CN111983598A

CN111983598A - Axle center track determining method and device based on multipath signals

Info

Publication number: CN111983598A
Application number: CN202010713370.5A
Authority: CN
Inventors: 何源; 郭俊辰; 蒋成堃; 刘云浩; 金梦
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2020-07-22
Filing date: 2020-07-22
Publication date: 2020-11-24
Anticipated expiration: 2040-07-22
Also published as: CN111983598B

Abstract

The embodiment of the invention discloses an axis track determination method and device based on multipath signals, wherein the method comprises the following steps: acquiring a beat signal in each chirp signal period of each streaming data frame of a target area, and performing conversion processing on the beat signal to obtain a target signal corresponding to the beat signal; generating an angle spectrum corresponding to the distance spectrum and a space spectrum corresponding to the target region for the distance spectrum formed by the target signal corresponding to the beat signal; based on a preset constant false alarm rate operator, carrying out region identification processing on the space spectrum so as to divide a target region into a plurality of two-dimensional position regions; determining a multipath signal corresponding to each two-dimensional position area based on the target signal; determining a one-dimensional vibration signal corresponding to each two-dimensional position area based on a preset radius constraint circle fitting algorithm and the multipath signals; and determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm.

Description

Axle center track determining method and device based on multipath signals

Technical Field

The invention relates to the technical field of computers, in particular to an axis locus determining method and device based on multipath signals.

Background

In modern industry, a rotating machine is an important component in modern industry, and how to accurately acquire a two-dimensional axis track of the rotating machine can be monitored through the two-dimensional axis track of a core component (namely a rotor) of the rotating machine, so that the method becomes a key problem in an industrial automation monitoring scene.

At present, one-dimensional displacements of a rotor on an X axis and a Y axis can be obtained based on a plurality of displacement sensors such as a piezoelectric ceramic sensor and an eddy current sensor, and then a two-dimensional axis locus of the rotor is calculated by the one-dimensional displacements on the X axis and the Y axis according to a motion synthesis method.

However, the above method needs to calibrate a plurality of secondary displacement sensors by a calibrator in advance to complete the conversion from the electrical signal to the displacement signal, and needs additional equipment to complete the high-precision synchronization of the plurality of sensors, so that the efficiency of determining the two-dimensional axis trajectory is low, and meanwhile, the problem of poor accuracy of determining the two-dimensional axis trajectory by a motion synthesis method is also present.

Disclosure of Invention

The embodiment of the invention aims to provide a method and a device for determining an axis locus based on a multipath signal, so as to solve the problems of low determination efficiency and poor determination accuracy when a two-dimensional axis locus is determined in the prior art.

To solve the above technical problem, the embodiment of the present invention is implemented as follows:

in a first aspect, an embodiment of the present invention provides a method for determining an axis trajectory based on a multipath signal, where the method includes:

acquiring a beat signal in each chirp signal cycle of each streaming data frame of a target area, and performing conversion processing on the beat signal based on a preset Fourier transform algorithm to obtain a target signal corresponding to the beat signal, wherein the beat signal is the product of the conjugate of a transmission signal of a signal transceiver and a reflection signal, returned by a target object for the transmission signal, received by the signal transceiver;

generating an angle spectrum corresponding to the distance spectrum aiming at a distance spectrum formed by the target signal corresponding to the beat signal in a target linear frequency modulation signal period of a target streaming data frame and a preset robust capone beam forming algorithm, and generating a spatial spectrum corresponding to the target region based on the distance spectrum and the angle spectrum, wherein the target streaming data frame is any one data frame in the streaming data frames, and the target linear frequency modulation signal period is any one period in linear frequency modulation signal periods corresponding to the target streaming data frames;

based on a preset constant false alarm rate operator, carrying out region identification processing on the space spectrum so as to divide the target region into a plurality of two-dimensional position regions;

determining a multipath signal corresponding to each two-dimensional position area based on a target signal in each chirp signal period of each streaming data frame, wherein the multipath signals comprise the target signals from different chirp signal periods of different streaming data frames and equivalent sampling time;

determining a one-dimensional vibration signal corresponding to each two-dimensional position area based on a preset radius constrained circle fitting algorithm and a multipath signal corresponding to each two-dimensional position area;

and determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, wherein the preset iterative algorithm is based on the projection of the one-dimensional vibration signal on a preset observation angle, and the determined two-dimensional axis track is subjected to iterative processing to obtain the two-dimensional axis track.

Optionally, the determining a one-dimensional vibration signal corresponding to each two-dimensional position region based on a preset radius constrained circle fitting algorithm and a multipath signal corresponding to each two-dimensional position region includes:

determining a static clutter component corresponding to the multipath signal of each two-dimensional position area based on the preset radius constraint circle fitting algorithm, the preset circle center direction constraint, the preset arc radius constraint and the multipath signal corresponding to each two-dimensional position area;

and determining the one-dimensional vibration signal corresponding to each two-dimensional position area based on the multipath signal of each two-dimensional position area and the corresponding static clutter component.

Optionally, before determining the static clutter component corresponding to the multipath signal in each two-dimensional position region based on the preset radius constrained circle fitting algorithm, the preset circle center direction constraint, the preset arc radius constraint, and the multipath signal corresponding to each two-dimensional position region, the method further includes:

acquiring the central point of an arc formed by the multipath signals corresponding to each two-dimensional position area in a preset complex signal plane;

determining central points of a plurality of arcs based on a preset search step length and the central points of the arcs;

acquiring a first circle center direction from the center point of each circular arc to the center point of each circular arc;

projecting the multipath signal corresponding to each two-dimensional position area to each first circle center direction to obtain a projection sequence frequency spectrum corresponding to each first circle center direction;

acquiring the kurtosis of the projection sequence frequency spectrum corresponding to each first circle center direction on a preset frequency band, and acquiring the ratio of the frequency spectrum energy of the projection sequence frequency spectrum corresponding to each first circle center direction on the preset frequency band to the frequency spectrum energy of the projection sequence frequency spectrum;

determining a target metric based on the kurtosis and the ratio corresponding to each of the first circle center directions;

determining a target circle center direction in the first circle center direction based on the target measurement standard, and determining the preset circle center direction constraint based on the target circle center direction;

projecting the multipath signal of each two-dimensional position area on the preset complex signal plane based on the direction of the center of the target circle to obtain a corresponding projection sequence and obtain the projection height of the projection sequence;

and determining the preset circular arc radius constraint based on the projection height and a preset amplitude range.

Optionally, before determining the two-dimensional axis trajectory corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, the method further includes:

clustering the one-dimensional vibration signals corresponding to each two-dimensional position area based on a preset density clustering and screening algorithm to obtain a plurality of clustering clusters, wherein the preset density clustering and screening algorithm is an algorithm for clustering based on preset weight of the one-dimensional vibration signals and based on a phase relation between the two-dimensional position areas corresponding to the one-dimensional vibration signals;

determining a target vibration signal of each cluster based on a one-dimensional vibration signal contained in each cluster;

the determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, wherein the preset iterative algorithm is based on a projection of the one-dimensional vibration signal on a preset observation angle, and the iteration processing is performed on the determined two-dimensional axis track to obtain the two-dimensional axis track, and the determining the two-dimensional axis track comprises the following steps:

and determining the two-dimensional axis locus corresponding to the target area based on the target vibration signal of each cluster and a preset iterative algorithm, wherein the preset iterative algorithm is based on the projection of the target vibration signal on a preset observation angle, and the determined two-dimensional axis locus is subjected to iterative processing to obtain the two-dimensional axis locus.

Optionally, the clustering, based on a preset density clustering screening algorithm, the one-dimensional vibration signals corresponding to each two-dimensional position region are clustered to obtain a plurality of clustering clusters, including:

acquiring a target arc radius obtained after the arc fitting processing based on the preset radius constrained circle fitting algorithm and the multipath signal corresponding to each two-dimensional position area;

determining preset weight of the one-dimensional vibration signal corresponding to each two-dimensional position area based on the target measurement standard, the target arc radius, and the spectral kurtosis and spectral energy of the one-dimensional vibration signal corresponding to each two-dimensional position area;

based on the preset weight of the one-dimensional vibration signal corresponding to each two-dimensional position area, screening the one-dimensional vibration signal corresponding to each two-dimensional position area to obtain a second vibration signal corresponding to each two-dimensional position area;

determining a corresponding distance metric matrix based on the second vibration signal corresponding to each two-dimensional position area, wherein the distance metric matrix is determined by a phase value between each two second vibration signals;

based on the distance measurement matrix, clustering the second vibration signals corresponding to each two-dimensional position area to obtain a plurality of clustering clusters;

the determining a target vibration signal of each cluster based on the one-dimensional vibration signal contained in each cluster comprises:

determining a target vibration signal for each of the clusters based on the second vibration signal contained within each of the clusters.

Optionally, the determining a two-dimensional axis locus corresponding to the target region based on the target vibration signal of each cluster and a preset iterative algorithm includes:

a target vibration signal based on each cluster, a preset weight of each target vibration signal, a preset observation angle of the target vibration signal of each cluster, a preset target diagonal matrix, a preset target projection vector matrix, and a formula

O＝(V^TWV)^-1V^TWEX，

Determining a first axis track corresponding to the target area, wherein O is the first axis track, W is a weight matrix formed by preset weights of each target vibration signal, E is the target diagonal matrix, and V is^TIs a transpose of the target projection vector matrix,

wherein, beta_pA preset observation angle of a target vibration signal of the p-th cluster is obtained,

the projection vector at the preset observation angle is obtained;

and under the condition that the first axis track meets a preset convergence condition, determining the first axis track as a two-dimensional axis track corresponding to the target area.

Optionally, the method further comprises:

under the condition that the first axis track does not meet the preset convergence condition, based on the first axis track, the target vibration signal of each cluster, the preset observation angle of the target vibration signal of each cluster, the target diagonal matrix and a formula

Determining a first projection vector matrix, wherein e_pIs a constituent element, x, in the target diagonal matrix corresponding to the target vibration signal of the p-th clustering cluster_pFor the target vibration signal of the p-th cluster,

is a transposed matrix of the first projection vector matrix, O is the first axial locus, β_pPre-determining a target vibration signal for the p-th clusterSetting an observation angle;

target vibration signal of each cluster based on the first projection vector matrix, and formula

Determining a first diagonal matrix;

and determining the first projection vector matrix as the target projection vector matrix, and determining the first diagonal matrix as the target diagonal matrix.

In a second aspect, an embodiment of the present invention provides an apparatus for determining an axial center trajectory based on a multipath signal, where the apparatus includes:

the system comprises a signal acquisition module, a signal processing module and a signal processing module, wherein the signal acquisition module is used for acquiring a beat signal in each chirp signal period of each streaming data frame aiming at a target area, and carrying out conversion processing on the beat signal based on a preset Fourier transform algorithm to obtain a target signal corresponding to the beat signal, and the beat signal is the product of the conjugate of a transmission signal of a signal transceiver and a reflection signal, which is received by the signal transceiver and returned by a target object aiming at the transmission signal;

a spatial spectrum determination module, configured to generate, for a distance spectrum formed by the target signal corresponding to the beat signal within a target chirp signal period of a target streaming data frame and a preset robust capone beamforming algorithm, an angle spectrum corresponding to the distance spectrum, and generate, based on the distance spectrum and the angle spectrum, a spatial spectrum corresponding to the target region, where the target streaming data frame is any one of the streaming data frames, and the target chirp signal period is any one of chirp signal periods corresponding to the target streaming data frame;

the region determination module is used for carrying out region identification processing on the space spectrum based on a preset constant false alarm rate operator so as to divide the target region into a plurality of two-dimensional position regions;

a signal determining module, configured to determine, based on a target signal in each chirp signal cycle of each streaming data frame, a multipath signal corresponding to each two-dimensional location area, where the multipath signal includes the target signal from different chirp signal cycles of different streaming data frames and equivalent sampling time;

the signal extraction module is used for determining a one-dimensional vibration signal corresponding to each two-dimensional position area based on a preset radius constraint circle fitting algorithm and a multipath signal corresponding to each two-dimensional position area;

and the track determining module is used for determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, wherein the preset iterative algorithm is based on the projection of the one-dimensional vibration signal on a preset observation angle, and the determined two-dimensional axis track is subjected to iterative processing to obtain the two-dimensional axis track.

Optionally, the signal extraction module is configured to:

Optionally, the apparatus further comprises:

the central point determining module is used for acquiring the central point of an arc formed by the multipath signals corresponding to each two-dimensional position area in a preset complex signal plane;

the central point determining module is used for determining the central points of the plurality of circular arcs based on a preset search step length and the central points of the circular arcs;

the direction obtaining module is used for obtaining a first circle center direction from a center point of each circular arc to a center point of each circular arc;

the spectrum determining module is used for projecting the multipath signal corresponding to each two-dimensional position area to each first circle center direction to obtain a projection sequence spectrum corresponding to each first circle center direction;

the data acquisition module is used for acquiring the kurtosis of the projection sequence frequency spectrum corresponding to each first circle center direction on a preset frequency band and acquiring the ratio of the frequency spectrum energy of the projection sequence frequency spectrum corresponding to each first circle center direction on the preset frequency band to the frequency spectrum energy of the projection sequence frequency spectrum;

a standard determination module, configured to determine a target metric based on the kurtosis and the ratio corresponding to each of the first circle center directions;

a first determining module, configured to determine a target circle center direction in the first circle center direction based on the target metric, and determine the preset circle center direction constraint based on the target circle center direction;

the projection module is used for projecting the multipath signals of each two-dimensional position area on the preset complex signal plane based on the direction of the center of the target circle to obtain a corresponding projection sequence and obtain the projection height of the projection sequence;

and the second determination module is used for determining the preset circular arc radius constraint based on the projection height and a preset amplitude range.

Optionally, the apparatus further comprises:

the clustering module is used for clustering the one-dimensional vibration signals corresponding to each two-dimensional position area based on a preset density clustering screening algorithm to obtain a plurality of clustering clusters, and the preset density clustering screening algorithm is an algorithm for clustering based on the preset weight of the one-dimensional vibration signals and the phase relationship between the two-dimensional position areas corresponding to the one-dimensional vibration signals;

the third determining module is used for determining a target vibration signal of each clustering cluster based on the one-dimensional vibration signal contained in each clustering cluster;

the trajectory determination module is configured to:

Optionally, the clustering module is configured to:

the third determining module is configured to:

Optionally, the trajectory determination module is configured to:

O＝(V^TWV)^-1V^TWEX，

the projection vector at the preset observation angle is obtained;

Optionally, the apparatus further comprises:

a first matrix determination module, configured to determine, based on the first axis trajectory, the target vibration signal of each cluster, the preset observation angle of the target vibration signal of each cluster, the target diagonal matrix, and a formula under the condition that the first axis trajectory does not satisfy the preset convergence condition

is a transposed matrix of the first projection vector matrix, O is the first axial locus, β_pPresetting an observation angle for a target vibration signal of the p-th clustering cluster;

a second matrix determination module for determining a target vibration signal for each of the clusters based on the first projection vector matrix, and a formula

Determining a first diagonal matrix;

and the third matrix determining module is used for determining the first projection vector matrix as the target projection vector matrix and determining the first diagonal matrix as the target diagonal matrix.

In a third aspect, an embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps of the method for determining a shaft center trajectory based on a multipath signal provided in the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for determining a shaft center trajectory based on a multipath signal provided in the first aspect are implemented.

As can be seen from the above technical solutions provided by the embodiments of the present invention, the embodiments of the present invention obtain a beat signal in each chirp signal cycle of each streaming data frame for a target area, and transform the beat signal based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal, where the beat signal is a product of a conjugate of a transmission signal of a signal transceiver device and a reflection signal of a target object received by the signal transceiver device and returned for the transmission signal, a distance spectrum formed by the target signal corresponding to the beat signal in the target chirp signal cycle of the target streaming data frame, and a preset robust capone beam forming algorithm, generate an angle spectrum corresponding to the distance spectrum, and generate a spatial spectrum corresponding to the target area based on the distance spectrum and the angle spectrum, where the target streaming data frame is any one of the streaming data frames, the method comprises the steps that a target linear frequency modulation signal period is any one period in linear frequency modulation signal periods corresponding to a target streaming data frame, region identification processing is carried out on a space spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, multipath signals corresponding to each two-dimensional position region are determined based on target signals in each linear frequency modulation signal period of each streaming data frame, the multipath signals comprise target signals which come from different linear frequency modulation signal periods of different streaming data frames and are equivalent to sampling time, one-dimensional vibration signals corresponding to each two-dimensional position region are determined based on a preset radius constraint circle fitting algorithm and the multipath signals corresponding to each two-dimensional position region, and two-dimensional axis tracks corresponding to the target region are determined based on the one-dimensional vibration signals corresponding to each two-dimensional position region and a preset iteration algorithm, the preset iterative algorithm is to perform iterative processing on the determined two-dimensional axis locus based on the projection of the one-dimensional vibration signal on a preset observation angle to obtain the two-dimensional axis locus. Therefore, the two-dimensional axis locus of the target area is determined through the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, the determination accuracy of the two-dimensional axis locus can be improved, meanwhile, the problem of low determination efficiency of the two-dimensional axis locus caused by the participation of extra equipment is avoided, and the determination efficiency of the two-dimensional axis locus is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a schematic flow chart of a method for determining an axis trajectory based on a multipath signal according to the present invention;

FIG. 2 is a schematic diagram of a target signal extraction process according to the present invention;

FIG. 3 is a schematic flow chart of another method for determining an axial center trajectory based on a multipath signal according to the present invention;

FIG. 4 is a schematic diagram of a method for determining a predetermined circle center direction constraint and a predetermined arc radius constraint according to the present invention;

FIG. 5 is a schematic structural diagram of an axis trajectory determination device based on multipath signals according to the present invention;

fig. 6 is a schematic structural diagram of an electronic device according to the present invention.

Detailed Description

The embodiment of the invention provides a method and a device for determining an axis track based on a multipath signal.

In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example one

As shown in fig. 1, an execution subject of the method may be a server, which may be an independent server or a server cluster composed of multiple servers. The method may specifically comprise the steps of:

in S102, a beat signal in each chirp signal cycle of each streaming data frame for the target region is acquired, and the beat signal is transformed based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal.

The target area may be a preset area in each streaming data frame, the beat signal may be a product of a conjugate of a transmission signal of the signal transceiver device and a reflection signal of a target object returned for the transmission signal, the signal transceiver device may be any device capable of transmitting the transmission signal and receiving the reflection signal (i.e., a transmission signal returned for the transmission signal by the target object), for example, the signal transceiver device may be a millimeter-wave radar, and the target signal may be a signal of a corresponding distance unit of the target object.

In implementation, in modern industry, a rotating machine is an important component in modern industry, and how to accurately acquire a two-dimensional axis track of the rotating machine by monitoring an operation condition of the rotating machine through the two-dimensional axis track of a core component (i.e., a rotor) of the rotating machine becomes a key problem in an industrial automation monitoring scene.

At present, one-dimensional displacements of a rotor on an X axis and a Y axis can be obtained based on a plurality of displacement sensors such as a piezoelectric ceramic sensor and an eddy current sensor, and then a two-dimensional axis locus of the rotor is calculated by the one-dimensional displacements on the X axis and the Y axis according to a motion synthesis method. However, the above method needs to calibrate a plurality of secondary displacement sensors by a calibrator in advance to complete the conversion from the electrical signal to the displacement signal, and needs additional equipment to complete the high-precision synchronization of the plurality of sensors, so that the efficiency of determining the two-dimensional axis trajectory is low, and meanwhile, the problem of poor accuracy of determining the two-dimensional axis trajectory by a motion synthesis method is also present. Therefore, the embodiment of the present invention provides a technical solution capable of solving the above problems, which can be specifically referred to as the following:

taking the millimeter wave radar as an example, the millimeter wave radar may generally modulate the transmission signal in a chirp continuous wave manner, and receive a reflection signal obtained by reflecting the transmission signal by the target object, where the received reflection signal still maintains a chirp characteristic, and the returned reflection signal only shows a frequency delay relative to a round trip delay. Therefore, the frequency difference between the transmission signal and the transmission signal can reflect the distance of the target object to the millimeter-wave radar. The hardware component of the millimeter wave radar may include a mixer, which may multiply the conjugate of the transmitted signal and the reflected signal to obtain a corresponding beat signal, where the frequency of the beat signal is the frequency difference between the transmitted signal and the reflected signal.

The server can acquire beat signals in each chirp signal period of each streaming data frame of the target area, then the server can transform the beat signals based on a preset Fourier transform algorithm to obtain a frequency spectrum of the beat signals, and the frequency spectrum of the beat signals is obtained according to a formula

And converting the frequency spectrum into a distance spectrum to obtain a corresponding target signal, wherein t is time, c is light speed, delta F is frequency of the beat signal, and K is frequency linear change slope of a sending signal in a period of the linear frequency modulation signal.

Furthermore, for sub-millimeter or even micrometer vibration signals, the amplitude of the sub-millimeter or even micrometer vibration signal is much smaller than the distance resolution R, wherein,

t is the total time length of the linear change. When R (t) is expressed as R (t) ═ R + x (t), where x (t) is a time-varying displacement representation of the minute vibration signal (i.e., a vibration signal of a submillimeter or even micrometer level), and R is a time-invariant constant portion, x (t) < R can be obtained. Assuming that the initial time is 0, any subsequent time can be expressed as τ T + T, where T is the total duration of the linear change, τ is the slow time, the basic unit of the slow time is T, T is the fast time, and the fast time T is e [0, T). Since T is extremely short, typically 100 μ s, it can be assumed that the displacement of the target object within one chirp period is negligible, i.e. the displacement is negligible

T is more than or equal to 0 and less than T. The beat signal of the τ -th periodic chirp signal period can be expressed as

T is more than or equal to 0 and less than T, wherein alpha is a preset path loss attenuation factor, and j is an imaginary number unit. The beat signal can be processed based on a preset Fourier transform algorithm to obtain the dynamic reflection of the vibration signal in the corresponding target signal.

In addition, the reflected signal includes not only the reflected signal from the target object but also clutter (i.e., static clutter components) of other static objects, and thus, the target signal in the τ th chirp signal period may be

Wherein the content of the first and second substances,

i.e. the static clutter component which is constant over time,

is a dynamic reflection of the vibration signal in the target signal.

In addition, the preset fourier transform algorithm can also be a fourier transform algorithm based on a blackman window to reduce the frequency spectrum leakage between distance spectra, and can perform direct current component filtering on the fourier transform algorithm, and only retain the dynamic reflection result.

In S104, an angular spectrum corresponding to the distance spectrum is generated for a distance spectrum formed by a target signal corresponding to a beat signal within a target chirp signal period of a target streaming data frame and a preset robust capone beamforming algorithm, and a spatial spectrum corresponding to the target region is generated based on the distance spectrum and the angular spectrum.

The target streaming data frame may be any one of streaming data frames, and the target chirp period may be any one of chirp periods corresponding to the target streaming data frame.

In an implementation, the server may perform high-resolution angular spectrum splitting on the distance spectrum based on a preset robust capone beamforming algorithm to obtain a corresponding angular spectrum, and may then generate a high-resolution spatial spectrum corresponding to the target region based on the distance spectrum and the angular spectrum.

In S106, based on a preset constant false alarm rate operator, region identification processing is performed on the spatial spectrum to divide the target region into a plurality of two-dimensional position regions.

In implementation, two constant false alarm rate operators of one-dimensional ordered statistics can be cascaded, and the region identification processing is performed on the distance domain and the angle domain of the determined spatial spectrum in sequence to obtain a plurality of two-dimensional position regions (called multipath regions).

In S108, a multipath signal corresponding to each two-dimensional location area is determined based on the target signal within each chirp signal period of each streaming data frame.

Wherein the multipath signal may comprise target signals of different chirp signal periods from different streaming data frames and equivalent sampling time.

In an implementation, the server may divide a plurality of streaming data frames for the target area into a plurality of data frame groups, then use a first streaming data frame of each group as a target streaming data frame of each group, generate a corresponding spatial spectrum based on a target signal corresponding to a beat signal in a 1 st chirp signal period included in the target streaming data frame, and determine a corresponding plurality of two-dimensional position areas. For example, assuming that there are 30 streaming data frames for the target area and each streaming data frame corresponds to 200 chirp periods, the 1 st to 10 th streaming data frames may be set as the 1 st data frame group, the 11 th to 20 th streaming data frames may be set as the 2 nd data frame group, and the 21 st to 30 th streaming data frames may be set as the 3 rd data frame group. Then, the server may take the 1 st streaming data frame, the 11 th streaming data frame, and the 21 st streaming data frame as target streaming data frames, and take the 1 st chirp cycle of the 1 st streaming data frame as a target chirp cycle, the 1 st chirp cycle of the 11 th streaming data frame as a target chirp cycle, and the 1 st chirp cycle of the 21 st streaming data frame as a target chirp cycle, respectively. The server may then determine a spatial spectrum corresponding to the target chirp period for each target streaming data frame, and a corresponding plurality of two-dimensional location areas, respectively.

Then, as shown in fig. 2, the server may extract the target signal in each chirp cycle of each streaming data frame according to the two-dimensional position area determined by the target streaming data frame (i.e., the 1 st frame streaming data frame) in the same data frame group (e.g., a data frame group consisting of the 1 st to 4 th frame streaming data frames) to determine the multipath signal corresponding to each two-dimensional position area.

That is, for each two-dimensional location area, one multipath signal may be included, and each multipath signal may include 10 × 200 ═ 2000 sampling points (i.e., the target signal).

In S110, a one-dimensional vibration signal corresponding to each two-dimensional position region is determined based on a preset radius constrained circle fitting algorithm and a multipath signal corresponding to each two-dimensional position region.

In implementation, a radius constrained circle fitting algorithm based on a geometric distance and a multipath signal corresponding to each two-dimensional position area may be used to determine a static clutter component corresponding to a target signal included in the multipath signal, then delete the corresponding static clutter component from the target signal, and a server extracts a one-dimensional vibration signal corresponding to each two-dimensional position area according to the deleted target signal.

In S112, a two-dimensional axis locus corresponding to the target area is determined based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm.

The preset iterative algorithm may be based on a projection of the one-dimensional vibration signal at a preset observation angle, and perform iterative processing on the determined two-dimensional axis trajectory to obtain the two-dimensional axis trajectory.

In practice, the corresponding two-dimensional axial center trajectory may be determined from a plurality of independent one-dimensional observations from different observation angles (i.e., one-dimensional vibration signals corresponding to each two-dimensional location area). For the p-th one-dimensional vibration signal, the projection of the two-dimensional motion track on the preset observation angle can be considered, so that the two-dimensional axis track corresponding to the target area can be determined according to the preset iterative algorithm and the one-dimensional vibration signal corresponding to each two-dimensional position area.

The embodiment of the invention provides a method for determining an axis locus based on a multipath signal, which comprises the steps of obtaining a beat signal in each chirp signal cycle of each streaming data frame of a target area, carrying out conversion processing on the beat signal based on a preset Fourier transform algorithm to obtain a target signal corresponding to the beat signal, generating an angle spectrum corresponding to the distance spectrum based on the distance spectrum and the angle spectrum, generating a spatial spectrum corresponding to the target area based on the distance spectrum and the angle spectrum, wherein the target streaming data frame is any one of the streaming data frames, the method comprises the steps that a target linear frequency modulation signal period is any one period in linear frequency modulation signal periods corresponding to a target streaming data frame, region identification processing is carried out on a space spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, multipath signals corresponding to each two-dimensional position region are determined based on target signals in each linear frequency modulation signal period of each streaming data frame, the multipath signals comprise target signals which come from different linear frequency modulation signal periods of different streaming data frames and are equivalent to sampling time, one-dimensional vibration signals corresponding to each two-dimensional position region are determined based on a preset radius constraint circle fitting algorithm and the multipath signals corresponding to each two-dimensional position region, and two-dimensional axis tracks corresponding to the target region are determined based on the one-dimensional vibration signals corresponding to each two-dimensional position region and a preset iteration algorithm, the preset iterative algorithm is to perform iterative processing on the determined two-dimensional axis locus based on the projection of the one-dimensional vibration signal on a preset observation angle to obtain the two-dimensional axis locus. Therefore, the two-dimensional axis locus of the target area is determined through the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, the determination accuracy of the two-dimensional axis locus can be improved, meanwhile, the problem of low determination efficiency of the two-dimensional axis locus caused by the participation of extra equipment is avoided, and the determination efficiency of the two-dimensional axis locus is improved.

Example two

As shown in fig. 3, an execution main body of the method may be a server, and the server may be an independent server or a server cluster composed of a plurality of servers. The method may specifically comprise the steps of:

in S302, a beat signal in each chirp signal cycle of each streaming data frame for the target region is obtained, and the beat signal is transformed based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal.

In S304, an angular spectrum corresponding to the distance spectrum is generated for a distance spectrum formed by a target signal corresponding to a beat signal within a target chirp signal period of a target streaming data frame and a preset robust capone beamforming algorithm, and a spatial spectrum corresponding to the target region is generated based on the distance spectrum and the angular spectrum.

In S306, based on a preset constant false alarm rate operator, region identification processing is performed on the spatial spectrum to divide the target region into a plurality of two-dimensional position regions.

In S308, a multipath signal corresponding to each two-dimensional location area is determined based on the target signal within each chirp period of each streaming data frame.

For the specific processing procedures of S302 to S308, reference may be made to relevant contents in S102 to S108 in the first embodiment, and details are not described herein again.

Compared with the line-of-sight path reflection, the multipath signals are attenuated by multiple reflection energy of a target rotor, an environment reflector and the like, and the signal to noise ratio is very limited, so that in this case, the shape of an arc formed by the one-dimensional vibration signals on a complex signal plane can be submerged by noise, and the extraction accuracy of the one-dimensional vibration signals is poor, so that the preset circle center direction constraint and the preset arc radius preset can be generated through S310-S326, and the extraction accuracy of the one-dimensional vibration signals is improved based on a preset radius constraint circle fitting algorithm, a preset circle center direction constraint and a preset arc radius constraint.

In S310, a central point of an arc formed by the multipath signals corresponding to each two-dimensional position region is acquired in a preset complex signal plane.

In S312, center points of the plurality of arcs are determined based on a preset search step and the center points of the arcs.

The preset search step length can be any length of step length within 0-2 pi, for example, the preset search step length can be 16/pi.

In S314, a first circle center direction from the center point of each circular arc to the center point of the circular arc is obtained.

In S316, the multipath signal corresponding to each two-dimensional position region is projected to each first circle center direction to obtain a projection sequence spectrum corresponding to each first circle center direction.

In S318, a kurtosis of the projection sequence spectrum corresponding to each first circle center direction on the preset frequency band is obtained, and a ratio between a spectrum energy of the projection sequence spectrum corresponding to each first circle center direction on the preset frequency band and a spectrum energy of the projection sequence spectrum is obtained.

In S320, a target metric is determined based on the kurtosis and the ratio corresponding to each first circle center direction.

In an implementation, the server may be max (κ) according to the formula k (α)_b，0)·∈_bDetermining a target metric, where k (α) is the target metric, k_bIs the kurtosis corresponding to the direction of the (b) th first circle center, belongs to_bIs the ratio corresponding to the direction of the (b) th first circle center.

In S322, a target circle center direction in the first circle center directions is determined based on the target metric, and a preset circle center direction constraint is determined based on the target circle center direction.

In implementation, the server may select, according to the target metric k (α), a direction that maximizes the metric to determine the direction of the center of the target circle as α^*The server may construct a preset circle center direction constraint according to the target circle center direction, for example, the constructed preset circle center direction constraint may be [ α [ ]^*-α，α^*+α]∪[α^*-α+π，α^*+α+π]，α^*E 0, pi), where α may be a preset search step.

In S324, the multipath signal in each two-dimensional position region is projected on a preset complex signal plane based on the direction of the center of the target circle, so as to obtain a corresponding projection sequence, and obtain the projection height of the projection sequence.

In S326, a preset arc radius constraint is determined based on the projection height and the preset amplitude range.

In implementation, the circular arc radius constraint can improve the accuracy of one-dimensional vibration signal extraction, and the circular arc radius constraint can be determined by constructing a geometric transformation relation according to a known preset amplitude range, wherein the preset amplitude range is assumed as [ D ]_min，D_max]And the projection height is h, namely the peak value of a projection sequence after the multipath signal in the two-dimensional position area is projected to the direction of the center of the target circle. As shown in fig. 4, when the radius of the circular arc is the minimum, the maximum value is taken corresponding to the central angle, and the maximum value is also taken for the amplitude; when the radius of the circular arc is the maximum value, the corresponding central angle is the minimum value, and the amplitude is also the minimum value. The relationship between the central angle θ and the amplitude D may be

Where λ is the wavelength. . From the projection degree h, the relationship between r and θ can be constructed as:

thus, by the above two equations, the relationship between the radius of the arc and the amplitude can be constructed as

Then according to the preset amplitude range [ D ]_min，D_max]The preset arc radius constraint may be determined as:

in S328, a static clutter component corresponding to the multipath signal of each two-dimensional position region is determined based on the preset radius constrained circle fitting algorithm, the preset circle center direction constraint, the preset arc radius constraint, and the multipath signal corresponding to each two-dimensional position region.

In S330, a one-dimensional vibration signal corresponding to each two-dimensional position region is determined based on the multipath signal and the corresponding static clutter component for each two-dimensional position region.

In implementation, multiple streaming data frames may be divided into a group, a static clutter component corresponding to a multipath signal in each two-dimensional region corresponding to each streaming data frame is determined based on a preset radius constraint circle fitting algorithm, a preset circle center direction constraint and a preset arc radius constraint, and a one-dimensional vibration signal corresponding to each two-dimensional position region is determined according to the static clutter component.

Because the extracted one-dimensional vibration signals may be partially similar, that is, may all include reflection signals from adjacent reflection parts, in order to balance the contribution of a plurality of one-dimensional vibration signals to the generated two-dimensional axis track, the one-dimensional vibration signals corresponding to each two-dimensional position region may be clustered based on a preset density clustering screening algorithm.

In S332, based on a preset density cluster screening algorithm, the one-dimensional vibration signals corresponding to each two-dimensional position region are clustered to obtain a plurality of cluster clusters.

The preset density clustering screening algorithm may be an algorithm for clustering based on a preset weight of the one-dimensional vibration signal and based on a phase relationship between two-dimensional position regions corresponding to the one-dimensional vibration signal.

In practice, the processing manner of S332 may be varied, and an alternative implementation manner is provided below, which may specifically refer to the following processing from step one to step five.

Step one, acquiring a target arc radius obtained after arc fitting processing based on a preset radius constraint circle fitting algorithm and a multipath signal corresponding to each two-dimensional position area.

And secondly, determining the preset weight of the one-dimensional vibration signal corresponding to each two-dimensional position area based on the target measurement standard, the target arc radius, and the frequency spectrum kurtosis and the frequency spectrum energy of the one-dimensional vibration signal corresponding to each two-dimensional position area.

And thirdly, screening the one-dimensional vibration signals corresponding to each two-dimensional position area based on the preset weight of the one-dimensional vibration signals corresponding to each two-dimensional position area to obtain second vibration signals corresponding to each two-dimensional position area.

In an implementation, the server may rearrange the preset weight to the first 70% of the one-dimensional vibration signals to determine as the second vibration signal.

And step four, determining a corresponding distance measurement matrix based on the second vibration signal corresponding to each two-dimensional position area.

Wherein the distance metric matrix may be determined by the phase value between every two second vibration signals.

In an implementation, the distance measure between every two second vibration signals may be in accordance with min [ φ [ ]₁-φ₂-π，φ₁-φ₂，φ₁-φ₂+π]Determining where phi₁，φ₂The phase values of the two second vibration signals are respectively.

And fifthly, clustering the second vibration signals corresponding to each two-dimensional position area based on the distance measurement matrix to obtain a plurality of cluster clusters.

In implementation, the server may obtain location information of every two second vibration signals on the spatial spectrum, if two-dimensional location areas corresponding to the two second vibration signals are adjacent on the spatial spectrum, keep their distance measures unchanged, and if two-dimensional location areas corresponding to the two second vibration signals are not adjacent on the spatial spectrum, set the distance measure corresponding to the two second vibration signals in the distance measure matrix to infinity, which indicates that the two second vibration signals whose two-dimensional location areas are not adjacent but have similar phases are not aggregated.

After the distance measurement matrix is updated, the second vibration signals corresponding to each two-dimensional position area may be clustered based on the updated distance measurement matrix, so as to obtain a plurality of cluster clusters.

In S334, a target vibration signal for each cluster is determined based on the one-dimensional vibration signal contained in each cluster.

In implementation, for each cluster, the server may perform weighted summation on the second vibration signals according to the second vibration signals contained therein and preset weights of the second vibration signals, and take the result as the target vibration signal of the cluster.

The method for determining the target vibration signal is an optional and realizable determination method, and in an actual application scenario, there may be a plurality of other determination methods, which may be different according to different actual application scenarios, and this is not specifically limited in the embodiment of the present invention.

In S336, a two-dimensional axis locus corresponding to the target region is determined based on the target vibration signal of each cluster and a preset iterative algorithm.

The preset iterative algorithm may be based on a projection of the target vibration signal at a preset observation angle, and perform iterative processing on the determined two-dimensional axis trajectory to obtain the two-dimensional axis trajectory.

In implementation, for the target vibration signal of the p-th cluster, the projection of the two-dimensional axis estimation on the preset observation angle is actually obtained, and the projection can be expressed as tau at any time_{Degree of rotation}，

Wherein, beta_pFor the p-th clusterThe preset observation angle of the target vibration signal,

as projection vector at viewing angle, x_p(τ_{Degree of rotation}) For the p-th target vibration signal at tau_{Degree of rotation}A sample point of time.

In order to tolerate the accuracy of the extraction of the target vibration signal, an error tolerance factor (epsilon)_p) Namely:

the above formula is that one path of target vibration signal is at the time tau_{Degree of rotation}Can synthesize multiple target vibration signals at tau_{Degree of rotation}＝τ₁…τ_NThe following matrix expression can be obtained by the internal projection relation:

EX＝VO

wherein E { [ Diag ] ({ [ epsilon ])_p}_1×P) Is expressed in { ∈ E_p}_1×PIs a diagonal matrix of diagonal elements, X ═ X_p(τ_{Degree of rotation})}_P×NIs a matrix formed by a plurality of target vibration signals,

projecting the vector matrix for viewing angles, O ═ O (τ)_{Degree of rotation})}_2×NIs a two-dimensional trajectory. In the four variables, E and V are unknown quantities, X is observed quantities, and O is a target quantity, so to solve O, E and V need to be solved simultaneously, and a preset iterative algorithm can be performed through the following steps one to five to obtain a two-dimensional axis locus.

Step one, based on a target vibration signal of each cluster, a preset weight of each target vibration signal, a preset observation angle of the target vibration signal of each cluster, a preset target diagonal matrix, a preset target projection vector matrix and a formula

O＝(V^TWV)^-1V^TWEX，

Determining a first axial center trajectory corresponding to the target area, wherein O is the first axial center trajectory,w is a weight matrix composed of preset weights of each target vibration signal, E is a target diagonal matrix, V^TIs a transposed matrix of the target projection vector matrix,

wherein, beta_pFor the preset observation angle of the target vibration signal of the p-th cluster,

is a projection vector at a preset observation angle.

And continuously executing the step two or the step three to the step five according to whether the first axis orbit meets the preset convergence condition.

And step two, determining the first axis trajectory as a two-dimensional axis trajectory corresponding to the target area under the condition that the first axis trajectory meets a preset convergence condition.

Thirdly, under the condition that the first axis trajectory does not meet the preset convergence condition, based on the first axis trajectory, the target vibration signal of each cluster, the preset observation angle and the target diagonal matrix of the target vibration signal of each cluster and a formula

Determining a first projection vector matrix, wherein e_pIs a constituent element, x, in the target diagonal matrix corresponding to the target vibration signal of the p-th cluster_pFor the target vibration signal of the p-th cluster,

is the transpose matrix of the first projection vector matrix, O is the first axial locus, beta_pAnd the preset observation angle of the target vibration signal of the p-th cluster is obtained.

Step four, based on the first projection vector matrix, the target vibration signal of each cluster and a formula

A first diagonal matrix is determined.

And step five, determining the first projection vector matrix as a target projection vector matrix, and determining the first diagonal matrix as the target diagonal matrix.

And continuing to execute the step one until the first axis trajectory meets the preset convergence condition.

EXAMPLE III

Based on the same idea, the foregoing method for determining an axial center trajectory based on a multipath signal provided in the embodiment of the present specification further provides an apparatus for determining an axial center trajectory based on a multipath signal, as shown in fig. 5.

The axis locus determining device based on the multipath signals comprises: a signal acquisition module 501, a spatial spectrum determination module 502, a region determination module 503, a signal determination module 504, a signal extraction module 505, and a trajectory determination module 506, wherein:

a signal obtaining module 501, configured to obtain a beat signal in each chirp signal cycle of each streaming data frame for a target area, and transform the beat signal based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal, where the beat signal is a product of a conjugate of a transmission signal of a signal transceiver and a reflection signal, returned by a target object for the transmission signal, received by the signal transceiver;

a spatial spectrum determining module 502, configured to generate, for a distance spectrum formed by the target signal corresponding to the beat signal within a target chirp signal period of a target streaming data frame and a preset robust capone beamforming algorithm, an angle spectrum corresponding to the distance spectrum, and generate, based on the distance spectrum and the angle spectrum, a spatial spectrum corresponding to the target region, where the target streaming data frame is any one of the streaming data frames, and the target chirp signal period is any one of chirp signal periods corresponding to the target streaming data frame;

a region determining module 503, configured to perform region identification processing on the spatial spectrum based on a preset constant false alarm rate operator, so as to divide the target region into a plurality of two-dimensional position regions;

a signal determining module 504, configured to determine, based on a target signal in each chirp period of each streaming data frame, a multipath signal corresponding to each two-dimensional location area, where the multipath signal includes the target signal from different chirp periods of different streaming data frames and equivalent sampling time;

a signal extraction module 505, configured to determine a one-dimensional vibration signal corresponding to each two-dimensional position region based on a preset radius constrained circle fitting algorithm and a multipath signal corresponding to each two-dimensional position region;

a track determining module 506, configured to determine a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, where the preset iterative algorithm is based on a projection of the one-dimensional vibration signal on a preset observation angle, and performs iterative processing on the determined two-dimensional axis track to obtain the two-dimensional axis track.

In this embodiment of the present invention, the signal extraction module 505 is configured to:

In the embodiment of the present invention, the apparatus further includes:

the trajectory determination module 506 is configured to:

In an embodiment of the present invention, the clustering module is configured to:

the third determining module is configured to:

In an embodiment of the present invention, the track determining module 506 is configured to:

O＝(V^TWV)^-1V^TWEX，

the projection vector at the preset observation angle is obtained;

In the embodiment of the present invention, the apparatus further includes:

Determining a first diagonal matrix;

Example four

Figure 6 is a schematic diagram of a hardware configuration of an electronic device implementing various embodiments of the invention,

the electronic device 600 includes, but is not limited to: a radio frequency unit 601, a network module 602, an audio output unit 603, an input unit 604, a sensor 605, a display unit 606, a user input unit 607, an interface unit 608, a memory 609, a processor 610, and a power supply 611. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 6 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.

The processor 610 is configured to acquire a beat signal in each chirp signal cycle of each streaming data frame in a target area, and transform the beat signal based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal, where the beat signal is a product of a conjugate of a transmission signal of a signal transceiver and a reflection signal, returned by a target object for the transmission signal, received by the signal transceiver; generating an angle spectrum corresponding to the distance spectrum aiming at a distance spectrum formed by the target signal corresponding to the beat signal in a target linear frequency modulation signal period of a target streaming data frame and a preset robust capone beam forming algorithm, and generating a spatial spectrum corresponding to the target region based on the distance spectrum and the angle spectrum, wherein the target streaming data frame is any one data frame in the streaming data frames, and the target linear frequency modulation signal period is any one period in linear frequency modulation signal periods corresponding to the target streaming data frames; based on a preset constant false alarm rate operator, carrying out region identification processing on the space spectrum so as to divide the target region into a plurality of two-dimensional position regions; determining a multipath signal corresponding to each two-dimensional position area based on a target signal in each chirp signal period of each streaming data frame, wherein the multipath signals comprise the target signals from different chirp signal periods of different streaming data frames and equivalent sampling time; determining a one-dimensional vibration signal corresponding to each two-dimensional position area based on a preset radius constrained circle fitting algorithm and a multipath signal corresponding to each two-dimensional position area; and determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, wherein the preset iterative algorithm is based on the projection of the one-dimensional vibration signal on a preset observation angle, and the determined two-dimensional axis track is subjected to iterative processing to obtain the two-dimensional axis track.

In addition, the processor 610 is further configured to determine a static clutter component corresponding to the multipath signal in each two-dimensional position region based on the preset radius constrained circle fitting algorithm, the preset circle center direction constraint, the preset arc radius constraint, and the multipath signal corresponding to each two-dimensional position region; and determining the one-dimensional vibration signal corresponding to each two-dimensional position area based on the multipath signal of each two-dimensional position area and the corresponding static clutter component.

In addition, the processor 610 is further configured to obtain, in a preset complex signal plane, a central point of an arc formed by the multipath signals corresponding to each of the two-dimensional position areas; determining central points of a plurality of arcs based on a preset search step length and the central points of the arcs; acquiring a first circle center direction from the center point of each circular arc to the center point of each circular arc; projecting the multipath signal corresponding to each two-dimensional position area to each first circle center direction to obtain a projection sequence frequency spectrum corresponding to each first circle center direction; acquiring the kurtosis of the projection sequence frequency spectrum corresponding to each first circle center direction on a preset frequency band, and acquiring the ratio of the frequency spectrum energy of the projection sequence frequency spectrum corresponding to each first circle center direction on the preset frequency band to the frequency spectrum energy of the projection sequence frequency spectrum; determining a target metric based on the kurtosis and the ratio corresponding to each of the first circle center directions; determining a target circle center direction in the first circle center direction based on the target measurement standard, and determining the preset circle center direction constraint based on the target circle center direction; projecting the multipath signal of each two-dimensional position area on the preset complex signal plane based on the direction of the center of the target circle to obtain a corresponding projection sequence and obtain the projection height of the projection sequence; and determining the preset circular arc radius constraint based on the projection height and a preset amplitude range.

In addition, the processor 610 is further configured to perform clustering processing on the one-dimensional vibration signal corresponding to each two-dimensional position region based on a preset density clustering and screening algorithm to obtain a plurality of clustering clusters, where the preset density clustering and screening algorithm is an algorithm for clustering based on a preset weight of the one-dimensional vibration signal and based on a phase relationship between the two-dimensional position regions corresponding to the one-dimensional vibration signal; determining a target vibration signal of each cluster based on a one-dimensional vibration signal contained in each cluster; and determining the two-dimensional axis locus corresponding to the target area based on the target vibration signal of each cluster and a preset iterative algorithm, wherein the preset iterative algorithm is based on the projection of the target vibration signal on a preset observation angle, and the determined two-dimensional axis locus is subjected to iterative processing to obtain the two-dimensional axis locus.

In addition, the processor 610 is further configured to obtain a target arc radius obtained after the arc fitting processing based on the preset radius constrained circle fitting algorithm and the multipath signal corresponding to each two-dimensional position area; determining preset weight of the one-dimensional vibration signal corresponding to each two-dimensional position area based on the target measurement standard, the target arc radius, and the spectral kurtosis and spectral energy of the one-dimensional vibration signal corresponding to each two-dimensional position area; based on the preset weight of the one-dimensional vibration signal corresponding to each two-dimensional position area, screening the one-dimensional vibration signal corresponding to each two-dimensional position area to obtain a second vibration signal corresponding to each two-dimensional position area; determining a corresponding distance metric matrix based on the second vibration signal corresponding to each two-dimensional position area, wherein the distance metric matrix is determined by a phase value between each two second vibration signals; based on the distance measurement matrix, clustering the second vibration signals corresponding to each two-dimensional position area to obtain a plurality of clustering clusters; determining a target vibration signal for each of the clusters based on the second vibration signal contained within each of the clusters.

In addition, the processor 610 is further configured to determine a target vibration signal for each cluster based on the target vibration signal, a preset weight of each target vibration signal, a preset observation angle of the target vibration signal for each cluster, a preset target diagonal matrix, a preset target projection vector matrix, and a formula

O＝(V^TWV)^-1V^TWEX，

the projection vector at the preset observation angle is obtained; and under the condition that the first axis track meets a preset convergence condition, determining the first axis track as a two-dimensional axis track corresponding to the target area.

In addition, the processor 610 is further configured to, when the first axis trajectory does not satisfy the preset convergence condition, determine a formula based on the first axis trajectory, the target vibration signal of each cluster, the preset observation angle of the target vibration signal of each cluster, the target diagonal matrix, and the formula

is the first projection vector matrixO is the first axial locus, β_pPresetting an observation angle for a target vibration signal of the p-th clustering cluster; target vibration signal of each cluster based on the first projection vector matrix, and formula

Determining a first diagonal matrix; and determining the first projection vector matrix as the target projection vector matrix, and determining the first diagonal matrix as the target diagonal matrix.

The embodiment of the invention provides an electronic device, which obtains a beat signal in each chirp signal cycle of each streaming data frame for a target area, and performs conversion processing on the beat signal based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal, wherein the beat signal is a product of a conjugate of a transmission signal of a signal transceiver and a reflection signal returned by a target object for the transmission signal received by the signal transceiver, a distance spectrum formed by the target signal corresponding to the beat signal in the target chirp signal cycle of the target streaming data frame, and a preset robust capone beam forming algorithm are used to generate an angle spectrum corresponding to the distance spectrum, and a spatial spectrum corresponding to the target area is generated based on the distance spectrum and the angle spectrum, the target streaming data frame is any one of the streaming data frames, the method comprises the steps that a target linear frequency modulation signal period is any one period in linear frequency modulation signal periods corresponding to a target streaming data frame, region identification processing is carried out on a space spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, multipath signals corresponding to each two-dimensional position region are determined based on target signals in each linear frequency modulation signal period of each streaming data frame, the multipath signals comprise target signals which come from different linear frequency modulation signal periods of different streaming data frames and are equivalent to sampling time, one-dimensional vibration signals corresponding to each two-dimensional position region are determined based on a preset radius constraint circle fitting algorithm and the multipath signals corresponding to each two-dimensional position region, and two-dimensional axis tracks corresponding to the target region are determined based on the one-dimensional vibration signals corresponding to each two-dimensional position region and a preset iteration algorithm, the preset iterative algorithm is to perform iterative processing on the determined two-dimensional axis locus based on the projection of the one-dimensional vibration signal on a preset observation angle to obtain the two-dimensional axis locus. Therefore, the two-dimensional axis locus of the target area is determined through the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, the determination accuracy of the two-dimensional axis locus can be improved, meanwhile, the problem of low determination efficiency of the two-dimensional axis locus caused by the participation of extra equipment is avoided, and the determination efficiency of the two-dimensional axis locus is improved.

It should be understood that, in the embodiment of the present invention, the radio frequency unit 601 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 610; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 601 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. Further, the radio frequency unit 601 may also communicate with a network and other devices through a wireless communication system.

The electronic device provides wireless broadband internet access to the user via the network module 602, such as assisting the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.

The audio output unit 603 may convert audio data received by the radio frequency unit 601 or the network module 602 or stored in the memory 609 into an audio signal and output as sound. Also, the audio output unit 603 may also provide audio output related to a specific function performed by the electronic apparatus 600 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 603 includes a speaker, a buzzer, a receiver, and the like.

The input unit 604 is used to receive audio or video signals. The input Unit 604 may include a Graphics Processing Unit (GPU) 6041 and a microphone 6042, and the Graphics processor 6041 processes image data of a still picture or video obtained by an image capturing apparatus (such as a camera) in a video capture mode or an image capture mode. The processed image frames may be displayed on the display unit 606. The image frames processed by the graphic processor 6041 may be stored in the memory 609 (or other storage medium) or transmitted via the radio frequency unit 601 or the network module 602. The microphone 6042 can receive sound, and can process such sound into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 601 in case of the phone call mode.

The electronic device 600 also includes at least one sensor 605, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 6061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 6061 and/or the backlight when the electronic apparatus 600 is moved to the ear. As one type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of an electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 605 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.

The display unit 606 is used to display information input by the user or information provided to the user. The Display unit 606 may include a Display panel 6061, and the Display panel 6061 may be configured by a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.

The user input unit 607 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device. Specifically, the user input unit 607 includes a touch panel 6071 and other input devices 6072. Touch panel 6071, also referred to as a touch screen, may collect touch operations by a user on or near it (e.g., operations by a user on or near touch panel 6071 using a finger, stylus, or any suitable object or accessory). The touch panel 6071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 610, receives a command from the processor 610, and executes the command. In addition, the touch panel 6071 can be implemented by various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. The user input unit 607 may include other input devices 6072 in addition to the touch panel 6071. Specifically, the other input devices 6072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a track ball, a mouse, and a joystick, which are not described herein again.

Further, the touch panel 6071 can be overlaid on the display panel 6061, and when the touch panel 6071 detects a touch operation on or near the touch panel 6071, the touch operation is transmitted to the processor 610 to determine the type of the touch event, and then the processor 610 provides a corresponding visual output on the display panel 6061 according to the type of the touch event. Although the touch panel 6071 and the display panel 6061 are shown in fig. 6 as two separate components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 6071 and the display panel 6061 may be integrated to implement the input and output functions of the electronic device, and this is not limited here.

The interface unit 608 is an interface for connecting an external device to the electronic apparatus 600. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 608 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the electronic device 600 or may be used to transmit data between the electronic device 600 and external devices.

The memory 609 may be used to store software programs as well as various data. The memory 609 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 409 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The processor 610 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 609, and calling data stored in the memory 609, thereby performing overall monitoring of the electronic device. Processor 610 may include one or more processing units; preferably, the processor 610 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 610.

The electronic device 600 may further include a power supply 611 (e.g., a battery) for supplying power to the various components, and preferably, the power supply 611 may be logically connected to the processor 610 via a power management system, such that the power management system may be used to manage charging, discharging, and power consumption.

Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor 610, a memory 609, and a computer program stored in the memory 609 and capable of running on the processor 610, where the computer program is executed by the processor 610 to implement each process of the foregoing method for determining an axis center trajectory based on a multipath signal, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.

EXAMPLE five

The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned method for determining an axis trajectory based on a multipath signal, and can achieve the same technical effect, and is not described herein again to avoid repetition. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

The embodiment of the invention provides a computer-readable storage medium, which obtains a beat signal in each chirp signal cycle of each streaming data frame for a target area, and performs conversion processing on the beat signal based on a preset fourier transform algorithm to obtain a target signal corresponding to the beat signal, wherein the beat signal is a product of a conjugate of a transmission signal of a signal transceiver and a reflection signal of a target object received by the signal transceiver and returned for the transmission signal, a distance spectrum formed by the target signal corresponding to the beat signal in the target chirp signal cycle of the target streaming data frame, and a preset robust capon beam forming algorithm are used to generate an angle spectrum corresponding to the distance spectrum, and a spatial spectrum corresponding to the target area is generated based on the distance spectrum and the angle spectrum, the target streaming data frame is any one of the streaming data frames, the method comprises the steps that a target linear frequency modulation signal period is any one period in linear frequency modulation signal periods corresponding to a target streaming data frame, region identification processing is carried out on a space spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, multipath signals corresponding to each two-dimensional position region are determined based on target signals in each linear frequency modulation signal period of each streaming data frame, the multipath signals comprise target signals which come from different linear frequency modulation signal periods of different streaming data frames and are equivalent to sampling time, one-dimensional vibration signals corresponding to each two-dimensional position region are determined based on a preset radius constraint circle fitting algorithm and the multipath signals corresponding to each two-dimensional position region, and two-dimensional axis tracks corresponding to the target region are determined based on the one-dimensional vibration signals corresponding to each two-dimensional position region and a preset iteration algorithm, the preset iterative algorithm is to perform iterative processing on the determined two-dimensional axis locus based on the projection of the one-dimensional vibration signal on a preset observation angle to obtain the two-dimensional axis locus. Therefore, the two-dimensional axis locus of the target area is determined through the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, the determination accuracy of the two-dimensional axis locus can be improved, meanwhile, the problem of low determination efficiency of the two-dimensional axis locus caused by the participation of extra equipment is avoided, and the determination efficiency of the two-dimensional axis locus is improved.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory computer readable media (transmyedia) such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to 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 scope of the claims of the present invention.

Claims

1. A method for determining an axis locus based on a multipath signal is characterized by comprising the following steps:

2. The method of claim 1, wherein determining the one-dimensional vibration signal corresponding to each of the two-dimensional location areas based on a pre-set radius constrained circle fitting algorithm and the multipath signal corresponding to each of the two-dimensional location areas comprises:

3. The method according to claim 2, further comprising, before said determining the static clutter component corresponding to the multipath signal for each of said two-dimensional location areas based on said preset radius constrained circle fitting algorithm, a preset circle center direction constraint, a preset arc radius constraint, and the multipath signal corresponding to each of said two-dimensional location areas:

4. The method according to claim 3, wherein before determining the two-dimensional axial center trajectory corresponding to the target area based on the one-dimensional vibration signal corresponding to each two-dimensional position area and a preset iterative algorithm, the method further comprises:

5. The method according to claim 4, wherein the clustering the one-dimensional vibration signals corresponding to each two-dimensional position region based on a preset density clustering screening algorithm to obtain a plurality of cluster clusters comprises:

6. The method according to claim 4, wherein the determining a two-dimensional axial center trajectory corresponding to the target area based on the target vibration signal of each cluster and a preset iterative algorithm comprises:

O＝(V^TWV)^-1V^TWEX，

the projection vector at the preset observation angle is obtained;

7. The method of claim 6, further comprising:

Determining a first projection vector matrix, wherein e_pTarget vibration signals of the p-th clustering cluster in the target diagonal arrayCorresponding constituent element, x_pFor the target vibration signal of the p-th cluster,

Determining a first diagonal matrix;

8. An apparatus for determining a trajectory of a shaft based on a multipath signal, comprising:

9. An electronic device comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the multipath signal based axis center trajectory determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the multipath signal-based axis center trajectory determination method according to any one of claims 1 to 7.