CN111427022A - Array radar angle measurement method based on maximum likelihood estimation - Google Patents
Array radar angle measurement method based on maximum likelihood estimation Download PDFInfo
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- CN111427022A CN111427022A CN202010381667.6A CN202010381667A CN111427022A CN 111427022 A CN111427022 A CN 111427022A CN 202010381667 A CN202010381667 A CN 202010381667A CN 111427022 A CN111427022 A CN 111427022A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Abstract
The invention provides an array radar angle measurement method based on maximum likelihood estimation, wherein the method comprises the following steps: acquiring array element information of the array radar, and calculating a guide vector of the array radar according to the array element information; constructing an initial echo signal model according to the guide vector, and performing anti-interference processing on the initial echo signal model according to a principal component inversion method to obtain a target echo signal model; constructing an angle measurement cost function related to echo signal parameters based on a target echo signal model according to a maximum likelihood estimation algorithm, wherein the echo signal parameters comprise azimuth and pitching; and sequentially bringing the echo signal parameters into an angle measurement cost function, selecting a target echo signal parameter which enables the angle measurement cost function to be minimum, wherein the angle corresponding to the target echo signal parameter is the measured target angle. According to the technical scheme, the angle estimation of the target angle is realized by utilizing the maximum likelihood estimation, so that the radar system utilizes the advantage of digital signal processing to realize the measurement of the target angle in a complex scene.
Description
Technical Field
The invention relates to the technical field of array radar angle measurement, in particular to an array radar angle measurement method based on maximum likelihood estimation.
Background
The target angle estimation is an important task in the field of radar detection, and has very important significance for target positioning and tracking.
Currently, a monopulse angle measurement technology is commonly used for estimating the target angle of an array radar, a phase sum difference monopulse angle measurement method divides the array into two completely same sub-arrays, a phase shifter is used for enabling beams of the left sub-array and the right sub-array to point to the same direction, and the angle is measured according to the phase difference of signals received by the two sub-arrays. When interference exists in the received signals, the left and right sub-arrays can be respectively subjected to self-adaptive beam forming to inhibit the interference, and then the difference and the ratio angle measurement are calculated. However, in the interference cancellation process or in a complex array arrangement scene, an array directional diagram is distorted, an angle identifying curve is jittered but not monotonously adjusted, and adverse effects are brought to monopulse angle measurement.
Disclosure of Invention
In view of the above, it is necessary to provide an array radar angle measurement method based on maximum likelihood estimation to solve the above technical problems.
A method for array radar angle measurement based on maximum likelihood estimation, the method comprising: acquiring array element information of an array radar, and calculating a guide vector of the array radar according to the array element information; constructing an initial echo signal model according to the guide vector, and performing anti-interference processing on the initial echo signal model according to a principal component inversion method to obtain a target echo signal model; constructing an angle measurement cost function related to echo signal parameters based on a target echo signal model according to a maximum likelihood estimation algorithm, wherein the echo signal parameters comprise azimuth and pitching; and sequentially bringing the echo signal parameters into the angle measurement cost function, and selecting a target echo signal parameter which enables the angle measurement cost function to be minimum, wherein the angle corresponding to the target echo signal parameter is the measured target angle.
In one embodiment, the calculating a steering vector of the array radar according to the array element information specifically includes: and calculating the response phase of the echo signal according to the phase center position coordinates of the array elements, and calculating to obtain the steering vector according to the response phase.
In one embodiment, the performing interference rejection processing on the initial echo signal model according to a principal component inversion method to obtain a target echo signal model includes: acquiring interference signal information, acquiring an interference matrix according to the interference signal information, and acquiring an anti-interference projection matrix according to a principal component inversion method based on the interference matrix; and substituting the anti-interference projection matrix into an initial echo signal model to process an interference signal to obtain the target echo signal model.
In one embodiment, the constructing an angle measurement cost function about echo signal parameters according to a maximum likelihood estimation algorithm based on a target echo signal model includes: carrying out logarithm taking processing on the target echo signal model to obtain a logarithm likelihood function related to echo signal parameters; bringing echo signal parameters into the log-likelihood function to obtain the maximum likelihood estimation of the echo signal about the amplitude; substituting the maximum likelihood estimation into the log-likelihood function to obtain a generalized likelihood function; and obtaining a generalized maximum likelihood estimation of the echo signal parameters according to the generalized likelihood function, and defining an angle measurement cost function related to the echo signal parameters according to the generalized maximum likelihood estimation.
According to the array radar angle measurement method based on the maximum likelihood estimation, the problem of angle measurement of the array radar is considered from the angle of parameter estimation, anti-interference processing is carried out on echo signals by using a principal component inversion method, an angle measurement cost function is obtained by using a maximum likelihood estimation algorithm, the angle with the smallest angle measurement cost function is used as a target angle estimation, and a radar system can fully utilize the advantage of digital signal processing to realize measurement of a target angle in a complex scene.
Drawings
Fig. 1 is a schematic flowchart of an array radar angle measurement method based on maximum likelihood estimation according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of constructing an angle measurement cost function according to an embodiment of the present invention;
FIG. 3 is a relationship between an angle measurement cost function and an angle φ provided in an embodiment of the present invention;
fig. 4 shows the target estimated angular deviation and the root mean square error at different signal-to-noise ratios according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings by way of specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In one embodiment, as shown in fig. 1, there is provided a maximum likelihood estimation-based array radar angle measurement method, including the following steps:
s110, array element information of the array radar is obtained, and a guide vector of the array radar is calculated according to the array element information.
Specifically, the acquired array element information includes the coordinates of the array elements, the number of the array elements, the distribution form of the array elements, the spacing between the array elements, and the excitation amplitude and phase of each array element. Wherein, the array radar with the array element number N has the guide vector of
a(θ,φ)＝[a1(θ,φ)…,an(θ,φ),…aN(θ,φ)]T#(1)
Wherein
Is the response of the nth array element to signals from the azimuth theta and pitch phi directions. Phase of response is controlled by
ψn(θ,φ)＝xncosφcosθ+yncosφsinθ+znsinφ#(3)
Determining in which (x)n,yn,zn) Is the phase center position coordinate of the nth array element.
For example, assume that the array is a one-dimensional array, the number of array elements is 16, the array element spacing is 1m, and the coordinates of the phase center positions of the array elements
(xn,yn,zn)＝(0,0,n),n＝1,2,…,N
Target and interference parameters are shown in the following table
| Target direction (theta)t,φt) | Signal to noise ratio | Direction of interference (theta)j,φj) | Dry to noise ratio |
| (0°,30°) | 15dB | (0°,29.8°) | 35dB |
Calculate its array steering according to step S110, i.e.:
a(θ,φ)＝[a1(θ,φ)…,an(θ,φ),…aN(θ,φ)]T#(4)
wherein
S120, an initial echo signal model is built according to the guide vector, anti-interference processing is carried out on the initial echo signal model according to a principal component inversion method, and a target echo signal model is obtained.
Specifically, consider the signal model as follows
Wherein the content of the first and second substances,
sr(t; N) is the signal received by the nth array element at time t, N is 1, …, N;
sT(t) is the target echo signal, θTAnd phiTRespectively the azimuth and the pitch of the target;
sj(t) is the jth interference signal, θjAnd phijThe azimuth and pitch, respectively, of the jth interferer may be obtained by techniques such as DOA estimation, which are known in the present invention. (DOA estimation is an industry term in the research fields of electronics, communication, radar, sonar and the like, and obtains distance information and orientation information of a target by processing received echo signals.)
w (t; n) is complex white Gaussian noise with variance σ2；
For symbol simplicity, the sampling at time t is ignored, and let aj＝a(θj,φj) Then the signal model can be expressed as
For example, based on the example of the one-dimensional linear array in step S110, after obtaining the array guide thereof, the initial echo signal model constructed according to the above step S120 is:
s＝sta(θt,φt)+sja(θj,φj)+w#(8)
the anti-interference processing on the initial echo signal model is specifically as follows:
setting a total of J interference signals, making the interference matrix
A＝[a1,a2,...,aJ]
From principal component inversion, the interference rejection projection matrix can be represented as PJ＝I-A(AHA)-1AH
Its projection result on the interference steering vector is 0, i.e.
Wherein
Therefore, the result obtained after the anti-interference processing is performed on the signal can be represented by the following model
According to the steps, performing anti-interference processing on the initial echo signal model of the one-dimensional linear array corresponding to the expression (8) to obtain a target echo signal model of the one-dimensional linear array:
PJ＝I-a(θj,φj)(a(θj,φj)Ha(θj,φj))-1a(θj,φj)H#(12)
y＝sTPJa(θt,φt)+PJw#(13)
in one embodiment, step S120 further includes obtaining interference signal information, obtaining an interference matrix according to the interference signal information, and obtaining an anti-interference projection matrix according to a principal component inversion method based on the interference matrix; and substituting the anti-interference projection matrix into the initial echo signal model to process the interference signal to obtain a target echo signal model.
S130, based on the target echo signal model, according to a maximum likelihood estimation algorithm, an angle measurement cost function related to echo signal parameters is constructed, wherein the echo signal parameters comprise azimuth and pitching.
The method comprises the steps of carrying out logarithm processing on a target echo signal model to obtain a log-likelihood function related to echo signal parameters, then bringing the echo signal parameters into the log-likelihood function to obtain a maximum likelihood estimation related to amplitude of an echo signal, bringing the maximum likelihood estimation into the log-likelihood function to obtain a generalized likelihood function, then obtaining the generalized maximum likelihood estimation related to the echo signal parameters according to the generalized likelihood function, and finally defining a tested angle cost function related to the echo signal parameters according to the generalized maximum likelihood estimation.
In one embodiment, as shown in fig. 2, step S130 further includes steps S131-S134, specifically as follows:
step S131 performs logarithm processing on the target echo signal model to obtain a log-likelihood function related to the echo signal parameter.
Based on the signal model after the anti-interference processing, the data y only contains a signal component and a noise component, and the log-likelihood function of the signal can be written as
Wherein the content of the first and second substances,
step S132 brings the echo signal parameters into a log-likelihood function to obtain the maximum likelihood estimation of the echo signal with respect to the amplitude.
Specifically, the target angle θ is givenT,φTThe maximum likelihood estimate of the amplitude of the target signal is
Step S133 brings the maximum likelihood estimation into the log-likelihood function to obtain a generalized likelihood function.
Specifically, the generalized likelihood function can be obtained by substituting the maximum likelihood estimation into the likelihood function
Order to
This is a unitary projection matrix, satisfying UH(theta, phi) ═ U (theta, phi) and U2(θ,φ)＝U(θ,φ)。
Substituting generalized likelihood function expression (16) to obtain
Step S134, a generalized maximum likelihood estimation of the echo signal parameters is obtained according to the generalized likelihood function, and an angle measurement cost function related to the echo signal parameters is defined according to the generalized maximum likelihood estimation.
Specifically, the target angle θ can be obtained from expression (18)T,φTIs estimated as
Defining an objective function
L(θ,φ)＝yHU(θ,φ)y#(20)
The angle estimation problem can be expressed as an optimization problem
The solution of (1).
For example, based on the one-dimensional linear arrays in steps S110 and S120, the angle-measuring cost function can be obtained according to step S130
L(θ,φ)＝yHU(θ,φ)y#(21)
Wherein
S140, the echo signal parameters are sequentially brought into the angle measurement cost function, a target echo signal parameter which enables the angle measurement cost function to be minimum is selected, and the angle corresponding to the target echo signal parameter is the measured target angle.
Specifically, the value of theta and phi is traversed, and the value with the smallest angle measurement cost function is used as the measured target angle.
For example, based on the one-dimensional linear arrays in the above steps S110 to S130, considering that the one-dimensional linear arrays are, let θ be 0 °, and the value of Φ traverse the range
φ＝25°：0.01°：35°
The relationship between the angle measurement cost function and the angle phi is shown in fig. 3, and the angle phi that minimizes the angle measurement cost function, i.e., phi is 30 °, is taken as the target estimated angle.
The target estimated angle deviation and the root mean square error under different signal-to-noise ratios are shown in fig. 4, the estimated deviation and the root mean square error are reduced along with the increase of the signal-to-noise ratio, and the correctness of the method can be verified.
In the embodiment, the problem of angle measurement of the array radar is considered from the angle of parameter estimation, anti-interference processing is performed on the echo signal by using a principal component inversion method, an angle measurement cost function is obtained by using a maximum likelihood estimation algorithm, and the angle at which the angle measurement cost function is the minimum is used as a target angle estimation, so that the radar system can fully utilize the advantage of digital signal processing to realize measurement of a target angle in a complex scene.
It will be apparent to those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented in program code executable by a computing device, such that they may be stored on a computer storage medium (ROM/RAM, magnetic disks, optical disks) and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a more detailed description of the present invention that is presented in conjunction with specific embodiments, and the practice of the invention is not to be considered limited to those descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (4)
1. An array radar angle measurement method based on maximum likelihood estimation is characterized by comprising
Acquiring array element information of an array radar, and calculating a guide vector of the array radar according to the array element information;
constructing an initial echo signal model according to the guide vector, and performing anti-interference processing on the initial echo signal model according to a principal component inversion method to obtain a target echo signal model;
constructing an angle measurement cost function related to echo signal parameters based on a target echo signal model according to a maximum likelihood estimation algorithm, wherein the echo signal parameters comprise azimuth and pitching;
and sequentially bringing the echo signal parameters into the angle measurement cost function, and selecting a target echo signal parameter which enables the angle measurement cost function to be minimum, wherein the angle corresponding to the target echo signal parameter is the measured target angle.
2. The method according to claim 1, wherein the calculating of the steering vector of the array radar according to the array element information includes:
and calculating the response phase of the echo signal according to the phase center position coordinates of the array elements, and calculating to obtain the steering vector according to the response phase.
3. The method of claim 1, wherein said interference rejection processing said initial echo signal model according to principal component inversion to obtain a target echo signal model comprises:
acquiring interference signal information, acquiring an interference matrix according to the interference signal information, and acquiring an anti-interference projection matrix according to a principal component inversion method based on the interference matrix;
and substituting the anti-interference projection matrix into an initial echo signal model to process an interference signal to obtain the target echo signal model.
4. The method of claim 1, wherein constructing an angle-measuring cost function for echo signal parameters according to a maximum likelihood estimation algorithm based on a target echo signal model comprises:
carrying out logarithm taking processing on the target echo signal model to obtain a logarithm likelihood function related to echo signal parameters;
bringing echo signal parameters into the log-likelihood function to obtain the maximum likelihood estimation of the echo signal about the amplitude;
substituting the maximum likelihood estimation into the log-likelihood function to obtain a generalized likelihood function;
and obtaining a generalized maximum likelihood estimation of the echo signal parameters according to the generalized likelihood function, and defining an angle measurement cost function related to the echo signal parameters according to the generalized maximum likelihood estimation.
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