiated in array antenna covering airspace is reflected
Signal be known as target echo signal, be known as direct-path signal without the electromagnetic wave that shines directly on reference antenna of reflection,
Also known as reference signal.External illuminators-based radar receives direct wave by array antenna received target echo signal, by reference to antenna
Then signal is handled target echo signal and direct-path signal using Radar Signal Processing algorithm, and then obtain target
Distance, speed and azimuth information.As shown in Figure 1, external illuminators-based radar array antenna can also in addition to receiving target echo signal
Inevitably receive the tetanic arrived wave signal from transmitting station direction and the multipath interference by the reflection of different barriers
Signal, target echo signal energy is far below direct wave and multipath interference signal under normal conditions, it is therefore desirable to using with reference to day
The received direct wave of line eliminates the direct wave and multipath interference signal and by distance-Doppler of array antenna received
Reason improves the energy of target echo.
Referring to Fig. 2, the embodiment of the present invention is provided super based on total least square-compressed sensing external illuminators-based radar
DOA estimation method is differentiated, implementation step includes the following:
Step 1: obtaining the echo-signal S of array antenna received respectivelyechThe through of radiation source direction is received with reference antenna
Wave signal Sref；
If array antenna is made of the even linear array that array element spacing is half-wavelength, array number M, M >=11, receives the road M and return
Wave signal Sech, wherein every road echo-signal SechComprising from transmitting station direction strong direct wave, through the multipath of Multipath reflection
Interference signal and noise signal；
If the narrow beam antenna that reference antenna is individually directed to transmitting station direction by one is constituted, receives and come from radiation source direction
Direct-path signal Sref。
Step 2: the direct-path signal S in radiation source direction is received using reference antennaref, using extension cancellation algorithm to return
Wave signal SechIn direct wave and multipath interference signal inhibited, the echo-signal S after obtaining clutter recognitionsur。
Due to the echo-signal S of array antenna receivedrefIn not only comprising target reflection echo-signal, further include coming from
The direct-path signal of radiation source and the multipath clutter signal reflected by building, road, energy are far longer than target echo
Signal cannot detect target, it is therefore necessary to inhibit to noise signal so that target echo is submerged in noise signal.
By projecting to echo-signal by direct-path signal SrefAnd its time delay constitute orthogonal subspaces V on, noise signal this just
Intersection of subspace V can be not all zero projection coefficient in the presence of one group, it represents the intensity of various noise signals, and it is incomplete to solve this group
The projection coefficient for being zero can fall clutter cancellation present in echo-signal, the echo-signal S after obtaining clutter recognitionsur。
This step is implemented as follows:
(2a) utilizes direct wave SrefAnd its time delay constructs clutter orthogonal subspaces V:
Wherein, G is the data length of direct-path signal, and C is clutter cancellation order, and the first row of matrix indicates direct wave letter
Number, secondary series indicates that time delay elements are one multipath signal, and Nth column indicates that time delay elements are the multipath signal of C；
(2b) is by echo-signal SechIt projects in clutter orthogonal subspaces V, solves this group and be not all zero on the subspace
Projection coefficient W:
W=(VH*V)-1VHSech,<3>
Wherein VHIndicate the conjugate transposition to matrix V, (VH*V)-1Expression inverts to matrix product result；
(2c) is according to by echo-signal Sech, clutter orthogonal subspaces V and be not all zero projection coefficient W, obtain clutter recognition
Residual echo signal S afterwardssur:
Ssur=Sech-V*W。 <4>
Step 3: to residual echo signal SsurThe processing of distance-Doppler two-dimensional correlation is carried out, complex vector signal S is obtained.
After clutter recognition, echo-signal SechIn include noise signal eliminated, however residual echo signal
SsurIn the energy of target echo signal be still below noise signal, therefore carry out the processing of distance-Doppler two-dimensional correlation and improve mesh
The energy for marking echo-signal, obtains signal model ideally, and S is to be answered after distance-Doppler two-dimensional correlation is handled
Vector signal.
This step is implemented as follows:
(3a) is by the residual echo signal S after clutter recognitionsurWith when the conjugation reference signal S that delaysref *[g- τ] dot product,
Complex vector signal S after obtaining distance dimension relevant treatmentm:
τ indicates the distance of moving target in formula, and G is residual echo signal SsurLength；
(3b) adjusts the distance tie up relevant treatment after complex vector signal SmAfter carrying out Doppler's dimension correlation accumulation, Doppler is obtained
Echo signal S after tieing up correlation accumulationtar:
(3c) is to echo signal StarSteering vector A, noise Z is added, obtains the multiple arrow of distance-Doppler two-dimensional correlation processing
Measure signal S:
S=A*Star+Z。 <7>
Step 4: width is added to complex vector signal S and mutually disturbs parameter, Δ A, obtains the TLS signal model there are amplitude phase error,For there are the complex vector signals of amplitude phase error:.
Complex vector signal S in step 3 is ideally derived by, but in external illuminators-based radar real work
In, complex vector signal S is inevitably influenced by amplitude phase error, therefore amplitude phase error Δ A is added in<7>formula, obtains TLS
Model,For there are the complex vector signals of amplitude phase error:
Step 5: constructing the steering vector D of entire observation space.
If the line number of entire observation space steering vector is element number of array M, columns is the division number N of observation space, structure
A M × N-dimensional matrix is built, the steering vector D as observation section:
Wherein, θ1For the Initial Azimuth for observing section, θNFor the cut-off orientation for observing section, d is bay spacing, and λ is
Emit electromagnetic wavelength.
Step 6: using the steering vector D in entire observation section as there are the steering vector that width mutually disturbs, substitution<6>formula
A+ Δ A, and it is solved using singular value decomposition method, the steering vector after obtaining amendment amplitude phase error
This step is implemented as follows:
(6a) constructs M × (N+1) and ties up extended matrixWhereinFor the dimension of M × 1, there are the complex vector of amplitude phase error letters
Number, D is that M × N-dimensional corrects the steering vector after amplitude phase error；
The singular value decomposition of (6b) calculating extended matrix B:
B=U Σ VH,
Wherein Σ is M × MM × M dimension diagonal matrix Σ=(diag (σ1,σ2,…,σM), 0), 0 ties up square for M × (N-M+1)
Battle array, element is 0；diag(σ1,σ2,…,σM) be main diagonal element be σ1,σ2,…,σMM × M tie up matrix, VHIndicate square
The conjugate transposition of battle array V；
(6c) is from main diagonal element σ1,σ2,…,σMFind a mutation element σp, work as σpMeet σp> σM+ξ≥σp+1≥…
≥σMWhen, ξ=max [(σ1-σ2),(σ2-σ3),…,(σM-1-σM)], using subscript P as effective order order, construct (N+1) × (N+
1) correction matrix: E=[I is tieed upp,0]T,IpUnit matrix is tieed up for p × p, 0 is null matrix；
Formula<7>are added in correction matrix E by (6d), premultiplication diagonal matrix Σ, and obtain augmented matrix B most preferably approaches matrix
(6e) approaches matrix to bestIt is split, it willThe 2nd column to N+1 column as correct amplitude phase error after
Steering vector For M × N-dimensional matrix.
Step 7: by complex vector signalSteering vector as measurement vector, after correcting amplitude phase errorPerceptually square
Battle array compresses the azimuth information of multiple targets in same distance-Doppler unit using iteration tracing algorithm is hated to leave
Sparse reconstruct is perceived, the azimuth information of multiple targets is obtained.
This step is implemented as follows:
(7a) will measure vectorAs initial input, it is denoted as e0；
(7b) from perception matrixMiddle screening and e0One column of inner product maximum absolute value, and be expressed as
(7c) is according to (7a) and (7b) as a result, residual value e is calculated1:
WhereinIndicate e0WithInner product；
The residual value that (7d) (7c) the is calculated input new as (7a), repeat (7b) and (7c) it is K times total, obtain
Perceive matrixIn with measurement vectorMaximally related K vectorThe range of K is less than or equal to 7, this example value
It is 7；
(7e) works as dependent vectorPositioned at perception matrixIn the n-th column, then the orientation θ of target are as follows:
θ=(n-N/2) * (θN-θ1)/N, n ∈ 1,2 ..., N
Wherein, N is total columns in entire space, θ1For the Initial Azimuth for observing section, θNFor the cut-off side for observing section
Position.
Effect of the invention can be further illustrated by following emulation experiment:
1. experiment condition:
Using fm broadcast signal FM as radiation source, frequency 93.1MHz, bandwidth 200kHz, sampling in present invention test
Rate is 200kHz, integration time 1s；Array antenna is made of the even linear array for being divided into half-wavelength, element number of array 15, together
When array antenna received to 2 be located at the same distance-Doppler unit target echo signal.It is real below by way of two groups of emulation
The performance to illustrate the method for the present invention is tested, the simulation parameter of target is as shown in Table 1.
The simulation parameter of one target of table
2. emulation content and result
Emulation one, under the conditions of amplitude phase error is not present in array, using conventional method and method of the invention to two mesh
Target azimuth information carries out the sparse reconstruct of compressed sensing and emulates, the orientation of two obtained targets, as a result as shown in Figure 3, in which:
Fig. 3 (a) is to perceive the azimuth information that super-resolution DOA estimation method obtains using conventional compression；
Fig. 3 (b) is the azimuth information that the method for the present invention obtains；
From figure 3, it can be seen that conventional method and the method for the present invention can effectively tell two targets, and detect
The orientation of target is [5 °, 14 °], consistent with target bearing is assumed.
Emulation two, under the conditions of array is -30dB there are amplitude phase error, using conventional method and the method for the present invention to two
The azimuth information of target carries out the sparse reconstruct of compressed sensing and emulates, the orientation of two obtained targets, as a result as shown in figure 4, its
In:
Super-resolution DOA estimation method is perceived using conventional compression when Fig. 4 (a) is array amplitude phase error -30dB to obtain
Azimuth information；
The azimuth information that Fig. 4 (b), which is array amplitude phase error, to be obtained using the method for the present invention when being -30dB；
From fig. 4, it can be seen that detecting two targets using the method for the present invention when the amplitude phase error of array is -30dB
Orientation be respectively 5 ° and 14 °, illustrate this method can array there are amplitude phase error when, inhibit amplitude phase error to swear guiding
Amount influences, and is effectively differentiated to two targets, and comes with the target of hypothesis to consistent, and is examined using conventional method
The multiple false bearing information of meeting are surveyed, and inconsistent with the target bearing information of hypothesis, two targets cannot effectively be divided
It distinguishes.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (6)
1. a kind of external illuminators-based radar super-resolution DOA estimation method based on TLS-CS, which is characterized in that include the following:
(1) the echo-signal S of array antenna received is obtained respectivelyechThe direct-path signal in radiation source direction is received with reference antenna
Sref；
(2) direct-path signal that radiation source direction is received using reference antenna, using extension cancellation algorithm in echo-signal
Direct wave and multipath interference are inhibited, the echo-signal S after obtaining clutter recognitionsur；
(3) to the echo-signal S after clutter recognitionsurThe processing of distance-Doppler two-dimensional correlation is carried out, complex vector signal S is obtained；
S=A*Star+Z <1>
StarIndicate that target echo signal, A indicate that the corresponding steering vector of target, Z indicate noise signal；
(4) complex vector signal S addition width is mutually disturbed into parameter, Δ A, obtains the TLS signal model there are amplitude phase error,To exist
The complex vector signal of amplitude phase error:
S=(A+ Δ A) * Star+Z <2>
(5) line number of entire observation space steering vector is set as element number of array M, and columns is the division number N of observation space, building
One M × N-dimensional matrix, the steering vector D as observation section；
(6) using the steering vector D in entire observation section as there are the steering vector that width mutually disturbs, the A+ Δ A of substitution<2>formula,
And<2>formula is solved using singular value decomposition method, the steering vector after obtaining amendment amplitude phase error
(7) by complex vector signalSteering vector as measurement vector, after correcting amplitude phase errorPerceptually matrix utilizes
It is sparse to the azimuth information progress compressed sensing of multiple targets in same distance-Doppler unit to hate to leave iteration tracing algorithm
Reconstruct, obtains the azimuth information of multiple targets.
2. the method according to claim 1, wherein the step (2) are accomplished by
(2a) utilizes direct wave SrefAnd its time delay constructs clutter orthogonal subspaces V:
Wherein, G is the data length of direct-path signal, and C is clutter cancellation order, and the first row of matrix indicates direct-path signal,
Secondary series indicates that time delay elements are one multipath signal, and Nth column indicates that time delay elements are the multipath signal of C；
(2b) is by echo-signal SechIt projects in clutter orthogonal subspaces V, solves the throwing that this group is not all zero on the subspace
Shadow coefficient W:
W=(VH*V)-1VHSech,<3>
Wherein VHIndicate the conjugate transposition to matrix V；(VH*V)-1Expression inverts to matrix product result；
(2c) is according to by echo-signal Sech, clutter orthogonal subspaces V and be not all zero projection coefficient W, after obtaining clutter recognition
Residual echo signal Ssur:
Ssur=Sech- V*W,<4>.
3. the method according to claim 1, wherein the step (3) is to the echo-signal S after clutter recognitionsur
The processing of distance-Doppler two-dimensional correlation is carried out, is accomplished by
(3a) is by the residual echo signal S after clutter recognitionsurWith when the conjugation reference signal S that delaysref *[g- τ] dot product, obtains
Complex vector signal S after distance dimension relevant treatmentm:
τ indicates the distance of moving target, f in formuladIndicate how general caused by the relative motion between moving target and array antenna
It strangles, G is residual echo signal SsurLength；
(3b) adjusts the distance tie up relevant treatment after complex vector signal SmAfter carrying out Doppler's dimension correlation accumulation, obtains Doppler and tie up phase
Echo signal S after closing accumulationtar:
(3c) is to echo signal StarSteering vector A, noise Z is added, obtains distance-Doppler two-dimensional correlation processing complex vector letter
Number S:
S=A*Star+Z。 <7>。
4. the method according to claim 1, wherein the observation space steering vector D in the step (5),
It is expressed as follows:
Wherein, M is element number of array, and N is total columns in entire space, θ1For the Initial Azimuth for observing section, θNFor observation section
End orientation, d is bay spacing, and λ is transmitting electromagnetic wavelength.
5. the method according to claim 1, wherein the step (6) are accomplished by
(6a) constructs M × (N+1) and ties up extended matrix For the dimension of M × 1, there are the complex vector signal of amplitude phase error, D M
× N-dimensional corrects the steering vector after amplitude phase error；
The singular value decomposition of (6b) calculating extended matrix B:
B=U Σ VH,<8>
Wherein Σ is M × MM × M dimension diagonal matrix Σ=(diag (σ1,σ2,…,σM), 0), 0 ties up matrix for M × (N-M+1),
Element is 0；diag(σ1,σ2,…,σM) be main diagonal element be σ1,σ2,…,σMM × M tie up matrix；VHRepresenting matrix V's
Conjugate transposition；
(6c) is from main diagonal element σ1,σ2,…,σMFind a mutation element σp, work as σpMeet σp> σM+ξ≥σp+1≥…≥σM
When, ξ=max [(σ1-σ2),(σ2-σ3),…,(σM-1-σM)], using P as effective order order, construct (N+1) × (N+1) dimension correction
Matrix: E=[Ip,0]T,IpUnit matrix is tieed up for p × p, 0 is null matrix, and element is 0；
Formula<8>are added in correction matrix E by (6d), premultiplication diagonal matrix Σ, and obtain augmented matrix B most preferably approaches matrix
(6e) approaches matrix to bestIt is split, it willThe 2nd column to N+1 column as correct amplitude phase error after guiding
Vector For M × N-dimensional matrix.
6. hating to leave iteration tracing algorithm pair the method according to claim 1, wherein utilizing in the step (7)
The azimuth information of multiple targets in same distance-Doppler unit carries out the sparse reconstruct of compressed sensing, obtains multiple targets
Azimuth information, be accomplished by
(7a) will measure vectorAs initial input, it is denoted as e0；
(7b) from perception matrixMiddle screening and e0One column of inner product maximum absolute value, and be expressed as
(7c) is according to (7a) and (7b) as a result, residual value e is calculated1:
WhereinIndicate e0WithInner product；
The residual value that (7d) (7c) the is calculated input new as (7a), repeat (7b) and (7c) it is K times total, perceived
MatrixIn with measurement vectorMaximally related K vector
(7e) works as dependent vectorPositioned at perception matrixIn the n-th column, then the orientation θ of target are as follows:
θ=(n-N/2) * (θN-θ1)/N, n ∈ 1,2 ..., N
Wherein, N is total columns in entire space, θ1For the Initial Azimuth for observing section, θNFor the cut-off orientation for observing section.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112083407A (en) * | 2020-09-17 | 2020-12-15 | 电子科技大学 | External radiation source three-dimensional positioning method using time difference and one-dimensional azimuth measurement |
| CN112104431A (en) * | 2020-11-23 | 2020-12-18 | 成都天锐星通科技有限公司 | Phased array antenna measurement error correction method, device and measurement system |
| CN112285695A (en) * | 2020-10-21 | 2021-01-29 | 浙江大学 | Interactive positioning system and method based on compressed sensing |
| CN113484854A (en) * | 2021-07-21 | 2021-10-08 | 电子科技大学 | Target positioning method with unknown external radiation source position |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6075484A (en) * | 1999-05-03 | 2000-06-13 | Motorola, Inc. | Method and apparatus for robust estimation of directions of arrival for antenna arrays |
| US20120259590A1 (en) * | 2011-04-11 | 2012-10-11 | Jong Chul Ye | Method and apparatus for compressed sensing with joint sparsity |
| CN104407335A (en) * | 2014-10-24 | 2015-03-11 | 哈尔滨工业大学深圳研究生院 | DOA estimation method of 3-axis cross array |
| CN104698433A (en) * | 2015-03-16 | 2015-06-10 | 电子科技大学 | Single-snapshot data-based coherent signal DOA (direction of arrival) estimating method |
| CN104749554A (en) * | 2015-03-20 | 2015-07-01 | 江苏大学 | Recursive rank loss based amplitude phase error calibrating and wave arrival direction estimating method |
| CN104820216A (en) * | 2015-05-08 | 2015-08-05 | 西北工业大学 | Multipath signal angle-of-arrival estimation method based on array response rotation invariance |
| CN104965188A (en) * | 2015-06-10 | 2015-10-07 | 重庆邮电大学 | Wave arrival direction estimation method under array error |
| CN106291452A (en) * | 2016-09-12 | 2017-01-04 | 电子科技大学 | A kind of direction of arrival estimation method based on enhanced greedy algorithm |
| WO2018045601A1 (en) * | 2016-09-09 | 2018-03-15 | 深圳大学 | Sparse recovery stap method for array error and system thereof |
| WO2018049595A1 (en) * | 2016-09-14 | 2018-03-22 | 深圳大学 | Admm-based robust sparse recovery stap method and system thereof |
| CN108761380A (en) * | 2018-05-23 | 2018-11-06 | 西安电子科技大学 | One kind is for carrying high-precision target Wave arrival direction estimating method |
| CN108872926A (en) * | 2018-07-11 | 2018-11-23 | 哈尔滨工程大学 | A kind of amplitude and phase error correction and DOA estimation method based on convex optimization |
-
2019
- 2019-07-13 CN CN201910632496.7A patent/CN110426670B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6075484A (en) * | 1999-05-03 | 2000-06-13 | Motorola, Inc. | Method and apparatus for robust estimation of directions of arrival for antenna arrays |
| US20120259590A1 (en) * | 2011-04-11 | 2012-10-11 | Jong Chul Ye | Method and apparatus for compressed sensing with joint sparsity |
| CN104407335A (en) * | 2014-10-24 | 2015-03-11 | 哈尔滨工业大学深圳研究生院 | DOA estimation method of 3-axis cross array |
| CN104698433A (en) * | 2015-03-16 | 2015-06-10 | 电子科技大学 | Single-snapshot data-based coherent signal DOA (direction of arrival) estimating method |
| CN104749554A (en) * | 2015-03-20 | 2015-07-01 | 江苏大学 | Recursive rank loss based amplitude phase error calibrating and wave arrival direction estimating method |
| CN104820216A (en) * | 2015-05-08 | 2015-08-05 | 西北工业大学 | Multipath signal angle-of-arrival estimation method based on array response rotation invariance |
| CN104965188A (en) * | 2015-06-10 | 2015-10-07 | 重庆邮电大学 | Wave arrival direction estimation method under array error |
| WO2018045601A1 (en) * | 2016-09-09 | 2018-03-15 | 深圳大学 | Sparse recovery stap method for array error and system thereof |
| CN106291452A (en) * | 2016-09-12 | 2017-01-04 | 电子科技大学 | A kind of direction of arrival estimation method based on enhanced greedy algorithm |
| WO2018049595A1 (en) * | 2016-09-14 | 2018-03-22 | 深圳大学 | Admm-based robust sparse recovery stap method and system thereof |
| CN108761380A (en) * | 2018-05-23 | 2018-11-06 | 西安电子科技大学 | One kind is for carrying high-precision target Wave arrival direction estimating method |
| CN108872926A (en) * | 2018-07-11 | 2018-11-23 | 哈尔滨工程大学 | A kind of amplitude and phase error correction and DOA estimation method based on convex optimization |
Non-Patent Citations (6)
| Title |
|---|
| HONGWEI LI ET AL.: "Passive Coherent Radar Tracking Algorithm Based", 《PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING》 * |
| XIN GUO: "Compressive Sensing for target DOA estimation in radar", 《2014 INTERNATIONAL RADAR CONFERENCE》 * |
| 周建卫等: "基于共形稀疏阵列的艇载外辐射源雷达性能分析", 《电子与信息学报》 * |
| 张佳佳: "非均匀线阵的互耦自校正", 《系统工程与电子技术》 * |
| 王海涛等: "基于压缩感知的无源雷达超分辨DOA估计", 《电子与信息学报》 * |
| 陈刚等: "外辐射源雷达参考信号提纯方法", 《系统工程与电子技术》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112083407A (en) * | 2020-09-17 | 2020-12-15 | 电子科技大学 | External radiation source three-dimensional positioning method using time difference and one-dimensional azimuth measurement |
| CN112083407B (en) * | 2020-09-17 | 2022-03-29 | 电子科技大学 | External radiation source three-dimensional positioning method using time difference and one-dimensional azimuth measurement |
| CN112285695A (en) * | 2020-10-21 | 2021-01-29 | 浙江大学 | Interactive positioning system and method based on compressed sensing |
| CN112285695B (en) * | 2020-10-21 | 2024-01-12 | 浙江大学 | Interactive positioning system and method based on compressed sensing |
| CN112104431A (en) * | 2020-11-23 | 2020-12-18 | 成都天锐星通科技有限公司 | Phased array antenna measurement error correction method, device and measurement system |
| CN113484854A (en) * | 2021-07-21 | 2021-10-08 | 电子科技大学 | Target positioning method with unknown external radiation source position |
| CN113484854B (en) * | 2021-07-21 | 2023-04-11 | 电子科技大学 | Target positioning method with unknown external radiation source position |
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