CN116106857A - Micro-motion form identification method based on sparse time-frequency-tone frequency representation - Google Patents
Micro-motion form identification method based on sparse time-frequency-tone frequency representation Download PDFInfo
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Abstract
The invention provides a micro-motion form identification method based on sparse time-frequency modulation frequency representation, which comprises the steps of establishing a time-frequency modulation model of a typical micro-motion signal; setting radar observation parameters and jog parameters of a time-frequency modulation model of a typical jog signal, and constructing a jog scattering center model set; acquiring a sparse time-frequency modulation frequency estimation sequence of a target scattering center; calculating a reconstruction error of a sparse time-frequency modulation frequency estimation sequence of a target scattering center and a micro scattering center model set; comparing the minimum reconstruction error with the decision threshold, and judging the inching form. The invention can correctly identify different inching modes and has better robustness to noise under low signal-to-noise ratio.
Description
Technical Field
The invention mainly relates to the technical field of radar signal processing, in particular to a micro-motion form identification method based on sparse time-frequency modulation frequency representation.
Background
The micro-motion is caused by the special structure of the target under the action of specific stress, reflects the fine characteristics of the target, and can be used as an important basis for target detection and identification. The micro-motion form identification is carried out by utilizing micro-motion characteristics of the radar target, and is mainly based on a micro-Doppler modulation rule of the target, key information such as the motion characteristics of the target can be obtained by extracting micro-Doppler of the target, the motion process of the target is inverted, and then the type and the micro-motion state of the target are judged.
At present, for the time-varying non-stationary characteristic of the micro-motion signal, the micro-Doppler characteristic extraction is mainly based on curve detection of a time-frequency domain, and comprises an optimal path Viterbi algorithm, a target tracking algorithm, a ridge path rearrangement algorithm and the like. The time-frequency domain representation mainly utilizes linear time-frequency distribution and secondary Cohen time-frequency distribution, and is limited by a measured inaccuracy principle, so that the linear time-frequency resolution is lower, the secondary Cohen time-frequency distribution resolution is higher, and the cross term interference is serious when multi-component signals exist. Because the traditional two-dimensional time-frequency characterization performance is limited, the micro Doppler features are difficult to extract, and the micro form identification performance is degraded. Therefore, the development of a new micro-motion signal modulation rule to reduce the complexity of micro-motion feature extraction and realize micro-motion form robust identification has important research value.
Disclosure of Invention
Aiming at the technical problems existing in the prior art, the invention provides a micro-motion form identification method based on sparse time-frequency modulation frequency representation.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
in one aspect, the invention provides a micro-motion form identification method based on sparse time-frequency-tone frequency representation, comprising the following steps:
establishing a time-frequency modulation model under a typical inching mode;
setting radar observation parameters and jog parameters of a time-frequency modulation model under a typical jog mode, and constructing a jog scattering center model set;
acquiring a sparse time-frequency modulation frequency estimation sequence of a target scattering center;
calculating a reconstruction error of a sparse time-frequency modulation frequency estimation sequence of a target scattering center and a micro scattering center model set;
comparing the minimum reconstruction error with the decision threshold, and judging the inching form.
Further, the invention uses the mass center of the targetOEstablishing a radar observation reference coordinate system for a coordinate originO-XYZLet the target precession axis beZAn axis, which is coplanar with the advancing axis and perpendicular to the advancing axis at the initial momentOZThe axial direction isYThe axis of the shaft is provided with a plurality of grooves,Xthe axis is determined by the right hand screw rule; the angle between the radar sight and the precession axis, i.e. the average angle of view is
Azimuth angle is +.>
A time-frequency modulation model is built in conjunction with a target motion model in a typical jog pattern, wherein the typical jog pattern includes one or more of precession, wobble, and nutation.
Further, in the precession form of the present invention, the target rotates around the spin axis while rotating around the cone spin axis, and the target cone spin angular frequency is
Precession angle +.>
The target spin axis is located at the initial momentYOZIn-plane, the time-frequency modulation model in the precession form comprises an instantaneous frequency parameter equation and an instantaneous frequency parameter equation of the scattering center in the precession form, and the instantaneous frequency parameter equation is as follows:
wherein 
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in precession form, < >>
Representing the target cone rotation frequency,/->
Represents the inching amplitude->
Represents the primary phase of the water-soluble polymer,λrepresenting the signal wavelength.
Further, the invention relates to the inching amplitude
And ++>
The following are provided:
wherein 
The scattering center is located in the body coordinate system.
Further, in the swing form of the invention, the swing plane is set asYOZThe target swing amplitude is
The swing angle frequency is +.>
The initial phase of swing is +.>
，/>
For the scattering center to be located in the body coordinate system, the time-frequency modulation model in the swinging form comprises an instantaneous frequency parameter equation and an instantaneous frequency parameter equation of the scattering center in the swinging form, and the time-frequency modulation model is as follows:
wherein 
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in the form of a wobble, < >>
Representing the signal wavelength, < >>
，/>
。
Further, in the nutation form of the present invention, the target oscillates about the precession axis based on the precession, and the target rotates about the spin axis while rotating about the cone spin axis with a target cone spin angle frequency of
Precession angle +.>
The target spin axis is located at the initial momentYOZIn the plane, the swing amplitude of the target under swing is +.>
The swing angle frequency is +.>
The initial phase of swing is +.>
The swinging plane isYOZThe time-frequency modulation model in nutation form includes the instantaneous frequency parameter equation and instantaneous frequency parameter equation of the scattering center in nutation form as follows:
wherein ：
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in nutation form, < >>
Representing the signal wavelength, < >>
For the scattering center to be positioned in the body coordinate system, at the same time, for simplifying the expression of the equation, let
Further, the radar observation parameters of the invention comprise carrier frequency, pulse repetition frequency, observation duration, average view angle and azimuth angle; the micro-motion parameters comprise cone rotation frequency and cone rotation angle under a precession form, swing frequency and swing amplitude under a swing form, and cone rotation frequency, cone rotation angle, swing frequency and swing amplitude under a nutation form.
Further, the micro-scattering center model set comprises a typical micro-form instantaneous frequency sequence set
And the typical inching form instantaneous frequency sequence set +.>
The following are respectively:
wherein ,
，/>
for the length of the signal sequence, +.>
Is the total number of inching forms>
Represent the firstkForm of inching->
For discrete time series time points->
For the scattering center jog parameter, < >>
、/>
and />
Respectively indicate->
Time->
Precession, wobble and nutation instantaneous frequency sequences built under parameters, < >>
、/>
and />
Respectively indicate->
Time->
And (3) constructing a precession, swing and nutation instantaneous frequency modulation sequence under the parameters.
Further, in order to overcome the problems that the traditional orthogonal matching tracking utilizes the maximum likelihood method to relate to multidimensional parameter searching, has low operation efficiency and the like, under the sparse representation framework, short-time sparse representation of signals can be obtained by applying an improved matching tracking method to local signal segments at each moment, and the method comprises the following steps:
meanwhile, considering that different scattering centers are not intersected in a three-dimensional space, applying a sliding window form to a short-time sparse representation resultKThe mean value clustering realizes the association of the scattering center in the time-frequency modulation space, and comprises the following steps:
wherein ,
，/>
for the length of the signal sequence, +.>
For the number of signal components>
For discrete time series time points->
Is->
Signal components>
、/>
、/>
and />
Respectively->
Time estimated ∈th>
Instantaneous amplitude, instantaneous frequency, instantaneous tuning frequency, and cluster labels of the individual signal components.
Further, in the present invention, a sparse time-frequency modulation rate estimation sequence of the target scattering center is obtained, expressed as:
wherein ,
、/>
true values of the acquired instantaneous frequency sequence and instantaneous frequency sequence, respectively,/->
、
The estimation errors of the instantaneous frequency sequence and the instantaneous modulation frequency sequence are respectively, the two errors are mutually independent, gaussian white noise is adopted, and the variance is +.>
and />
。
Further, the reconstruction error of the invention
The method comprises the following steps:
wherein ,
and->
Error weighting coefficients are estimated for the instantaneous frequency sequence and the instantaneous frequency sequence, respectively. />
Further, the invention sets the micro-motion form and micro-motion parameter corresponding to the minimum reconstruction error as
、/>
Expressed as
If it is
The scattering center is a non-micro scattering center;
otherwise, the scattering center is a micro-scattering center, and the micro-motion is in the form of
The inching parameter is->
, wherein ,/>
Is the set decision threshold.
In another aspect, the present invention provides a jog form identification device based on sparse time-frequency-modulated frequency representation, comprising:
the first module is used for establishing a time-frequency modulation model under a typical inching mode;
the second module is used for setting radar observation parameters and jog parameters of a time-frequency modulation model under a typical jog mode and constructing a jog scattering center model set;
a third module, configured to obtain a sparse time-frequency modulation frequency estimation sequence of the target scattering center;
a fourth module, configured to calculate a reconstruction error between the sparse time-frequency modulation rate estimation sequence of the target scattering center and the fine scattering center model set;
and the fifth module is used for comparing the minimum reconstruction error with the decision threshold and judging the inching form.
In another aspect, the present invention provides a computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
establishing a time-frequency modulation model under a typical inching mode;
setting radar observation parameters and jog parameters of a time-frequency modulation model under a typical jog mode, and constructing a jog scattering center model set;
acquiring a sparse time-frequency modulation frequency estimation sequence of a target scattering center;
calculating a reconstruction error of a sparse time-frequency modulation frequency estimation sequence of a target scattering center and a micro scattering center model set;
comparing the minimum reconstruction error with the decision threshold, and judging the inching form.
Compared with the prior art, the invention has the technical effects that:
according to the invention, different inching forms can be correctly identified by establishing the three-dimensional representation of the modulation model, and the method has better robustness to noise under low signal-to-noise ratio.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a spatial cone target jog model in accordance with an embodiment of the present invention;
FIG. 3 is a graph showing the instantaneous frequency of a scattering center in a precession mode for a precession cone echo signal modulation model in accordance with an embodiment of the present invention;
FIG. 4 is a graph showing instantaneous frequency modulation of a scattering center in a precession mode for a precession cone echo signal modulation model in accordance with an embodiment of the present invention;
FIG. 5 is a graph showing frequency-modulated frequencies of scattering centers in a precession mode for a precession cone echo signal modulation model in accordance with an embodiment of the present invention;
FIG. 6 is a graph showing time-frequency modulation of scattering centers in a precession mode for a precession cone echo signal modulation model in accordance with an embodiment of the present invention;
FIG. 7 is a graph showing the instantaneous frequency of a scattering center in a wobble pattern for a wobble cone echo signal modulation model in accordance with an embodiment of the invention;
FIG. 8 is a graph showing the instantaneous frequency modulation of a scattering center in a wobble pattern for a wobble cone echo signal modulation model in accordance with an embodiment of the invention;
FIG. 9 is a graph showing frequency-modulated frequencies of scattering centers in a wobble pattern for a wobble cone echo signal modulation model in accordance with an embodiment of the invention;
FIG. 10 is a graph showing time-frequency modulation of scattering centers in a wobble pattern for a wobble cone echo signal modulation model in accordance with an embodiment of the invention;
FIG. 11 is a graph of the instantaneous frequency of the scattering center for a nutating cone echo signal modulation model in nutating form in accordance with an embodiment of the present invention;
FIG. 12 is a graph of instantaneous frequency modulation of a scattering center in nutating form for a nutating cone echo signal modulation model in accordance with an embodiment of the present invention;
FIG. 13 is a frequency-modulated frequency of the scattering center of the nutating cone echo signal modulation model in nutating form in an embodiment of the invention;
FIG. 14 is a time-frequency-modulated frequency of a scattering center in nutating form for a nutating cone echo signal modulation model in an embodiment of the invention;
FIG. 15 is a graph showing the correlation result of multi-component signal sparse time-frequency modulation frequency sequence extraction, wherein (a) is a short-term sparse representation result in accordance with one embodiment of the present invention; (b) is a multi-component signal correlation result;
FIG. 16 is a graph showing the result of matching the error of the sequence reconstruction under the condition of-6 dB in an embodiment of the present invention, wherein (a) the result of instantaneous frequency estimation; (b) estimating the instantaneous frequency modulation;
FIG. 17 is a graph showing the accuracy of the inching pattern recognition according to the signal to noise ratio according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention establishes a new micro-motion characteristic characterization method by developing a new micro-motion signal modulation rule, thereby realizing the robust identification of the micro-motion form. Firstly, a time-frequency modulation model of a typical micro-motion signal is established, secondly, a sparse time-frequency modulation sequence of a target scattering center is extracted, then a micro-motion scattering center model set is established, and finally, a preset model representation error is calculated based on the global property of the sequence to realize micro-motion form identification.
Referring to fig. 1, in one embodiment, a method for identifying a jog form based on sparse time-frequency-tone frequency representation is provided, including:
establishing a time-frequency modulation model under a typical inching mode;
setting radar observation parameters and jog parameters of a time-frequency modulation model under a typical jog mode, and constructing a jog scattering center model set;
acquiring a sparse time-frequency modulation frequency estimation sequence of a target scattering center;
calculating a reconstruction error of a sparse time-frequency modulation frequency estimation sequence of a target scattering center and a micro scattering center model set;
comparing the minimum reconstruction error with the decision threshold, and judging the inching form.
The analysis of the modulation rule of the micro-motion signal is the basis of micro-motion signal processing. The Doppler frequency of the radar echo is changed by the target motion, and for a spatial axisymmetric cone target, the target has different inching modes due to the differences of stress and attitude control modes under the assumption that the translational component is completely compensated. Thus, the typical jog form is modeled in conjunction with the target motion model.
In one embodiment, the mass center of the targetOEstablishing a radar observation reference coordinate system for a coordinate originO-XYZLet the target precession axis beZAn axis, which is coplanar with the advancing axis and perpendicular to the advancing axis at the initial momentOZThe axial direction isYThe axis of the shaft is provided with a plurality of grooves,Xthe axis is determined by the right hand screw rule; the angle between the radar sight and the precession axis, i.e. the average angle of view is
Azimuth angle is +.>
Radar line of sightLOSThe unit vector in the reference coordinate system can be expressed as +.>
. And (5) establishing a time-frequency modulation model under a typical inching mode by combining the target motion model. It will be appreciated that typical jog forms of the present invention, i.e., jog forms widely known in the art, include primarily precession, wobble, nutation, etc., and that typical jog forms of the present invention include one or more of precession, wobble, and nutation. For these typical jog forms, modeling can be done in a manner known in the art. In some preferred embodiments below, new modeling methods are presented for several jog modes typical in the art, respectively.
In a preferred embodiment, a method for constructing a time-frequency modulation model in a precession mode is provided, which specifically includes the following steps:
in the precession mode, the target rotates around the spin axis and rotates around the cone spin axis at the same time, and the target cone spin angle frequency is
Precession angle +.>
The target spin axis is located at the initial momentYOZIn the plane.
Considering that spin does not affect echo when the target is axisymmetric, therefore, the scattering center
In radarLOSThe radial distance variation in direction can be expressed as
wherein ,
and />
The cone rotation matrix and the initial matrix are obtained according to the Rodrigues rotation formula, respectively,/-A>
The scattering center is located in the body coordinate system.
The above formula can be further simplified into
wherein ,
let the name->
In order to be able to be a relative initial distance,
The above-mentioned radial distance is derived to obtain the time-frequency modulation model under the precession form constructed in this embodiment, which includes the instantaneous frequency parameter equation and the instantaneous frequency parameter equation of the scattering center under the precession form, as follows:
wherein 
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in precession form, < >>
Representing the signal wavelength.
Further, as shown by the constructed time-frequency modulation model under the precession form, the instantaneous frequency and instantaneous frequency of the micro-scattering center are both sine functions, the spatial track of the time-frequency modulation is a spiral line, and the plane projection of the frequency-frequency modulation is an ellipse, which can be expressed as:
in a preferred embodiment, a method for constructing a time-frequency modulation model in a wobble form is provided, which specifically comprises the following steps:
when the target swings, the swinging plane is set asYOZThe target swing amplitude is
The swing angle frequency is +.>
The initial phase of swing is +.>
，/>
For the scattering center position in the body coordinate system, the swing angle is changed to be:
therefore, the scattering center
The radial distance from the radar is:
wherein ,
for a wobble matrix, can be composed of->
The rotation formula is obtained.
Considering that the target swing amplitude is smaller in the actual motion, the first-order Taylor expansion can be adopted for the composite function term to approximate, and the method is obtained:
for convenience of formulation and simplification, let
，/>
The radial distance of the scattering center from the radar can therefore be further reduced to:
deriving the above to obtain the time-frequency modulation model under the wobble form in this embodiment includes an instantaneous frequency parameter equation and an instantaneous frequency parameter equation of the scattering center under the wobble form, as follows:
wherein 
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in the form of a wobble, < >>
Representing the signal wavelength.
The time-frequency modulation model under the swinging form shows that the instantaneous frequency and the instantaneous frequency change of the scattering center comprise swinging frequency components and frequency multiplication components of the swinging frequency, the space track of the time-frequency modulation is a spiral line, and the plane projection of the frequency-frequency modulation is an epicycloid.
In a preferred embodiment, a method for constructing a time-frequency modulation model in a wobble form is provided, which specifically comprises the following steps:
when the target nutates, the target swings on the precession axis, and the target rotates around the spin axis and simultaneously rotates around the cone spin axis under the precession, wherein the frequency of the cone spin angle of the target is
Precession angle +.>
The target spin axis is located at the initial momentYOZIn the plane, the swing amplitude of the target under swing is +.>
The swing angle frequency is +.>
The initial phase of swing is +.>
The swinging plane isYOZ。
Nutation angle variation can be expressed as:
therefore, the scattering center
In radarLOSThe radial distance in the direction is:
wherein ,
and />
Respectively a cone rotation matrix and an initial matrix, which can be based on +.>
The rotation formula is obtained.
Considering that in actual motion, the precession angle and the swing amplitude are relatively smaller, the first-order Taylor expansion approximation can be utilized to obtain:
by simplifying, the radial distance can be further simplified as:
wherein, for the convenience of formula expression, let
For after simplification
The derivation obtains a time-frequency modulation model under the nutation form in this embodiment, which includes an instantaneous frequency parameter equation and an instantaneous frequency parameter equation of the scattering center under the nutation form, and specifically includes the following steps: />
wherein ：
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in nutation form, < >>
Representing the signal wavelength, < >>
The scattering center is located in the body coordinate system.
The constructed time-frequency modulation model under the nutation form can know that the instantaneous frequency and instantaneous frequency of the micro-motion scattering center comprise precession frequency, swinging frequency and sum and difference frequency components, the superposition of high-order sine forms is realized, the space track of the time-frequency modulation is a spiral line, and the plane projection of the frequency-frequency modulation can be regarded as a popularization form of the epicycloid.
Further, the radar observation parameters of the invention comprise carrier frequency, pulse repetition frequency, observation duration, average view angle and azimuth angle; the micro-motion parameters comprise cone rotation frequency and cone rotation angle under a precession form, swing frequency and swing amplitude under a swing form, and cone rotation frequency, cone rotation angle, swing frequency and swing amplitude under a nutation form.
In one embodiment, the instantaneous frequency and instantaneous frequency modulation sequence of the scattering center are constructed from the model by traversing the possible jog patterns and corresponding jog parameters, as follows:
the constructed set of micro-scattering center models comprises a typical micro-form instantaneous frequency sequence set
And the typical inching form instantaneous frequency sequence set +.>
The following are respectively:
wherein ,
，Nfor the length of the signal sequence, +.>
Is the total number of inching forms>
Indicate->
Form of inching->
For discrete time series time points->
For the scattering center jog parameter, < >>
、/>
And
respectively indicate->
Time->
Precession, wobble and nutation instantaneous frequency sequences built under parameters, < >>
、
and />
Respectively indicate->
Time->
And (3) constructing a precession, swing and nutation instantaneous frequency modulation sequence under the parameters.
Further, in order to overcome the problems that the traditional orthogonal matching tracking utilizes the maximum likelihood method to relate to multidimensional parameter searching, has low operation efficiency and the like, under the sparse representation framework, the short-time sparse representation of the signals can be obtained by applying the improved matching tracking method to the local signal segments at each moment
Meanwhile, considering that different scattering centers are not intersected in a three-dimensional space, applying a sliding window form to a short-time sparse representation resultKMean value clustering for realizing correlation of scattering centers in time-frequency modulation frequency space
wherein ,
，/>
for the length of the signal sequence, +.>
For the number of signal components>
For discrete time series time points->
Is->
Signal components>
、/>
、/>
and />
Respectively->
Time estimated ∈th>
Instantaneous amplitude, instantaneous frequency, instantaneous tuning frequency, and cluster labels of the individual signal components.
Because the extracted sequence contains complete information of the scattering center of the target, the sequence has obvious characteristic differences for different inching forms. Therefore, the identification of the movement form of the scattering center can be realized based on the sparse time-frequency modulation sequence. In one embodiment, the reconstruction error of the sparse time-frequency modulation rate estimation sequence of the target scattering center and the set of micro-scattering center models is calculated as follows:
(1) Acquiring a sparse time-frequency modulation frequency estimation sequence of a target scattering center, wherein the sparse time-frequency modulation frequency estimation sequence is expressed as:
wherein ,
、/>
the obtained instantaneous frequency sequence and instantaneous frequency sequence are respectively true,
、/>
the estimation errors of the instantaneous frequency sequence and the instantaneous modulation frequency sequence are respectively, the two errors are mutually independent, gaussian white noise is adopted, and the variance is +.>
and />
。
(2) Calculating reconstruction errors
The method specifically comprises the following steps:
wherein ,
and->
Error weighting coefficients are estimated for the instantaneous frequency sequence and the instantaneous frequency sequence, respectively. />
And finally, comparing the minimum reconstruction error with a judgment threshold, and judging the inching form. In one embodiment, the process is as follows:
setting the micro-motion form and micro-motion parameter corresponding to the minimum reconstruction error as
、/>
Expressed as
If it is
The scattering center is a non-micro scattering center;
otherwise, the scattering center is a micro-scattering center, and the micro-motion is in the form of
The inching parameter is->
。
wherein ,
is the set decision threshold. The decision threshold can be set reasonably by a person skilled in the art according to the application situation, and can also be obtained according to the reconstruction error statistical analysis of the sequence.
In summary, through the embodiments described above, the present invention establishes a time-frequency modulation model of a typical micro-motion signal, discovers a new micro-motion signal modulation rule, converts a crossed curve on an original time-frequency plane into a non-crossed curve of a time-frequency modulation space by increasing an information dimension, and can more finely describe a modulation rule of a micro-motion target, thereby more comprehensively describing a micro-motion characteristic of the target. Furthermore, the invention provides a micro-motion form identification method based on sequence reconstruction errors by combining a sparse time-frequency modulation frequency sequence, and the reconstruction errors are calculated by constructing a micro-motion scattering center model set, so that the robust identification of the micro-motion form is realized, and the method has higher engineering application value.
In one embodiment, the method of the present invention is applied to perform inching form identification, and the method is specifically as follows:
in this embodiment, radar observation parameters are set for the application scenario thereof, as shown in table 1:
table 1 radar observation parameter settings
In this embodiment, the typical jog form established sets jog parameters as shown in table 2:
table 2 jog parameter settings
FIG. 2 is a schematic diagram of a spatial cone target jog model. By the mass center of the targetOEstablishing a radar observation reference coordinate system for a coordinate originO-XYZThe target precession axis isZAn axis, which is coplanar with the advancing axis and perpendicular to the advancing axis at the initial momentOZThe axial direction isYThe axis of the shaft is provided with a plurality of grooves,Xthe axis is determined by the right hand screw rule. The angle between the radar sight and the precession axis, i.e. the average angle of view is
Azimuth angle of
. For different jog modes:
when the target precesses, the target rotates around the spin axis (self symmetry axis) and simultaneously rotates around the cone spin axis;
when the target swings, the swinging plane is set asYOZ；
When the target nutates, the target swings on the precession basis;
the instantaneous frequency and the instantaneous frequency modulation frequency of the combined scattering center are used for obtaining the three-dimensional representation of the time-frequency modulation frequency space of the combined scattering center, so that the modulation rule of the micro-motion target can be more finely described. From the equivalent scattering center model, a scattering point (i.e. a component signal) corresponds to a trajectory in time-frequency modulated space.
Fig. 3 to 6 are precession cone echo signal modulation models, wherein fig. 3 is an instantaneous frequency of a scattering center of the precession cone echo signal modulation model in a precession form; FIG. 4 is a graph showing the instantaneous frequency modulation of a scattering center in a precession mode for a precession cone echo signal modulation model; FIG. 5 is a graph showing frequency-modulated frequencies of scattering centers of a precession cone echo signal modulation model in a precession mode; fig. 6 is a graph of time-frequency modulation of scattering centers in a precession form for a precession cone echo signal modulation model. The instantaneous frequency and instantaneous frequency modulation of the micro-scattering center are sinusoidal functions, the space track of the time-frequency modulation frequency is a spiral line, and the plane projection of the frequency-frequency modulation frequency is an ellipse.
Fig. 7 to 10 are swing cone echo signal modulation models, wherein fig. 7 is the instantaneous frequency of the scattering center of the swing cone echo signal modulation model in a swing form; FIG. 8 is a graph of the instantaneous frequency modulation of the scattering center in a wobble pattern for a wobble cone echo signal modulation model; FIG. 9 is a graph of frequency versus modulation frequency of scattering centers for a wobble cone echo signal modulation model in a wobble format; fig. 10 is a graph of time-frequency modulation of scattering centers in wobbled form for a wobble cone echo signal modulation model. The instantaneous frequency and instantaneous frequency modulation of the micro-scattering center are superposed as a sine function, the space track of the time-frequency modulation is a spiral line, and the plane projection of the frequency-frequency modulation is an epicycloidal line.
FIGS. 11-14 are nutating cone echo signal modulation models, where FIG. 11 is the instantaneous frequency of the scattering center of the nutating cone echo signal modulation model in nutating form; FIG. 12 is a graph of instantaneous frequency modulation of a scattering center in nutating form for a nutating cone echo signal modulation model; FIG. 13 is a graph of frequency versus modulation frequency of scattering centers for a nutating cone echo signal modulation model in nutating form; FIG. 14 is a time-frequency-modulated frequency of a scattering center in nutating form for a nutating cone echo signal modulation model. The instantaneous frequency and instantaneous frequency modulation of the micro-scattering center are shown as superposition of higher-order sine functions, the space track of the time-frequency modulation frequency is a spiral line, and the frequency-frequency modulation frequency plane projection can be regarded as a popularization form of an epicycloid.
FIG. 15 is a graph showing correlation results of a multi-component signal sparse time-frequency modulation frequency sequence, where (a) is a short-term sparseRepresenting the result; (b) is a multi-component signal correlation result. By means ofchirpThe dictionary base function adopts an improved OMP algorithm to realize joint estimation of the target scattering center frequency and the tuning frequency, and sparse representation of the three-dimensional space is obtained. Further using local part in sliding window mode for short-time sparse representation resultKAnd (3) mean value clustering, so that the correlation of different signal components in a three-dimensional space is realized.
The spatial trajectory of the three-dimensional time-frequency modulation taking into account typical jog targets can be analyzed on the modulation law of the individual scattering points. In the time-frequency modulated space, a scattering point (i.e. a component signal) corresponds to a track. And constructing a micro-scattering center model set according to the radar observation and micro-motion parameters, and identifying three micro-motion modes of nutation, precession and swinging.
FIG. 16 is a graph showing the result of sequence-based reconstruction error matching for a signal-to-noise ratio of-6 dB, wherein (a) the instantaneous frequency estimate; (b) is the instantaneous frequency modulation estimation result. As can be seen by comparing the matching value with the true value, although the precession and nutation inching forms are similar, a higher inching form identification accuracy can be obtained by constructing a inching scattering center model set and calculating an estimated sequence reconstruction error.
FIG. 17 is a graph showing the accuracy of inching pattern recognition as a function of signal to noise ratio. As can be seen from the graph, as the signal-to-noise ratio increases, the accuracy of the inching form identification increases. When the signal-to-noise ratio is-2 dB, the identification accuracy reaches 97.92% by adopting a sequence reconstruction error method, and different inching forms can be identified correctly, so that the method has better robustness to noise under the condition of low signal-to-noise ratio.
In another aspect, an embodiment provides a micro form recognition device, including:
the first module is used for establishing a time-frequency modulation model under a typical inching mode;
the second module is used for setting radar observation parameters and jog parameters of a time-frequency modulation model under a typical jog mode and constructing a jog scattering center model set;
a third module, configured to obtain a sparse time-frequency modulation frequency estimation sequence of the target scattering center;
a fourth module, configured to calculate a reconstruction error between the sparse time-frequency modulation rate estimation sequence of the target scattering center and the fine scattering center model set;
and the fifth module is used for comparing the minimum reconstruction error with the decision threshold and judging the inching form.
The implementation method of each module and the construction of the model can be the method described in any of the foregoing embodiments, which is not described herein.
In another aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the jog form identification method provided in any of the above embodiments when executing the computer program. The computer device may be a server. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing sample data. The network interface of the computer device is used for communicating with an external terminal through a network connection.
In another aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the jog form identification method provided in any of the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The invention is not a matter of the known technology.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. The inching form identification method based on sparse time-frequency-tone frequency representation is characterized by comprising the following steps of:
establishing a time-frequency modulation model under a typical inching mode;
setting radar observation parameters and jog parameters of a time-frequency modulation model under a typical jog mode, and constructing a jog scattering center model set;
acquiring a sparse time-frequency modulation frequency estimation sequence of a target scattering center;
calculating a reconstruction error of a sparse time-frequency modulation frequency estimation sequence of a target scattering center and a micro scattering center model set;
comparing the minimum reconstruction error with the decision threshold, and judging the inching form.
2. The method for recognition of jog form based on sparse time-frequency-tuned frequency representation of claim 1, wherein the target centroid is defined byOEstablishing a radar observation reference coordinate system for a coordinate originO-XYZLet the target precession axis beZAn axis, which is coplanar with the advancing axis and perpendicular to the advancing axis at the initial momentOZThe axial direction isYThe axis of the shaft is provided with a plurality of grooves,Xthe axis is determined by the right hand screw rule; the angle between the radar sight and the precession axis, i.e. the average angle of view is
Azimuth angle is +.>
A time-frequency modulation model is built in conjunction with a target motion model in a typical jog pattern, wherein the typical jog pattern includes one or more of precession, wobble, and nutation.
3. The method for identifying the inching form based on sparse time-frequency-modulated frequency representation according to claim 2, wherein in the precession form, the target rotates around the spin axis while rotating around the coning axis, and the target coning angle frequency is the precession angleThe moving angle is
The target spin axis is located at the initial momentYOZIn-plane, the time-frequency modulation model in the precession form comprises an instantaneous frequency parameter equation and an instantaneous frequency parameter equation of the scattering center in the precession form, and the instantaneous frequency parameter equation is as follows:
wherein 
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in precession form, < >>
Representing the target cone rotation frequency,/->
Represents the inching amplitude->
Represents the primary phase of the water-soluble polymer,λrepresenting the signal wavelength.
4. A method for recognition of jog form based on sparse time-frequency-tuned frequency representation as in claim 3, wherein jog amplitude
And ++>
The following are provided:
wherein 
The scattering center is located in the body coordinate system.
5. The method for recognizing micro-motion pattern based on sparse time-frequency-modulated frequency representation according to claim 2, wherein in the wobble pattern, a wobble plane is set asYOZThe target swing amplitude is
The swing angle frequency is +.>
The initial phase of swing is +.>
，/>
For the scattering center to be located in the body coordinate system, the time-frequency modulation model in the swinging form comprises an instantaneous frequency parameter equation and an instantaneous frequency parameter equation of the scattering center in the swinging form, and the time-frequency modulation model is as follows:
wherein 
and />
Respectively representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in the form of a wobble, < >>
Representing the signal wavelength, < >>
，/>
。
6. The method for identifying the inching form based on sparse time-frequency-modulated frequency representation according to claim 2, wherein the target is driven to oscillate by the precession axis based on the precession, the target is driven to rotate around the spin axis while rotating around the cone spin axis, and the target cone spin angle frequency is
Precession angle +.>
The target spin axis is located at the initial momentYOZIn the plane, the swing amplitude of the target under swing is +.>
The swing angle frequency is +.>
The initial phase of swing is +.>
The swinging plane isYOZThe method comprises the steps of carrying out a first treatment on the surface of the Time-frequency in nutating formThe modulation model comprises the instantaneous frequency parameter equation and the instantaneous frequency parameter equation of the scattering center in nutation form, as follows:
wherein 
and />
Representing the instantaneous frequency and instantaneous tuning frequency of the scattering center in nutating form,
representing the signal wavelength, < >>
For the scattering center to be positioned in the body coordinate system, at the same time, for simplifying the expression of the equation, let
7. The method for recognition of micro-motion patterns based on sparse time-frequency-modulated frequency representation according to any one of claims 2 to 6, wherein radar observation parameters include carrier frequency, pulse repetition frequency, observation duration, average view angle, azimuth angle; the micro-motion parameters comprise cone rotation frequency and cone rotation angle under a precession form, swing frequency and swing amplitude under a swing form, and cone rotation frequency, cone rotation angle, swing frequency and swing amplitude under a nutation form.
8. The method for identifying a micro-motion pattern based on sparse time-frequency-modulated frequency representation according to claim 7, wherein the set of micro-motion scattering center models comprises a set of typical micro-motion pattern transient frequency sequences
And the typical inching form instantaneous frequency sequence set +.>
The following are respectively:
wherein ,
，/>
for the length of the signal sequence,Kin the total number of the inching forms,krepresent the firstkForm of inching->
For discrete time series time points->
For the scattering center jog parameter, < >>
、/>
And
respectively indicate->
Time->
Precession, wobble and nutation instantaneous frequency sequences built under parameters, < >>
、/>
and />
Respectively indicate->
Time->
And (3) constructing a precession, swing and nutation instantaneous frequency modulation sequence under the parameters.
9. The method for identifying the inching form based on sparse time-frequency modulated frequency representation according to claim 8, wherein the sparse time-frequency modulated frequency estimation sequence of the target scattering center is obtained, expressed as:
wherein ,
、/>
true values of the acquired instantaneous frequency sequence and instantaneous frequency sequence, respectively,/->
、
The estimation errors of the instantaneous frequency sequence and the instantaneous modulation frequency sequence are respectively, the two errors are mutually independent, gaussian white noise is adopted, and the variance is +.>
and />
。/>
10. The sparse time-frequency-modulated frequency representation based jog form recognition method of claim 9, wherein the reconstruction errorξ(k, θ) The method comprises the following steps:
wherein ,
and->
Error weighting coefficients are estimated for the instantaneous frequency sequence and the instantaneous frequency sequence, respectively.
11. The method for identifying a jog form based on sparse time-frequency-tuned frequency representation according to claim 10, wherein the jog form and jog parameter corresponding to the smallest reconstruction error are set as
、/>
Expressed as
If it is
The scattering center is a non-micro scattering center;
otherwise, the scattering center is a micro-scattering center, and the micro-motion is in the form of
The inching parameter is->
, wherein />
Is the set decision threshold. />
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Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5329286A (en) * | 1993-06-29 | 1994-07-12 | The United States Of America As Represented By The Secretary Of The Air Force | Method for two dimensional doppler imaging of radar targets |
| US20100128823A1 (en) * | 2008-11-21 | 2010-05-27 | Semiconductor Technology Academic Research Center | Doppler frequency estimating device, receiving device, recording medium and doppler frequency estimating method |
| CN102914772A (en) * | 2012-09-18 | 2013-02-06 | 西安电子科技大学 | Precession target two-dimensional imaging method based on equivalent scattering points |
| CN103235297A (en) * | 2013-05-07 | 2013-08-07 | 西安电子科技大学 | Space nutation target parameter estimation method based on broadband radar observation |
| CN104007430A (en) * | 2014-05-29 | 2014-08-27 | 西安电子科技大学 | Precession target micro-Doppler extracting method based on instant frequency modulation rate estimation |
| CN109001705A (en) * | 2018-06-27 | 2018-12-14 | 西安电子科技大学 | Wideband radar three-dimensional interference measures cone target fine motion method for parameter estimation |
| CN110568432A (en) * | 2019-06-10 | 2019-12-13 | 南京理工大学 | micro Doppler frequency-based geometric parameter estimation method for precession cone target |
| KR20200070595A (en) * | 2018-12-10 | 2020-06-18 | 재단법인대구경북과학기술원 | Motion recognition apparatus and method for recognizing macro motion and micro motion |
| CN111443335A (en) * | 2020-03-17 | 2020-07-24 | 中山大学 | Method, system and device for estimating target micro-motion parameters of broadband radar and storage medium |
| CN112904327A (en) * | 2021-01-19 | 2021-06-04 | 中国人民解放军国防科技大学 | Composite micro-motion target parameter estimation method based on frequency modulation fuzzy function |
| AU2021105650A4 (en) * | 2021-08-17 | 2021-10-14 | Naval Aviation University | On-line intelligent classification method of aerial entity targets based on micro-motion characteristics |
| CN114859298A (en) * | 2022-04-26 | 2022-08-05 | 中国人民解放军空军工程大学 | Precession cone target micro Doppler parameter extraction method under forward-looking condition |
| CN115184933A (en) * | 2022-07-07 | 2022-10-14 | 中国人民武装警察部队工程大学 | Non-coherent signal radar target micro-motion feature extraction and imaging method |
| WO2022226948A1 (en) * | 2021-04-29 | 2022-11-03 | 华为技术有限公司 | Target feature extraction method and apparatus |
-
2023
- 2023-04-13 CN CN202310394014.5A patent/CN116106857B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5329286A (en) * | 1993-06-29 | 1994-07-12 | The United States Of America As Represented By The Secretary Of The Air Force | Method for two dimensional doppler imaging of radar targets |
| US20100128823A1 (en) * | 2008-11-21 | 2010-05-27 | Semiconductor Technology Academic Research Center | Doppler frequency estimating device, receiving device, recording medium and doppler frequency estimating method |
| CN102914772A (en) * | 2012-09-18 | 2013-02-06 | 西安电子科技大学 | Precession target two-dimensional imaging method based on equivalent scattering points |
| CN103235297A (en) * | 2013-05-07 | 2013-08-07 | 西安电子科技大学 | Space nutation target parameter estimation method based on broadband radar observation |
| CN104007430A (en) * | 2014-05-29 | 2014-08-27 | 西安电子科技大学 | Precession target micro-Doppler extracting method based on instant frequency modulation rate estimation |
| CN109001705A (en) * | 2018-06-27 | 2018-12-14 | 西安电子科技大学 | Wideband radar three-dimensional interference measures cone target fine motion method for parameter estimation |
| KR20200070595A (en) * | 2018-12-10 | 2020-06-18 | 재단법인대구경북과학기술원 | Motion recognition apparatus and method for recognizing macro motion and micro motion |
| CN110568432A (en) * | 2019-06-10 | 2019-12-13 | 南京理工大学 | micro Doppler frequency-based geometric parameter estimation method for precession cone target |
| CN111443335A (en) * | 2020-03-17 | 2020-07-24 | 中山大学 | Method, system and device for estimating target micro-motion parameters of broadband radar and storage medium |
| CN112904327A (en) * | 2021-01-19 | 2021-06-04 | 中国人民解放军国防科技大学 | Composite micro-motion target parameter estimation method based on frequency modulation fuzzy function |
| WO2022226948A1 (en) * | 2021-04-29 | 2022-11-03 | 华为技术有限公司 | Target feature extraction method and apparatus |
| AU2021105650A4 (en) * | 2021-08-17 | 2021-10-14 | Naval Aviation University | On-line intelligent classification method of aerial entity targets based on micro-motion characteristics |
| CN114859298A (en) * | 2022-04-26 | 2022-08-05 | 中国人民解放军空军工程大学 | Precession cone target micro Doppler parameter extraction method under forward-looking condition |
| CN115184933A (en) * | 2022-07-07 | 2022-10-14 | 中国人民武装警察部队工程大学 | Non-coherent signal radar target micro-motion feature extraction and imaging method |
Non-Patent Citations (4)
| Title |
|---|
| ZHANG W P等: ""Sparse Time-Frequency-Frequency-Rate Representation for Multicomponent Nonstationary Signal Analysis"", 《2018 26TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)》, pages 717 - 727 * |
| 卢杰等: ""基于检测-跟踪算法的多分量瞬时频率-调频率估计"", 《系统工程与电子技术》, pages 1 - 16 * |
| 束长勇等: ""基于微多普勒的空间锥体目标微动分类"", 《北京航空航天大学学报》, vol. 43, no. 7, pages 1387 - 1391 * |
| 韩勋等: ""基于时频分布的空间锥体目标微动形式分类"", 《系统工程与电子技术》, vol. 35, no. 4, pages 684 - 691 * |
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