CN111431641B - Unmanned aerial vehicle DOA estimation method and device based on antenna array - Google Patents

Unmanned aerial vehicle DOA estimation method and device based on antenna array Download PDF

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CN111431641B
CN111431641B CN202010220530.2A CN202010220530A CN111431641B CN 111431641 B CN111431641 B CN 111431641B CN 202010220530 A CN202010220530 A CN 202010220530A CN 111431641 B CN111431641 B CN 111431641B
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antenna
signal
radio frequency
uav
signals
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CN111431641A (en
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曹聪慧
侯群
漆为民
王芳
张建敏
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Jianghan University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0404—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas the mobile station comprising multiple antennas, e.g. to provide uplink diversity

Abstract

The invention relates to the technical field of unmanned aerial vehicles, and discloses an unmanned aerial vehicle DOA estimation method based on an antenna array, which comprises the following steps: passively collecting radio frequency signals communicated between the unmanned aerial vehicle and a remote controller through an equilateral polygonal antenna array, and preprocessing the radio frequency signals; carrying out frequency domain accumulation on a plurality of groups of radio frequency signals received by the antenna on each side to obtain accumulated signals; calculating the initial frequency and the cut-off frequency of the UAV signal by adopting a cross-correlation algorithm on the accumulated signals with the UAV signal; calculating a UAV signal strength of the UAV signal from the starting frequency and a cut-off frequency; screening two antennas which are adjacent in position and have the maximum UAV signal intensity, and calculating the signal intensity ratio of the two antennas to obtain an actual signal intensity ratio; and estimating the DOA angle of the unmanned aerial vehicle according to the actual signal intensity ratio and the antenna directional diagram. The invention has the technical effects of wide range and strong concealment for unmanned aerial vehicle detection.

Description

Unmanned aerial vehicle DOA estimation method and device based on antenna array
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle DOA estimation method and device based on an antenna array and a computer storage medium.
Background
In recent years, along with the development of technologies such as micro-mechanical sensors, integrated circuits and the like, the cost of the unmanned aerial vehicle is lower and lower, more and more developers are provided, the scale is gradually increased, and the unmanned aerial vehicle has a huge application prospect in military and civil related industries such as military battles, aerial photography and video recording, surveying and mapping, search and rescue, environmental monitoring, precision agriculture and the like. The development of unmanned aerial vehicles brings positive effects to all aspects, but harm and potential safety hazards caused by unmanned aerial vehicles have gradually attracted public and authority attention, and the out-of-control and missing detection of black flying unmanned aerial vehicles can pose serious threats to military operations, air traffic, competitions, fire fighting, human life and privacy.
At present, researches on black-flying unmanned aerial vehicle detection are relatively few, and existing unmanned aerial vehicle detection technologies comprise visual detection, infrared detection, acoustic detection, radar detection and the like. At most, vision, infrared, acoustics and the like can only detect unmanned aerial vehicle signals in a small range, and low-altitude targets such as birds and the like easily interfere the detection of the unmanned aerial vehicle; in the unmanned detection, radar detection needs to actively transmit radio frequency waves, which may expose the identity of the radar and have low concealment.
Disclosure of Invention
The invention aims to overcome the technical defects, provides an unmanned aerial vehicle DOA estimation method and device based on an antenna array and a computer storage medium, and solves the technical problems of small detection range and low concealment of the unmanned aerial vehicle in the prior art.
In order to achieve the technical purpose, the technical scheme of the invention provides an unmanned aerial vehicle DOA estimation method based on an antenna array, which comprises the following steps:
passively collecting radio frequency signals communicated between the unmanned aerial vehicle and a remote controller through an equilateral polygonal antenna array, and preprocessing the radio frequency signals;
carrying out frequency domain accumulation on a plurality of groups of radio frequency signals received by the antenna on each side to obtain accumulated signals;
calculating the initial frequency and the cut-off frequency of the UAV signal by adopting a cross-correlation algorithm on the accumulated signals with the UAV signal;
calculating a UAV signal strength of the UAV signal from the starting frequency and a cut-off frequency;
screening two antennas which are adjacent in position and have the maximum UAV signal intensity, and calculating the signal intensity ratio of the two antennas to obtain an actual signal intensity ratio;
and estimating the DOA angle of the unmanned aerial vehicle according to the actual signal intensity ratio and the antenna directional diagram.
The invention also provides an unmanned aerial vehicle DOA estimation device based on the antenna array, which comprises a processor and a memory, wherein the memory is stored with a computer program, and when the computer program is executed by the processor, the unmanned aerial vehicle DOA estimation method based on the antenna array is realized.
The invention provides a computer storage medium on which a computer program is stored, which, when executed by a processor, implements the antenna array based drone DOA estimation method.
Compared with the prior art, the invention has the beneficial effects that: the unmanned aerial vehicle detection method provided by the invention is the same as a radar detection method, and is also based on radio frequency signals for detection, so that the unmanned aerial vehicle detection method has the advantage of wide detection range. However, the invention is different from radar detection in that the invention does not need to actively transmit radio frequency signals through a radar to detect the unmanned aerial vehicle, but sets an antenna array, and passively receives the radio frequency signals transmitted by the unmanned aerial vehicle through the antenna array, so that the estimation of the arrival angle (DOA) of the unmanned aerial vehicle can be realized by using a signal intensity ratio fitting algorithm under the condition of ensuring no identity exposure, and the invention has strong anti-interference performance, higher resolution and stronger adaptability.
Drawings
Fig. 1 is a flowchart of an embodiment of a method for estimating DOA of an unmanned aerial vehicle based on an antenna array according to the present invention;
fig. 2 is a model diagram of an embodiment of a DOA estimation method for an unmanned aerial vehicle based on an antenna array according to the present invention;
FIG. 3 is a block diagram of one embodiment of a matched filter block provided in the present invention;
FIG. 4a is a signal diagram of a set of radio frequency signals provided by the present invention, including UAV signals;
FIG. 4b is a graph of the cross-correlation results of the RF signals of FIG. 4 a;
fig. 4c is a signal diagram of the radio frequency signal in fig. 4a after the WIFI interference signal is replaced by the WGN;
FIG. 4d is a signal diagram of the radio frequency signals of FIG. 4a after ensemble empirical mode decomposition;
FIG. 5a is a signal diagram of a set of radio frequency signals provided by the present invention that do not include UAV signals;
FIG. 5b is a graph of the cross-correlation results of the RF signals of FIG. 5 a;
fig. 5c is a signal diagram of the radio frequency signal in fig. 5a after the WIFI interference signal is removed;
FIG. 5d is a signal diagram of the radio frequency signals of FIG. 5a after ensemble empirical mode decomposition;
fig. 6 is an antenna pattern of an embodiment of a method for estimating DOA of an unmanned aerial vehicle based on an antenna array according to the present invention;
fig. 7 is a diagram of an adjacent antenna angle relationship in an embodiment of a method for estimating DOA of an unmanned aerial vehicle based on an antenna array according to 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 and 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.
Example 1
As shown in fig. 1, embodiment 1 of the present invention provides a method for estimating DOA of an unmanned aerial vehicle based on an antenna array, including the following steps:
s1, passively collecting radio frequency signals communicated between the unmanned aerial vehicle and the remote controller through an equilateral polygonal antenna array, and preprocessing the radio frequency signals;
s2, carrying out frequency domain accumulation on a plurality of groups of radio frequency signals received by the antenna on each side to obtain accumulated signals;
s3, calculating the accumulated signals with UAV signals by adopting a cross-correlation algorithm to obtain the starting frequency and the cut-off frequency of the UAV signals;
s4, calculating UAV signal strength of the UAV signal according to the starting frequency and the cut-off frequency;
s5, screening two antennas which are adjacent in position and have the maximum UAV signal strength, and calculating the signal strength ratio of the two antennas to obtain an actual signal strength ratio;
and S6, estimating the DOA angle of the unmanned aerial vehicle according to the actual signal strength ratio and the antenna pattern.
As shown in fig. 2, the present embodiment considers a model formed by an unmanned plane u, a remote controller c, and a passive receiving antenna array Rx, and in the present embodiment, the antenna array includes eight directional panel antennas distributed in an equilateral octagon to form an octagonal antenna array as a passive receiving mechanism. Active communication is performed between the drone and the remote control, accompanied by the transmission of a radio frequency signal that the antenna array may passively receive. In this embodiment, after the antenna array receives the radio frequency signal, the arrival angle of the drone, i.e., DOA, is estimated by using a corresponding algorithm.
Before carrying out DOA estimation based on passively collected radio frequency signals, in order to avoid interference signals in the radio frequency signals from influencing DOA estimation results, frequency domain signals in a frequency hopping range of an unmanned aerial vehicle need to be preprocessed first, and WiFi interference signals and Gaussian white noise in a complex environment are removed. The preprocessing method of the radio frequency signal is slightly different for the two cases of containing the UVA signal and not containing the UVA signal.
Preferably, when the radio frequency signal includes a UAV signal, the preprocessing is performed on the radio frequency signal, specifically:
designing a matched filtering template:
calculating a cross-correlation value of the matched filtering template and each group of data of each antenna at the central frequency position of each carrier of the WIFI interference signal;
setting a detection threshold value for the matched filtering template according to the cross-correlation value;
filtering the radio frequency signals through the matched filtering template, judging whether the cross-correlation value of each group of radio frequency signals of each antenna exceeds a set threshold value, if so, judging that the radio frequency signals of the corresponding group contain WIFI interference signals, replacing the WIFI interference signals at the corresponding frequency band with WGN, and if not, judging that the radio frequency signals of the corresponding group do not contain the WIFI interference signals;
and removing the WGN in the radio frequency signal by adopting ensemble empirical mode decomposition to obtain a preprocessed radio frequency signal.
In particular, assuming that each antenna passively receives J groups of data in each test, considering all signals within the UAV frequency hopping range, the received discrete frequency domain signal can be expressed as:
yijk＝sijk+wijk+nijk
wherein, the UAV frequency hopping range is 2.4-2.5GHz, i is the ith antenna, i is 1., 8, J is the jth group of data, J is 1., J, k is the kth frequency point, corresponding to the frequency kfw+2.4×109，fwIs the frequency domain sampling interval, k is 1., (2.5-2.4) × 109/fw，yijkThe power value s of the k frequency point corresponding to the j group of data received by the ith antennaijkIs the UAV signal, wijkFor WiFi interference signals, nijkOther clutter interference signals.
When UAV signals are present, a set of data is received as shown in figure 4 a. According to the 802.11 standard, the WiFi signal may be any one of 14 carrier frequencies with a bandwidth of 22MHz in the range of 2.4-2.5GHz, with each adjacent center frequency being separated by 5 MHz. In order to filter the WiFi interference signal, a matched filtering template is designed by using its frequency domain characteristics as shown in fig. 3, where the matched filtering template is represented as:
Figure GDA0003452937650000051
wherein the content of the first and second substances,
Figure GDA0003452937650000052
for the length of the matched filter template,
Figure GDA0003452937650000053
fwis the frequency domain sampling interval of the radio frequency signal,
Figure GDA0003452937650000054
for the purpose of the matched filtering template, the template is,
Figure GDA0003452937650000055
for the matched filtering template
Figure GDA0003452937650000056
Each element in (1); .
The cross-correlation value of the matched filtering template and the antenna j group data at the central frequency position of each carrier wave of the WIFI interference signal is as follows:
Figure GDA0003452937650000057
K＝1.2×106/fw,1.7×106/fw,2.2×106/fw,2.7×106/fw,3.2×106/fw,
3.7×106/fw,4.2×106/fw,4.7×106/fw,5.2×106/fw,5.7×106/fw,
6.2×106/fw,6.7×106/fw,7.2×106/fw,8.4×106/fw，
wherein, the data K is the center frequency of 14 carriers corresponding to the WiFi interference signal,
Figure GDA0003452937650000058
is the mean of the matched filter template and,
Figure GDA0003452937650000061
is the frequency corresponding to the j group of radio frequency signals received by the ith antenna
Figure GDA0003452937650000062
The value of the power at which the voltage is to be measured,
Figure GDA0003452937650000063
is that
Figure GDA0003452937650000064
To
Figure GDA0003452937650000065
The mean value of (a);
setting a detection threshold value for the matched filtering template according to the cross-correlation value; the cross-correlation result is shown in fig. 4b, based on which the detection threshold for the matched filter template is set to 0.5 in this embodiment;
and filtering the radio frequency signals through the matched filtering template, judging whether the cross-correlation value of each group of radio frequency signals of each antenna exceeds a set threshold value, and if the cross-correlation value of a certain position in the 14 central frequency positions exceeds the threshold value, indicating that a WiFi interference signal is detected. Replacing WiFi interference signals at corresponding frequency bands with WGNs to obtain signals as shown in figure 4c, and uniformly filtering the signals in the next step of Ensemble Empirical Mode Decomposition (EEMD);
the radio frequency signal after the WIFI interference signal is removed is as follows:
Figure GDA0003452937650000066
wherein the content of the first and second substances,
Figure GDA0003452937650000067
in order to remove the jth group of radio frequency signals received by the ith antenna after the WiFi interference signals are removed,
Figure GDA0003452937650000068
is the mean value (min (y)ij) +5) dBm, WGN with variance of 2.5dBm, and setting threshold of cross-correlation value of 0.5;
the ensemble empirical mode decomposition is an effective method for removing the WGN, and the WGN is removed by the ensemble empirical mode decomposition, and for the signal of the jth group of radio frequency signals received by the ith antenna after the h iteration:
Figure GDA0003452937650000069
wherein the content of the first and second substances,
Figure GDA00034529376500000610
received for the ith antennaThe signal of the jth group of radio frequency signals after the H iteration, H being 1.. H, H being the total number of iterations,
Figure GDA00034529376500000611
white noise added in the h iteration;
performing empirical mode decomposition on signals of a jth group of radio frequency signals received by an ith antenna after the h iteration:
Figure GDA0003452937650000071
wherein the content of the first and second substances,
Figure GDA0003452937650000072
is the G-th IMF, G is the number of IMFs,
Figure GDA0003452937650000073
is a residual wave signal;
finally, the result of the ensemble empirical mode decomposition of each group of radio frequency signals in each antenna is:
Figure GDA0003452937650000074
wherein the content of the first and second substances,
Figure GDA0003452937650000075
fig. 4d is a graph of the result of preprocessing the rf signals received by the post-EEMD antenna array, and it can be seen that the UAV signals are more significant in the frequency domain.
Preferably, when the radio frequency signal does not include a UAV signal, the radio frequency signal is preprocessed, specifically:
designing a matched filtering template:
calculating a cross-correlation value of the matched filtering template and each group of data of each antenna at the central frequency position of each carrier of the WIFI interference signal;
setting a detection threshold value for the matched filtering template according to the cross-correlation value;
and filtering the radio frequency signals through the matched filtering template, judging whether the cross-correlation value of each group of radio frequency signals of each antenna exceeds a set threshold value, if so, judging that the radio frequency signals of the corresponding group contain WIFI interference signals, deleting the WIFI interference signals at the corresponding frequency band to obtain preprocessed radio frequency signals, and if not, judging that the radio frequency signals of the corresponding group do not contain the WIFI interference signals.
Compared with the preprocessing method of the radio frequency signal containing the UAV signal, the preprocessing method of the radio frequency signal not containing the UAV signal is different in that the detected WIFI interference signal can be directly deleted, and WGN replacement is not needed. As shown in fig. 5a, fig. 5a is a set of rf signals without UAV signal, fig. 5b is a cross-correlation result of rf signals without UAV signal, it can be seen that there are two WiFi interference signals included in the rf signals, fig. 5c is a signal diagram after removing the WiFi interference signals, and fig. 5d is a preprocessing result after EEMD.
Preferably, the frequency domain accumulation is performed on multiple groups of radio frequency signals received by the antennas on each side to obtain an accumulated signal, specifically:
Figure GDA0003452937650000081
wherein the content of the first and second substances,
Figure GDA0003452937650000082
j is the number of sets of rf signals received by each of the antennas, I is the total number of antennas included in the antenna array,
Figure GDA0003452937650000083
for the jth group of rf signals received by the ith antenna,
Figure GDA0003452937650000084
fwis the frequency domain sampling interval of the radio frequency signal.
Using a frequency domain accumulation algorithm for frequency domain accumulation may enhance the UAV signal while clipping clutter.
For the accumulated signals accumulated by each antenna frequency domain, after UAV signals exist in the accumulated signals are detected, for the antenna with the UAV signals in the received radio frequency signals, a cross-correlation algorithm is used for obtaining the starting frequency f of the UAV signalsstartAnd a cut-off frequency fendAnd then, calculating to obtain the signal strength of the corresponding UAV signal.
Preferably, calculating the UAV signal strength of the UAV signal according to the start frequency and the cut-off frequency, specifically:
Figure GDA0003452937650000085
wherein, PiUAV Signal Strength, f, received for the ith antennastartIs the starting frequency, fendIs the cut-off frequency, fwIs the frequency domain sampling interval of the radio frequency signal,
Figure GDA0003452937650000086
the radio frequency signal at the kth frequency location for the ith antenna.
Generally, if the antenna array receives the UAV signal, then the UAV signal power of two adjacent antennas in the octagonal antenna array is maximum and second maximum, which can be expressed as PiAnd Pi+1Which can be used to estimate the DOA of the drone, first requires the ratio of the maximum and the next largest signal strengths.
Preferably, two antennas with adjacent positions and the maximum UAV signal strength are screened out, and the ratio of the signal strengths of the two antennas is calculated to obtain the actual signal strength ratio, which specifically is as follows:
Figure GDA0003452937650000091
where ρ is the actual signal strength ratio, PiUAV signals received for the ith antennaStrength, Pi+1For the UAV signal strength received by the i +1 th antenna, the i th antenna and the i +1 th antenna are two adjacent antennas, and the i th antenna and the i +1 th antenna are two antennas with the largest UAV signal strength among UAV signals received by the multiple antennas.
In order to perform DOA estimation on the unmanned aerial vehicle in a complex environment, the present embodiment provides a signal strength ratio fitting algorithm to perform DOA estimation on the UAV in combination with an antenna pattern. Each antenna in the octagonal-antenna array is a directional antenna, and has the same parameters and different orientations. The antenna pattern is a pattern in which the relative intensity of the radiation field changes with the direction, and each antenna in the array has the same pattern, which can be expressed as D ═ D0，...，Dα，...，D360]As shown in fig. 6.
As shown in fig. 7, the internal angle between adjacent antennas of the octagonal antenna array is 135 °, and considering the unmanned aerial vehicle at a long distance, the UAV signal emitted by the octagonal antenna array can be regarded as a far-field signal source, the antenna array receives the UAV signal transmitted by a far field, and the finding of two adjacent antennas and the UAV signal form an included angle having the following relationship:
αi+αi+1＝45°
wherein alpha isiIs the angle between the UAV signal and the normal of the ith antenna, alphai+1Is the included angle between the UAV signal and the normal of the (i + 1) th antenna; 360-alphaiIs DOA, α relative to the ith antennai+1Is the DOA relative to the (i + 1) th antenna.
From the actual signal strength ratio and the antenna pattern D, the DOA of the UAV can be estimated. In practical applications, the actual ratio of the signal strengths can be obtained, and it can be known that there must be an optimum angle αi+1The field strength ratio on its corresponding antenna pattern is closest to p.
Preferably, the estimating a DOA angle of the drone according to the actual signal strength ratio and the antenna pattern specifically includes:
the antenna pattern is:
D＝[D0，...，Dα，...，D360]
wherein D is the antenna pattern, DαRelative field strength at angle α in the antenna pattern, α is 0, …, 360;
determining an angle, closest to the actual signal strength ratio, of the field strength ratio on the antenna directional diagram as the DOA angle:
Figure GDA0003452937650000101
wherein A isi+1Is the DOA angle of the UAV signal of the drone relative to the (i + 1) th antenna,
Figure GDA0003452937650000103
for alpha in antenna patterni+1Relative field strength at an angle, D360°Is the relative field strength at 360 degrees in the antenna directional diagram, rho is the actual signal strength ratio, alpha0Is the included angle between the ith antenna and the (i + 1) th antenna.
Where ρ and D are known, the only adjustable parameter is αi+1When estimating alphai+1Thereafter, the DOA relative to the ith antenna may also be estimated.
The DOA of the UAV relative to the (i + 1) th antenna can be estimated as:
Figure GDA0003452937650000102
to verify the performance effect of the embodiment of the present invention, an experimental test was performed, where each antenna in the octagonal antenna array receives 50 groups of data, where J is set to 50, and the radio frequency signals received by the eight antennas are combined into one large data set to perform DOA estimation on the UAV. The UAV signal strength decreases continuously with increasing distance and at least two of the eight antennas can receive the UAV signal. In the experiment, the correct DOAs of the unmanned aerial vehicle are 347 °, 348 ° and 349 ° at distances of 1000m, 2500m, and 4000m from the unmanned aerial vehicle, respectively.
Table 1 shows the different chambersMaximum and second largest UAV Signal Strength P at external distanceiAnd Pi+1Actual signal strength ratio ρ, DOA estimate, and DOA estimate error. It can be known that the DOA estimation error increases with the increase of the outdoor distance, but within the range of 4000m, the DOA estimation error within 4 degrees can still be ensured, and the accuracy is higher.
Table 1, DOA estimation at different outdoor distances:
1000m 2500m 4000m
Pi(W) 9.7447e-12 2.0193e-12 5.1241e-13
Pi+1(W) 6.8561e-12 1.2455e-12 2.6209e-13
ρ 1.421 1.621 1.9551
DOA estimation (°) 346.2 349.5 352.7
DOA error (°) 1.8 2.5 3.7
Example 2
Embodiment 2 of the present invention provides an unmanned aerial vehicle DOA estimation apparatus based on an antenna array, including a processor and a memory, where the memory stores a computer program, and when the computer program is executed by the processor, the unmanned aerial vehicle DOA estimation method based on an antenna array provided in embodiment 1 is implemented.
The unmanned aerial vehicle DOA estimation device based on the antenna array is used for realizing the unmanned aerial vehicle DOA estimation method based on the antenna array, so that the unmanned aerial vehicle DOA estimation method based on the antenna array has the technical effects, and the unmanned aerial vehicle DOA estimation device based on the antenna array also has the advantages, and the details are not repeated herein.
Example 3
Embodiment 3 of the present invention provides a computer storage medium having a computer program stored thereon, which when executed by a processor, implements the drone DOA estimation method based on antenna arrays provided in embodiment 1.
The computer storage medium provided by the embodiment of the invention is used for realizing the unmanned aerial vehicle DOA estimation method based on the antenna array, so that the technical effect of the unmanned aerial vehicle DOA estimation method based on the antenna array is also achieved by the computer storage medium, and the description is omitted.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention. Any other corresponding changes and modifications made according to the technical idea of the present invention should be included in the protection scope of the claims of the present invention.

Claims (7)

1. An unmanned aerial vehicle DOA estimation method based on an antenna array is characterized by comprising the following steps:
passively collecting radio frequency signals communicated between the unmanned aerial vehicle and a remote controller through an equilateral polygonal antenna array, and preprocessing the radio frequency signals;
carrying out frequency domain accumulation on a plurality of groups of radio frequency signals received by the antenna on each side to obtain accumulated signals;
calculating the initial frequency and the cut-off frequency of the UAV signal by adopting a cross-correlation algorithm on the accumulated signals with the UAV signal;
calculating a UAV signal strength of the UAV signal from the starting frequency and a cut-off frequency;
screening two antennas which are adjacent in position and have the maximum UAV signal intensity, and calculating the signal intensity ratio of the two antennas to obtain an actual signal intensity ratio;
estimating the DOA angle of the unmanned aerial vehicle according to the actual signal intensity ratio and the antenna directional diagram;
calculating the UAV signal strength of the UAV signal according to the starting frequency and the cut-off frequency, specifically:
Figure FDA0003452937640000011
wherein, PiUAV Signal Strength, f, received for the ith antennastartIs the starting frequency, fendIs the cut-off frequency, fwIs the frequency domain sampling interval of the radio frequency signal,
Figure FDA0003452937640000012
is the radio frequency signal of the ith antenna at the kth frequency position, k is the kth frequency point, and k is 19/fw；
Estimating the DOA angle of the unmanned aerial vehicle according to the actual signal intensity ratio and the antenna directional diagram, specifically:
the antenna pattern is:
D＝[D0,...,Dα，...，D360]
wherein D is the antenna pattern, DαRelative field strength at angle α in the antenna pattern, α is 0, …, 360;
determining an angle, closest to the actual signal strength ratio, of the field strength ratio on the antenna directional diagram as the DOA angle:
Figure FDA0003452937640000021
wherein A isi+1DOA Angle, α, of UAV Signal for unmanned aerial vehicle with respect to the i +1 st antennaiIs the angle between the UAV signal and the normal of the ith antenna, alphai+1Is the angle between the UAV signal and the normal of the (i + 1) th antenna,
Figure FDA0003452937640000022
for alpha in antenna patterni+1Relative field strength at an angle, D360°Is the relative field strength at 360 degrees in the antenna directional diagram, rho is the actual signal strength ratio, alpha0Is the included angle between the ith antenna and the (i + 1) th antenna.
2. The method of estimating DOA of an unmanned aerial vehicle based on an antenna array of claim 1, wherein when the radio frequency signal includes a UAV signal, the radio frequency signal is preprocessed, specifically:
designing a matched filtering template:
calculating a cross-correlation value of the matched filtering template and each group of data of each antenna at the central frequency position of each carrier of the WIFI interference signal;
setting a detection threshold value for the matched filtering template according to the cross-correlation value;
filtering the radio frequency signals through the matched filtering template, judging whether the cross-correlation value of each group of radio frequency signals of each antenna exceeds a set threshold value, if so, judging that the radio frequency signals of the corresponding group contain WIFI interference signals, replacing the WIFI interference signals at the corresponding frequency band with WGN, and if not, judging that the radio frequency signals of the corresponding group do not contain the WIFI interference signals;
and removing the WGN in the radio frequency signal by adopting ensemble empirical mode decomposition to obtain a preprocessed radio frequency signal.
3. The method of estimating DOA of an unmanned aerial vehicle based on an antenna array of claim 1, wherein when the radio frequency signal does not include a UAV signal, the radio frequency signal is preprocessed, specifically:
designing a matched filtering template:
calculating a cross-correlation value of the matched filtering template and each group of data of each antenna at the central frequency position of each carrier of the WIFI interference signal;
setting a detection threshold value for the matched filtering template according to the cross-correlation value;
and filtering the radio frequency signals through the matched filtering template, judging whether the cross-correlation value of each group of radio frequency signals of each antenna exceeds a set threshold value, if so, judging that the radio frequency signals of the corresponding group contain WIFI interference signals, deleting the WIFI interference signals at the corresponding frequency band to obtain preprocessed radio frequency signals, and if not, judging that the radio frequency signals of the corresponding group do not contain the WIFI interference signals.
4. The unmanned aerial vehicle DOA estimation method based on the antenna array as claimed in claim 1, wherein the frequency domain accumulation is performed on the multiple groups of radio frequency signals received by the antennas on each side to obtain an accumulated signal, specifically:
Figure FDA0003452937640000031
wherein the content of the first and second substances,
Figure FDA0003452937640000032
j is the number of sets of rf signals received by each of the antennas, I is the total number of antennas included in the antenna array,
Figure FDA0003452937640000033
for the jth group of rf signals received by the ith antenna,
Figure FDA0003452937640000034
fwis the frequency domain sampling interval of the radio frequency signal.
5. The method of claim 1, wherein two antennas with adjacent positions and maximum UAV signal strength are screened out, and the ratio of the signal strengths of the two antennas is calculated to obtain an actual signal strength ratio, specifically:
Figure FDA0003452937640000035
where ρ is the actual signal strength ratio, PiUAV Signal Strength, P, received for the ith antennai+1For the UAV signal strength received by the i +1 th antenna, the i th antenna and the i +1 th antenna are two adjacent antennas, and the i th antenna and the i +1 th antenna are two antennas with the largest UAV signal strength among UAV signals received by the multiple antennas.
6. An antenna array based drone DOA estimation device, characterized by comprising a processor and a memory, said memory having stored thereon a computer program which, when executed by said processor, implements the antenna array based drone DOA estimation method according to any one of claims 1-5.
7. A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for drone DOA estimation based on antenna arrays according to any one of claims 1 to 5.
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