CN107677988A - A kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method - Google Patents

A kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method Download PDF

Info

Publication number
CN107677988A
CN107677988A CN201710810481.6A CN201710810481A CN107677988A CN 107677988 A CN107677988 A CN 107677988A CN 201710810481 A CN201710810481 A CN 201710810481A CN 107677988 A CN107677988 A CN 107677988A
Authority
CN
China
Prior art keywords
linear array
array
finding
atom
special
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201710810481.6A
Other languages
Chinese (zh)
Other versions
CN107677988B (en
Inventor
高洪元
陈梦晗
张世铂
刘丹丹
刁鸣
池鹏飞
侯阳阳
梁炎松
刘子奇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin Engineering University
Original Assignee
Harbin Engineering University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Harbin Engineering University filed Critical Harbin Engineering University
Priority to CN201710810481.6A priority Critical patent/CN107677988B/en
Publication of CN107677988A publication Critical patent/CN107677988A/en
Application granted granted Critical
Publication of CN107677988B publication Critical patent/CN107677988B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • G01S3/14—Systems for determining direction or deviation from predetermined direction
    • 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
    • G01S3/78—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 electromagnetic waves other than radio waves
    • G01S3/782—Systems for determining direction or deviation from predetermined direction
    • 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
    • G01S3/80—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 ultrasonic, sonic or infrasonic waves
    • G01S3/802—Systems for determining direction or deviation from predetermined direction
    • 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
    • G01S3/80—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 ultrasonic, sonic or infrasonic waves
    • G01S3/86—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 ultrasonic, sonic or infrasonic waves with means for eliminating undesired waves, e.g. disturbing noises

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Electromagnetism (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The invention belongs to array signal processing field, and in particular to a kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method.This method carries out array extension using the structure of special Nonuniform Linear Array, perception direction finding is compressed to target under impulsive noise environment with reference to Infinite Norm, so as to obtain its optimal angle estimate.The suitable environment of this method includes impact noise, Gaussian noise and thump noise, suitable for various, severe direction finding environment, in addition designed Infinite Norm compressed sensing direction-finding method can carry out high-precision direction finding to the target under impulsive noise environment, simultaneously it is also ensured that the robustness of direction finding, and the special Nonuniform Linear Array designed by this method has a variety of antenna arrangement methods while Measure direction performance is not influenceed, suitable for harsher putting position requirement, the resolution ratio and direction finding precision of compressed sensing direction-finding method is greatly improved in last this method, with broader practice scope.

Description

A kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method
Technical field
The invention belongs to array signal processing field, and in particular to a kind of Efficient Compression sense based on special Nonuniform Linear Array Know direction-finding method.
Background technology
Direction of arrival (Direction of Arrival, DOA) estimation has act foot light in array signal processing field The status of weight, rapid development of the technology in military and national economy field bring huge change for array signal processing Leather.Compressive sensing theory can be compressed and sample to signal simultaneously, so as to which signal sampling is transformed into intelligence sample.Should Theory is pointed out, available that the signal is entered less than Nyquist sample frequencys for sparse in any transform domain or compressible signal Row sampling, then by solving the sparse reconstruct original signal of an optimization problem.Estimate to only exist a small amount of sense in observation space in DOA Signal-of-interest, remaining is useless ambient noise, therefore for whole space, signal is sparse, can feel compression Know that the theoretical DOA that is applied to estimates.DOA estimations based on compressive sensing theory breach traditional Nyquist sampling thheorems so that letter Number sampling rate depend no longer on the bandwidth of signal and depending on the position of information in signal.With traditional DOA estimation method phase Than this method effectively reduces the measurement data amount of signal, improves signal sampling speed, has saved signal processing time, drop Low signal transmission and carrying cost.
Compressed sensing DOA estimations have many advantages, such as, but most of research for the theory is all in even linear array Carried out under conditions of (Uniform Linear Array, ULA), if Wang Ying are in article《Direction estimation using compressive sampling array processing》In analyze based on even linear array Compressed sensing DOA estimates that Diao Ming is in the article delivered《Compressed sensing Mutual coupling based on Nonuniform Linear Array》Middle design Nonuniform Linear Array compressed sensing direction-finding method under a kind of Gaussian noise environment, but this method has problems, such as it is non- Even linear array array extending aperture is indifferent, lacks strict theoretical foundation, and only effective in Gaussian noise environment.
When direction finding is carried out under the adverse noise environment such as impact noise, the robustness of direction finding it is difficult to ensure that, simultaneous direction finding Difficulty can also increase, therefore be compressed under impulsive noise environment and perceive direction finding technology research, it is necessary to design high performance Shandong Rod compressed sensing direction-finding method.No matter in Gaussian noise or under impulsive noise environment, classical compressed sensing direction-finding method is very The deficiency of direction finding failure when difficulty breaks away from convergence precision difference and very few antenna number, it is therefore desirable to design new based on special heterogeneous line The robust compressed sensing direction-finding method of battle array, solves the compressed sensing direction finding problem under impulsive noise environment by this method, finally Realization equally can have preferable performance under the adverse noise environment such as impact noise.
The content of the invention
It is an object of the invention to provide one kind to be based on special Nonuniform Linear Array, Infinite Norm and compressed sensing direction-finding method The efficient and compressed sensing direction-finding method of robust, this method can apply to the noise circumstance of complexity.
The object of the present invention is achieved like this：
A kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method, and concrete implementation step is as follows：
Step 1. sets special Nonuniform Linear Array, and Infinite Norm low-order moment is constructed according to reception signal；
Step 2. invents the Infinite Norm low-order moment of special Nonuniform Linear Array the extension of the even linear array of more array elements Infinite Norm low-order moment, extension are oriented to matrix and obtain the extension guiding matrix of virtual uniform linear array；
Step 3. carries out singular value decomposition to extension Infinite Norm low-order moment R, obtains signal subspace component, then by signal Subspace component extraction observation signal y；
Step 4. divides observation space, constructs redundant dictionary；
Step 5. initialization residual error v0, atom sequence number indexed set close Ω0With atom set Q0, make residual error v0=y, atomic number Number index set omega0And atom set Q0Empty set is initialized as, if current iteration number is t=1；
Step 6. calculates residual error vt-1With atom b (μg) inner product, record inner product maximum and its corresponding atom sequence numberAtom sequence number indexed set is updated to closeAnd atom set Wherein ∪ represents union,Carry out zero-setting operation；
Step 7. obtains approximation signal with least square methodUpdate residual error
Step 8. judges whether iterations t and number of source P meets condition t ＞ P, if not satisfied, making t=t+1, then Return to step 6 and continue iteration；If satisfied, direction corresponding to then exporting the conjunction of atom sequence number indexed set, as estimates angleWherein t represents iterations；
Special Nonuniform Linear Array described in step 1 includes minimum redundant array, maximum continuous delay array and minimum Gap array.
The dividing mode of division observation space described in step 4, which is divided into, angularly divides and waits sinusoidal two kinds of division.
The beneficial effects of the present invention are：
The present invention is applicable not only to the direction finding problem under impulsive noise environment, while is also applied for Gaussian noise environment and strong Impulsive noise environment, new method improve the direction of arrival angular estimation performance of even linear array under the conditions of identical array number；The present invention The resolution ratio and direction finding precision of compressed sensing direction-finding method is greatly improved, there is broader practice scope；The present invention is set The Infinite Norm compressed sensing direction-finding method of meter can carry out high-precision direction finding to the target under impulsive noise environment, while also may be used To ensure the robustness of direction finding；Compressed sensing direction-finding method designed by the present invention has stronger array extension ability, anti-impact Noise immune and natural decoherence ability are hit, suitable for worse direction finding environment；It is special non-homogeneous designed by the present invention Linear array has a variety of antenna arrangement methods while Measure direction performance is not influenceed, suitable for harsher putting position requirement.
Brief description of the drawings
Fig. 1 is the system flow chart of the present invention.
When Fig. 2 is the characteristic index α=0.8 of thump noise, projection coefficient of the present invention to 2 independent source direction findings Figure.
When Fig. 3 is the characteristic index α=0.8 of thump noise, projection of the FLOM-OMP methods to 2 independent source direction findings Coefficient figure.
When Fig. 4 is the characteristic index α=1.5 of weak impact noise, projection coefficient of the present invention to 2 coherent direction findings Figure.
When Fig. 5 is the characteristic index α=1.5 of weak impact noise, projection coefficients of the FLOM-OMP to 2 coherent direction findings Figure.
The graph of relation of the probability of success and signal to noise ratio when Fig. 6 is independent source direction finding under Gaussian noise environment.
The graph of relation of the probability of success and signal to noise ratio when Fig. 7 is coherent direction finding under Gaussian noise environment.
Embodiment：
1 to 7 the present invention will be further described below in conjunction with the accompanying drawings：
The present invention relates to a kind of Efficient Compression based on special Nonuniform Linear Array to perceive direction-finding method, and it is special that this method utilizes The structure of Nonuniform Linear Array carries out array extension, and perception is compressed to target under impulsive noise environment with reference to Infinite Norm surveys To so as to obtain its optimal angle estimate.
The present invention sets special Nonuniform Linear Array first, and Infinite Norm low-order moment is constructed by reception signal；Again will be special The Infinite Norm low-order moment of Nonuniform Linear Array invents the extension Infinite Norm low-order moment of the even linear array of more array elements, and extension is led The extension that virtual uniform linear array is obtained to matrix is oriented to matrix；Singular value decomposition is carried out to extension Infinite Norm low-order moment, obtained Signal subspace component, then by signal subspace component extraction observation signal；Observation space is divided, constructs redundant dictionary；Initially Change residual error, atom sequence number indexed set closes and atom set；The inner product of residual error and atom is calculated, records inner product maximum and its correspondingly Atom sequence number, renewal atom sequence number indexed set closes and atom set, and by atom zero setting corresponding to inner product maximum；Utilize Least square method obtains approximation signal, updates residual error；Direction corresponding to finally exporting the conjunction of atom sequence number indexed set, as estimates angle Degree.
As shown in figure 1, the detailed process of the method proposed in the present invention is as follows：
Step 1. sets special Nonuniform Linear Array, and Infinite Norm low-order moment, wherein minimal redundancy are constructed according to reception signal Array, maximum continuous delay array and minimum clearance array belong to special Nonuniform Linear Array.If special Nonuniform Linear Array is by M Individual isotropic antenna array element is formed, and array element spacing is the integral multiple of half-wavelength, and m-th of array element is relative to first battle array in array The spacing of member is set to dmAnd m=1, wherein 2 ..., M, d1=0 ＜ d2＜ ... ＜ dM, gather Δ={ dm-dz| m, z=1, 2 ..., M, m ＞ z } it is a continuous natural number set.Assuming that there is plane of the P arrowband point source using wavelength as λ in array far field Ripple is incident, then the kth time snapshot data that special Nonuniform Linear Array receives can be expressed as x (k)=A (θ) s (k)+n (k), in formula A (θ)=[a (θ1),a(θ2),...,a(θP)] it is that M × P dimensions are oriented to matrix, wherein p-th of steering vector is
P=1,2 ..., P, θ=(θ1,θ2,...,θP) it is incoming wave Orientation vector, x (k)=[x1(k),x2(k),...,xM(k)]TFor the dimension array snapshot data of M × 1, wherein k is snap number, s (k)=[s1(k),s2(k),...,sP(k)]TFor the dimensional signal of P × 1, n (k) is the multiple impulse noise that the dimension of M × 1 obeys S α S distributions Sound, j are complex unit.Then the weighting Infinite Norm normalized signal of kth time sampled data can be expressed asThe nothing constructed according to special Nonuniform Linear Array reception signal Norm low-order moment is thoroughlyWherein H represents conjugate transposition, and E () represents mathematic expectaion.
Step 2. invents the Infinite Norm low-order moment of special Nonuniform Linear Array the extension of the even linear array of more array elements Infinite Norm low-order moment, extension are oriented to matrix and obtain the extension guiding matrix of virtual uniform linear array.If array element spacing ε=λ/2, Array element coordinate is d=[d1,d2,...,dM]=ε [h1,h2,...,hM], wherein h1,h2,…,hMAll it is integer.Infinite Norm is low Rank square can be expressed as C=[c1,c2,...,cM], whereinM=1,2 ..., M.According to The characteristics of special Nonuniform Linear Array, Nonuniform Linear Array can invent the even linear array of more array elements, if according to Nonuniform Linear Array The maximal correlation being calculated postponesThen the Virtual array number of virtual uniform linear array isIt is individual.If order(l-q) ε=dw-dm,1≤w, m≤M, then extending Infinite Norm low-order moment isWherein It is B (θ)=[b (θ that extension, which is oriented to matrix,1),b(θ2),..., b(θP)], p-th of extension steering vector isP=1,2 ..., P.
Step 3. carries out singular value decomposition to extension Infinite Norm low-order moment R, obtains signal subspace component, then by signal Subspace component extraction observation signal y.
Step 4. divides observation space, constructs redundant dictionary.Dividing mode, which is divided into, angularly divides and waits sinusoidal division, this Equiangularly illustrated in embodiment exemplified by dividing mode, by whole observation spaceIt is empty by G parts are angularly divided into Between grid, i.e. μ=[μ1,μ2,...,μG], wherein G ＞ ＞ P, μgG part space lattices of expression observation space, g=1, 2 ..., G a, it is assumed that signal is corresponded to per a space lattice.WillThe extension of first virtual uniform linear array is oriented to matrix B and expanded It is charged in the whole observation space by angularly dividing, constructs redundant dictionaryI.e. Wherein g-th of dictionary atom isG=1,2 ..., G.
Linear array array has certain orthogonality between being oriented to each steering vector of matrix, can be used as observing matrix, and orthogonal Property it is bigger, signal it is sparse reconstruct it is more accurate.It can be seen from the variation tendency research of matrix orthogonality is oriented to even linear array array, When observation space existsIn the range of, the redundant dictionary of angularly model split is pressed in selectionAs observing matrix Φ；Work as sight Space is surveyed to existIn the range of, the redundant dictionary of mapping mode division is pressed in selectionAs observing matrix Φ.
Step 5. initialization residual error v0, atom sequence number indexed set close Ω0With atom set Q0.Make residual error v0=y, atomic number Number index set omega0And atom set Q0Empty set is initialized as, if current iteration number is t=1.
Step 6. calculates residual error vt-1With atom b (μg) inner product, record inner product maximum and its corresponding atom sequence numberAtom sequence number indexed set is updated to closeAnd atom setWherein ∪ represents union,Carry out zero-setting operation.
Step 7. obtains approximation signal with least square methodUpdate residual error
Step 8. judges whether iterations t and number of source P meets condition t ＞ P, if not satisfied, making t=t+1, returns Step 6 continues iteration；If satisfied, direction corresponding to then exporting the conjunction of atom sequence number indexed set is to estimate angle
As shown in Fig. 2 to 7 simulation result, according to the variation tendency research that matrix orthogonality is oriented to even linear array array Understand, when observation space existsIn the range of, the redundant dictionary of angularly model split is pressed in selectionAs observing matrix Φ；When observation space existsIn the range of, the redundant dictionary of mapping mode division is pressed in selectionAs observation Matrix Φ.
Under impulsive noise environment, Fig. 2, Fig. 3, Fig. 4 and Fig. 5 emulation experiment parameter setting are as follows：
7 antennas are used during direction finding, fast umber of beats is 100, and broad sense signal to noise ratio is arranged to 0dB, and angle-resolved unit is 0.1 °, space arrival bearing is { 30 °, 20 ° }, in order to which more intuitively performance estimate and the gap of actual value, actual value assume it Projection coefficient is 0.1, and is labeled in analogous diagram with asterisk；
The algorithm of Fig. 2 and Fig. 4 emulation is the infinite of the special Nonuniform Linear Array that the present invention designs under impulsive noise environment Norm OMP compressed sensing direction-finding methods, can simply be denoted as SNL-IN-OMP under impulsive noise environment；
The algorithm of Fig. 3 and Fig. 5 emulation is the method combined in even linear array using the OMP compressed sensings realized and FLOM, Simply it is denoted as FLOM-OMP；
The parameter setting of SNL-IN-OMP methods is as follows under impulsive noise environment in Fig. 2 and Fig. 4：Special Nonuniform Linear Array is adopted With the continuous delay array of the maximum of 7 array elements, its array element putting position isWhat is expanded is virtual Even linear array array number is 19；
Comparison diagram 2 and Fig. 3 can see for two independent sources, designed method characteristic index be 0.8 it is strong Arrival bearing can be accurately estimated under impulsive noise environment, and uses the FLOM-OMP direction findings of same antenna number to fail；
Comparison diagram 4 and Fig. 5 can see for two coherents, designed method characteristic index be 1.5 it is weak Arrival bearing can be accurately estimated under impulsive noise environment, and uses the FLOM-OMP direction findings of same antenna number to fail.
Under Gaussian noise environment, Fig. 6 and Fig. 7 emulation experiment parameter setting are as follows：
Special nonuniform noise uses the minimum-redundancy linear arrays of 5 array element, and array element putting position is Under Gaussian noise environment, designed SNL-IN-OMP is clearly denoted as MRLA-OMP, and (OMP under the conditions of minimum-redundancy linear arrays is calculated Method), in order to verify the performance of set calculating method, 2 emulation experiments are carried out, the algorithm has been put down with MUSIC algorithms, based on space OMP (ULA-OMP) algorithm under the conditions of sliding MUSIC (SS-MUSIC) algorithms and even linear array is compared.And will success Standard of the probability as measure algorithm performance, when the actual value of the angle of information source to be estimated and the absolute value of estimate error are less than When 1, then it is assumed that this time to information source direction estimation success；
Assuming that there is two independent sources, arrival bearing is respectively 6 ° and 12 °, and angle-resolved unit is 0.1 °, ambient noise For white Gaussian noise.When fast umber of beats is 100, respectively under the conditions of 5 array element even linear arrays and 5 array element minimum-redundancy linear arrays, DOA estimations are carried out to information source using OMP algorithms and MUSIC algorithms, Monte Carlo experiment number is 1000 times；
Fig. 6 is the probability of success that above-mentioned algorithm carries out DOA estimations to information source.ULA-OMP is under the conditions of even linear array in figure OMP algorithms, ULA-MUSIC be even linear array under the conditions of MUSIC algorithms, MRLA-MUSIC be minimum-redundancy linear arrays under the conditions of MUSIC algorithms.Emulation shows that under conditions of high signal/noise ratio, above-mentioned algorithm is all when angle interval is larger, fast umber of beats is more Arrival bearing can accurately be estimated with the higher probability of success.When signal to noise ratio is reduced to 0dB, ULA-MUSIC and MRLA- The probability of success of two kinds of algorithms of MUSIC has failed below 0.1；ULA-OMP algorithms can estimate arrival bearing, but into Work(probability is relatively low；The probability of success of MRLA-OMP algorithms can reach 0.9.As can be seen here, MRLA-OMP algorithms are in above-mentioned algorithm In there is highest angle measurement resolving power；
Assuming that there is two coherents, arrival bearing is respectively 5 ° and 11 °, and angle-resolved unit is 0.1 °, ambient noise For white Gaussian noise.It is sharp under the conditions of 5 array element even linear arrays and 5 array element minimum-redundancy linear arrays respectively when fast umber of beats is 100 DOA estimations are carried out with OMP algorithms.Because SS-MUSIC algorithms can not handle coherent under conditions of minimum-redundancy linear arrays, So using the 10 array element even linear arrays equal with 5 array element minimum-redundancy linear arrays array apertures as receiving array.It is uniform in 5 array elements DOA estimations are carried out to coherent using SS-MUSIC algorithms under linear array and 10 array element even linear array backgrounds, Monte Carlo is real Number is tested as 1000 times；
Fig. 7 is the probability of success that above-mentioned algorithm carries out DOA estimations to coherent.ULA-SS-MUSIC (5) is equal in figure MUSIC algorithms based on space smoothing, array number 5 under the conditions of even linear array；ULA-SS-MUSIC (10) is even linear array condition Under the MUSIC algorithms based on space smoothing, array number 10.Simulation result shows, ULA-SS-MUSIC (5) and ULA-SS- MUSIC (10) needs higher signal to noise ratio to obtain the larger probability of success and when signal to noise ratio reduces, and algorithm performance is drastically Decline, or even failure.It can be seen that seriously reduce MUSIC calculations to lose space smoothing decorrelation LMS method of the array aperture as cost The angle measurement resolving power of method.ULA-OMP algorithms can handle coherent under Low SNR but its probability of success is relatively low.With Above-mentioned three kinds of algorithms are compared, and MRLA-OMP algorithms probability of success in 5dB can level off to 1, it is seen that algorithm proposed by the present invention Still there is higher angle measurement resolving power and anti-noise ability when handling coherent.
Here it must be noted that other provided in the present invention are unaccounted partly because being all that the known of this area is known Know, according to title of the present invention or function, those skilled in the art can just find the document of related record, therefore not do Further illustrate.Technological means disclosed in this programme is not limited only to the technological means disclosed in above-mentioned embodiment, in addition to Formed technology is combined by above technical characteristic.

Claims (3)

1. a kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method, it is characterised in that concrete implementation step It is as follows：
Step 1. sets special Nonuniform Linear Array, and Infinite Norm low-order moment is constructed according to reception signal；
The extension for the even linear array that the Infinite Norm low-order moment of special Nonuniform Linear Array is invented more array elements by step 2. is infinite Norm low-order moment, extension are oriented to matrix and obtain the extension guiding matrix of virtual uniform linear array；
Step 3. carries out singular value decomposition to extension Infinite Norm low-order moment R, obtains signal subspace component, then empty by signal subspace Between component extraction observation signal y；
Step 4. divides observation space, constructs redundant dictionary；
Step 5. initialization residual error v0, atom sequence number indexed set close Ω0With atom set Q0, make residual error v0=y, atom sequence number index Set omega0And atom set Q0Empty set is initialized as, if current iteration number is t=1；
Step 6. calculates residual error vt-1With atom b (μg) inner product, record inner product maximum and its corresponding atom sequence numberAtom sequence number indexed set is updated to closeAnd atom set Wherein ∪ represents union,Carry out zero-setting operation；
Step 7. obtains approximation signal with least square methodUpdate residual error
Step 8. judges whether iterations t and number of source P meets condition t ＞ P, if not satisfied, making t=t+1, is then back to Continue iteration to step 6；If satisfied, direction corresponding to then exporting the conjunction of atom sequence number indexed set, as estimates angleWherein t represents iterations；
2. a kind of Efficient Compression based on special Nonuniform Linear Array according to claim 1 perceives direction-finding method, its feature It is：Special Nonuniform Linear Array described in step 1 includes minimum redundant array, maximum continuous delay array and minimum clearance Array.
3. a kind of Efficient Compression based on special Nonuniform Linear Array according to claim 1 perceives direction-finding method, its feature It is：The dividing mode of division observation space described in step 4, which is divided into, angularly divides and waits sinusoidal two kinds of division.
CN201710810481.6A 2017-09-11 2017-09-11 Efficient compressed sensing direction-finding method based on special inhomogeneous linear array Active CN107677988B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710810481.6A CN107677988B (en) 2017-09-11 2017-09-11 Efficient compressed sensing direction-finding method based on special inhomogeneous linear array

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710810481.6A CN107677988B (en) 2017-09-11 2017-09-11 Efficient compressed sensing direction-finding method based on special inhomogeneous linear array

Publications (2)

Publication Number Publication Date
CN107677988A true CN107677988A (en) 2018-02-09
CN107677988B CN107677988B (en) 2021-05-11

Family

ID=61135819

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710810481.6A Active CN107677988B (en) 2017-09-11 2017-09-11 Efficient compressed sensing direction-finding method based on special inhomogeneous linear array

Country Status (1)

Country Link
CN (1) CN107677988B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108519576A (en) * 2018-03-21 2018-09-11 华南理工大学 Underwater Wave arrival direction estimating method based on the adjustable Nonuniform Linear Array of angle and device

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080231505A1 (en) * 2007-03-23 2008-09-25 Weiqing Zhu Method of Source Number Estimation and Its Application in Method of Direction of Arrival Estimation
CN103902826A (en) * 2014-04-02 2014-07-02 哈尔滨工程大学 Method for tracking multiple moving targets under impact noise environment
CN106291541A (en) * 2016-10-28 2017-01-04 中国人民解放军信息工程大学 MIMO radar array design methodology based on non-homogeneous Subarray partition

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080231505A1 (en) * 2007-03-23 2008-09-25 Weiqing Zhu Method of Source Number Estimation and Its Application in Method of Direction of Arrival Estimation
CN103902826A (en) * 2014-04-02 2014-07-02 哈尔滨工程大学 Method for tracking multiple moving targets under impact noise environment
CN106291541A (en) * 2016-10-28 2017-01-04 中国人民解放军信息工程大学 MIMO radar array design methodology based on non-homogeneous Subarray partition

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
刁鸣 等: "基于非均匀线阵的压缩感知波达方向估计", 《计算机工程》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108519576A (en) * 2018-03-21 2018-09-11 华南理工大学 Underwater Wave arrival direction estimating method based on the adjustable Nonuniform Linear Array of angle and device
CN108519576B (en) * 2018-03-21 2021-07-20 华南理工大学 Underwater direction of arrival estimation method and device based on included angle adjustable non-uniform linear array

Also Published As

Publication number Publication date
CN107677988B (en) 2021-05-11

Similar Documents

Publication Publication Date Title
CN106021637B (en) DOA estimation method based on the sparse reconstruct of iteration in relatively prime array
CN110824415B (en) Sparse direction-of-arrival angle estimation method based on multiple-sending and multiple-receiving array
CN110109050B (en) Unknown mutual coupling DOA estimation method based on sparse Bayes under nested array
CN110244272B (en) Direction-of-arrival estimation method based on rank-denoising model
CN107238812B (en) Robust dynamic direction finding method based on minimum gap array
CN112379327A (en) Two-dimensional DOA estimation and cross coupling correction method based on rank loss estimation
CN104931920A (en) Rapid estimation algorithm IESPRIT of spatial signal DOA based on arbitrary array
Mao et al. An Improved DOA Estimation Algorithm Based on Wavelet Operator.
CN112255629A (en) Sequential ESPRIT two-dimensional incoherent distribution source parameter estimation method based on combined UCA array
CN113567913B (en) Two-dimensional plane DOA estimation method based on iterative re-weighting dimension-reducible
CN113835063B (en) Unmanned aerial vehicle array amplitude and phase error and signal DOA joint estimation method
CN111896929B (en) DOD/DOA estimation algorithm of non-uniform MIMO radar
Bhargav et al. Compressive sensing based doa estimation for multi-path environment
CN107677988A (en) A kind of Efficient Compression based on special Nonuniform Linear Array perceives direction-finding method
He et al. Efficient underwater two-dimensional coherent source localization with linear vector-hydrophone array
CN106844886B (en) Target direction of arrival acquisition method based on principal component analysis
Choi Maximum likelihood estimation for angles of arrival of coherent signals using a coherency profile
CN113093093A (en) Vehicle positioning method based on linear array direction of arrival estimation
CN112327244A (en) L-shaped array-based two-dimensional incoherent distributed target parameter estimation method
Wu et al. An efficient gridless 2-D DOA estimation method for sparse and uniform L-shaped arrays
Liu et al. A semi-real-valued capon algorithm for 2-D DOA estimation of coherent signals with L-shape array
Al Jabr et al. Modified UCA-ESPRIT for estimating DOA of coherent signals using one snapshot
Li et al. Combined real-valued subspace based two dimensional angle estimation using L-shaped array
CN108957386B (en) Incoherent direction of arrival estimation method under phase error
Yang et al. High-resolution algorithm based on temporal-spatial extrapolation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant