CN105548994B - A kind of underwater more bright spot mesh object detection methods based on compressed sensing - Google Patents
A kind of underwater more bright spot mesh object detection methods based on compressed sensing Download PDFInfo
- Publication number
- CN105548994B CN105548994B CN201510900596.5A CN201510900596A CN105548994B CN 105548994 B CN105548994 B CN 105548994B CN 201510900596 A CN201510900596 A CN 201510900596A CN 105548994 B CN105548994 B CN 105548994B
- Authority
- CN
- China
- Prior art keywords
- target
- bright spot
- baseband signal
- compressed sensing
- highlight structure
- 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.)
- Expired - Fee Related
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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
- G01S7/539—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Abstract
The present invention discloses a kind of underwater more bright spot mesh object detection methods based on compressed sensing, including：(1) transmitting baseband signal may be constructed over-complete dictionary of atoms, and reception signal is expressed as the product of over-complete dictionary of atoms and highlight structure；(2) matching pursuit algorithm of compressed sensing technology is used, estimates the highlight structure of target；(3) go to correct the coefficient of matched filter using the target highlight structure of estimation gained；(4) matched filtering processing is carried out to target echo with the coefficient of revised matched filter.In the detection process of present invention bright spot targets more under water, the matched filter output of " hedgehog " shape can be improved to succinct unimodal output, so as to improve signal transacting gain, reduce false-alarm quantity, be effectively improved the detection performance of sonar.
Description
Technical field
The present invention relates to sonar signals processing technology field, more particularly to it is a kind of underwater how bright based on compressed sensing
The detection method of point target.
Background technology
It is well known that active sonar emission detection signal first, target reflects in water echo is then received to detect mesh
Mark and obtain the information such as position and the kinematic parameter of target.Current active sonar uses pulse regime, transmitting broadband letter mostly
Number, higher processing gain is obtained using matched filtering technique.But submarine target especially underwater hiding-machine, configuration one
As it is more complicated, target echo includes profile echo, corner reflection ripple etc., and comparison of ingredients is complicated.So this kind of target can be regarded as
The combination scattering body that a few strong reflector and multiple random scatterers are formed, these scattering objects can regard bright spot knot as
Structure, and it is relevant with the posture of target.When direct impulse is big bandwidth, long pulse width signal, each bright spot echo overlaps each other generation
Random structure is presented in interference, echo strength.After echo signal of underwater target carries out quadrature demodulation, matched filtering processing, mesh
" hedgehog " structure is presented in the result for marking echo, as shown in figure 1, this result is unfavorable for the judgement of target and parameter is estimated
Meter, and multiple targets may be mistaken for, produce false-alarm.
Compressive sensing theory is that a kind of new signal processing theory, its thought are caused by field of signal processing recent years
Openness using signal is compressed measurement to signal, and then signal is rebuild using corresponding restructing algorithm.Compression
Perception can lead to too small amount of sampled value to signal reconstruction, breach the limitation of traditional Shannon's sampling theorem, greatly reduce
Collection, the difficulty of processing to high-resolution signal, it is mainly used in the estimation of compression of images, condition of sparse channel.Match tracing (MP)
Algorithm is a kind of sparse algorithm for reconstructing based on the greedy tracking of iteration, and basic thought is each time in iterative process, from excessively complete
The atom structure sparse bayesian learning that selection is most matched with signal in atom, and obtain signal and represent residual error, then proceed to selection and
Signal residual error most matched atoms, by certain number of iterations, signal can be by some atom linear expressions.
The content of the invention
In more highlight structures of submarine target, strong reflector has openness, can use the underwater mesh of 3-6 bright spot expression
Target key reflections characteristic.The present invention realizes the estimation of submarine target bright spot distribution using sensing technology is compressed, and utilizes target
Bright spot distribution character, the coefficient of matched filter is modified, with revised matched filter to target echo at
Reason, improve the detection performance of underwater more bright spot targets.
To reach above-mentioned purpose, the technical proposal of the invention is realized in this way：
A kind of underwater more bright spot mesh object detection methods based on compressed sensing, comprise the following steps：
(1) over-complete dictionary of atoms is formed using transmitting baseband signal, then target echo baseband signal was expressed as complete original
Word bank and the product of target highlight structure add additive white Gaussian noise；
(2) matching pursuit algorithm of compressed sensing technology is used, the target highlight structure to improve and estimation obtain dilute
Thin target highlight structure；
(3) the target highlight structure obtained using estimation goes to correct the coefficient of matched filter；
(4) original target echo baseband signal is carried out at matched filtering with the coefficient of revised matched filter
Reason.
Preferably, step (1) described over-complete dictionary of atoms is matrix, and each column vector of the matrix is prolonged by some
When transmitting baseband signal.
Preferably, the target highlight knot that step (2) described matching pursuit algorithm using compressed sensing technology improves
The step of structure is：
(201) each row in the over-complete dictionary of atoms seek inner product with target echo baseband signal respectively, find maximum
Value, and the columns where corresponding column vector, the maximum and the columns respectively with the amplitude of target highlight structure and
It is delayed relevant；
(202) bright spot of target highlight structure is obtained using the maximum and the columns；
(203) target echo baseband signal is updated, known bright spot is subtracted from target echo baseband signal and is formed
Echo-signal, obtain the residual signals of target echo baseband signal；
(204) processing procedure of step (201)-(203) is continued to the residual signals of target echo baseband signal, obtained
Whole target highlight structure.
Further, step (2) is described estimates that obtaining the method for sparse target highlight structure is：It is bright from complete target
3-6 strong bright spots are selected in point structure, as target highlight structure.
Preferably, the method that obtains of the target echo baseband signal is：The target that the receiving array of active sonar receives
Echo passes through signal condition and analog-to-digital conversion, and obtained data signal carries out conventional Wave beam forming, quadrature demodulation, down-sampled,
Obtain target echo baseband signal.
Relative to prior art, the advantage of the invention is that：
The innovative point of the present invention is the sparse characteristic using target highlight, and the match tracing in compressed sensing technology is calculated
Method is used for the estimation of target highlight structure, the highlight structure amendment matched filter coefficient obtained with estimation, target echo is entered
Row matched filtering is handled.It improves the processing gain to underwater more highlight structure target detections, reduces target void
Alert quantity.
Brief description of the drawings
Fig. 1 is the ordinary matches filtering process result of more bright spot target echoes；
Fig. 2 is the technical scheme block diagram of the underwater more bright spot target detections of the present invention；
Fig. 3 is the embodiment flow chart of the underwater more bright spot target detections of the present invention；
Fig. 4 is the highlight structure of matching pursuit algorithm of the present invention estimation；
Fig. 5 is the result of the revised matched filter of the present invention.
Embodiment
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the present invention can phase
Mutually combination.
The present invention is described in further detail below in conjunction with the accompanying drawings.
The present invention proposes a kind of underwater more bright spot mesh object detection methods based on compressed sensing, below to the tool of the present invention
Body embodiment is described in detail.
S (n) (0≤n≤N-1) expressions of the baseband waveform of transmission signal, distribution situation h (n) (0≤n≤L- of bright spot
1) represent.Quadrature demodulation is carried out to the target echo received, obtains baseband signal R (n) (0≤n≤M-1, M=N+L-1).
The superposition of the strong bright spot echo of multiple sparse distributions is contained in 2.R (n), can be expressed as
Wherein, u (n) is additive white Gaussian noise.Above formula is write as matrix form
It can be abbreviated as
R=Ch+u (3)
3. solving h according to formula (3), the matching in compressive sensing theory can be utilized to chase after middle algorithm (MP algorithms), solved
Step is as follows：
(1) p=1, r are madep=R, ciRepresenting matrix C i-th of column vector,For ciAssociate matrix, by Matrix C
Back up as Cb。
(2) solution matrix C column vector and rpInner product, i.e.,Obtain inner product vector
B maximum spAnd obtain maximum when Matrix C column vector label Ip。
(3) obtain representing the vectorial h of highlight structure p-th of valueIpRepresent position of the value in vector.
(4) p=p+1 is made, updates residual vectorOrder matrix C I simultaneouslyp0 is classified as, i.e.,
(5) (2) (3) (4) are repeated, until obtain complete vectorial h, i.e. the bright spot distribution of target.
(6) vectorial h is sparse to retain 3-6 maximum, and its residual value can be obtained with zero setting
4. utilize over-complete dictionary of atoms and the coefficient of highlight structure amendment matched filter.
5. the copy signal R of the matched filter using amendmentPMatched filtering processing is carried out to receiving baseband signal R, with
And follow-up signal processing algorithm.
The embodiment of the present invention can be described by Fig. 2, Fig. 3.
In the detection process of present invention bright spot targets more under water, the matched filter output of " hedgehog " shape can be changed
Enter for succinct unimodal output, so as to improve signal transacting gain, reduce false-alarm quantity, be effectively improved the spy of sonar
Survey performance.Fig. 1, Fig. 4 and Fig. 5 intuitively show the effect of the present invention：Underwater more bright spot target echoes are directly over matching filter
Ripple processing, is shown as " hedgehog " shape shown in Fig. 1；By the present invention it is estimated that the highlight structure of target, three width in Fig. 4
Figure show respectively the distribution of the real part of highlight structure, imaginary part and mould；Using the highlight structure of estimation gained to matched filtering system
Number is modified, and more bright spot target echoes are detected with revised matched filter, and effect is as shown in figure 5, mixed and disorderly peak value shape
As succinct unimodal, processing gain is improved, false target quantity is reduced, is easy to the judgement of target.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
God any modification, equivalent substitution and improvements made etc., should be included in the scope of the protection with principle.
Claims (5)
1. a kind of underwater more bright spot mesh object detection methods based on compressed sensing, it is characterised in that comprise the following steps：
(1) over-complete dictionary of atoms is formed using transmitting baseband signal, then target echo baseband signal is expressed as over-complete dictionary of atoms
Additive white Gaussian noise is added with the product of target highlight structure；
(2) matching pursuit algorithm of compressed sensing technology is used, the target highlight structure to improve and estimation obtain sparse
Target highlight structure；
(3) the target highlight structure obtained using estimation goes to correct the coefficient of matched filter；
Modification method is：
Wherein RpFor the coefficient of matched filter, CbFor over-complete dictionary of atoms,For sparse target highlight structure；
(4) matched filtering processing is carried out to original target echo baseband signal with the coefficient of revised matched filter.
2. a kind of underwater more bright spot mesh object detection methods based on compressed sensing according to claim 1, its feature exist
In step (1) described over-complete dictionary of atoms is matrix, and each column vector of the matrix is the transmitting baseband by some delay
Signal.
3. a kind of underwater more bright spot mesh object detection methods based on compressed sensing according to claim 1, its feature exist
It is in the step of, target highlight structure that step (2) described matching pursuit algorithm using compressed sensing technology improves：
(201) each row in the over-complete dictionary of atoms seek inner product with target echo baseband signal respectively, maximizing, with
And the columns where corresponding column vector, the maximum and the columns have with the amplitude of target highlight structure and delay respectively
Close；
(202) bright spot of target highlight structure is obtained using the maximum and the columns；
(203) target echo baseband signal is updated, time that known bright spot is formed is subtracted from target echo baseband signal
Ripple signal, obtain the residual signals of target echo baseband signal；
(204) processing procedure of step (201)-(203) is continued to the residual signals of target echo baseband signal, obtained complete
Target highlight structure.
4. a kind of underwater more bright spot mesh object detection methods based on compressed sensing according to claim 1, its feature exist
In the method that step (2) estimation obtains sparse target highlight structure is：3- is selected from complete target highlight structure
6 strong bright spots, as target highlight structure.
5. a kind of underwater more bright spot mesh object detection methods based on compressed sensing according to claim any one of 1-4,
Characterized in that, the method that obtains of the target echo baseband signal is：The target echo that the receiving array of active sonar receives
By signal condition and analog-to-digital conversion, obtained data signal carries out conventional Wave beam forming, quadrature demodulation, down-sampled, obtains
Target echo baseband signal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510900596.5A CN105548994B (en) | 2015-12-08 | 2015-12-08 | A kind of underwater more bright spot mesh object detection methods based on compressed sensing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510900596.5A CN105548994B (en) | 2015-12-08 | 2015-12-08 | A kind of underwater more bright spot mesh object detection methods based on compressed sensing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105548994A CN105548994A (en) | 2016-05-04 |
| CN105548994B true CN105548994B (en) | 2017-12-12 |
Family
ID=55828304
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510900596.5A Expired - Fee Related CN105548994B (en) | 2015-12-08 | 2015-12-08 | A kind of underwater more bright spot mesh object detection methods based on compressed sensing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105548994B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112714083B (en) * | 2020-12-31 | 2022-10-18 | 深圳市智慧海洋科技有限公司 | Underwater sound channel estimation method, device, underwater sound equipment and storage medium |
| CN113052872B (en) * | 2021-03-12 | 2022-06-10 | 浙江大学 | Underwater moving object tracking method based on sonar image |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6654365B1 (en) * | 1998-02-24 | 2003-11-25 | L-3 Communications Corporation | Reduced complexity trellis-based multiuser detector for CDMA |
| CN102183762B (en) * | 2011-03-15 | 2012-09-05 | 北京航空航天大学 | Method for acquiring and imaging data of compressive sensing synthetic aperture radar |
| US8897571B1 (en) * | 2011-03-31 | 2014-11-25 | Raytheon Company | Detection of targets from hyperspectral imagery |
| CN104320144B (en) * | 2014-11-18 | 2017-12-22 | 电子科技大学 | Degree of rarefication self-adapting signal reconstructing method |
| CN104515981A (en) * | 2014-12-08 | 2015-04-15 | 广西大学 | Radar signal processing method and device based on compressive sensing |
| CN104977579B (en) * | 2015-07-03 | 2017-07-28 | 中国科学院声学研究所 | A kind of many bright spot target space-time detecting methods based on random covariance matrix |
-
2015
- 2015-12-08 CN CN201510900596.5A patent/CN105548994B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN105548994A (en) | 2016-05-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Shang et al. | Radar detection based on compound-Gaussian model with inverse gamma texture | |
| CN106772365B (en) | A kind of multipath based on Bayes's compressed sensing utilizes through-wall radar imaging method | |
| CN105403856B (en) | Wave arrival direction estimating method based on nested type minimum redundant array | |
| CN106707257B (en) | MIMO radar Wave arrival direction estimating method based on nested array | |
| CN105676168A (en) | Acoustic vector array DOA estimation method | |
| CN111965632B (en) | Radar target detection method based on Riemann manifold dimensionality reduction | |
| CN110231617B (en) | Target obstacle position detection method and device, vehicle-mounted radar and storage medium | |
| CN106500671B (en) | Method for determining sea water depth by decomposing laser radar waveform based on LM algorithm | |
| CN110297233B (en) | LFMCW array radar signal parallel pipelining processing method | |
| CN104076360B (en) | The sparse target imaging method of two-dimensional SAR based on compressed sensing | |
| CN112612006B (en) | Deep learning-based non-uniform clutter suppression method for airborne radar | |
| CN104111449B (en) | A kind of space-time adaptive processing method of based on broad sense inner product of improvement | |
| CN113238211B (en) | Parameterized adaptive array signal detection method and system under interference condition | |
| CN113221631B (en) | Sequence pulse anti-interference target detection method based on convolutional neural network | |
| CN106199602B (en) | A kind of Staggered-SAR echo-signals method for reconstructing | |
| CN105548994B (en) | A kind of underwater more bright spot mesh object detection methods based on compressed sensing | |
| CN104155653B (en) | SAR back projection imaging method based on feature distance subspace | |
| CN108828504A (en) | MIMO radar target direction method for quick estimating based on part waveform correlation | |
| CN106154241B (en) | Tough parallel factorial analysis algorithm under impulse noise environment | |
| CN108845318B (en) | Satellite-borne high-resolution wide-range imaging method based on Relax algorithm | |
| CN117148353B (en) | Close-range multi-target detection method and security inspection system based on millimeter wave SAR | |
| CN108490425B (en) | Angle measuring method of bistatic MIMO radar | |
| CN109061598A (en) | A kind of STAP clutter covariance matrix estimation method | |
| CN106324576B (en) | Radar target adaptive matched filter method based on autoregression model | |
| Xu et al. | A generalized sample weighting method in heterogeneous environment for space-time adaptive processing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20171212 Termination date: 20181208 |