CN111983598B

CN111983598B - Axis locus determining method and device based on multipath signals

Info

Publication number: CN111983598B
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: 2024-03-01
Anticipated expiration: 2040-07-22
Also published as: CN111983598A

Abstract

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

Axis locus determining method and device based on multipath signals

Technical Field

The present invention relates to the field of computer technologies, and in particular, to a method and an apparatus for determining an axis track based on multipath signals.

Background

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

At present, a one-dimensional displacement 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, an eddy current sensor and the like, and then a two-dimensional axis locus of the rotor is calculated through the one-dimensional displacement on the X axis and the Y axis according to a motion synthesis method.

However, the method can complete conversion from the electric signal to the displacement signal only after the plurality of secondary displacement sensors are calibrated in advance through the calibrator, and meanwhile, additional equipment is required to complete high-precision synchronization of the plurality of sensors, so that the determination efficiency of the two-dimensional axis track is low, and meanwhile, the problem of poor determination accuracy exists when the two-dimensional axis track is determined through a motion synthesis method.

Disclosure of Invention

The embodiment of the invention aims to provide an axis track determining method and device based on multipath signals, which are used for solving the problems of low determining efficiency and poor determining accuracy in the prior art when a two-dimensional axis track is determined.

In order to solve the technical problems, the embodiment of the invention is realized as follows:

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

acquiring a beat signal in each linear frequency modulation signal period of each stream data frame aiming at a target area, and carrying out transformation processing on the beat signal based on a preset Fourier transformation algorithm to obtain a target signal corresponding to the beat signal, wherein the beat signal is the product of the conjugate of a transmitting signal of signal receiving and transmitting equipment and a reflected signal returned by a target object aiming at the transmitting signal and received by the signal receiving and transmitting equipment;

generating an angle spectrum corresponding to a distance spectrum aiming at a distance spectrum formed by the target signal corresponding to the beat signal in a target chirp signal period of a target streaming data frame and a preset robust capone beam forming algorithm, and generating a space 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, and the target chirp signal period is any one of the chirp signal periods corresponding to the target streaming data frame;

Based on a preset constant false alarm rate operator, carrying out region identification processing on the spatial 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 stream data frame, wherein the multipath signal comprises the target signals with equivalent sampling time from different chirp signal periods of different stream data frames;

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 determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signals corresponding to each two-dimensional position area and a preset iteration algorithm, wherein the preset iteration algorithm is to perform iteration processing on the determined two-dimensional axis track based on projection of the one-dimensional vibration signals on a preset observation angle so as to acquire the two-dimensional axis track.

Optionally, the 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 signal corresponding to each two-dimensional position area includes:

Determining static clutter components corresponding to the multipath signals of each two-dimensional position area based on the preset radius constraint circle fitting algorithm, the preset circle center direction constraint, the preset circular arc radius constraint and the multipath signals corresponding to each two-dimensional position area;

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

Optionally, before the determining the 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 circular arc radius constraint and the multipath signal corresponding to each two-dimensional position area, the method further includes:

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

determining center points of a plurality of circular arcs based on a preset searching step length and center points of the circular arcs;

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

projecting the multipath signals 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;

Obtaining kurtosis of the projection sequence frequency spectrum corresponding to each first circle center direction on a preset frequency band, and obtaining the ratio between the frequency spectrum energy of the projection sequence frequency spectrum corresponding to each first circle center direction on the preset frequency band and 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 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 signals of each two-dimensional position area on the preset complex signal plane based on the direction of the center of the target to obtain a corresponding projection sequence, and obtaining 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 locus 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 clusters, wherein the preset density clustering and screening algorithm is an algorithm for clustering based on preset weights of the one-dimensional vibration signals and based on phase relations between the two-dimensional position areas corresponding to the one-dimensional vibration signals;

determining a target vibration signal of each cluster based on one-dimensional vibration signals 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 to perform iterative processing on the determined two-dimensional axis track based on projection of the one-dimensional vibration signal on a preset observation angle so as to obtain the two-dimensional axis track, and the method comprises the following steps:

and determining the two-dimensional axis track 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 projection of the target vibration signal on a preset observation angle, and performing iterative processing on the determined two-dimensional axis track to obtain the two-dimensional axis track.

Optionally, the clustering processing is performed on the one-dimensional vibration signal corresponding to each two-dimensional position area based on a preset density clustering screening algorithm to obtain a plurality of clusters, including:

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

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

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;

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

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

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

a target vibration signal for each of the clusters is determined based on the second vibration signals contained within each of the clusters.

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

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

O＝(V ^T WV) ^-1 V ^T WEX，

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, V ^T Is a transpose of the target projection vector matrix,wherein beta is _p A preset observation angle for the target vibration signal of the p-th cluster is +.>The projection vector on the preset observation angle is set;

And under the condition that the first axis locus meets a preset convergence condition, determining the first axis locus as a two-dimensional axis locus 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, a preset observation angle of the target vibration signal of each cluster, the target diagonal array of each cluster and a formula are based on the first axis track, the target vibration signal of each cluster

Determining a first projection vector matrix, wherein E _p For the constituent element corresponding to the target vibration signal of the p-th cluster in the target diagonal array, x _p For the target vibration signal of the p-th cluster,is the transpose of the first projection vector matrix, O is the first axis locus, beta _p A preset observation angle of a target vibration signal of the p-th cluster;

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

Determining a first diagonal matrix;

the first projection vector matrix is determined as the target projection vector matrix, and the first diagonal matrix is determined as the target diagonal matrix.

In a second aspect, an embodiment of the present invention provides an axis trajectory determining device based on a multipath signal, where the device includes:

the signal acquisition module is used for acquiring a beat signal in each linear frequency modulation signal period of each stream 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, wherein the beat signal is the product of the conjugate of a transmitting signal of signal receiving and transmitting equipment and a reflected signal returned by a target object aiming at the transmitting signal and received by the signal receiving and transmitting equipment;

the spatial spectrum determining module is used for generating a distance spectrum corresponding to a distance spectrum aiming at a target signal corresponding to the beat signal in a target chirp 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 area based on the distance spectrum and the angle spectrum, wherein the target streaming data frame is any one of the streaming data frames, and the target chirp signal period is any one of the chirp signal periods corresponding to the target streaming data frame;

The region determining module is used for carrying out 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, configured to determine, based on a target signal in each chirp signal 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 a different chirp signal period of a different streaming data frame and having an equivalent sampling time;

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

the track determining module is used for determining a two-dimensional axle center track corresponding to the target area based on the one-dimensional vibration signals corresponding to each two-dimensional position area and a preset iteration algorithm, wherein the preset iteration algorithm is used for carrying out iteration processing on the determined two-dimensional axle center track based on projection of the one-dimensional vibration signals on a preset observation angle so as to obtain the two-dimensional axle center track.

Optionally, the signal extraction module is configured to:

Optionally, the apparatus further comprises:

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

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

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

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

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

the standard determining module is used for determining a target measurement standard based on the kurtosis and the ratio corresponding to each first circle center direction;

the first determining module is used for 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;

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 circle of the target to obtain a corresponding projection sequence, and acquiring the projection height of the projection sequence;

and the second determining 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 carrying out clustering processing on 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, wherein the preset density clustering screening algorithm is an algorithm for carrying out clustering based on preset weights of the one-dimensional vibration signals and on the phase relation between the two-dimensional position areas corresponding to the one-dimensional vibration signals;

A third determining module, configured to determine a target vibration signal of each cluster based on one-dimensional vibration signals included in each cluster;

the track determining module is used for:

Optionally, the clustering module is configured to:

the third determining module is configured to:

Optionally, the track determining module is configured to:

O＝(V ^T WV) ^-1 V ^T WEX，

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, V ^T Is a transpose of the target projection vector matrix, Wherein beta is _p A preset observation angle for the target vibration signal of the p-th cluster is +.>For the preset observation angleProjection vectors on;

Optionally, the apparatus further comprises:

a first matrix determining module, configured to, in a case where the first axis locus does not satisfy the preset convergence condition, base on the first axis locus, the target vibration signal of each cluster, the preset observation angle of the target vibration signal of each cluster, and the target diagonal matrix, and a formula

a second matrix determining module, configured to determine a target vibration signal of each cluster 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, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the computer program when executed by the processor implements the steps of the method for determining an axis locus 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, where the computer program, when executed by a processor, implements the steps of the method for determining an axis locus based on a multipath signal provided in the first aspect.

As can be seen from the technical solutions provided in the embodiments of the present invention, by acquiring a beat signal in each chirp signal period of each streaming data frame for a target area, and performing a transform process on 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 received by the signal transceiver for the transmission signal, a distance spectrum formed by the target signal corresponding to the beat signal in the target chirp signal period of the target streaming data frame, and a preset robust capone beamforming algorithm, an angle spectrum corresponding to the distance spectrum is generated, and a spatial spectrum corresponding to the target area is generated based on the distance spectrum and the angle spectrum, where the target streaming data frame is any one of the streaming data frames, the target chirp signal period is any period in the chirp signal periods corresponding to the target streaming data frames, the region identification processing is performed on the spatial spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, the multipath signals corresponding to each two-dimensional position region are determined based on the target signals in each chirp signal period of each streaming data frame, the multipath signals comprise target signals which come from different chirp signal periods of different streaming data frames and are equivalent in sampling time, the 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, the one-dimensional vibration signals corresponding to each two-dimensional position region are determined based on the one-dimensional vibration signals corresponding to each two-dimensional position region and a preset iterative algorithm, and determining a two-dimensional axis track corresponding to the target area, wherein the preset iterative algorithm is based on projection of the one-dimensional vibration signal on a preset observation angle, and performing iterative processing on the determined two-dimensional axis track to acquire the two-dimensional axis track. In this way, the two-dimensional axis track of the target area is determined by the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, so that the determination accuracy of the two-dimensional axis track can be improved, and meanwhile, the problem of low determination efficiency of the two-dimensional axis track caused by the participation of additional equipment is avoided, namely, the determination efficiency of the two-dimensional axis track 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 that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for determining an axis locus based on a multipath signal;

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

FIG. 3 is a flow chart of another method for determining an axis locus based on multipath signals according to the present invention;

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

FIG. 5 is a schematic diagram of an axis locus determining 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 an axis track determining method and device based on multipath signals.

In order to make the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, shall fall within the scope of the invention.

Example 1

As shown in fig. 1, the embodiment of the present disclosure provides a method for determining an axis track based on a multipath signal, where an execution body of the method may be a server, and the server may be an independent server or a server cluster formed by a plurality of servers. The method specifically comprises the following steps:

in S102, a beat signal in each chirp signal period for each stream data frame of the target area is acquired, and the beat signal is subjected to a transform process 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 and a reflected signal returned by the signal transceiver for the transmission signal, where the signal transceiver may be any device capable of transmitting the transmission signal and receiving the reflected signal (i.e., a transmission signal returned by the target object for the transmission signal), for example, the signal transceiver may be a millimeter wave radar, and the target signal may be a signal corresponding to a distance unit of the target object.

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

At present, a one-dimensional displacement 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, an eddy current sensor and the like, and then a two-dimensional axis locus of the rotor is calculated through the one-dimensional displacement on the X axis and the Y axis according to a motion synthesis method. However, the method can complete conversion from the electric signal to the displacement signal only after the plurality of secondary displacement sensors are calibrated in advance through the calibrator, and meanwhile, additional equipment is required to complete high-precision synchronization of the plurality of sensors, so that the determination efficiency of the two-dimensional axis track is low, and meanwhile, the problem of poor determination accuracy exists when the two-dimensional axis track is determined through a motion synthesis method. Therefore, the embodiment of the present invention provides a technical solution capable of solving the above problems, and specifically can be seen in the following:

Taking a signal transceiver as an example of a millimeter wave radar, the millimeter wave radar can modulate a transmission signal by using a linear frequency modulation continuous wave mode, and receive a reflected signal after the transmission signal is reflected by a target object, wherein the received reflected signal still maintains the characteristic of linear frequency modulation, and the returned reflected signal only shows a frequency delay relative to round trip delay. Thus, the frequency difference between the transmission signal and the emission signal may reflect the distance of the target object to the millimeter wave radar. The hardware component of the millimeter wave radar may include a mixer that multiplies the conjugate of the transmission signal and the reflection signal to obtain a corresponding beat signal, where the frequency of the beat signal is the frequency difference between the transmission signal and the reflection signal.

The server can acquire the beat signal in each chirp signal period of each stream data frame of the target area, then the server can perform transformation processing on the beat signal based on a preset Fourier transformation algorithm to obtain a frequency spectrum of the beat signal according to a formulaConverting the frequency spectrum into a distance spectrum to obtain a corresponding target signal, wherein t is time, c is light speed, deltaF is the frequency of the beat signal, and K is the linear change slope of the frequency of the transmitted signal in the period of the linear frequency modulation signal 。

Furthermore, for sub-millimeter and even micrometer vibration signals, the amplitude of the sub-millimeter and even micrometer vibration signals is much smaller than the distance resolution δr, wherein,t is the total length of time 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 sub-millimeter level or even micrometer level), and R is a constant portion that is time-invariant, x (t) < δr can be obtained. Assuming that the initial time is 0, any subsequent time can be expressed as τt+t, where T is the total linear change duration, τ is the slow time, the basic unit of the slow time is T, T is the fast time, and the fast time T e [0, T). Since T is extremely short, typically 100 μs, it can be assumed that the displacement of the target object within one chirp period is negligible, i.e.> T is more than or equal to 0 and less than T. The beat signal of the period of the τ -th period chirp signal can be expressed as +.>And 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 unit. The beat signal may be processed based on a preset fourier transform algorithm to obtain a 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 period may be Wherein (1)>I.e. 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 be a fourier transform algorithm based on a blackman window so as to weaken spectrum leakage among distance spectrums, and can be used for carrying out direct current component filtering, so that only dynamic reflection results are reserved.

In S104, a distance spectrum formed by a target signal corresponding to a beat signal in a target chirp signal period of a 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 a target area is generated based on the distance spectrum and the angle spectrum.

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

In implementation, the server may split the distance spectrum into high-resolution angle spectrums based on a preset robust capone beamforming algorithm to obtain corresponding angle spectrums, and may then generate a high-resolution spatial spectrum corresponding to the target region based on the distance spectrum and the angle spectrums.

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 region identification processing is sequentially performed on a distance region and an angle region of the determined spatial spectrum, so as to obtain a plurality of two-dimensional position regions (called multipath regions).

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

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

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 take 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 location areas. For example, assuming that there are 30 stream data frames for the target area, each stream data frame corresponds to 200 chirp signal periods, the 1 st to 10 th stream data frames may be regarded as the 1 st data frame group, the 11 th to 20 th stream data frames may be regarded as the 2 nd data frame group, and the 21 st to 30 th stream data frames may be regarded as the 3 rd data frame group. The server may then use the 1 st, 11 th, and 21 st stream data frames as target stream data frames, respectively, and use the 1 st chirp period of the 1 st stream data frame as target chirp period, the 1 st chirp period of the 11 st stream data frame as target chirp period, and the 1 st chirp period of the 21 st stream data frame as target chirp period, 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 signal period of each streaming data frame according to the two-dimensional location area determined by the target streaming data frame (i.e. the 1 st streaming data frame) in the same data frame group (e.g. the data frame group formed by the 1 st to 4 th streaming data frames) so as to determine the multipath signal corresponding to each two-dimensional location area.

I.e. for each two-dimensional location area, one multipath signal may be included, each multipath signal may contain 10 x 200 = 2000 samples (i.e. the target signal).

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

In implementation, a static clutter component corresponding to a target signal contained in a multipath signal can be determined based on a geometric distance radius constraint circle fitting algorithm and the multipath signal corresponding to each two-dimensional position area, then the corresponding static clutter component is deleted from the target signal, and the server extracts a one-dimensional vibration signal corresponding to each two-dimensional position area according to the target signal after deletion.

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

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

In practice, a corresponding two-dimensional axis trajectory may be determined from a plurality of independent one-dimensional observations (i.e., one-dimensional vibration signals corresponding to each two-dimensional location area) from different angles of observation. 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 a 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 multipath signals, which obtains a beat signal in each linear frequency modulation signal period of each streaming data frame aiming at a target area, 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 the product of the conjugate of a transmitting signal of a signal transceiver and a reflecting signal returned by a target object received by the signal transceiver aiming at the transmitting signal, a distance spectrum formed by the target signal corresponding to the beat signal in the target linear frequency modulation signal period of the target streaming data frame and a preset robust capone beam forming algorithm, generates an angle spectrum corresponding to the distance spectrum, and generates a space spectrum corresponding to the target area based on the distance spectrum and the angle spectrum, the target streaming data frame is any one of the streaming data frames, the target chirp signal period is any one of the chirp signal periods corresponding to the target streaming data frame, the spatial spectrum is subjected to region identification processing based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, the multipath signal corresponding to each two-dimensional position region is determined based on the target signal in each chirp signal period of each streaming data frame, the multipath signal comprises the target signal which is from different chirp signal periods of different streaming data frames and has equivalent sampling time, the one-dimensional vibration signal corresponding to each two-dimensional position region is determined based on a preset radius constraint circle fitting algorithm and the multipath signal corresponding to each two-dimensional position region, the one-dimensional vibration signal corresponding to each two-dimensional position region is determined based on the one-dimensional vibration signal corresponding to each two-dimensional position region and a preset iterative algorithm, and determining a two-dimensional axis track corresponding to the target area, wherein the preset iterative algorithm is based on projection of the one-dimensional vibration signal on a preset observation angle, and performing iterative processing on the determined two-dimensional axis track to acquire the two-dimensional axis track. In this way, the two-dimensional axis track of the target area is determined by the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, so that the determination accuracy of the two-dimensional axis track can be improved, and meanwhile, the problem of low determination efficiency of the two-dimensional axis track caused by the participation of additional equipment is avoided, namely, the determination efficiency of the two-dimensional axis track is improved.

Example two

As shown in fig. 3, an embodiment of the present invention provides a method for determining an axis track based on a multipath signal, where an execution body of the method may be a server, and the server may be an independent server or a server cluster formed by a plurality of servers. The method specifically comprises the following steps:

in S302, a beat signal in each chirp signal period for each stream data frame of the target area is acquired, and the beat signal is subjected to a transform process based on a preset fourier transform algorithm, to obtain a target signal corresponding to the beat signal.

In S304, a distance spectrum formed by a target signal corresponding to a beat signal in a target chirp signal period of a target streaming data frame and a preset robust capone beam forming algorithm are generated, and a spatial spectrum corresponding to a target area is generated based on the distance spectrum and the angle 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 position area is determined based on the target signal in each chirp period of each stream data frame.

The specific processing procedures of S302 to S308 may be referred to the relevant contents of S102 to S108 in the first embodiment, and are not described herein.

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

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

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

The preset search step may be a step of any length within 0 to 2 pi, for example, the preset search step may be 16/pi.

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

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

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

In implementations, the server may determine the value of k (α) =max (κ) _b ，0)·∈ _b Determining a target metric, wherein k (alpha) is the target metric, and κ _b E is the kurtosis corresponding to the b first circle center direction _b The ratio corresponding to the b first circle center direction.

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

In practice, the server can select the direction with the maximum metric to determine the direction of the center of the target circle as alpha according to the target metric k (alpha) ^* 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 ] ^* -δα，α ^* +δα]∪[α ^* -δα+π，α ^* +δα+π]，α ^* E 0, pi), wherein δα may be a preset search step.

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

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

In implementation, the accuracy of one-dimensional vibration signal extraction can be improved by the circular arc radius constraint, the circular arc radius constraint can be determined by constructing a geometric transformation relation according to a known preset amplitude range, and the preset amplitude range is assumed to be [ D ] _min ，D _max ]The projection height is h, namely, the peak value of the projection sequence after the multipath signal of the two-dimensional position area is projected to the center direction of the target. As shown in fig. 4, when the radius of the circular arc takes the minimum value, the corresponding central angle takes the maximum value, and the amplitude takes the maximum value; when the radius of the circular arc takes the maximum value, the corresponding central angle takes the minimum value, and the amplitude also takes the minimum value. The relationship between the central angle θ and the amplitude D may be Where λ is the wavelength. . By the projection degree h, the relation between r and θ can be constructed as follows: />Thus, by the above two formulas, it is possible to construct a relationship between the radius of the circular arc and the amplitude 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 for each two-dimensional location area is determined 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 location area.

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

In implementation, multiple frames of streaming data frames can be divided into a group, multipath signals corresponding to each two-dimensional area corresponding to each group of streaming data frames are determined based on a preset radius constraint circle fitting algorithm, a preset circle center direction constraint and a preset circular arc radius constraint, static clutter components corresponding to the multipath signals of each two-dimensional position area are determined, and one-dimensional vibration signals corresponding to each two-dimensional position area are determined according to the static clutter components.

Because the extracted one-dimensional vibration signals may have partial similarity and may all contain reflection signals from adjacent reflection positions, in order to balance the contributions 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 area may be clustered based on a preset density clustering and screening algorithm.

In S332, based on a preset density cluster screening algorithm, a clustering process is performed on the one-dimensional vibration signals corresponding to each two-dimensional position area, so as to obtain a plurality of clusters.

The preset density clustering and screening algorithm can be an algorithm for clustering based on preset weights of one-dimensional vibration signals and based on phase relations between two-dimensional position areas corresponding to the one-dimensional vibration signals.

In practice, the processing manner of S332 may be varied, and the following alternative implementation manner is provided, which may be specifically referred to as the following steps one to five.

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

And step two, 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 circular arc radius, the spectral kurtosis and the spectral 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 so as to obtain a second vibration signal corresponding to each two-dimensional position area.

In an implementation, the server may determine the one-dimensional vibration signal with the preset weight ranked at the top 70% as the second vibration signal.

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

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

In practice, the distance measure between every two second vibration signals may be based on min [ phi ] ₁ -φ ₂ -π，φ ₁ -φ ₂ ，φ ₁ -φ ₂ +π]Determining, wherein phi ₁ ，φ ₂ The 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 clusters.

In an implementation, the server may acquire the position information of each two second vibration signals on the spatial spectrum, if two second vibration signals correspond to two-dimensional position areas that are spatially adjacent, keep their distance measurement unchanged, and if two second vibration signals correspond to two-dimensional position areas that are spatially not adjacent, set the distance measurement corresponding to the two second vibration signals in the distance measurement matrix to infinity, which indicates that the two second vibration signals with two-dimensional position areas that are not adjacent but have similar phases are not aggregated.

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

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

In an implementation, for each cluster, the server may weight sum the second vibration signals according to the second vibration signals contained therein and a preset weight of the second vibration signals, and take the result as a target vibration signal of the cluster.

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

In S336, a two-dimensional axis trajectory 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 projection of the target vibration signal on a preset observation angle, and perform iterative processing on the determined two-dimensional axis track to obtain the two-dimensional axis track.

In practice, for the target vibration signal of the p-th cluster, it is actually the projection of the two-dimensional axis estimate onto the preset observation angle, which projection can be expressed as, for any instant τ _{Degree of} ， Wherein beta is _p Preset observation angle for target vibration signal of p-th cluster,/for the target vibration signal of p-th cluster>To observe projection vector at angle, x _p (τ _{Degree of} ) At τ for the p-th target vibration signal _{Degree of} Sampling points at the time.

To tolerate the accuracy of target vibration signal extraction, an error tolerance factor (e) can be introduced _p ) The method comprises the following steps:the formula is that one path of target vibration signal is at the moment tau _{Degree of} Can synthesize the projection relation of the multipath target vibration signal at tau _{Degree of} ＝τ ₁ …τ _N The projection relationship in the matrix can be expressed in the following form:

EX＝VO

where e=diag ({ E) _p } _1×P ) Expressed as { E } _p } _1×P As a diagonal array of diagonal elements, x= { X _p (τ _{Degree of} )} _P×N A matrix of multiple target vibration signals,for viewing the angular projection vector matrix, o= { O (τ _{Degree of} )} _2×N Is a two-dimensional track. In the four variables, E and V are unknown quantities, X is an observed quantity, and O is a target quantity, so that E and V need to be solved simultaneously for solving O, and the two-dimensional axis track can be obtained by carrying out processing of a preset iterative algorithm through the following steps one to five.

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 ^T WV) ^-1 V ^T WEX，

Determining a first axis track corresponding to a 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 a target diagonal matrix, and V ^T Is the transpose of the matrix of the projection vector of the object,wherein beta is _p Preset observation angle for target vibration signal of p-th cluster,/for the target vibration signal of p-th cluster>Is a projection vector on a preset observation angle.

And (3) continuously executing the second step or the third to fifth steps according to whether the first axis track meets the preset convergence condition.

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

Step three, 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 and the target diagonal array of the target vibration signal of each cluster, and the formula

Determining a first projection vector matrix, wherein E _p Is the constituent element corresponding to the target vibration signal of the p-th cluster in the target diagonal array, x _p The target vibration signal for the p-th cluster,is the transpose matrix of the first projection vector matrix, O is the first axis track, beta _p And the preset observation angle of the target vibration signal of the p-th cluster is set.

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

A first diagonal array is determined.

And fifthly, 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 first step until the first axis track meets a preset convergence condition.

Example III

The method for determining the axis locus based on the multipath signal provided in the embodiment of the present disclosure is based on the same concept, and the embodiment of the present disclosure further provides an apparatus for determining the axis locus based on the multipath signal, as shown in fig. 5.

The axis track determining device based on the multipath signal 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 period of each stream data frame for a target area, and perform a transformation process on the beat signal based on a preset fourier transform algorithm, so as 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 reflected signal returned by a target object received by the signal transceiver for the transmission signal;

the spatial spectrum determining module 502 is configured to generate, for a distance spectrum formed by the target signal corresponding to the beat signal in a target chirp signal period of a target streaming data frame, and a preset robust capone beam forming 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 the 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 location regions;

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

the signal extraction module 505 is configured to determine 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;

the track determining module 506 is 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 projection of the one-dimensional vibration signal on a preset observation angle, and perform iterative processing on the determined two-dimensional axis track to obtain the two-dimensional axis track.

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

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

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

O＝(V ^T WV) ^-1 V ^T WEX，

Determining a first axis track corresponding to the target area, wherein O is the first axis track, and W is the first axis trackA weight matrix formed by preset weight values of each target vibration signal, wherein E is the target diagonal matrix, V ^T Is a transpose of the target projection vector matrix, Wherein beta is _p A preset observation angle for the target vibration signal of the p-th cluster is +.>The projection vector on the preset observation angle is set;

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

Determining a first diagonal matrix;

Example IV

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

the electronic device 600 includes, but is not limited to: radio frequency unit 601, network module 602, audio output unit 603, input unit 604, sensor 605, display unit 606, user input unit 607, interface unit 608, memory 609, processor 610, and power supply 611. It will be appreciated by those skilled in the art that the electronic device structure shown in fig. 6 is not limiting of the electronic device and that the electronic device may include more or fewer components than shown, or may combine certain components, or a different arrangement of components. In the embodiment of the invention, the electronic equipment comprises, 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 obtain a beat signal in each chirp signal period of each streaming data frame for a target area, and perform a transform process on the beat signal based on a preset fourier transform algorithm, so as 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 the signal transceiver and a reflected signal returned by a target object received by the signal transceiver for the transmission signal; generating an angle spectrum corresponding to a distance spectrum aiming at a distance spectrum formed by the target signal corresponding to the beat signal in a target chirp signal period of a target streaming data frame and a preset robust capone beam forming algorithm, and generating a space 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, and the target chirp signal period is any one of the chirp signal periods corresponding to the target streaming data frame; based on a preset constant false alarm rate operator, carrying out region identification processing on the spatial 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 stream data frame, wherein the multipath signal comprises the target signals with equivalent sampling time from different chirp signal periods of different stream data frames; 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 determining a two-dimensional axis track corresponding to the target area based on the one-dimensional vibration signals corresponding to each two-dimensional position area and a preset iteration algorithm, wherein the preset iteration algorithm is to perform iteration processing on the determined two-dimensional axis track based on projection of the one-dimensional vibration signals on a preset observation angle so as to acquire the two-dimensional axis track.

In addition, the processor 610 is further configured to determine a static clutter component corresponding to the multipath signal of each of the two-dimensional location areas 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 of the two-dimensional location areas; the one-dimensional vibration signal corresponding to each of the two-dimensional position areas is determined based on the multipath signal of each of the two-dimensional position areas and the corresponding static clutter component.

In addition, the processor 610 is further configured to obtain, in a preset complex signal plane, a center point of an arc formed by multipath signals corresponding to each of the two-dimensional location areas; determining center points of a plurality of circular arcs based on a preset searching step length and center points of the circular arcs; acquiring a first circle center direction from a circle center point of each circular arc to a center point of the circular arc; projecting the multipath signals 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; obtaining kurtosis of the projection sequence frequency spectrum corresponding to each first circle center direction on a preset frequency band, and obtaining the ratio between the frequency spectrum energy of the projection sequence frequency spectrum corresponding to each first circle center direction on the preset frequency band and 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 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 signals of each two-dimensional position area on the preset complex signal plane based on the direction of the center of the target to obtain a corresponding projection sequence, and obtaining 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 area based on a preset density cluster screening algorithm, so as to obtain a plurality of clusters, where the preset density cluster 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 two-dimensional position areas corresponding to the one-dimensional vibration signal; determining a target vibration signal of each cluster based on one-dimensional vibration signals contained in each cluster; and determining the two-dimensional axis track 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 projection of the target vibration signal on a preset observation angle, and performing iterative processing on the determined two-dimensional axis track to obtain the two-dimensional axis track.

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

In addition, the processor 610 is further configured to determine a target vibration signal of each of the clusters, a preset weight of each of the target vibration signals, a preset observation angle of each of the target vibration signals of each of the clusters, a preset target diagonal array, a preset target projection vector matrix, and a formula

O＝(V ^T WV) ^-1 V ^T WEX，

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, V ^T Is a transpose of the target projection vector matrix,wherein beta is _p A preset observation angle for the target vibration signal of the p-th cluster is +.>The projection vector on the preset observation angle is set; and under the condition that the first axis locus meets a preset convergence condition, determining the first axis locus as a two-dimensional axis locus corresponding to the target area.

In addition, the processor 610 is further configured to, in a case where the first axis locus does not satisfy the preset convergence condition, base on the first axis locus, the target vibration signal of each cluster, the preset observation angle of the target vibration signal of each cluster, and the target diagonal array, and the formula

Determining a first projection vector matrix, wherein E _p For the constituent element corresponding to the target vibration signal of the p-th cluster in the target diagonal array, x _p For the target vibration signal of the p-th cluster,is the transpose of the first projection vector matrix, O is the first axis locus, beta _p A preset observation angle of a target vibration signal of the p-th cluster; based on the first projection vector matrix, a target vibration signal of each cluster, and a formula

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

The embodiment of the invention provides an electronic device, which obtains a beat signal in each linear frequency modulation signal period of each stream-type data frame aiming at a target area, 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 the product of the conjugate of a transmission signal of a signal transceiver and a reflection signal returned by a target object received by the signal transceiver aiming at the transmission signal, the distance spectrum formed by the target signal corresponding to the beat signal in the target linear frequency modulation signal period of the target stream-type data frame, and a preset robust capone beam forming algorithm, generates an angle spectrum corresponding to the distance spectrum, generates a spatial spectrum corresponding to the target area based on the distance spectrum and the angle spectrum, and the target stream-type data frame is any one data frame in the stream-type data frames, the target chirp signal period is any period in the chirp signal periods corresponding to the target streaming data frames, the region identification processing is performed on the spatial spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, the multipath signals corresponding to each two-dimensional position region are determined based on the target signals in each chirp signal period of each streaming data frame, the multipath signals comprise the target signals which come from different chirp signal periods of different streaming data frames and are equivalent in sampling time, the 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, the two-dimensional axis track corresponding to the target region is 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 based on projection of a 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 this way, the two-dimensional axis track of the target area is determined by the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, so that the determination accuracy of the two-dimensional axis track can be improved, and meanwhile, the problem of low determination efficiency of the two-dimensional axis track caused by the participation of additional equipment is avoided, namely, the determination efficiency of the two-dimensional axis track is improved.

It should be understood that, in the embodiment of the present invention, the radio frequency unit 601 may be used to receive and send information or signals during a call, specifically, receive downlink data from a base station, and then process the downlink data with the processor 610; and, the uplink data is transmitted to the base station. Typically, the 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. In addition, the radio frequency unit 601 may also communicate with networks 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 helping the user to send and receive e-mail, browse web pages, and access streaming media, etc.

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 (e.g., a call signal reception sound, a message reception sound, etc.) related to a specific function performed by the electronic device 600. The audio output unit 603 includes a speaker, a buzzer, a receiver, and the like.

The input unit 604 is used for receiving audio or video signals. The input unit 604 may include a graphics processor (Graphics Processing Unit, GPU) 6041 and a microphone 6042, the graphics processor 6041 processing image data of still pictures or video obtained by an image capturing apparatus (such as a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 606. The image frames processed by the graphics 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. Microphone 6042 may receive sound and can process such sound into audio data. The processed audio data may be converted into a format output that can be transmitted to the mobile communication base station via the radio frequency unit 601 in the case of a telephone call mode.

The electronic device 600 also includes at least one sensor 605, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 6061 according to the brightness of ambient light, and the proximity sensor can turn off the display panel 6061 and/or the backlight when the electronic device 600 moves to the ear. As one of the motion sensors, the accelerometer sensor can detect the acceleration in all directions (generally three axes), and can detect the gravity and direction when stationary, and can be used for recognizing the gesture of the electronic equipment (such as horizontal and vertical screen switching, related games, magnetometer gesture calibration), vibration recognition related functions (such as pedometer and knocking), and the like; the sensor 605 may also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which are not described herein.

The display unit 606 is used to display information input by a 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 in the form of a liquid crystal display (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 to 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 thereon or thereabout by a user (e.g., operations of the user on touch panel 6071 or thereabout using any suitable object or accessory such as a finger, stylus, or the like). The touch panel 6071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch azimuth 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 detection device and converts it into touch point coordinates, which are then sent to the processor 610, and receives and executes commands sent from the processor 610. In addition, the touch panel 6071 may be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. The user input unit 607 may include other input devices 6072 in addition to the touch panel 6071. Specifically, other input devices 6072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a track ball, a mouse, and a joystick, which are not described herein.

Further, the touch panel 6071 may be overlaid on the display panel 6061, and when the touch panel 6071 detects a touch operation thereon or thereabout, the touch operation is transmitted to the processor 610 to determine a type of a 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 in fig. 6, the touch panel 6071 and the display panel 6061 are two independent components for implementing 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, which is not limited herein.

The interface unit 608 is an interface to which an external device is connected to the electronic apparatus 600. For example, the external devices may include a wired or wireless headset port, an external power (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 an external device and transmit the received input to one or more elements within the electronic apparatus 600 or may be used to transmit data between the electronic apparatus 600 and an external device.

The memory 609 may be used to store software programs as well as various data. The memory 609 may mainly include a storage program area that may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), and a storage data area; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, 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 entire electronic device using various interfaces and lines, and 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. The processor 610 may include one or more processing units; preferably, the processor 610 may integrate an application processor that primarily handles operating systems, user interfaces, applications, etc., with a modem processor that primarily 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 also include a power supply 611 (e.g., a battery) for powering the various components, and preferably the power supply 611 may be logically coupled to the processor 610 via a power management system that performs functions such as managing charging, discharging, and power consumption.

Preferably, the embodiment of the present invention further provides an electronic device, including 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 when executed by the processor 610 implements each process of the foregoing embodiment of the axis track determining method based on multipath signals, and the same technical effects can be achieved, so that repetition is avoided, and no further description is given here.

Example five

The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the processes of the above-mentioned embodiment of the method for determining the axis track based on the multipath signal, and can achieve the same technical effects, so that repetition is avoided, and no further description is given here. Wherein the computer readable storage medium is selected from Read-Only Memory (ROM), random access Memory (RandomAccess Memory, RAM), magnetic disk or optical disk.

The embodiment of the invention provides a computer readable storage medium, which is used for obtaining a beat signal in each linear frequency modulation signal period of each stream data frame aiming at 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, 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 received by the signal transceiver aiming at the transmission signal, aiming at a distance spectrum formed by the target signal corresponding to the beat signal in the target linear frequency modulation signal period of the target stream data frame, and a preset robust capone beam forming algorithm, generating an angle spectrum corresponding to the distance spectrum, generating a spatial spectrum corresponding to the target area based on the distance spectrum and the angle spectrum, wherein the target stream data frame is any one data frame in the stream data frames, the target chirp signal period is any period in the chirp signal periods corresponding to the target streaming data frames, the region identification processing is performed on the spatial spectrum based on a preset constant false alarm rate operator to divide the target region into a plurality of two-dimensional position regions, the multipath signals corresponding to each two-dimensional position region are determined based on the target signals in each chirp signal period of each streaming data frame, the multipath signals comprise the target signals which come from different chirp signal periods of different streaming data frames and are equivalent in sampling time, the 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, the two-dimensional axis track corresponding to the target region is 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 based on projection of a 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 this way, the two-dimensional axis track of the target area is determined by the one-dimensional vibration signals corresponding to the multipath signals of each two-dimensional position area, so that the determination accuracy of the two-dimensional axis track can be improved, and meanwhile, the problem of low determination efficiency of the two-dimensional axis track caused by the participation of additional equipment is avoided, namely, the determination efficiency of the two-dimensional axis track is improved.

It will be appreciated by those skilled in the art that 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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 one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

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

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 storage media for a computer 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, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transshipment) 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 one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

The foregoing is merely exemplary of the present invention and is not intended to limit the present invention. Various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are to be included in the scope of the claims of the present invention.

Claims

1. The axis track determining method based on the multipath signals is characterized by comprising the following steps:

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

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

4. The method of claim 3, further comprising, prior to said determining a two-dimensional axis trajectory corresponding to said target region based on said one-dimensional vibration signal corresponding to each two-dimensional location region and a preset iterative algorithm:

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

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

O＝(V ^T WV) ^-1 V ^T WEX，

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, V ^T Is a transpose of the target projection vector matrix,wherein beta is _p Presetting the target vibration signal of the p-th clusterViewing angle (I)>The projection vector on the preset observation angle is set;

7. The method of claim 6, wherein the method further comprises:

Determining a first diagonal matrix;

8. An axis locus determining device based on multipath signals, comprising:

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

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