CN112034416B - Method for automatically detecting direction-finding unmanned aerial vehicle - Google Patents

Method for automatically detecting direction-finding unmanned aerial vehicle Download PDF

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CN112034416B
CN112034416B CN202010786192.9A CN202010786192A CN112034416B CN 112034416 B CN112034416 B CN 112034416B CN 202010786192 A CN202010786192 A CN 202010786192A CN 112034416 B CN112034416 B CN 112034416B
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detection
signal
antenna
signals
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CN112034416A (en
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史治国
陈剑锋
单国峰
郑航
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Zhejiang Eusoft Low Altitude Defense Technology Co ltd
Zhejiang University ZJU
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Zhejiang Eusoft Low Altitude Defense Technology Co ltd
Zhejiang University ZJU
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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
    • G01S3/16—Systems for determining direction or deviation from predetermined direction using amplitude comparison of signals derived sequentially from receiving antennas or antenna systems having differently-oriented directivity characteristics or from an antenna system having periodically-varied orientation of directivity characteristic
    • 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
    • G01S3/04—Details
    • G01S3/043—Receivers
    • 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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  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
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  • Variable-Direction Aerials And Aerial Arrays (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses an unmanned aerial vehicle method for automatically detecting direction finding, which comprises the steps of firstly arranging 6 detection antennas to poll and detect aerial radio frequency signals and receiving the signals; when the center frequency of the receiving signal of the detecting antenna accords with the range of 0.4-6 GHz, the square array is used for accurately detecting the direction, and a signal incoming wave area and a selection strategy of a single-sided direction-finding linear array in the square array are determined according to the level of the receiving signal of the detecting antenna; then carrying out tensor modeling and tensor spatial spectrum construction on the received signals of the single-sided direction-finding linear array to realize accurate direction finding; and finally, judging the level of the received signals of two adjacent detection antennas in the direction-finding sector again, so as to obtain the direction-of-arrival estimation of the target signal, namely the positioning result of the unmanned aerial vehicle. According to the invention, tensor modeling is adopted in direction finding, and a mode of joint judgment of the detecting antenna and the direction finding antenna is adopted, so that the influence of multipath signals is overcome, target signal screening is realized, and an accurate unmanned aerial vehicle positioning result is obtained.

Description

Method for automatically detecting direction-finding unmanned aerial vehicle
Technical Field
The invention belongs to the field of unmanned aerial vehicle detection and positioning, and relates to a method for automatically detecting an unmanned aerial vehicle.
Background
In recent years, the types and the number of unmanned aerial vehicles on the market are increasing, the unmanned aerial vehicles are applied to various fields more and more widely, meanwhile, as people can easily contact and use the unmanned aerial vehicles, the events of 'black flight' and 'flying over the air' of the unmanned aerial vehicles are endless, serious influences are brought to public safety and personal privacy, and difficult to predict results are easily caused in specific fields such as security protection, aviation and the like, so that the defense and the reverse of the unmanned aerial vehicles are focused on research in various national academies and industry.
The current detection and positioning methods for unmanned aerial vehicles mainly comprise radar, audio frequency, video frequency and radio frequency. Because illegal flight of the unmanned aerial vehicle often occurs in places with complex terrains, such as building groups, prisons and the like, various echoes can seriously influence the radar to process the echoes of the unmanned aerial vehicle; the unmanned aerial vehicle is detected by using a voiceprint recognition method, and is easily influenced by environmental background sounds such as cicada, an electric fan and the like, so that the unmanned aerial vehicle is easy to take effect only in very special scenes; the scheme based on optical image detection is also easily affected by the shielding of leaves, buildings and the like. According to the method based on the unmanned aerial vehicle radio frequency signals, the radio frequency signals or image transmission signals between the unmanned aerial vehicle and the remote controller are searched, and information in the signals can be effectively extracted through a series of distinguishing and processing, so that the existence of the unmanned aerial vehicle is judged, the direction of arrival estimation of the unmanned aerial vehicle radio frequency signals can be obtained through parameter extraction, and the azimuth of the unmanned aerial vehicle is determined.
However, the existing direction-finding detection method based on unmanned aerial vehicle radio frequency signal processing is relatively independent in detection and direction finding, lacks a certain linkage mechanism, and therefore has limited flexibility, on the other hand, due to multipath effects, the direction-finding detection device often receives not only signals directly from a target source but also a plurality of other multipath signals with weaker strength, the conventional method generally ignores the discrimination processing of the multipath signals, and finally, due to the hardware limitation of the device, the conventional method can only identify and process radio frequency signals in a narrower frequency range, and therefore, the conventional unmanned aerial vehicle direction-finding detection method still lacks reliability in practical application.
Disclosure of Invention
The invention aims to provide a method for automatically detecting a direction-finding unmanned aerial vehicle, which aims at overcoming the defects of insufficient linkage, neglecting influence of multipath signals and narrower processable frequency band of the existing unmanned aerial vehicle detection direction-finding method, forms a detection and direction-finding linkage mechanism, can effectively overcome the influence of multipath signals and has the radio frequency signal processing capability of a wide frequency band of 0.4-6 GHz.
The aim of the invention is realized by the following technical scheme: a method of automatically detecting a direction-finding drone, the method comprising:
step 1: arranging 6 detection antennas, wherein each detection antenna covers a detection sector range of 60 degrees, each detection antenna polls and detects an aerial radio frequency signal, and when the signal is detected, the signal is received and the center frequency of the signal is obtained;
step 2: if the center frequency of the signal received by the detection antenna falls within the range of 0.4-6 GHz, the direction-finding antenna is used for direction finding, and the direction-finding antenna is a square array which consists of four single-sided direction-finding linear arrays, wherein each single-sided direction-finding linear array comprises 4 antenna arrays and is used in the direction-finding process. Before the detection, comparing the level of the signals received by 6 detection antennas, wherein the detection sector corresponding to the detection antenna with the largest level is taken as a target signal incoming wave area, and selecting one of the square arrays to be a direction-finding linear array according to the corresponding position of the incoming wave area so as to accurately measure the direction of the target signal incoming wave area;
step 3: tensor modeling is carried out on the received signals of the direction finding antenna, original structural information of the signals is reserved, tensor space spectrum based on multiple signal classification is constructed based on autocorrelation tensor statistic processing of the received signals, and accordingly direction of arrival estimation is achieved through spectrum peak searching of the tensor space spectrum.
Step 4: if the direction of arrival estimation yields multiple angle results, it may contain multipath signals in addition to the direction of arrival of the target signal, which may have less intensity than the target signal due to the attenuation effect of the path. Therefore, in order to extract the target signal, two adjacent detection antennas in the direction-finding sector of the direction-finding linear array are opened, the level of the received signal is judged again, and the relative positions of the target signals in the signals are screened out according to the relative direction of the detection antenna with the largest signal level, so that the arrival direction estimation of the target signal is obtained, namely the positioning result of the unmanned aerial vehicle.
Further, in the step 1, the control switches of the 6 detection antennas are turned on according to a preset fixed period, so that the wireless radio frequency signals in the air are detected through the polling of the 6 antennas, each antenna covers a 60-degree detection sector, the whole detection range of all the detection antennas covers a 360-degree space, and when the unmanned aerial vehicle radio frequency signals exist in the space, the detection antennas receive the signals and acquire the center frequency of the signals.
Further, in the step 2, according to the level comparison of the signals received by the 6 detecting antennas, a 60 ° sector corresponding to the detecting antenna with the largest signal level is selected as the incoming wave area of the target signal, at this time, the coverage detection sector range of the single-sided direction-finding linear array is 90 °, and according to the selected incoming wave area of the target signal, the single-sided direction-finding linear array at the corresponding position is selected. However, if the selected incoming wave area falls within the range of the direction-finding sectors of the two single-sided direction-finding linear arrays at the same time, the magnitudes of the received signal levels of the two adjacent left and right detection antennas of the detection antenna are compared, and the single-sided direction-finding linear array at the corresponding position of the one detection antenna with the largest received signal level in the two detection antennas is the finally selected direction-finding array. Specifically, when the receiving signal level of the left detection antenna is maximum, the left single-sided direction-finding linear array is selected, and when the receiving signal level of the right detection antenna is maximum, the right single-sided direction-finding linear array is selected, so that one array is determined from the two single-sided direction-finding linear arrays to carry out direction finding.
Further, in the step 3, for the antenna array of M array elements and K radio frequency signals, the direction of arrival is represented as θ= [ θ ] 1 ,θ 2 ,...,θ K ]Modeling a received signal of L sample snapshots as
Figure BDA0002622053440000021
X＝A(θ)S+N,
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002622053440000022
Figure BDA0002622053440000023
the representation of the complex number field is provided,
Figure BDA0002622053440000024
to pair(s)K=1, 2 k Is the sign of the imaginary number, (·) T Representing a transpose operation, u m Represents the position of the mth antenna in the antenna array, m=1, 2,.. 1 =0 as reference position, λ is signal wavelength, u m ＝md，/>
Figure BDA0002622053440000031
For signal waveform, ++>
Figure BDA0002622053440000032
For the waveform vector corresponding to the kth signal, < +.>
Figure BDA0002622053440000033
Is white gaussian noise. Taking the front M-1 and the rear M-1 rows of X to obtain X 1 ,/>
Figure BDA0002622053440000034
X is to be 1 And X 2 Superposition in the third dimension, thus obtaining a three-dimensional tensor signal +.>
Figure BDA0002622053440000035
Figure BDA0002622053440000036
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002622053440000037
the omicron represents the outer product operation; use->
Figure BDA0002622053440000039
Representation->
Figure BDA00026220534400000310
Along the first slice of the third dimension, if no noise-influencing situation is assumed, +.>
Figure BDA00026220534400000311
The ideal modeling of the autocorrelation tensor of (c) is:
Figure BDA00026220534400000312
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA00026220534400000313
representing the power of the kth signal, E [. Cndot.]Express mathematical expectations (.) * Representing a conjugate fetching operation. In practical use, the->
Figure BDA00026220534400000314
From the sampled autocorrelation tensor->
Figure BDA00026220534400000315
Replacement:
Figure BDA00026220534400000316
for a pair of
Figure BDA00026220534400000317
Tensor decomposition is carried out to obtain->
Figure BDA00026220534400000318
B＝[b 1 ,b 2 ,...b K ],
Figure BDA00026220534400000319
Figure BDA00026220534400000320
Constructing a signal subspace U s ：
Figure BDA00026220534400000321
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA00026220534400000322
for U as Kronecker product s Normalizing and orthogonalizing to obtain +.>
Figure BDA00026220534400000323
Figure BDA00026220534400000324
Where orth (·) represents the orthogonalization operation and II·| represents the Frobenius norm. Defining noise subspace U n Then the following relationship is provided:
Figure BDA00026220534400000325
wherein ( H Representing the conjugate transpose operation, I represents the identity matrix. Setting a search angle
Figure BDA00026220534400000326
Constructing a guide matrix:
Figure BDA00026220534400000327
Figure BDA00026220534400000328
thereby constructing a tensor spatial spectrum function:
Figure BDA00026220534400000329
at the position of
Figure BDA00026220534400000330
In the range of the values of 0.1 DEG, gradually increases +.>
Figure BDA00026220534400000331
Values, each->
Figure BDA00026220534400000332
The value corresponds to a tensor spatial spectrum value, so that a search angle corresponding to +.>
Figure BDA00026220534400000333
By searching for the highest point of the spatial spectrum, i.e. the spectral peak of the spatial spectrum, according to the corresponding +.>
Figure BDA00026220534400000334
The value, get the direction of arrival estimation of the signal source +.>
Figure BDA00026220534400000335
Further, for the two-dimensional direction of arrival, corresponding estimation results can be obtained by means of tensor modeling and tensor spatial spectrum construction in the step 3.
Further, in the step 4, the direction of arrival of the target unmanned aerial vehicle signal is estimated as
Figure BDA0002622053440000041
The rest result is the direction of arrival estimate of the multipath signal>
Figure BDA0002622053440000042
p＝1,2,...,K,p≠e，/>
Figure BDA0002622053440000043
And->
Figure BDA0002622053440000044
With relative orientation therebetween, i.e.)>
Figure BDA0002622053440000045
At->
Figure BDA0002622053440000046
Due to one side of left or right side of (C)The range of the coverage direction-finding sector of the direction-finding linear array is 90 degrees, and the interval of the detection antennas is 60 degrees, so that two adjacent detection antennas are arranged in the direction-finding sector. Selecting two adjacent detection antennas in the range of the direction-finding sector, setting one detection antenna on the left side and one detection antenna on the right side, wherein the size of the whole detection sector of the two detection antennas is 120 DEG, and the two detection antennas can comprise the 90 DEG direction-finding sector of the single-sided direction-finding linear array, so as to compare the received signal level of the two detection antennas, and estimating the direction of arrival of a target signal source if the received signal level of the detection antenna on the left side is larger>
Figure BDA0002622053440000047
Selecting left side result, and similarly, if the level of the received signal of the right side detection antenna is larger, estimating the direction of arrival of the target signal source>
Figure BDA0002622053440000048
Selecting right side result, thereby screening +.>
Figure BDA0002622053440000049
The invention has the beneficial effects that: the invention effectively realizes the linkage detection and positioning of the 0.4-6 GHz frequency band unmanned aerial vehicle signal, overcomes the relative independent mechanism of the traditional unmanned aerial vehicle detection and direction finding method, and designs a method for automatically detecting the direction finding unmanned aerial vehicle with a wide frequency band; on the other hand, the original structural information of the signal is effectively reserved by adopting a tensor modeling mode during direction finding, and the parameter feature extraction of a tensor space is realized, so that the accuracy and the high efficiency of direction finding are ensured; and finally, a mode of joint judgment of the detection antenna and the direction finding antenna is adopted, the influence of multipath signals is overcome, target signal screening is realized, and finally, an accurate unmanned aerial vehicle positioning result is obtained.
Drawings
FIG. 1 is an antenna assembly of an automatic detection direction-finding drone;
fig. 2 is a tensor spatial spectrum of a single-sided direction-finding linear array performing a direction-of-arrival estimation process on a received signal.
Detailed Description
The following describes the embodiments of the present invention in further detail with reference to the drawings.
The invention provides a method for automatically detecting a direction-finding unmanned aerial vehicle, which comprises the following steps:
step 1: on the device shown in fig. 1, a control switch of 6 detection antennas is turned on according to a preset period, the radio frequency signals in the air are detected through polling of the 6 detection antennas, each detection antenna covers a detection sector range of 60 degrees, all detection antennas can integrally cover a space of 360 degrees, and when the radio frequency signals of the unmanned aerial vehicle exist in the air, the signals are received and the center frequency of the signals is obtained;
step 2: if the center frequency of the receiving signal of the detecting antenna falls within the range of 0.4-6 GHz, the direction of arrival estimation of the target signal is performed by the direction finding antenna, which comprises a square array containing 16 antenna elements and a circular array containing 5 antenna elements, as shown in fig. 1. The square array consists of four single-sided direction-finding linear arrays, each linear array comprises 4 antenna arrays, and one linear array is used in each direction-finding process; the circular array selects three adjacent antenna elements of the 5 antenna elements each time it is used. In practice, when direction finding is performed on a signal in the 0.4-6 GHz frequency band, a single-sided direction finding linear array of a square array is generally used, however, when the signal is in the 0.4-2.5 GH low frequency band, errors may exist in using the linear array, and at this time, three adjacent antenna elements of a circular array may be used to participate in direction finding, and the direction finding result is used to correct the direction finding result of the square array. Before starting the measurement, according to the level comparison of signals received by 6 detection antennas, selecting a 60-degree sector corresponding to one detection antenna with the largest signal level as an incoming wave area of a target signal, wherein the coverage detection sector range of the single-sided direction-finding linear array is 90 degrees, and selecting the single-sided direction-finding linear array at a corresponding position according to the selected incoming wave area of the target signal. However, if the selected incoming wave area falls within the range of the direction-finding sectors of the two single-sided direction-finding linear arrays at the same time, the magnitudes of the received signal levels of the two adjacent left and right detection antennas of the detection antenna are compared, and the single-sided direction-finding linear array at the corresponding position of the one detection antenna with the largest received signal level in the two detection antennas is the finally selected direction-finding array. Specifically, when the receiving signal level of the left detection antenna is maximum, a left single-sided direction-finding linear array is selected, and when the receiving signal level of the right detection antenna is maximum, a right single-sided direction-finding linear array is selected, so that one array is determined to accurately measure the incoming wave area of the target signal from the two single-sided direction-finding linear arrays.
Step 3: tensor modeling is carried out on the received signals of the direction finding antenna, original structural information of the signals is reserved, tensor space spectrum based on multiple signal classification is constructed based on autocorrelation tensor statistic processing of the received signals, and accordingly direction of arrival estimation is achieved through spectrum peak searching of the tensor space spectrum. The direction of arrival estimation process of the single-sided direction-finding linear array on the received signal is specifically described as follows:
first, for an antenna array of M array elements and K radio frequency signals (for one-dimensional direction of arrival estimation, the direction of arrival is denoted as θ= [ θ ] 1 ,θ 2 ,…,θ K ]) Modeling a received signal of L sample snapshots as
Figure BDA0002622053440000051
X＝A(θ)S+N,
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002622053440000052
for k=1, 2, K signal source incidence angles θ k Guide vector of u m (m=1, 2,., M represents the position of the mth antenna in the antenna array, u 1 =0 as reference position, λ is signal wavelength, u m ＝md，
Figure BDA0002622053440000053
Is a signal source waveform>
Figure BDA0002622053440000054
For waveforms corresponding to the kth signalThe vector of the vector,
Figure BDA0002622053440000055
is white gaussian noise. Taking the front M-1 and the rear M-1 rows of X to obtain X 1 ,/>
Figure BDA0002622053440000056
X is to be 1 And X 2 Superposition in the third dimension, thus obtaining a three-dimensional tensor signal +.>
Figure BDA0002622053440000057
Figure BDA0002622053440000058
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002622053440000059
Figure BDA00026220534400000510
representing an outer product operation; use->
Figure BDA00026220534400000511
Representation->
Figure BDA00026220534400000512
The first slice along the third dimension, then +.>
Figure BDA00026220534400000513
The ideal modeling of the autocorrelation tensor of (assuming no noise effects) is:
Figure BDA0002622053440000061
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002622053440000062
representing the power of the kth signal, E [. Cndot.]Representation ofMathematical expectation (·) * Representing a conjugate fetching operation. In practical use, the->
Figure BDA0002622053440000063
From the sampled autocorrelation tensor->
Figure BDA0002622053440000064
Replacement:
Figure BDA0002622053440000065
for a pair of
Figure BDA0002622053440000066
Tensor decomposition is carried out to obtain->
Figure BDA0002622053440000067
B＝[b 1 ,b 2 ,...b K ],
Figure BDA0002622053440000068
Figure BDA0002622053440000069
Constructing a signal subspace U s ：
Figure BDA00026220534400000610
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA00026220534400000611
for U as Kronecker product s Normalizing and orthogonalizing to obtain +.>
Figure BDA00026220534400000612
Figure BDA00026220534400000613
Where orth (·) represents the orthogonalization operation and II·| represents the Frobenius norm. Defining noise subspace U n Then the following relationship is provided:
Figure BDA00026220534400000614
wherein ( H Representing the conjugate transpose operation, I represents the identity matrix. Setting a search angle
Figure BDA00026220534400000615
Constructing a guide matrix:
Figure BDA00026220534400000616
Figure BDA00026220534400000617
thereby constructing a tensor spatial spectrum function:
Figure BDA00026220534400000618
at the position of
Figure BDA00026220534400000619
In the range of the value of 0.1 DEG, gradually increases +.>
Figure BDA00026220534400000620
Values, each->
Figure BDA00026220534400000621
The value corresponds to a tensor spatial spectrum value, so that a search angle corresponding to +.>
Figure BDA00026220534400000622
As shown in FIG. 2, by searching for +.A corresponding to the highest point (i.e., spectral peak)>
Figure BDA00026220534400000623
The value, get the direction of arrival estimation of the signal source +.>
Figure BDA00026220534400000624
Similarly, for the two-dimensional direction of arrival +.>
Figure BDA00026220534400000625
Corresponding estimation results can be obtained through tensor modeling and the construction thought of the tensor spatial spectrum.
Step 4: because of multipath effect, K (K > 2) signals are detected at this time, wherein the K (K > 2) signals comprise a target unmanned aerial vehicle signal and a plurality of multipath signals with relatively weak intensity, in order to screen out the target signal, two adjacent detection antennas in a direction-finding sector at this time are opened, the level of the received signal is judged again, the relative positions of the target signal in a plurality of signals are judged according to the direction corresponding to the detection antenna with the largest signal level, and therefore the direction-of-arrival estimation of the target signal is obtained, namely the positioning result of the unmanned aerial vehicle. The method comprises the following steps: direction of arrival of the target unmanned aerial vehicle signal is estimated as
Figure BDA00026220534400000626
The rest result is the direction of arrival estimate of the multipath signal>
Figure BDA00026220534400000627
(p＝1,2,...,K,p≠e)，/>
Figure BDA00026220534400000628
And->
Figure BDA00026220534400000629
Has a relative orientation therebetween (i.e.)>
Figure BDA00026220534400000630
At->
Figure BDA00026220534400000631
Since the coverage direction-finding sector of the single-sided direction-finding linear array is 90 ° and the interval between the detection antennas is 60 °, two adjacent detection antennas are provided in the direction-finding sector, two adjacent detection antennas (one of which is set on the left side and one on the right side) in the direction-finding sector are selected, the size of the whole coverage detection sector of the two adjacent detection antennas is 120 °, the 90 ° direction-finding sector of the single-sided direction-finding linear array can be included, and then the received signal level of the two detection antennas is compared, and if the received signal level of the detection antenna on the left side is greater, the direction of arrival of the target signal source is estimated>
Figure BDA0002622053440000071
Selecting left side result, and similarly, if the level of the received signal of the right side detection antenna is larger, estimating the direction of arrival of the target signal source>
Figure BDA0002622053440000072
Selecting right side result, thereby screening +.>
Figure BDA0002622053440000073
In step 3, when the direction of the target signal is detected, the conventional matrix-based processing method is to process a covariance matrix R of the received signal X, where the covariance matrix R is expressed as:
R＝E[XX H ].
then, eigenvalue decomposition is carried out on the covariance matrix R to obtain eigenvalue lambda m M=1, 2,..m, taking the first K largest eigenvalues lambda k The eigenvectors corresponding to k=1, 2..k (K < M) constitute the signal subspace
Figure BDA0002622053440000074
The eigenvectors corresponding to the remaining M-K eigenvalues form a noise subspace +.>
Figure BDA0002622053440000075
According to the search angle->
Figure BDA0002622053440000076
Variable structure guide vector of (a)
Figure BDA0002622053440000077
Thereby constructing a spatial spectrum based on matrix processing. And searching spectral peaks of the spatial spectrum to obtain the direction of arrival estimation. However, the method does not consider the multidimensional nature of the signals, and when the scale of the signal matrix is increased, the scale of the covariance matrix is correspondingly increased, and at the moment, the characteristic value decomposition of the covariance matrix has larger requirements on the software and hardware of the system, so that the realization is inconvenient. The method for extracting the multidimensional features through tensor signal modeling and tensor decomposition based on the direction finding means effectively solves the problems, is not only suitable for the situation of one-dimensional direction of arrival estimation, but also suitable for two-dimensional and above parameter estimation scenes, can exert the structural advantages of multidimensional signals, and ensures the high efficiency of tensor spatial spectrum construction. Finally, the automatic detection direction-finding unmanned aerial vehicle method provided by the invention effectively realizes linkage detection and positioning of the 0.4-6 GHz wide-band unmanned aerial vehicle signal, overcomes the relative independent mechanism of the traditional unmanned aerial vehicle detection and direction-finding method, adopts a tensor modeling mode in the direction-finding stage, and ensures the accuracy and high efficiency of direction finding; on the other hand, after the direction finding is finished, the influence of multipath signals is overcome by adopting a mode of jointly judging the detection antenna and the direction finding antenna, the target signal screening is realized, and finally, the accurate unmanned aerial vehicle positioning result is obtained.
The above-described embodiments are intended to illustrate the present invention, not to limit it, and any modifications and variations made thereto are within the spirit of the invention and the scope of the appended claims.

Claims (6)

1. A method of automatically detecting a direction-finding drone, the method comprising:
step 1: arranging 6 detection antennas, wherein each detection antenna covers a detection sector range of 60 degrees, each detection antenna polls and detects an aerial radio frequency signal, and when the signal is detected, the signal is received and the center frequency of the signal is obtained;
step 2: if the center frequency of the signal received by the detection antenna falls within the range of 0.4-6 GHz, the direction-finding antenna is used for direction finding, and the direction-finding antenna is a square array which consists of four single-sided direction-finding linear arrays, each single-sided direction-finding linear array comprises 4 antenna arrays, and one linear array is used in the direction-finding process; before the detection, comparing the level of the signals received by 6 detection antennas, wherein the detection sector corresponding to the detection antenna with the largest level is taken as a target signal incoming wave area, and selecting one of the square arrays to be a direction-finding linear array according to the corresponding position of the incoming wave area so as to accurately measure the direction of the target signal incoming wave area;
step 3: tensor modeling is carried out on the received signals of the direction finding antenna, original structural information of the signals is reserved, tensor space spectrum based on multiple signal classification is constructed based on autocorrelation tensor statistic processing of the received signals, and therefore direction of arrival estimation is achieved through spectrum peak searching of the tensor space spectrum;
step 4: if the direction of arrival estimation obtains a plurality of angle results, the direction of arrival estimation may include multipath signals besides the direction of arrival of the target signal, wherein the multipath signals are less than the target signal in strength due to attenuation effects of paths; therefore, in order to extract the target signal, two adjacent detection antennas in the direction-finding sector of the direction-finding linear array are opened, the level of the received signal is judged again, and the relative positions of the target signals in the signals are screened out according to the relative direction of the detection antenna with the largest signal level, so that the arrival direction estimation of the target signal is obtained, namely the positioning result of the unmanned aerial vehicle.
2. The method of claim 1, wherein in the step 1, the control switches of the 6 detection antennas are turned on according to a preset fixed period, so that the wireless radio frequency signals in the air are detected through the polling of the 6 antennas, each antenna covers a 60 ° detection sector, the whole detection range of all detection antennas covers a 360 ° space, and when the unmanned radio frequency signals exist in the space, the detection antennas receive the signals and acquire the center frequency thereof.
3. The method of automatically detecting a direction-finding unmanned aerial vehicle according to claim 1, wherein in the step 2, according to the level comparison of the signals received by 6 detection antennas, a 60 ° sector corresponding to one detection antenna with the largest signal level is selected as the incoming wave area of the target signal, at this time, the coverage detection sector range of the single-sided direction-finding linear array is 90 °, and according to the selected incoming wave area of the target signal, the single-sided direction-finding linear array at the corresponding position is selected; however, if the selected incoming wave area falls within the range of the direction-finding sectors of the two single-sided direction-finding linear arrays at the same time, comparing the received signal level of the left and right adjacent two detection antennas of the detection antenna, wherein the single-sided direction-finding linear array of the corresponding position of the one detection antenna with the largest received signal level in the two detection antennas is the finally selected direction-finding array; when the receiving signal level of the left detection antenna is maximum, the left single-sided direction-finding linear array is selected, and when the receiving signal level of the right detection antenna is maximum, the right single-sided direction-finding linear array is selected, so that one array is determined from the two single-sided direction-finding linear arrays to carry out direction finding.
4. The method of claim 1, wherein in the step 3, for the antenna array of M array elements and K radio frequency signals, the direction of arrival is represented as θ= [ θ ] 1 ,θ 2 ,…,θ K ]Modeling a received signal of L sample snapshots as
Figure FDA0004189674820000021
X＝A(θ)S+N,
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA0004189674820000022
Figure FDA0004189674820000023
the representation of the complex number field is provided,
Figure FDA0004189674820000024
for the K-th, k=1, 2, …, the incident angle θ of the K signal sources k Is the sign of the imaginary number, (·) T Representing a transpose operation, u m Represents the position of the mth antenna in the antenna array, m=1, 2, …, M, u 1 =0 as reference position, λ is signal wavelength, u m ＝md，/>
Figure FDA0004189674820000025
Figure FDA0004189674820000026
For signal waveform, ++>
Figure FDA0004189674820000027
For the waveform vector corresponding to the kth signal, < +.>
Figure FDA0004189674820000028
Is Gaussian white noise; taking the front M-1 and the back M-1 lines of X to obtain +.>
Figure FDA00041896748200000228
X is to be 1 And X 2 Superposition in a third dimension to obtain a three-dimensional tensor signal
Figure FDA00041896748200000211
Figure FDA00041896748200000212
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA00041896748200000213
the degree represents an outer product operation; use->
Figure FDA00041896748200000230
Representation->
Figure FDA00041896748200000214
Along the first slice of the third dimension, if no noise-influencing situation is assumed, +.>
Figure FDA00041896748200000231
The ideal modeling of the autocorrelation tensor of (c) is:
Figure FDA00041896748200000215
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA00041896748200000216
representing the power of the kth signal, E [. Cndot.]Express mathematical expectations (.) * Representing a conjugate fetching operation; in practical use, the->
Figure FDA00041896748200000229
From the sampled autocorrelation tensor->
Figure FDA00041896748200000217
Replacement:
Figure FDA00041896748200000218
for a pair of
Figure FDA00041896748200000219
Tensor decomposition is carried out to obtain
Figure FDA00041896748200000220
Figure FDA00041896748200000221
Constructing a signal subspace U s ：
Figure FDA00041896748200000222
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA00041896748200000223
for U as Kronecker product s Normalizing and orthogonalizing to obtain +.>
Figure FDA00041896748200000227
Figure FDA00041896748200000224
Where orth (·) represents the orthogonalization operation, the expression of Frobenius norms; defining noise subspace U n Then the following relationship is provided:
Figure FDA00041896748200000225
wherein ( H Representing conjugate transpose operations, I representing an identity matrix; setting a search angle
Figure FDA00041896748200000226
Constructing a guide matrix:
Figure FDA0004189674820000031
Figure FDA0004189674820000032
thereby constructing tensorsSpatial spectral function:
Figure FDA0004189674820000033
at the position of
Figure FDA0004189674820000034
In the range of the values of 0.1 DEG, gradually increases +.>
Figure FDA0004189674820000035
Values, each->
Figure FDA0004189674820000036
The value corresponds to a tensor spatial spectrum value, so that a search angle corresponding to +.>
Figure FDA0004189674820000037
By searching for the highest point of the spatial spectrum, i.e. the spectral peak of the spatial spectrum, according to the corresponding +.>
Figure FDA0004189674820000038
The value, get the direction of arrival estimation of the signal source +.>
Figure FDA0004189674820000039
5. The method for automatically detecting a direction-finding unmanned aerial vehicle according to claim 4, wherein the corresponding estimation results can be obtained by means of tensor modeling and tensor spatial spectrum construction in step 3 for the two-dimensional direction of arrival.
6. The method for automatically detecting a direction-finding unmanned aerial vehicle according to claim 1, wherein in the step 4, the direction of arrival of the target unmanned aerial vehicle signal is estimated as
Figure FDA00041896748200000318
The rest result is the direction of arrival estimate of the multipath signal>
Figure FDA00041896748200000310
p＝1,2,…,K,p≠e，/>
Figure FDA00041896748200000311
And->
Figure FDA00041896748200000312
With relative orientation therebetween, i.e.)>
Figure FDA00041896748200000313
At->
Figure FDA00041896748200000314
Because the coverage direction-finding sector range of the single-sided direction-finding linear array is 90 degrees, and the interval of the detection antennas is 60 degrees, two adjacent detection antennas are arranged in the direction-finding sector; selecting two adjacent detection antennas in the range of the direction-finding sector, setting one detection antenna on the left side and one detection antenna on the right side, wherein the size of the whole detection sector of the two detection antennas is 120 DEG, and the two detection antennas can comprise the 90 DEG direction-finding sector of the single-sided direction-finding linear array, so as to compare the received signal level of the two detection antennas, and estimating the direction of arrival of a target signal source if the received signal level of the detection antenna on the left side is larger>
Figure FDA00041896748200000315
Selecting left side result, and similarly, if the level of the received signal of the right side detection antenna is larger, estimating the direction of arrival of the target signal source>
Figure FDA00041896748200000316
Selecting right side result, thereby screening +.>
Figure FDA00041896748200000317
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