Unmanned aerial vehicle direction finding method, device and system, electronic equipment and storage medium

Abstract

The invention provides an unmanned aerial vehicle direction finding method, device and system, electronic equipment and a storage medium. The method comprises the following steps: receiving signal data of at least two antennas each time; performing cross-correlation operation on the signal data of one antenna received at the time and the signal data of the other antennas received at the time to obtain cross-correlation signal strength; performing error measurement on the cross-correlation signal intensity and a corresponding signal intensity theoretical value in a theoretical set; wherein the signal strength theoretical values corresponding to the cross-correlation signal strength in the theoretical set comprise signal strength theoretical values of a plurality of search azimuth angles; the error measure is minimum through searching, and the corresponding searching azimuth angle is the estimated signal incoming wave direction. According to the technical scheme of the invention, through the cross-correlation operation of the at least two antennas received each time, the information provided by the amplitude response and the phase response of the antennas is fully utilized, the direction finding precision is improved, and the performance adaptability in various scenes is stronger.

Description

Technical Field

[0001] The present invention relates to a field, and in particular to a method, device and system for finding the direction of an unmanned aerial vehicle, an electronic device, and a storage medium. Background Art

[0002] With the rapid development of drone technology, drones have also begun to be used in large numbers, bringing many challenges in security supervision, anti-terrorism and stability maintenance, environmental protection, etc., such as effectively monitoring and locating drones that illegally invade no-fly zones or drones without flight permission. Drone direction finding technology can measure the direction of drones in the air, which is of great significance in radio positioning and is widely used in the field of drone supervision and tracking.

[0003] The existing UAV direction finding technologies mainly include the following:

[0004] 1. Spectrum detection technology:

[0005] There is a wireless communication link between the drone and its remote controller, including image transmission (image transmission) signals and remote control signals. By passively intercepting these signals, the RF receiving equipment can be used to measure signal strength and parameters such as time difference of arrival (TOA) and angle of arrival (AOA), thereby realizing passive detection, direction finding and positioning of the drone.

[0006] 2. Radio direction finding technology:

[0007] Radio Direction Finding (RDF), also known as passive direction finding, is a technique that uses an antenna array to capture radio signals from drones and calculate the direction of the signal source by comparing the time difference or phase difference between signals received by different antennas. For example, the Bloodhound project uses this technology to locate the position of drones.

[0008] 3. Interferometer direction finding system:

[0009] Interferometer direction-finding systems usually use variable baseline technology. Through medium and large-sized antenna arrays, equipped with multi-channel receivers and advanced signal processing algorithms (such as fast Fourier transform), they can achieve high-precision and high-speed direction-finding, and can also determine the elevation angle of the signal, effectively counteracting the influence of wavefront distortion.

[0010] 4. Photoelectric detection technology:

[0011] Photoelectric detection uses photoelectric sensors to capture light signals reflected or emitted by drones, such as infrared, visible light or lidar, and determines the position of the drone through optical systems and image processing technology.

[0012] 5. Acoustic wave detection technology:

[0013] Although the noise generated by drone flight is relatively small, in certain specific environments, especially when flying at low altitudes, sound wave detection equipment can be used to monitor and analyze the noise generated by the drone flight and then locate it.

[0014] In summary, UAV direction-finding technology integrates multidisciplinary technical means such as radio communications, electronic warfare, signal processing, optoelectronic sensing, and acoustic wave detection, and is constantly improving and perfecting; especially in terms of measurement accuracy, it needs to continue to improve and perfect in order to adapt to the growing demand for UAV supervision. Summary of the invention

[0015] The present invention provides a method, device and system for finding the direction of an unmanned aerial vehicle, an electronic device and a storage medium, so as to solve the problem that the measurement accuracy needs to be continuously improved and perfected.

[0016] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0017] According to a first aspect of the present invention, a method for direction finding of a drone is provided, wherein a plurality of antennas are used to receive drone signal data, and the method comprises:

[0018] receiving signal data from at least two of the antennas each time;

[0019] Processing the signal data received each time specifically includes: performing a cross-correlation operation on the signal data of one of the antennas received this time with the signal data of the remaining antennas received this time to obtain a cross-correlation signal strength;

[0020] Perform error measurement on the cross-correlation signal strength and the corresponding theoretical value of signal strength in a theoretical set; wherein the theoretical value of signal strength corresponding to the cross-correlation signal strength in the theoretical set includes theoretical values ​​of signal strength at multiple search azimuth angles;

[0021] The search is performed so that the error metric is minimized, and the corresponding search azimuth is the estimated signal arrival direction.

[0022] Optionally, the performing a cross-correlation operation on the signal data of one of the antennas received this time with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength specifically includes:

[0023] For the signal data of the i-th antenna received this time, a cross-correlation operation is performed on it and the signal data of the j-th antenna received this time to obtain the cross-correlation signal strength of the i-th antenna, which is expressed as:

[0024]

[0025] Among them, θ represents the direction of the signal wave, m represents the mth received signal data, represents the signal data of the i-th antenna, represents the signal data of the jth antenna, (·) * represents the conjugate of the signal, Δt represents the time delay of the signal data received from the jth antenna relative to the signal data received from the ith antenna, and 2πf c Δt represents the phase deviation between the signal data received from the two antennas, f c is the frequency at which the signal data resides.

[0026] Optionally, when the number of antennas received each time includes more than two, cross-correlation operation is performed on the signal data of one of the antennas received this time with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength, specifically including:

[0027] For the signal data of one of the antennas received this time, cross-correlation operation is performed on it and the signal data of each of the remaining antennas received this time to obtain multiple cross-correlation signal strengths;

[0028] An average value of a plurality of the cross-correlation signal strengths is calculated.

[0029] Optionally, the number of antennas is greater than the number of antennas used for receiving each time;

[0030] The receiving signal data of at least two antennas each time specifically includes:

[0031] In a period T, the antennas are polled in a time-sharing manner, and signal data from at least two antennas are received each time.

[0032] Optionally, the performing error measurement on the cross-correlation signal strength and a corresponding theoretical value of signal strength in a theoretical set specifically includes:

[0033] The error measurement is performed between the cross-correlation signal strength obtained from all polling within a period T and the theoretical value of the corresponding signal strength in the theoretical set;

[0034] The error metrics obtained from all polls are summed.

[0035] Optionally, all obtained error metrics are added together, specifically:

[0036] The error metrics obtained from all polls are weighted and added, expressed as:

[0037]

[0038] in, represents the weight coefficient of the mth poll, J represents the total number of polls, and wm is the absolute value of the cross-correlation signal strength obtained in the mth polling, w sum It is the sum of the absolute values ​​of the cross-correlation signal strengths obtained from all pollings, and Err(m) represents the error metric of the mth polling.

[0039] Optionally, the error measure between the cross-correlation signal strength and the corresponding theoretical value of the signal strength in the theoretical set is the Euclidean distance between the two.

[0040] According to a second aspect of the present invention, a drone direction finding device is provided, wherein the number of antennas for receiving drone signal data is multiple, and the device comprises:

[0041] A signal receiving module, used for receiving signal data from at least two antennas each time;

[0042] The cross-correlation module is used to process the signal data received each time, specifically to: for the signal data of one of the antennas received this time, perform a cross-correlation operation on it with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength;

[0043] An error measurement module is used to perform error measurement on the cross-correlation signal strength and the corresponding signal strength theoretical value in a theoretical set; wherein the signal strength theoretical value in the theoretical set corresponding to the cross-correlation signal strength includes the signal strength theoretical values ​​of multiple search azimuth angles;

[0044] The arrival direction determination module is used to search so that the error metric is minimized, and the corresponding search azimuth is the estimated signal arrival direction.

[0045] According to a third aspect of the present invention, there is provided a drone direction finding system, comprising:

[0046] Multiple antennas for receiving signal data from drones;

[0047] A multi-channel receiver, used for receiving signal data from at least two antennas at a time; each channel receives signal data from one antenna at a time;

[0048] A plurality of switches, connected between the antenna and the receiver, for controlling the receiving time of the multi-channel receiver and the antenna corresponding to each reception;

[0049] The signal processing device is used to process the signal data received each time, specifically: for the signal data of one of the antennas received this time, it is cross-correlated with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength; it is also used to measure the error between the cross-correlation signal strength and the corresponding signal strength theoretical value in a theoretical set; wherein the signal strength theoretical value corresponding to the cross-correlation signal strength in the theoretical set includes the signal strength theoretical values ​​of multiple search azimuth angles; it is also used to search for a method that minimizes the error measurement, and the corresponding search azimuth angle is the estimated signal arrival direction.

[0050] Optionally, the number of the antennas is a multiple of the number of channels of the receiver;

[0051] The switches correspond one to one to the channels of the receiver;

[0052] The switch is a multi-way switch, and each way of the switch corresponds to one of the antennas.

[0053] Optionally, multiple antennas are evenly distributed on a circle.

[0054] According to a fourth aspect of the present invention, there is provided an electronic device, comprising:

[0055] processor;

[0056] and, a memory for storing processor-executable instructions;

[0057] The processor implements the steps in the above method by running the executable instructions.

[0058] According to a fifth aspect of the present invention, there is provided a storage medium having a computer program stored thereon, wherein the computer program implements the steps in the above-mentioned method when executed by a processor.

[0059] The drone direction-finding method, device and system, electronic device and storage medium provided by the present invention perform cross-correlation operation on the signal data received from the two antennas each time, and the obtained cross-correlation signal strength includes the signal strength of the signal and the direction of the signal wave, and weights the phase with the amplitude as the weight, so as to make full use of the information that can be provided by the amplitude response and phase response of the antenna, improve the direction-finding accuracy, and make the performance in various scenarios more adaptable.

[0060] In an optional solution of the present invention, a weight coefficient is added during error measurement, taking into account the impact of differences in antenna placement positions on the accuracy of error measurement, thereby further improving the direction finding accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0062] Figure 1 A flowchart of a method for direction finding of a UAV according to an embodiment of the present invention;

[0063] Figure 2 A schematic diagram of a direction-finding device for a drone according to an embodiment of the present invention;

[0064] Figure 3 A schematic diagram of a UAV direction finding system according to an embodiment of the present invention;

[0065] Figure 4 A switching signal waveform diagram of a UAV direction finding system according to an embodiment of the present invention;

[0066] Figure 5 A schematic diagram of the distribution of multiple antennas according to an embodiment of the present invention;

[0067] Figure 6 is a schematic diagram of an electronic device according to an embodiment of the present invention;

[0068] Description of reference numerals:

[0069] 11-Signal receiving module,

[0070] 12- Cross-correlation module,

[0071] 13- Error metric module,

[0072] 14- wave direction determination module;

[0073] 21- Antenna,

[0074] 22-Multi-channel receiver,

[0075] 23- switch,

[0076] 24-Signal processing equipment;

[0077] 31- Processor,

[0078] 32-internal bus,

[0079] 33- Network interface,

[0080] 34-Memory,

[0081] 35-Memory. DETAILED DESCRIPTION

[0082] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0083] In the description of the specification of the present invention, it is necessary to understand that the orientation or position relationship indicated by the terms "upper part", "lower part", "upper end", "lower end", "lower surface", "upper surface", etc. is based on the orientation or position relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0084] In the description of the present specification, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0085] In the description of the present invention, "plurality" means a plurality, such as two, three, four, etc., unless otherwise clearly and specifically defined.

[0086] In the description of the present invention, unless otherwise clearly specified and limited, the term "connection" and other terms should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or mutual communication; it can be directly connected or indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0087] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0088] In one embodiment, a method for finding the direction of an unmanned aerial vehicle is provided, which refers to Figure 1 , which includes:

[0089] S11: Receive signal data from at least two antennas each time.

[0090] In practice, there are multiple antennas for receiving drone signal data. When receiving signal data from two antennas each time, the number of antennas is at least two; when receiving signal data from three antennas each time, the number of antennas is at least three, and so on. No further examples are given.

[0091] S12: Processing the signal data received each time, specifically including: performing a cross-correlation operation on the signal data of one of the antennas received this time and the signal data of the remaining antennas received this time to obtain a cross-correlation signal strength.

[0092] In practice, when signal data from two antennas are received each time in S11, S12 is to perform a cross-correlation operation on the signal data from one of the received antennas and the signal data from the other antenna, and obtain a cross-correlation signal strength each time, and the cross-correlation signal strength is the cross-correlation signal strength of this time. When the number of antennas received each time in S11 includes more than two, a cross-correlation operation is performed on one of the received antennas and each of the remaining antennas to obtain multiple cross-correlation signal strengths, and the multiple cross-correlation signal strengths can be averaged as the cross-correlation signal strength of this time. For example, taking the example of receiving signal data from three antennas each time, S12 is to perform a cross-correlation operation on the signal data from one of the received antennas and the remaining two antennas respectively, to obtain two cross-correlation signal strengths, and the average of the two cross-correlation signal strengths is calculated as the cross-correlation signal strength of this time. When S11 receives signal data from more than three antennas each time, the principle is similar to that of three antennas. Assuming that signal data from K antennas are received each time, S12 can obtain K-1 cross-correlation signal strengths related to one of the antennas each time, and the average of these K-1 cross-correlation signal strengths is used as the cross-correlation signal strength for this time.

[0093] S13: performing error measurement between the cross-correlation signal strength and the corresponding theoretical value of signal strength in the theoretical set; wherein the theoretical value of signal strength corresponding to the cross-correlation signal strength in the theoretical set includes theoretical values ​​of signal strength at multiple search azimuth angles.

[0094] In practice, the received signal strength is related to the direction of the wave, and the azimuth angle can be within a certain range [θ low -θ high ] with a certain step size θ step Divide and obtain L search azimuth angles θ l , where L = (θ low -θ high ) / θ step +1; then calculate the i-th antenna at θ l Theoretical value of signal strength received at:

[0095]

[0096] Among them, θ l =θ low +l×θ step , l=0,…L-1, P0 represents the receiving strength when the azimuth angle θ is 0, g(·) represents the receiving strength change function of the i-th antenna caused by the change of θ, and for each antenna, this function is known. Assuming that P0 is known, the theoretical value of the signal strength of all antennas at each search azimuth can be obtained Wherein, i represents the i-th antenna.

[0097] Calculate the theoretical values ​​of all antennas at each search azimuth, and then construct a theoretical set. The theoretical set can be represented in the form of a matrix, such as one column for each search azimuth, or one row for easy comparison. Among them, the theoretical value of signal strength corresponding to the cross-correlation signal strength in the theoretical set can be understood as follows: the cross-correlation signal strength is the cross-correlation signal strength related to the antenna, and the corresponding theoretical value of signal strength is the theoretical value of signal strength at all search azimuths of the corresponding antenna.

[0098] In one example, the azimuth angle is divided into a certain range with a certain step length to obtain multiple search azimuth angles. For example, the azimuth angle is divided into a range of -180°C to 180°C with a step length of l=10°C to obtain multiple search azimuth angles θ l .

[0099] S14: Search to minimize the error metric, and the corresponding search azimuth is the estimated signal arrival direction.

[0100] In practice, in S13, the cross-correlation signal strength is subjected to error measurement with the corresponding theoretical signal strength values ​​at all search azimuths, and it is possible to find out which search azimuth has the smallest error measurement with the theoretical signal strength value. The corresponding search azimuth is then the estimated signal arrival direction.

[0101] In one embodiment, it is assumed that the signal data received by each antenna is represented by r a (t), assuming that the two receiving antennas are: the i-th antenna and the j-th antenna; with the i-th antenna as a reference, the signal received from the j-th antenna has a certain time delay Δt relative to the signal received from the i-th antenna. The time delay can be calculated based on the signals of the two antennas, such as by using algorithms such as GCC. Therefore, the received signal can be phase compensated according to the time delay, and then the two signals can be cross-correlated. The cross-correlation signal strength of the i-th antenna received for the mth time and the j-th antenna can be expressed as:

[0102]

[0103] Among them, θ represents the direction of the signal wave, (·) * represents the conjugate of the signal, 2πf c Δt represents the phase deviation between the signal data received from the two antennas, f c is the frequency of the signal data; It includes the direction of the signal and the received signal strength.

[0104] When there are more than two antennas for each reception, for the ith antenna, a cross-correlation operation is performed with each of the remaining antennas to obtain multiple cross-correlation signal strengths related to the ith antenna. Each cross-correlation strength j represents a different value, and the average value is obtained to obtain the final cross-correlation signal strength, which can be recorded as

[0105] In one embodiment, between S11 and S12, the signal data may be sampled to obtain a time domain sampling signal of a certain length, namely, r a (k), where k is the number of sampling points, such as k=1, 2, 3, 1000. Then the cross-correlation signal strength obtained in S12 can be expressed as:

[0106] In one embodiment, the number of antennas is greater than the number of antennas received each time. Correspondingly, receiving signal data from at least two antennas each time specifically includes: within a period T, using a time-division polling method for the antennas, receiving signal data from at least two antennas each time.

[0107] In one embodiment, S13 performs error measurement on the cross-correlation signal strength and the theoretical value of the signal strength corresponding to the theoretical set, specifically including:

[0108] S131: performing error measurement between the cross-correlation signal strengths obtained from all polling within a period T and the corresponding theoretical signal strength values ​​in the theoretical set;

[0109] S132: Add all the obtained error metrics.

[0110] The error metric obtained after the above steps includes the error metric between the cross-correlation signal strength of all antennas obtained by polling and the theoretical value of signal strength within a period T; therefore, the error metric obtained by the subsequent S14 search is the smallest, which can ensure that the error metric sum of all antennas obtained by polling is the smallest.

[0111] In one embodiment, since the differences in the placement positions of different antennas will affect the accuracy of the error metric, weight coefficients can be used to re - represent the error metric of the cross - correlation intensity signal obtained in each polling. First, add up the magnitudes of all the obtained cross - correlation signal intensities to get w sum ; then the weight coefficient for each polling can be expressed as:

[0112]

[0113] where w m is the absolute value of the cross - correlation signal intensity obtained in the m - th polling; w sum is the sum of the absolute values of the cross - correlation intensities of all pollings.

[0114] The weighted error metric at each θ is expressed as:

[0115]

[0116] where J represents the total number of pollings, Err(m) is the error metric obtained in each polling, and the error metric can be the Euclidean distance between the two. When the number of antennas in each polling is two, Err(m) can be expressed as: When the number of antennas in each polling is more than two,

[0117] The above - mentioned direction - finding method will be described in detail below with specific examples:

[0118] Suppose there are a total of N receiving antennas and a total of M pollings are performed. In each polling, the cross - correlation signal intensity related to one antenna will be finally obtained. In particular, when M = N, the more information the system uses (the cross - correlation signal intensities of each antenna can be obtained), the better the positioning effect, but the computational amount is slightly more; when M < N, the less information the system uses (the cross - correlation signal intensities of some antennas are obtained), the slightly worse the positioning effect, but the computational amount is reduced. In different embodiments, a trade - off between the positioning effect and the computational amount can be made to select an appropriate polling method.

[0119] Further, in the m - th polling (1 <= m <= M), the signal data of K antennas are received through multiple channels. Among the K received antennas, assume that the cross - correlation signal intensity of the i - th antenna is selected as the output of this polling, where i is the index of the antenna sequence (1 <= i <= N). Using the signal data of the K antennas, this polling will obtain K - 1 cross - correlation signal intensities related to the i - th antenna. On this basis, the relevant K - 1 cross - correlation signal intensities are averaged (preferably, weighted average) to obtain the cross - correlation signal intensity related to the i - th antenna in this polling.

[0120] In each polling, the cross-correlation signal strength related to one of the antennas is obtained. Preferably, the antenna numbers corresponding to the cross-correlation signal strengths obtained in each polling are different, so that the system can use more information.

[0121] After M pollings, the cross-correlation signal strengths of M×1 antennas with different serial numbers will be obtained. In order to facilitate subsequent comparison, we can use the polling times m, the antenna serial number i corresponding to each polling, and the different assumed range angles θ to calculate the signal strengths of M×1 antennas with different serial numbers. l Automatically generate an M×L signal strength theoretical value table.

[0122] Finally, the error metric is performed on each column of the table of the M×1 cross-correlation signal strength and the theoretical value of the signal strength. If the error metric of a column is the smallest, it is considered that the azimuth angle corresponding to this column is the estimated signal arrival direction.

[0123] The following is a detailed description of polling with various examples:

[0124] (1) This example takes the case of receiving signal data from two antennas each time, that is, K = 2:

[0125] (1a) M = N:

[0126] Time-sharing polling can be achieved by receiving twice by each antenna and combining it with the two adjacent antennas before and after it once respectively. For N antennas, polling is required N times, and N cross-correlation signal strengths will be obtained. The N cross-correlation signal strengths can be combined into an N×1 column vector. At this time, if each search azimuth angle of the corresponding theoretical set also corresponds to a column, the obtained theoretical value matrix is ​​an N×L matrix, and each row in the N×1 column vector of each polling corresponds to each row in the theoretical value matrix.

[0127] For example: M=N=8, the following polling method can be used:

[0128] When m=1, receive: signal data of antenna 8, 1, output: cross-correlation signal strength (actual strength) corresponding to antenna i=1;

[0129] When m=2, receive: signal data of antennas 1 and 2, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=2;

[0130] When m=3, receive: received signals from antennas 2 and 3, output: cross-correlation signal strength (actual strength) corresponding to antenna i=3;

[0131] When m=4, receive: received signals from antennas 3 and 4, output: cross-correlation signal strength (actual strength) corresponding to antenna i=4;

[0132] When m=5, receive: received signals from antennas 4 and 5, output: cross-correlation signal strength (actual strength) corresponding to antenna i=5;

[0133] When m=6, receive: received signals of antennas 5 and 6, output: cross-correlation signal strength (actual strength) corresponding to antenna i=6;

[0134] When m=7, receive: received signals from antennas 6 and 7, output: cross-correlation signal strength (actual strength) corresponding to antenna i=7;

[0135] When m=8, receive: received signals from antennas 7 and 8, output: cross-correlation signal strength (actual strength) corresponding to antenna i=8;

[0136] Finally, the eight actual intensity values ​​are compared with the theoretical value table for error measurement, and then positioning is performed to obtain the estimated signal direction.

[0137] (1b)M <N:

[0138] When the number of antennas is multiple times the number of antennas for each reception, each antenna can also be used to receive only once. For N antennas, N / 2 cross-correlation signal strengths need to be polled. In order to facilitate subsequent comparison, the N / 2 cross-correlation signal strengths can be combined into an N / 2×1 column vector. At this time, if each search azimuth angle of the corresponding theoretical set also corresponds to a column, the obtained theoretical value matrix can also be an N / 2×L matrix of the corresponding antenna. Each row in the N / 2×1 column vector of each polling corresponds to each row in the theoretical value matrix. Of course, the theoretical value matrix can also use an N×L matrix of all antennas. When measuring the error, just find the theoretical value of the corresponding antenna. Compared with the case where each antenna receives twice, although the search calculation amount will be reduced by half when each antenna receives only once, the positioning accuracy will also be reduced because the cross-correlation signal strength is only obtained for half of the antennas.

[0139] For example, if N=8 and M=4, the following polling method can be used:

[0140] When m=1, receive: signal data of antennas 1 and 8, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=1; or output cross-correlation signal strength (actual strength) corresponding to antenna i=8;

[0141] When m=2, receive: signal data of antennas 2 and 3, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=3; or output cross-correlation signal strength (actual strength) corresponding to antenna i=2;

[0142] When m=3, receive: signal data of antennas 4 and 5, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=5; or output cross-correlation signal strength (actual strength) corresponding to antenna i=4;

[0143] When m=4, receive: signal data of antennas 6 and 7, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=7; or output cross-correlation signal strength (actual strength) corresponding to antenna i=6;

[0144] Finally, the error between the four actual intensity values ​​and the theoretical value table is measured (eg, i=1, 3, 5, 7), and then positioning is performed to obtain the estimated signal direction.

[0145] In different embodiments, when N=8, M may also be other values ​​smaller than N, which will not be illustrated one by one here.

[0146] In different embodiments, the antenna numbers received in each polling are not necessarily the same as those in the above examples. The above examples are only for the convenience of description, and the antenna numbers received each time may also be non-adjacent. For example, when m=1, the antenna numbers received may also be (1, 3) or (1, 4), etc. In addition, when receiving signal data from antennas 1 and 8, the output may not necessarily be the cross-correlation signal strength corresponding to antenna i=1, but may also be the cross-correlation signal strength corresponding to antenna i=8. The following takes the above M=N=8 and N=8, M=4 as examples to describe the error metric weighting in detail.

[0147] For M=N=8,

[0148] w sum =|w 1，8 |+|w 1，2 |+|w 2，3 |+|w 3，4 |+|w 4，5 |+|w 5，6 |+|w 6，7 |+|w 7，8 |,

[0149]

[0150] For N=8, M=4, w sum =|w 1，2 |+|w 3，4 |+|w 5，6 |+|w 7，8 |,

[0151] (2) This example takes the case of receiving signal data from three antennas each time, that is, K = 3:

[0152] (2a) M = N = 9, the following polling method can be used:

[0153] When m=1, receive: signal data of antennas 1, 2, and 3, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=1;

[0154] When m=2, receive: signal data of antennas 2, 3, and 4, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=2;

[0155] When m=3, receive: received signals from antennas 3, 4, and 5, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=3;

[0156] When m=4, receive: received signals from antennas 4, 5, and 6, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=4;

[0157] When m=5, receive: received signals from antennas 5, 6, and 7, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=5;

[0158] When m=6, receive: received signals from antennas 6, 7, and 8, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=6;

[0159] When m=7, receive: received signals from antennas 7, 8, and 9, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=7;

[0160] When m=8, receive: received signals from antennas 8, 9, and 1, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=8;

[0161] When m=9, receive: received signals from antennas 9, 1, 2, output: cross-correlation signal strength (actual strength) corresponding to antenna i=9;

[0162] Finally, the nine actual intensity values ​​are compared with the theoretical value table for error measurement, and then positioning is performed to obtain the estimated signal direction.

[0163] (1b)M <N:

[0164] When the number of antennas is multiple times the number of antennas for each reception, each antenna can also be used to receive only once. For N antennas, N / 3 polling times are required, and N / 3 cross-correlation signal strengths will be obtained. In order to facilitate subsequent comparison, the N / 3 cross-correlation signal strengths can be combined into an N / 3×1 column vector. At this time, if each search azimuth angle of the corresponding theoretical set also corresponds to a column, the obtained theoretical value matrix is ​​an N / 3×L matrix, and each row in the N / 3×1 column vector of each polling corresponds to each row in the theoretical value matrix. Of course, the theoretical value matrix can also use the N×L matrix of all antennas, and the theoretical value of the corresponding antenna can be found when measuring the error.

[0165] For example, if N=9 and M=3, the following polling method can be used:

[0166] When m=1, receive: signal data of antennas 1, 2, and 3, and output: the cross-correlation signal strength (actual strength) corresponding to antenna i=1; or the cross-correlation signal strength corresponding to antenna i=2; or the cross-correlation signal strength corresponding to antenna n=3;

[0167] When m=2, receive: signal data of antennas 4, 5, and 6, and output: the cross-correlation signal strength (actual strength) corresponding to antenna i=4; or the cross-correlation signal strength corresponding to antenna n=5; or the cross-correlation signal strength corresponding to antenna n=6;

[0168] When m=3, receive: signal data of antennas 7, 8, and 9, and output: the cross-correlation signal strength (actual strength) corresponding to antenna i=7; or the cross-correlation signal strength corresponding to antenna i=8; or the cross-correlation signal strength corresponding to antenna n=9;

[0169] Finally, the three actual intensity values ​​are compared with the theoretical value table to perform error measurement (eg, i=1, 4, 7), and then positioning is performed to obtain the estimated signal direction.

[0170] In different embodiments, when N=9, M may also be other values ​​smaller than N, which will not be illustrated one by one here.

[0171] (3) This example takes the case of receiving signal data from four antennas each time, that is, K = 4:

[0172] (3a) M = N = 8:

[0173] When m=1, receive: signal data of antennas 8, 1, 2, 3, and output: cross-correlation signal strength (actual strength) corresponding to antenna i=1;

[0174] When m=2, receive: signal data of antennas 1, 2, 3, 4, output: cross-correlation signal strength (actual strength) corresponding to antenna i=2

[0175] When m = 3, receive the signal data of antennas 2, 3, 4, 5, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 3.

[0176] When m = 4, receive the received signals of antennas 3, 4, 5, 6, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 4;

[0177] When m = 5, receive the signal data of antennas 4, 5, 6, 7, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 5;

[0178] When m = 6, receive the signal data of antennas 5, 6, 7, 8, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 6;

[0179] When m = 7, receive the signal data of antennas 6, 7, 8, 1, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 7;

[0180] When m = 8, receive the signal data of antennas 7, 8, 1, 2, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 8;

[0181] Finally, measure the error between these eight actual strength values and the theoretical value table, and then perform positioning to obtain the estimated signal arrival direction.

[0182] (3b) M < N, for example: N = 8, M = 2:

[0183] When m = 1, receive the signal data of antennas 8, 1, 2, 3, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 1;

[0184] When m = 2, receive the signal data of antennas 4, 5, 6, 7, and output the cross-correlation signal strength (actual strength) corresponding to antenna i = 5;

[0185] Finally, measure the error between these two actual strength values and the theoretical value table (i = 1, 5), and then perform positioning to obtain the estimated signal arrival direction.

[0186] The above examples are only for better illustrating the present invention. In different embodiments, the number of antennas, the number of polling times, and the antenna numbers received each time of polling are not necessarily the same as those in the above examples.

[0187] Preferably, the antenna numbers corresponding to the received signals and the output signals each time of polling are preferably different as much as possible, so as to better reflect a certain difference, thereby improving the positioning accuracy.

[0188] In one embodiment, a drone direction finding device is also provided, and the antenna for receiving drone signal data includes multiple antennas, please refer to Figure 2 , the device comprises:

[0189] A signal receiving module 11, used for receiving signal data from at least two antennas each time;

[0190] The cross-correlation module 12 is used to process the signal data received each time, specifically, to: for the signal data of one antenna received this time, perform a cross-correlation operation on it with the signal data of the remaining antennas received this time, to obtain the cross-correlation signal strength;

[0191] An error measurement module 13 is used to perform error measurement between the cross-correlation signal strength and the theoretical value of the signal strength corresponding to the theoretical set; wherein the theoretical value of the signal strength corresponding to the cross-correlation signal strength in the theoretical set includes the theoretical values ​​of the signal strength of multiple search azimuths;

[0192] The arrival direction determination module 14 is used to search for a minimum error metric, and the corresponding search azimuth is the estimated signal arrival direction.

[0193] In one embodiment, a drone direction finding system is also provided, please refer to Figure 3 , which includes:

[0194] Multiple antennas 21, used to receive signal data from drones;

[0195] A multi-channel receiver 22, configured to receive signal data from at least two antennas at a time; each channel receives signal data from one antenna at a time;

[0196] A plurality of switches 23 are connected between the antenna and the receiver; they are used to control the receiving time of the multi-channel receiver and the antenna corresponding to each reception; the switches can be used to control the multiple channels of the multi-channel receiver to be turned on at the same time; in addition, the switches can be used to control which antenna's signal data the multi-channel receiver receives each time.

[0197] The signal processing device is used to process the signal data received each time, specifically including: for the signal data of one of the antennas received this time, cross-correlation operation is performed on it with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength; it is also used to measure the error between the cross-correlation signal strength and the corresponding signal strength theoretical value in the theoretical set; wherein the signal strength theoretical value corresponding to the cross-correlation signal strength in the theoretical set includes the signal strength theoretical values ​​of multiple search azimuth angles; it is also used to search for the minimum error measurement, and the corresponding search azimuth angle is the estimated signal arrival direction.

[0198] In one embodiment, the multi-channel receiver 22 may be a dual-channel receiver, that is, it receives signal data from two antennas each time.

[0199] In one embodiment, the number of antennas is a multiple of the number of channels of the receiver, and the switches correspond to the channels of the receiver one by one. Correspondingly, the switch is a multi-way switch, and each way of the switch corresponds to an antenna.

[0200] Please refer to Figure 3 , Figure 3 In the example, a dual-channel receiver is used, that is, the number of channels of the receiver is 2, namely R1 and R2, and the corresponding number of multi-way switches is also two, and the number of corresponding antennas is an even number, and the number of antennas corresponding to each multi-way switch is the same. Assuming that different antennas are represented by discontinuous numbers in the order of arrangement, the first multi-way switch T1 can be connected to the numbers with odd numbers, and the second multi-way switch T2 can be connected to the numbers with even numbers. That is, for the case of two multi-way switches, adjacent antennas are connected to different multi-way switches, and then connected to different receiver channels, and the receiver can choose to receive signal data from two adjacent antennas each time.

[0201] For example, if the number of antennas is four times the number of channels of the receiver, then the switch is a four-way switch, and each switch corresponds to four antennas. In one cycle T, the signals of two antennas can be received each time in the following polling order: Ant1 / Ant8, Ant1 / Ant2, Ant3 / Ant2, Ant3 / Ant4, Ant5 / Ant4, Ant5 / Ant6, Ant7 / Ant6, Ant7 / Ant8. The signal waveforms of the two multi-way switches T1 and T2 can be as follows: Figure 4 shown.

[0202] Of course, in different embodiments, the number of antennas may also be consistent with the number of channels of the receiver, in which case each switch only needs to correspond to one antenna.

[0203] In different embodiments, when the number of channels of the receiver is more than two, such as three, the number of switches is also three. In this case, the antennas can be classified into groups of three adjacent antennas, and the three antennas in each group are respectively connected to different multi-way switches. That is, assuming that the number of channels of the receiver is s, the antennas can be classified into groups of s adjacent antennas, and the s antennas in each group are respectively connected to different multi-way switches.

[0204] In different embodiments, the number of antennas may not be a multiple of the number of channels. Although it is more complicated to implement, it is also achievable. For example, for receiving signal data from two antennas each time, if the number of antennas is 5, three channels can be set, and two of the channels are used each time. The first channel corresponds to the first and third antennas, the second channel corresponds to the second and fourth antennas, and the third channel corresponds to the fifth antenna.

[0205] In one embodiment, multiple antennas are evenly distributed on a circle. Figure 5 , the figure takes an even number of antennas as an example.

[0206] In one embodiment, an electronic device is also provided, please refer to Figure 6 . At the hardware level, the device includes a processor 31, an internal bus 32, a network interface 33, a memory 34 and a storage 35, and of course may also include hardware required for other services. One or more embodiments of the present invention can be implemented based on software, such as the processor 31 reading the corresponding computer program from the storage 35 into the memory 34 and then running it. Of course, in addition to the software implementation, one or more embodiments of the present invention do not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0207] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer, which may be in the form of a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver, a game console, a tablet computer, a wearable device or a combination of any of these devices.

[0208] In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0209] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0210] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0211] The above describes specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0212] In the description of this specification, the description with reference to the terms "an implementation", "an example", "a specific implementation process", "an example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0213] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for direction finding of an unmanned aerial vehicle, characterized in that: There are multiple antennas for receiving drone signal data, and the method includes: receiving signal data from at least two of the antennas each time; Processing the signal data received each time specifically includes: performing a cross-correlation operation on the signal data of one of the antennas received this time with the signal data of the remaining antennas received this time to obtain a cross-correlation signal strength; Perform error measurement on the cross-correlation signal strength and the corresponding theoretical value of signal strength in the theoretical set; wherein the theoretical value of signal strength corresponding to the cross-correlation signal strength in the theoretical set includes theoretical values ​​of signal strength at multiple search azimuth angles; The search is performed so that the error metric is minimized, and the corresponding search azimuth is the estimated signal arrival direction.

2. The drone direction finding method according to claim 1, characterized in that: The cross-correlation operation is performed on the signal data of one of the antennas received this time with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength, specifically including: For the signal data of the i-th antenna received this time, a cross-correlation operation is performed on it and the signal data of the j-th antenna received this time to obtain the cross-correlation signal strength of the i-th antenna, which is expressed as: Among them, θ represents the direction of the signal wave, m represents the mth received signal data, represents the signal data of the i-th antenna, represents the signal data of the jth antenna, (·) * represents the conjugate of the signal, Δt represents the time delay of the signal data received from the jth antenna relative to the signal data received from the ith antenna, and 2πf c Δt represents the phase deviation between the signal data received from the two antennas, f c is the frequency at which the signal data resides.

3. The drone direction finding method according to claim 1, characterized in that: When the number of antennas received each time includes more than two, the signal data of one of the antennas received this time is cross-correlated with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength, specifically including: For the signal data of one of the antennas received this time, cross-correlation operation is performed on it and the signal data of each of the remaining antennas received this time to obtain multiple cross-correlation signal strengths; An average value of a plurality of the cross-correlation signal strengths is calculated.

4. The drone direction finding method according to claim 1, characterized in that: The number of antennas is greater than the number of antennas for each reception; The receiving signal data of at least two antennas each time specifically includes: In a period T, the antennas are polled in a time-sharing manner, and signal data from at least two antennas are received each time.

5. The drone direction finding method according to claim 4, characterized in that: The error measurement of the cross-correlation signal strength and the theoretical value of the signal strength corresponding to the theoretical set specifically includes: The error measurement is performed between the cross-correlation signal strength obtained from all polling within a period T and the theoretical value of the corresponding signal strength in the theoretical set; The error metrics obtained from all polls are summed.

6. The drone direction finding method according to claim 5, characterized in that: All obtained error metrics are added together, specifically: The error metrics obtained from all polls are weighted and added, expressed as: in, represents the weight coefficient of the mth poll, J represents the total number of polls, and w m is the absolute value of the cross-correlation signal strength obtained in the mth polling, w sum It is the sum of the absolute values ​​of the cross-correlation signal strengths obtained from all pollings, and Err(m) represents the error metric of the mth polling.

7. The drone direction finding method according to any one of claims 1 to 6, characterized in that: The error measure between the cross-correlation signal strength and the corresponding theoretical value of the signal strength in the theoretical set is the Euclidean distance between the two.

8. A drone direction finding device, characterized in that: There are multiple antennas for receiving drone signal data, and the device includes: A signal receiving module, used for receiving signal data from at least two antennas each time; The cross-correlation module is used to process the signal data received each time, specifically to: for the signal data of one of the antennas received this time, perform a cross-correlation operation on it with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength; An error measurement module is used to perform error measurement on the cross-correlation signal strength and the corresponding signal strength theoretical value in a theoretical set; wherein the signal strength theoretical value in the theoretical set corresponding to the cross-correlation signal strength includes the signal strength theoretical values ​​of multiple search azimuth angles; The arrival direction determination module is used to search so that the error metric is minimized, and the corresponding search azimuth is the estimated signal arrival direction.

9. A UAV direction finding system, characterized in that: include: Multiple antennas for receiving signal data from drones; A multi-channel receiver for receiving signal data from at least two antennas at a time; Each channel receives signal data from one antenna at a time; a plurality of switches connected between the antenna and the receiver; Used to control the receiving time of the multi-channel receiver and the antenna corresponding to each reception; The signal processing device is used to process the signal data received each time, specifically: for the signal data of one of the antennas received this time, it is cross-correlated with the signal data of the remaining antennas received this time to obtain the cross-correlation signal strength; it is also used to measure the error between the cross-correlation signal strength and the corresponding signal strength theoretical value in a theoretical set; wherein the signal strength theoretical value corresponding to the cross-correlation signal strength in the theoretical set includes the signal strength theoretical values ​​of multiple search azimuth angles; it is also used to search for a method that minimizes the error measurement, and the corresponding search azimuth angle is the estimated signal arrival direction.

10. The UAV direction finding system according to claim 9, characterized in that: The number of the antennas is a multiple of the number of channels of the receiver; The switches correspond one to one to the channels of the receiver; The switch is a multi-way switch, and each way of the switch corresponds to one of the antennas.

11. The drone direction finding method according to claim 8 or 9, characterized in that: The multiple antennas are evenly distributed on a circle.

12. An electronic device, characterized in that: include: processor; and, a memory for storing processor-executable instructions; The processor implements the steps in the method of any one of claims 1 to 7 by running the executable instructions.

13. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

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