CN104793213A - Long-distance laser ranging echo signal identification method based on sparse representation - Google Patents
Long-distance laser ranging echo signal identification method based on sparse representation Download PDFInfo
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- CN104793213A CN104793213A CN201510137929.3A CN201510137929A CN104793213A CN 104793213 A CN104793213 A CN 104793213A CN 201510137929 A CN201510137929 A CN 201510137929A CN 104793213 A CN104793213 A CN 104793213A
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- rarefaction representation
- laser ranging
- echo
- signal
- echo signal
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Classifications
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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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/08—Systems determining position data of a target for measuring distance only
-
- 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
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/483—Details of pulse systems
- G01S7/486—Receivers
- G01S7/487—Extracting wanted echo signals, e.g. pulse detection
- G01S7/4873—Extracting wanted echo signals, e.g. pulse detection by deriving and controlling a threshold value
Abstract
The invention provides a long-distance laser ranging echo signal identification method based on sparse representation. The long-distance laser ranging echo signal identification method based on sparse representation is used for applying a sparse decomposition algorithm to the field of long-distance laser ranging. The long-distance laser ranging echo signal identification method based on sparse representation specifically comprises the following steps that firstly, a short-distance laser echo signal is obtained through detection, and an optimal wavelet base of the laser echo signal is calculated; secondly, the optimal wavelet base is extended, and an optimal wavelet atom library is constructed; thirdly, a fast fourier transform algorithm and an OMP algorithm are combined, and sparse decomposition is conducted on a long-distance laser echo signal, so that sparse representation of the echo signal is obtained; fourthly, a sparse representation coefficient is processed to obtain a threshold value, a feature sparse representation coefficient is obtained, the moment when an echo happens is determined according to the feature sparse representation coefficient, and therefore the echo is identified.
Description
Technical field
The present invention relates to long distance laser ranging echo blipology, be specifically related to a kind of long distance laser ranging echo signal recognition method based on rarefaction representation.
Background technology
Laser because its brightness is high, monochromaticity and good directionality, be the desirable range finding light source that people thirst for obtaining for a long time, therefore after its occurs, be just used to range finding less than year.Can say that laser ranging be laser the earliest, is also one of application that laser technology is the most ripe.Laser measurement system not only civilian, and countries in the world military in be obtained for and apply widely.In long distance laser range measurement system; the precision of range finding and accuracy depend on the accurate identification to echoed signal; usual echoed signal is attenuated to very weak and with various noise; and very large by the impact of weather, so the identification of echoed signal has become a study hotspot and the difficult point of laser ranging field.
In prior art, rarefaction representation is that a kind of adaptivity is good, the signal method for expressing be concise in expression, by crossing the atom that in complete storehouse, adaptive selection is the most similar to signal, and make the atom number of selection few as much as possible, thus original signal is expressed as the linear expansion of one group of minimum basis function.It is good that sparse signal representation possesses adaptivity, and the feature such as be concise in expression, and has been widely applied to many aspects of the signal transacting such as denoising, compression, coding, parameter estimation, feature extraction, target identification.
The transform domain developing into signal of Its Sparse Decomposition represents and provides new developing direction with target identification.The method, according to the feature of signal to be decomposed, selects the atom pressing close to residual signals most from over-complete dictionary of atoms, and what decompose that the atomic parameter that obtains characterizes is the feature of representative waveform.But in actual applications, there is the problems such as calculating degree is complicated, Riming time of algorithm is long in Its Sparse Decomposition algorithm, propose high requirement to hardware implementing and algorithm time, simultaneously in actual environment, the noise that signal comprises in real work brings more complicated resolution to decomposition.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of long distance laser ranging echo signal recognition method based on rarefaction representation, the method adopts based on wavelet analysis and FFT signal Its Sparse Decomposition OMP algorithm, the complexity of effective reduction Its Sparse Decomposition algorithm, improve the speed of signal Its Sparse Decomposition and the effect of signal Its Sparse Decomposition, improve the discrimination to long distance laser ranging echo signal and speed.
For achieving the above object, the invention provides following technical scheme:
Based on a long distance laser ranging echo signal recognition method for rarefaction representation, it is characterized in that described method comprises the steps: step one: record in-plant laser echo signal, and calculate the optimal wavelet substrate of this signal; Step 2: expand optimal wavelet substrate, constructs optimal wavelet atom; Step 3: be combined with OMP algorithm by fast fourier transform algorithm, to long distance laser echoed signal Its Sparse Decomposition, obtains the rarefaction representation of echoed signal; Step 4: get threshold value to rarefaction representation coefficient, obtains feature rarefaction representation coefficient, determines the moment that echo occurs, thus identify echo according to feature rarefaction representation coefficient.
Further, specifically comprise the following steps in step one: 11: set up wavelet library, described wavelet library is the set of one group of small echo atom; 12: the similarity calculating small echo atom in closely laser ranging echoed signal and described wavelet library; 13: the small echo atom the highest with closely laser ranging echoed signal similarity degree is defined as optimal wavelet substrate;
Further, specifically comprise the following steps in step 2: 21: described optimal wavelet substrate is ψ (f, ζ, τ, t), wherein f, ζ, τ and t represent corresponding frequency, decay factor, delay parameter and time parameter respectively; 22: with default sample frequency for time delay interval, expand by different time shift, structure trip represents different time parameter, and the optimal wavelet atom of different delayed time parameter is shown in list;
Further, specifically comprise the following steps in step 3: 31: utilize FFT to realize long distance laser ranging echo signal Its Sparse Decomposition, thus obtain a series of atomic parameters describing this signal characteristic; 32: adopt 0MP algorithm to obtain signal and selected component on atom and residual component at each, then residual component is decomposed to the rarefaction representation obtaining this signal;
Further, specifically comprise the following steps in step 4: 41: according to 3 σ criterions, get threshold value to described rarefaction representation coefficient, obtain feature rarefaction representation coefficient, wherein said σ is the standard deviation of described rarefaction representation coefficient; 42: determine that the moment occurs long distance laser ranging echo according to the feature rarefaction representation coefficient obtained, thus identify echo.
Accompanying drawing explanation
In order to make the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail, wherein:
Fig. 1 is the long distance laser ranging echo Signal analysis process flow diagram based on rarefaction representation.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
Fig. 1 is the process flow diagram of the method for the invention, and this method comprises the following steps:
S1: record in-plant laser echo signal, and the optimal wavelet substrate calculating this signal, concrete steps are as follows:
S11: closely record laser echo signal and be designated as y (t);
S12: set up wavelet library Φ, carries out parametrization expression by described wavelet library Φ, is designated as Φ={ ψ (f, ζ, τ, t) }.Wherein f, ζ, τ and t represent corresponding frequency, decay factor, delay parameter and time parameter respectively, and the value that parameter f, ζ and τ can be discrete in presetting scope, this presetting scope can be determined according to priori.For long distance laser ranging echo Signal analysis, selected wavelet library is Morlet small echo, and its expression formula is
S13: the similarity calculating small echo atom ψ (f, ζ, τ, t) in signal y (t) and described wavelet library, wherein similarity can be evaluated with related coefficient k, and related coefficient can be expressed as
< ψ (f, ζ, τ, t), y> represent the inner product with signal y at the bottom of wavelet basis, || ψ ||
2with || y||
2represent at the bottom of wavelet basis respectively and the mould of signal;
S14: when at the bottom of wavelet basis when constantly changing, can produce different related coefficients, choosing at the bottom of wavelet basis corresponding to maximum correlation coefficient is optimal wavelet substrate;
S2: optimal wavelet substrate is expanded, construct optimal wavelet atom, concrete steps are as follows:
S21: described optimal wavelet substrate is ψ (f, ζ, τ, t), wherein f, ζ, τ and t represent corresponding frequency, decay factor, delay parameter and time parameter respectively;
S22: with default sample frequency for time delay interval, expands by different time shift, and structure trip represents different time parameter, and the optimal wavelet atom of different delayed time parameter is shown in list;
S3: fast fourier transform algorithm is combined with OMP algorithm, to long distance laser echoed signal Its Sparse Decomposition, obtain the rarefaction representation of echoed signal, concrete steps are as follows:
S31: utilize FFT to realize long distance laser ranging echo signal Its Sparse Decomposition, thus obtain a series of atomic parameters describing this signal characteristic;
S32: adopt 0MP algorithm to obtain signal and selected component on atom and residual component at each, then residual component is decomposed to the rarefaction representation obtaining this signal;
S4: threshold value is got to rarefaction representation coefficient, obtain feature rarefaction representation coefficient, determine the moment that echo occurs further, thus identify echo, concrete steps are as follows:
S41: the rarefaction representation that note step S3 obtains is sparse is b, and compute sparse represents the standard deviation sigma of coefficient vector b.Computing formula is
), wherein b
irepresent the element in rarefaction representation b;
S42: judge b
iif, b
i< 3 σ, then b
i=0, i=i+1; If i>N, then stop calculating, otherwise continue to judge b
i;
S43: feature rarefaction representation coefficient can be obtained according to step 42
therefrom determine the moment that echo occurs, thus identify echo.
By above step, the identification of echoed signal in long distance laser range finding can be realized.
What finally illustrate is, above preferred embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although by above preferred embodiment to invention has been detailed description, but those skilled in the art are to be understood that, various change can be made to it in the form and details, and not depart from claims of the present invention limited range.
Claims (5)
1., based on a long distance laser ranging echo signal recognition method for rarefaction representation, it is characterized in that, comprise the following steps:
Step one: record in-plant laser echo signal, and the optimal wavelet substrate calculating this signal;
Step 2: expand optimal wavelet substrate, constructs optimal wavelet atom;
Step 3: be combined with OMP algorithm by fast fourier transform algorithm, to long distance laser echoed signal Its Sparse Decomposition, obtains the rarefaction representation of echoed signal;
Step 4: get threshold value to rarefaction representation coefficient, obtains feature rarefaction representation coefficient, determines the moment that echo occurs, thus identify echo according to feature rarefaction representation coefficient.
2. a kind of long distance laser ranging echo signal recognition method based on rarefaction representation according to claim 1, it is characterized in that described step 1 specifically comprises the following steps: 11: set up wavelet library, described wavelet library is the set of one group of small echo atom; 12: the similarity calculating small echo atom in closely laser ranging echoed signal and described wavelet library; 13: the small echo atom the highest with closely laser ranging echoed signal similarity degree is defined as optimal wavelet substrate.
3. according to a kind of long distance laser ranging echo signal recognition method based on rarefaction representation according to claim 1, it is characterized in that described step 2 specifically comprises the following steps: 21: described optimal wavelet substrate is ψ (f, ζ, τ, t), wherein f, ζ, τ and t represent corresponding frequency, decay factor, delay parameter and time parameter respectively; 22: with default sample frequency for time delay interval, expand by different time shift, structure trip represents different time parameter, and the optimal wavelet atom of different delayed time parameter is shown in list.
4. according to a kind of long distance laser ranging echo signal recognition method based on rarefaction representation according to claim 1, it is characterized in that described step 3 specifically comprises the following steps: 31: utilize FFT to realize long distance laser ranging echo signal Its Sparse Decomposition, thus obtain a series of atomic parameters describing this signal characteristic; 32: adopt 0MP algorithm to obtain signal and selected component on atom and residual component at each, then residual component is decomposed to the rarefaction representation obtaining this signal.
5. according to a kind of long distance laser ranging echo signal recognition method based on rarefaction representation according to claim 1, it is characterized in that described step 4 specifically comprises the following steps: 41: according to 3 σ criterions, threshold value is got to described rarefaction representation coefficient, obtain feature rarefaction representation coefficient, wherein said σ is the standard deviation of described rarefaction representation coefficient; 42: determine that the moment occurs long distance laser ranging echo according to the feature rarefaction representation coefficient obtained, thus identify echo.
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020149512A1 (en) * | 2001-04-16 | 2002-10-17 | Nissan Motor Co., Ltd. | Radar apparatus |
| US20060028373A1 (en) * | 2004-08-06 | 2006-02-09 | Time Domain Corporation | System and method for active protection of a resource |
| CN103792000A (en) * | 2014-02-20 | 2014-05-14 | 苏州大学 | Method and device for detecting transient components in signal based on sparse representation |
| CN103927761A (en) * | 2014-05-05 | 2014-07-16 | 重庆大学 | Fault weak signal feature extraction method based on sparse representation |
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