CN117310600A - Signal azimuth estimation method and equipment based on high-order cumulant and auxiliary array elements - Google Patents

Signal azimuth estimation method and equipment based on high-order cumulant and auxiliary array elements Download PDF

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Publication number
CN117310600A
CN117310600A CN202311215184.9A CN202311215184A CN117310600A CN 117310600 A CN117310600 A CN 117310600A CN 202311215184 A CN202311215184 A CN 202311215184A CN 117310600 A CN117310600 A CN 117310600A
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array
signal
matrix
order
azimuth
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周彬
刘枫
李涛
王明扬
罗李焱
梁敏
曹毅
徐海源
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CETC 29 Research Institute
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CETC 29 Research Institute
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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
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/14—Systems for determining direction or deviation from predetermined direction
    • G01S3/143—Systems for determining direction or deviation from predetermined direction by vectorial combination of signals derived from differently oriented antennae
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

The invention provides a signal azimuth estimation method and equipment based on a high-order cumulant and an auxiliary array element, comprising the following steps of S1: receiving N far-field signals by using M sensor arrays in space to obtain an array manifold formed by the sensor arrays for the N signals; s2: performing Fourier transform on the received array signals to obtain a signal model; s3: expanding the array based on the signal model to obtain a fourth-order cumulative amount of the received signals in the model; s4: acquiring a direction vector of the expanded signal, generating a construction matrix of fourth-order accumulation quantity based on the Cronecker product, and transforming the matrix; s5: and carrying out eigenvalue decomposition on the fourth-order cumulant to obtain a noise subspace, adjusting the row sequence of the noise subspace according to the element sequence of the array vector to obtain an adjusted noise subspace, and estimating the azimuth of the information source according to the subspace orthogonal principle. The problem of correcting the array error depending on the position is solved.

Description

Signal azimuth estimation method and equipment based on high-order cumulant and auxiliary array elements
Technical Field
The invention relates to the technical field of electromagnetic wave monitoring, in particular to a signal azimuth estimation method and device based on a high-order cumulant and auxiliary array elements.
Background
In practical engineering applications, the array error forms mainly include: array element pattern errors, array channel amplitude and phase errors and array element position errors, and the existence of the errors greatly influences the accuracy of information source azimuth estimation. Therefore, eliminating the influence of array errors by adopting an effective method is a key for improving the azimuth estimation precision.
Most of the existing array correction methods adopt an array amplitude-phase error model which is irrelevant to the direction, and the model is not in accordance with the actual array error characteristic. In practical engineering applications, almost all azimuth dependent array errors are encountered. Therefore, when the patterns of the array elements are inconsistent or isotropy is not satisfied between the array elements, or multiple error forms exist simultaneously, the array element amplitude-phase error with one direction dependence needs to be used for expression. How to correct for orientation dependent array errors has been a challenge faced in the underlying array correction technique.
Disclosure of Invention
In order to solve the problems, the invention provides a signal azimuth estimation method based on a high-order accumulation amount and auxiliary array elements, which comprises the following specific technical scheme:
s1: receiving N far-field signals by using M sensor arrays in space to obtain an array manifold formed by the sensor arrays for the N signals;
the array elements of the M sensor arrays are formed by M P A corrected auxiliary array element and M with azimuth dependent amplitude-phase error K Each array element is formed;
the array manifold is represented as follows:
A(θ)＝[a 1 (θ),a 2 (θ),…,a M (θ)]
where a () represents the array system response vector and θ represents the signal azimuth.
S2: performing Fourier transform on the received array signals to obtain a signal model;
s3: based on the signal model, the array is expanded, and the fourth-order accumulated quantity of the received signals in the model is obtained, wherein the fourth-order accumulated quantity is expressed as follows:
wherein Γ is a diagonal matrix, representing gain and phase of a receiving channel, matrix B represents Kronecker product of response vectors of an array system, and matrix C S The Kronecker product representing the transmitted data vector.
S4: acquiring a direction vector of the expanded signal, generating a construction matrix of fourth-order accumulation amount based on Kronecker product, and transforming the matrix;
s5: performing eigenvalue decomposition on the fourth-order cumulant to obtain a noise subspace U N And according to array vector a f Element order adjustment of (θ) noise subspace U N To obtain the adjusted noise subspace U' N According to the subspace orthogonality principle, the source azimuth is estimated based on the following:
wherein lambda is min []Representing the matrix noise subspace.
Further, when the array signal is received, the amplitude phase of each receiving channel is inconsistent, and the amplitude phase characteristic is unchanged in the signal frequency range.
Further, the signal model is expressed as follows:
X(j)＝ΓAS(j)+N(j)
wherein,α m sum phi m The gain and phase values of the mth receive channel are shown, respectively.
Further, the expanding of the array is performed;
for an equidistant array, the number of array elements after expansion is 2.M-1;
for non-equidistant array expansion, the number of the expansion arrays can be obtained to be M 2 -M+1。
Further, C S The non-zero elements are positioned at the (M-1) th N+m position on the diagonal, wherein M is more than or equal to 1 and less than or equal to M;
C S the expression is as follows:
wherein the matrix S is represented as a data vector of spatially transmitted signals.
Further, in step S4, the matrix transformation process is as follows:
obtaining the direction vector of the i signal after expansion:
according to Kronecker product (Kronecker product), the direction vector relation after primary conversion is obtained by conversion:
according to the direction vector relation of the primary transformation, carrying out secondary transformation based on Kronecker product (Cronecker product) to obtain the direction vector relation after the secondary transformation:
relative amount of expanded websSetting the corresponding value of the corrected array element as 1, and then carrying out equivalent transformation on the direction vector relation after secondary transformation to obtain a final transformation result:
where Γ (θ) represents the amplitude-phase disturbance matrix.
The invention provides a signal azimuth estimation device based on a high-order cumulant and auxiliary array elements, which comprises: the signal azimuth estimating device comprises a memory, a processor and a signal azimuth estimating program which is stored in the memory and can run on the processor and is based on the high-order accumulated quantity and the auxiliary array element, wherein the signal azimuth estimating program based on the high-order accumulated quantity and the auxiliary array element is executed by the processor to realize the steps of the signal azimuth estimating method based on the high-order accumulated quantity and the auxiliary array element.
The beneficial effects of the invention are as follows:
the invention obtains a corresponding mathematical model according to the amplitude-phase error characteristic, transforms a signal model by adopting an ISM-like method, generates a construction matrix of fourth-order accumulation according to the Kronecker product, carries out corresponding matrix transformation, and then adjusts the sequence of noise subspace row vectors according to the element sequence of the array vector to obtain the spatial spectrum of the signal. The method is suitable for any array geometric structure, has small operand, only needs one-dimensional search, does not have the problem of local convergence in parameter joint estimation, and solves the problem of high-resolution signal azimuth estimation of non-Gaussian signals under the condition of considering that azimuth dependent array errors exist.
Drawings
FIG. 1 is a schematic overall process flow diagram of the process.
Detailed Description
In the following description, the technical solutions of the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only some embodiments of the present invention, but 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, are intended to be within the scope of the invention.
In the description of the embodiments of the present invention, it should be noted that, the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship conventionally put in use of the product of the present invention as understood by those skilled in the art, merely for convenience of describing the present invention and simplifying the description, and is not indicative or implying that the apparatus or element to be referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used merely for distinguishing between descriptions and not for understanding as indicating or implying a relative importance.
In the description of the embodiments of the present invention, it should also be noted that, unless explicitly specified and limited otherwise, the terms "disposed," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; may be directly connected or indirectly connected through an intermediate medium. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Example 1
The embodiment 1 of the invention discloses a signal azimuth estimation method based on a high-order accumulation amount and auxiliary array elements, as shown in fig. 1, and specifically comprises the following steps:
s1: receiving N far-field signals by using M sensor arrays in space to obtain an array manifold formed by the sensor arrays for the N signals;
wherein M are transmittedThe array element of the sensor array is composed of M P A corrected auxiliary array element and M with azimuth dependent amplitude-phase error K Each array element is formed;
the N far-field signal directions are misaligned, and an array manifold formed by the sensor array for the N signals is represented as follows:
A(θ)＝[a 1 (θ),a 2 (θ),…,a M (θ)]
where a () represents the array system response vector and θ represents the signal azimuth.
S2: performing Fourier transform on the received array signals to obtain a signal model;
when the array signals are received, amplitude-phase inconsistency exists in each receiving channel, and the amplitude-phase characteristics are unchanged in the frequency range of the signals;
after fourier transformation of the received array signal, the signal model is expressed as follows:
X(j)＝ΓAS(j)+N(j)
wherein,α m sum phi m Respectively represent the gain and phase values of the mth receiving channel, and the frequencies of N narrowband signals are omega 0 Nearby.
S3: and expanding the array based on the signal model to obtain the fourth-order cumulant of the received signals in the model.
For an ideal array, the fourth order cumulative amount of the array received signal can be expressed as:
wherein, m is more than or equal to 1 1 ,m 2 ,m 3 ,m 4 M.ltoreq.M, thus, with M 1 ,m 2 ,m 3 ,m 4 M is shared when the variation range is changed 4 The value results in M 2 ×M 2 Matrix C of (2) X Matrix C X Written in the form of Kronecker product (Kronecker product), i.e.
Under the premise of assuming non-Gaussian property and Gaussian noise of far-field signals, the result of the fourth-order cumulant is:
C X ＝BC s B H
wherein,C S kronecker product representing S, data matrix of S space transmission signal, C S In (c) and they are located at the (M-1) ·n+m, 1+.m.ltoreq.m position on the diagonal, thus, there is b= [ B (θ) 1 ),b(θ 2 ),…,b(θ N )]；
Wherein,according to->Form expansion: the number of the extended arrays is 2.M-1 for equidistant array extension and M for unequal spacing array extension 2 -M+1。
As can be seen from the above, in the present embodiment, when the array amplitude-phase error exists, the parameter j can be omitted when the cumulative amount of the received signal in the model is calculated by using the Kronecker product property, that is, under the condition that the amplitude-phase inconsistency exists, the fourth-order moment of the received signal is:
the cumulative amount of received signals in the model is:
wherein Γ is a diagonal matrix, representing the gain and phase of the receive channel, matrix B represents the Kronecker product of the response vector of the array system, and matrix Cs is the Kronecker product of the transmit data vector. B is M 2 XN matrix, i.e.Is M 2 X 1 vector.
S4: and obtaining the direction vector of the expanded signal, generating a construction matrix of fourth-order accumulation quantity based on the Kronecker product, and transforming the matrix.
In the embodiment, the fuzzy-free joint estimation is carried out on the information source azimuth and the corresponding array element amplitude-phase error under the multi-source condition by introducing a small amount of auxiliary array element methods for accurate correction;
that is, in this embodiment, M array elements are formed by M P Auxiliary array element with accurate correction and M with azimuth dependent amplitude-phase error K And each array element is formed.
When the array is in the form of extensionWhen the number of the array elements after expansion is M 2 -m+1; the cumulative amount of the received signal is: />
Wherein,is M 2 ×M 2 The diagonal matrix, for the direction vector of the i (1.ltoreq.i.ltoreq.N) th signal after expansion, is:
according to the property of Kronecker product (Cronecker product), the transformation is carried out to obtain a direction vector relation after primary transformation:
according to the direction vector relation of the primary transformation, carrying out secondary transformation based on Kronecker product (Cronecker product) to obtain the direction vector relation after the secondary transformation:
where Q represents a diagonal matrix and f represents an amplitude-phase vector.
In M array elements, M P The individual array elements are accurately corrected in the amplitude-phase disturbance matrix Γ (θ i ) The corresponding values of (1) are 1, and thus the web-facing amount is expanded for the higher-order cumulative amountThe corresponding value of the corrected array element is set to 1, i.e. there is +.>1, based on the result, carrying out equivalent transformation on the direction vector relation after secondary transformation to obtain a final transformation result:
where Γ (θ) represents the amplitude-phase disturbance matrix.
S5: performing eigenvalue decomposition on the fourth-order cumulant to obtain a noise subspace U N And according to array vector a f Element order adjustment of (θ) noise subspace U N To obtain the adjusted noise subspace U' N According to the subspace orthogonal principle, the method comprises the following steps of:
further, the source azimuth is estimated based on:
wherein lambda is min []Representing the matrix noise subspace.
Example 2
Embodiment 2 of the present invention discloses a signal azimuth estimation device based on a higher-order accumulation amount and an auxiliary array element, which may be a Mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a Personal Digital Assistant (PDA), a tablet personal computer (PAD), or other User Equipment (UE), a handheld device, an in-vehicle device, a wearable device, a computing device, or other processing device connected to a wireless modem, a Mobile Station (MS), or the like, for performing the signal azimuth estimation method based on the higher-order accumulation amount and the auxiliary array element. The device may be referred to as a user terminal, portable terminal, desktop terminal, etc.
Generally, an apparatus comprises: at least one processor, a memory and a higher order cumulant and auxiliary element based signal position estimation program stored on the memory and operable on the processor, the higher order cumulant and auxiliary element based signal position estimation program configured to implement the steps of the higher order cumulant and auxiliary element based signal position estimation method as described in embodiment 1.
The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor may also include a main processor, which is a processor for processing data in an awake state, also called a CPU (Central ProcessingUnit ), and a coprocessor; a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor may incorporate a GPU (Graphics Processing Unit, image processor) for rendering and rendering of content required to be displayed by the display screen. The processor may further include an AI (Artificial Intelligence ) processor for processing computational operations with respect to a signal azimuth estimation procedure based on the high-order cumulants and the auxiliary array elements, such that the signal azimuth estimation method based on the high-order cumulants and the auxiliary array elements may autonomously train learning, improving efficiency and accuracy.
The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory is used to store at least one instruction for execution by a processor to implement the high order cumulant and auxiliary array element based signal position estimation method described in method embodiment 1 herein.
In some embodiments, the terminal may further optionally include: a communication interface and at least one peripheral device. The processor, the memory and the communication interface may be connected by a bus or signal lines. The respective peripheral devices may be connected to the communication interface via a bus, signal lines or a circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit, a display screen, and a power supply.
The communication interface may be used to connect at least one Input/Output (I/O) related peripheral device to the processor and the memory. The communication interface is used for receiving the movement tracks and other data of the plurality of mobile terminals uploaded by the user through the peripheral equipment. In some embodiments, the processor, memory, and communication interface are integrated on the same chip or circuit board; in some other embodiments, any one or both of the processor, memory, and communication interface may be implemented on a separate chip or circuit board, which is not limited in this embodiment.
The Radio Frequency circuit is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuit communicates with a communication network and other communication devices through electromagnetic signals, so that the movement tracks and other data of a plurality of mobile terminals can be acquired. The radio frequency circuit converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit comprises: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuitry may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (Wireless Fidelity ) networks. In some embodiments, the radio frequency circuitry may also include NFC (Near Field Communication, short range wireless communication) related circuitry, which is not limited in this application.
The display screen is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display is a touch display, the display also has the ability to collect touch signals at or above the surface of the display. The touch signal may be input to the processor for processing as a control signal. At this time, the display screen may also be used to provide virtual buttons and/or virtual keyboards, also referred to as soft buttons and/or soft keyboards. In some embodiments, the display screen may be one, the front panel of the electronic device; in other embodiments, the display screen may be at least two, and disposed on different surfaces of the electronic device or in a folded design; in some embodiments, the display may be a flexible display disposed on a curved surface or a folded surface of the electronic device. Even more, the display screen may be arranged in a non-rectangular irregular pattern, i.e. a shaped screen. The display screen may be made of LCD (LiquidCrystal Display ), OLED (Organic Light-Emitting Diode) or other materials.
The power supply is used to power the various components in the electronic device. The power source may be alternating current, direct current, disposable or rechargeable. When the power source comprises a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.
The invention is not limited to the specific embodiments described above. The invention extends to any novel one, or any novel combination, of the features disclosed in this specification, as well as to any novel one, or any novel combination, of the steps of the method or process disclosed.

Claims (7)

1. The signal azimuth estimation method based on the high-order accumulation amount and the auxiliary array elements is characterized by comprising the following steps of:
s1: receiving N far-field signals by using M sensor arrays in space to obtain an array manifold formed by the sensor arrays for the N signals;
the array elements of the M sensor arrays are formed by M P A corrected auxiliary array element and M with azimuth dependent amplitude-phase error K Each array element is formed;
the array manifold is represented as follows:
A(θ)＝[a 1 (θ),a 2 (θ),…,a M (θ)]
where a () represents the array system response vector and θ represents the signal azimuth.
S2: performing Fourier transform on the received array signals to obtain a signal model;
s3: based on the signal model, the array is expanded, and the fourth-order accumulated quantity of the received signals in the model is obtained, wherein the fourth-order accumulated quantity is expressed as follows:
wherein Γ is a diagonal matrix, representing gain and phase of a receiving channel, matrix B represents Kronecker product of response vectors of an array system, and matrix C S A Kronecker product representing the transmitted data vector;
s4: acquiring a direction vector of the expanded signal, generating a construction matrix of fourth-order accumulation amount based on Kronecker product, and transforming the matrix;
s5: performing eigenvalue decomposition on the fourth-order cumulant to obtain a noise subspace U N And according to array vector a f Element order adjustment of (θ) noise subspace U N To obtain the adjusted noise subspace U' N According to the subspace orthogonality principle, the source azimuth is estimated based on the following:
wherein lambda is min []Representing the matrix noise subspace.
2. The method of claim 1, wherein each of the receive channels has an amplitude phase that is non-uniform and the amplitude phase characteristics are constant over the frequency range of the signal when the array signal is received.
3. The method for estimating signal orientations based on higher order cumulants and auxiliary array elements of claim 1, wherein the signal model is expressed as follows:
X(j)＝ΓAS(j)+N(j)
wherein,α m sum phi m The gain and phase values of the mth receive channel are shown, respectively.
4. The method for estimating signal azimuth based on higher-order accumulation and auxiliary array elements according to claim 1, wherein the expanding of the array is performed;
for an equidistant array, the number of array elements after expansion is 2.M-1;
for non-equidistant array expansion, the number of the expansion arrays can be obtained to be M 2 -M+1。
5. The method for estimating signal azimuth based on higher-order accumulation and auxiliary array elements according to claim 1, wherein C S The non-zero elements are positioned at the (M-1) th N+m position on the diagonal, wherein M is more than or equal to 1 and less than or equal to M;
C S the expression is as follows:
wherein the matrix S is a data vector of the spatially transmitted signal.
6. The method for estimating signal azimuth based on higher-order accumulation and auxiliary array elements according to claim 1, wherein in step S4, the matrix transformation process is as follows:
obtaining the direction vector of the i signal after expansion:
according to the Kronecker product, the transformation is carried out to obtain a direction vector relation after primary transformation:
according to the direction vector relation of the primary transformation, carrying out secondary transformation based on the Kronecker product to obtain the direction vector relation after the secondary transformation:
relative amount of expanded websSetting the corresponding value of the corrected array element as 1, and then carrying out equivalent transformation on the direction vector relation after secondary transformation to obtain a final transformation result:
where Γ (θ) represents the amplitude-phase disturbance matrix.
7. A signal orientation estimation device based on a higher order accumulation amount and an auxiliary array element, characterized in that the signal orientation estimation device based on a higher order accumulation amount and an auxiliary array element comprises: the device comprises a memory, a processor and a signal azimuth estimation program stored in the memory, wherein the signal azimuth estimation program based on the high-order accumulation amount and the auxiliary array element can be run on the processor, and the signal azimuth estimation program based on the high-order accumulation amount and the auxiliary array element realizes the steps of the signal azimuth estimation method based on the high-order accumulation amount and the auxiliary array element according to any one of claims 1-6 when the signal azimuth estimation program based on the high-order accumulation amount and the auxiliary array element is executed by the processor.
CN202311215184.9A 2023-09-20 2023-09-20 Signal azimuth estimation method and equipment based on high-order cumulant and auxiliary array elements Pending CN117310600A (en)

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