A broadband navigation interference suppression method for UAV cluster equivalent array

Abstract

The present invention provides a broadband navigation interference suppression method for an equivalent array of a drone cluster, wherein the method includes: receiving the initial navigation signals of each of the second drones and its own initial navigation signal through the first drone to form an initial navigation signal data set, analyzing the influence of array element spacing, drone clock error, and crystal oscillator offset on array signal processing, and introducing a time domain filter for processing on the basis of spatial domain processing. The beneficial effects of the present invention: focusing on analyzing the influence of array element spacing, drone clock error, and crystal oscillator offset on array signal processing, modeling the above three factors as fixed and linearly growing delay deviation terms, introducing a time domain filter on the basis of spatial domain processing, and compensating for the delay through space-time adaptive processing, thereby achieving interference suppression of the drone cluster on the navigation signal and improving the accuracy of drone cluster positioning.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicles (UAVs), and in particular to a method for suppressing broadband navigation interference of an equivalent array of a UAV cluster. Background Art

[0002] With the development of space-air-ground interconnection and drone technology, unmanned system clusters have become an important direction for the development of unmanned systems in the world and are widely used in various fields such as military and civilian. One of the prerequisites for the successful execution of tasks by drone clusters is the accurate knowledge of their absolute position. At present, satellite navigation is still the core information source for their absolute positioning. However, due to the very weak satellite navigation signals, GNSS receivers are easily affected by radio frequency interference (RFI), which reduces the positioning accuracy or even makes it impossible to obtain positioning information, especially broadband Gaussian noise interference, which is not sparse in the time and frequency domains and cannot be suppressed by time and frequency anti-interference means. Summary of the invention

[0003] The main purpose of the present invention is to provide a broadband navigation interference suppression method for an equivalent array of a drone cluster, aiming to solve the problem that the existing drone equipment does not have sparseness in the time and frequency domains and cannot be suppressed by time and frequency anti-interference means.

[0004] The present invention provides a broadband navigation interference suppression method for an equivalent array of a drone cluster, which is implemented by a drone cluster. The drone cluster includes a first drone and multiple second drones. The first drone and each of the second drones are provided with an array element and a time domain filter. The output channel of the array element is connected in series with the time domain filter. The drone cluster is connected for communication through each array element. Each of the second drones transmits a received navigation signal to the first drone for processing through the array element. The broadband navigation interference suppression method for an equivalent array of a drone cluster is applied to the first drone, and includes:

[0005] receiving, by the first drone, initial navigation signals of each of the second drones and its own initial navigation signal to form an initial navigation signal data set;

[0006] Obtaining the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element, and calculating the delay deviation according to the array element spacing between the first UAV and each of the second UAVs, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set, to obtain the delay deviation of each UAV in the UAV cluster;

[0007] The adjustment parameters of the time domain filters corresponding to the respective UAVs are obtained according to the time delay deviations of the respective UAVs, and the corresponding time domain filters are adjusted according to the respective adjustment parameters.

[0008] Furthermore, the drone cluster is any one of a uniform rectangular array, a 4-element central circle array, a 7-element central circle array, and a distributed array.

[0009] Furthermore, the first drone is a central drone; wherein the central drone is a drone having the smallest sum of distances to each drone in the drone cluster.

[0010] Furthermore, the array element spacing between any two drones in the drone cluster is greater than half the wavelength of the carrier.

[0011] Further, the step of obtaining the array element spacing between the first drone and each of the second drones, as well as the clock error and sampling rate deviation of each array element, and calculating the delay deviation according to the array element spacing between the first drone and each of the second drones, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set to obtain the delay deviation of each drone in the drone cluster includes:

[0012] Obtaining the spacing between the array elements of the first UAV and the array elements of each of the second UAVs, as well as the clock error and sampling rate deviation of each array element;

[0013] According to the formula Calculate the first delay deviation and obtain the second delay deviation based on the clock difference , according to the formula Calculate the third delay deviation; where, , , They represent the first delay deviation, the second delay deviation, and the third delay deviation of the nth UAV in the UAV cluster, respectively. , represents transpose, is the elevation angle of the incident signal, is the azimuth of the incident signal, c is the speed of light, is the array element spacing d n The maximum delay value under represents the array element spacing between the nth UAV and the first UAV, represents the position coordinates of the nth drone, represents the sampling rate deviation between the nth UAV and the first UAV, k represents the sampling point index, represents the actual sampling rate of the first drone, represents the actual sampling rate of the nth UAV;

[0014] According to the formula Get the delay deviation of each drone in the drone cluster.

[0015] Furthermore, the time delay of the time domain taps in the time domain filter is greater than the time delay of the signal between the array elements.

[0016] The present invention also provides a drone cluster, the drone cluster includes a first drone and a plurality of second drones, the first drone and each of the second drones are provided with an array element and a time domain filter, the output channel of the array element is connected in series with the time domain filter, the drone cluster is connected for communication through each array element, each of the second drones transmits a received navigation signal to the first drone for processing through the array element, and the first drone includes:

[0017] a receiving module, configured to receive, through the first drone, initial navigation signals of each of the second drones and its own initial navigation signal to form an initial navigation signal data set;

[0018] An acquisition module, used to acquire the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element, and calculate the delay deviation according to the array element spacing between the first UAV and each of the second UAVs, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set, to obtain the delay deviation of each UAV in the UAV cluster;

[0019] The adjustment module is used to obtain the adjustment parameters of the time domain filter corresponding to each drone according to the delay deviation of each drone, and adjust the corresponding time domain filter according to each adjustment parameter.

[0020] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0021] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described above are implemented.

[0022] The beneficial effects of the present invention are as follows: the influence of array element spacing, UAV clock error, and crystal oscillator offset on array signal processing is analyzed in detail, the above three factors are modeled as fixed and linearly growing delay deviation terms, a time domain filter is introduced on the basis of spatial domain processing, and the delay is compensated through space-time adaptive processing, thereby realizing the interference suppression of the UAV cluster to the navigation signal and improving the accuracy of UAV cluster positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1It is a flow chart of a method for suppressing broadband navigation interference of a drone cluster equivalent array according to an embodiment of the present invention;

[0024] Figure 2 is a schematic block diagram of the structure of a first drone according to an embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of an array element arrangement and incident signal of a drone according to an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the effect of a sampling rate deviation on signal delay according to an embodiment of the present invention;

[0027] Figure 5 is a schematic diagram of the power of a central channel tap relative to the power of other taps according to an embodiment of the present invention;

[0028] Figure 6 A schematic block diagram of the structure of a computer device according to an embodiment of the present application.

[0029] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0030] 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.

[0031] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there may be three relationships. For example, A and B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone.

[0032] In addition, in the present invention, descriptions such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their 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 at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0033] Reference Figure 1The present invention proposes a broadband navigation interference suppression method for an equivalent array of a drone cluster, which is implemented by a drone cluster. The drone cluster includes a first drone and multiple second drones. The first drone and each of the second drones are provided with an array element and a time domain filter. The output channel of the array element is connected in series with the time domain filter. The drone cluster is connected for communication through each array element. Each of the second drones transmits a received navigation signal to the first drone for processing through the array element. The broadband navigation interference suppression method for an equivalent array of a drone cluster is applied to the first drone, and includes:

[0034] S1: receiving, through the first drone, initial navigation signals of each of the second drones and its own initial navigation signal to form an initial navigation signal data set;

[0035] S2: Obtain the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element, and calculate the delay deviation according to the array element spacing between the first UAV and each of the second UAVs, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set to obtain the delay deviation of each UAV in the UAV cluster;

[0036] S3: Acquire adjustment parameters of the time domain filters corresponding to the respective UAVs according to the time delay deviations of the respective UAVs, and adjust the corresponding time domain filters according to the respective adjustment parameters.

[0037] As described in step S1 above, the first drone receives the initial navigation signals of each of the second drones and its own initial navigation signals to form an initial navigation signal data set. In the present application, the drones in the drone cluster are all small drones. For small drone clusters, most of them are composed of small fixed-wing or rotary-wing drones, with limited space resources and load capacity. The installation of conventional antenna arrays requires increasing the size of the drone, which undoubtedly increases the cost and reduces the concealment. Therefore, array elements can be set on each drone, and the navigation signals can be concentrated on the first drone for processing through the array elements.

[0038] As described in the above step S2, the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element are obtained, and the delay deviation is calculated based on the array element spacing between the first UAV and each of the second UAVs, the clock error of each array element, the sampling rate deviation and the initial navigation signal data set to obtain the delay deviation of each UAV in the UAV cluster. Since, firstly, there will be a fixed clock error between different array element nodes; secondly, the difference in crystal oscillator accuracy causes the sampling rate of different array element signals to deviate, therefore, the deviation affected by each factor can be calculated separately and summed to obtain the total delay deviation.

[0039] As described in step S3 above, the adjustment parameters of the time domain filters corresponding to each drone are obtained according to the delay deviation of each drone, and the corresponding time domain filters are adjusted according to each adjustment parameter. After obtaining the corresponding deviation, the delay deviation can be eliminated by the time domain filter. The specific setting method is not limited here, and can be achieved by setting the number of time domain taps in the time domain filter and the corresponding processing weights.

[0040] In one embodiment, the drone cluster is any one of a uniform rectangular array, a 4-element central circle array, a 7-element central circle array, and a distributed array. In the navigation field, the drones can be arranged in the above manner, and the drone cluster can be better navigated. Preferably, a distributed array can reduce the distance between the first drone and each second drone. Compared with a sparse array, the spacing of all array elements in this distributed array is greater than the half wavelength of the carrier, which will lead to the ambiguity of the array manifold, that is, the array calculates multiple DOA values ​​when estimating the direction of a single event signal, which reduces the effectiveness of the beamforming algorithm; since each drone has an independent clock crystal, the clock crystal can drive a local analog-to-digital converter (ADC). Therefore, there are two problems with the data stream from each drone node: one is the clock error problem, that is, there is a fixed deviation between the clocks of different drones; the other is the sampling rate deviation problem, that is, each drone node has a slightly different sampling rate for the signal. This will also reduce the correlation of the signal and reduce the interference suppression performance.

[0041] In one embodiment, the first drone is a central drone; wherein the central drone is a drone in the drone cluster with the smallest sum of distances to each drone. Setting the first drone as the central drone can reduce the error caused by array element spacing and signal transmission, so it is preferred to set the first drone as the central drone.

[0042] In one embodiment, the array element spacing between any two drones in the drone cluster is greater than half the carrier wavelength. Compared with traditional arrays, the array element spacing of this array design is much larger than half the carrier wavelength, which means that the correlation between the incident signal received by the antenna element and the actual signal will be reduced, so a single incident signal will cause multiple (rather than a single) eigenvalues ​​in the covariance matrix estimate between the antenna signals. Currently, for interference mitigation, an interference source may consume multiple degrees of freedom, not just one; therefore, the total amount of interference that can be suppressed will be reduced.

[0043] In one embodiment, the step S2 of obtaining the array element spacing between the first drone and each of the second drones, as well as the clock error and sampling rate deviation of each array element, and calculating the delay deviation according to the array element spacing between the first drone and each of the second drones, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set to obtain the delay deviation of each drone in the drone cluster includes:

[0044] S201: Obtaining the distance between the array element of the first UAV and the array element of each of the second UAVs, as well as the clock error and sampling rate deviation of each array element;

[0045] S202: According to the formula Calculate the first delay deviation and obtain the second delay deviation based on the clock difference , according to the formula Calculate the third delay deviation; where, , , They represent the first delay deviation, the second delay deviation, and the third delay deviation of the nth UAV in the UAV cluster, respectively. , represents transpose, is the elevation angle of the incident signal, is the azimuth of the incident signal, c is the speed of light, is the array element spacing d n The maximum delay value under represents the array element spacing between the nth UAV and the first UAV, represents the position coordinates of the nth drone, represents the sampling rate deviation between the nth UAV and the first UAV, k represents the sampling point index, represents the actual sampling rate of the first drone, represents the actual sampling rate of the nth UAV;

[0046] S203: According to the formula Get the delay deviation of each drone in the drone cluster.

[0047] In one embodiment, the time delay of the time domain taps in the time domain filter is greater than the time delay of the signal between array elements.

[0048] In a specific embodiment, assume a distributed planar array consisting of N antenna elements, such as Figure 3 As shown. The signal emitted by the signal source Ri located in the far field of the transmission hits the ideal isotropic antenna array element 1 located at the origin in the form of a plane wave. The analytical signal ri(t) is expressed as:

[0049] (1)

[0050] Complex signal Baseband signal The signal is modulated onto a carrier signal defined by the receive carrier frequency defined by formula (2):

[0051] (2)

[0052] The received signal frequency contains the transmitting frequency and the Doppler shift due to relative motion The position of any array element on the xy plane is recorded as , please note that in the following equations, the lowercase bold parameters represent vectors and the uppercase bold parameters represent matrices. The signal received from array element n can be expressed in the form of formula (3):

[0053] (3)

[0054] It differs from the signal received by the origin reference array element by a time delay related to the array element position and the direction of signal incidence. , a time delay caused by different clock sources , an additive Doppler , and the overall differences in amplitude and phase due to differences in the receiving components of each drone The influence of different clock sources on time delay is reflected in two aspects: first, there will be a fixed clock difference between different array element nodes; second, the difference in crystal oscillator accuracy causes deviations in the sampling rates of different array element signals. The following analyzes the influence of array element spacing and different clock sources on array element signal time delay one by one.

[0055] It can be calculated by formula (4):

[0056] (4)

[0057] in, is the unit propagation vector of the plane wave, represents transpose, is the elevation angle of the incident signal, is the azimuth of the incident signal, and c is the speed of light. is the maximum delay value under the array element spacing dn. It can be seen that It only depends on the array element spacing and the incident angle of the signal. It is worth noting that in a distributed array, since the array element spacing is much larger than half a wavelength, the narrowband assumption of the received signal no longer holds.

[0058] Each drone has an independent clock, so there will be a fixed clock difference between different array element nodes, which is recorded as The clock error term depends on the satellite timing accuracy and the receiver crystal oscillator accuracy. The timing accuracy of Beidou's B3I signal can reach ns, so under the condition of being able to receive satellite signals, the clock delay difference between the two receivers is ; After losing the satellite signal, timekeeping mainly depends on the local crystal oscillator.

[0059] Conventional arrays use only one crystal oscillator to sample signals, but in the distributed array designed by the present invention, since the frequency of the crystal oscillator clock signal in each node always has a certain tolerance with the nominal frequency, the sampling rate deviation between two network nodes is inevitable. Depending on the crystal oscillator device, the sampling rate mismatch may range from 0.1ppm (parts per million, 10-6) to tens of ppm. The sampling rate deviation will add a large delay deviation between the network node signals after a long sampling time, which is recorded as ,The effect of sampling rate deviation on delay is deduced in detail below.

[0060] Assume that the nominal sampling rate of each node in the distributed array is f s The actual sampling rates of the i-th and j-th array element nodes are defined as and ,in,

[0061] (5)

[0062] is the sampling rate deviation between the two nodes, which is determined by the crystal oscillator accuracy. When receiving the signal, the analog signal received by the two nodes and After digital sampling, the and They are:

[0063] (6)

[0064] (7)

[0065] in, and represent continuous and discrete signals respectively. From equations (6) and (7), we can see that due to the influence of sampling rate deviation, the same sampling point index k is actually and The two nodes correspond to different time points, and as the sampling time increases, the deviation will gradually increase. When two nodes receive signals from the same signal source incident from the far field, then:

[0066] (8)

[0067] (9)

[0068] in, Continuous delay The corresponding sampling delay. is the deviation constant. Without loss of generality, let node 1 be the reference node and the sampling rate .but The maximum value of is:

[0069] (10)

[0070] Assumptions Within, the receiver sampling rate The receiver crystal oscillator accuracy is ±10ppm. , the maximum deviation constant can reach

[0071] (11)

[0072] Much smaller than the signal sampling interval , so the deviation constant can be ignored, and equation (9) can be approximated as:

[0073] (12)

[0074] It can be seen that the sampling rate mismatch causes the signal of the nth array element to increase the partial delay difference term that grows linearly with time relative to the reference array element signal, and its expression is:

[0075] (13)

[0076] Take the sampling time as 1s and the crystal oscillator accuracy as 10ppm as an example. The changing trend of Figure 4 shown.

[0077] pass Figure 4It can be seen that the sampling rate deviation will cause a linear increase in the signal delay between array elements. The final delay of 1s of sampling data will increase by 10 microseconds, which is equivalent to the corresponding signal under the same sampling index being offset by more than 200 sampling points.

[0078] Combined with the above analysis, the expression of the overall received signal of the antenna array is given:

[0079] (14)

[0080] in represents the Hadamard product, , the present invention makes the following assumptions for the above formula:

[0081] There is no relative motion between the array elements;

[0082] Each array element is an ideal omnidirectional array element, and there is no amplitude or phase difference between the array elements;

[0083] There is no bandwidth limitation for communication between drones.

[0084] From the above analysis, it can be seen that the influence of array element spacing, signal incident angle and clock delay difference on the signal is equivalent to changing the signal delay between different array elements. Therefore, for the convenience of analysis, the influence of array element spacing, signal incident angle and clock delay difference on signal delay is regarded as a whole and recorded as , whose expression is:

[0085] (15)

[0086] Combined with the assumptions made, formula (14) can be finally simplified as:

[0087] (16)

[0088] At this time, the receiving signal frequency of each array element is the same. .

[0089] Considering the interference scenario with L satellite signals and P interference signals j(t), the received signal vector of the N-element distributed array can be expressed as:

[0090] (17)

[0091] Where n(t) is a vector of zero-mean Gaussian white noise with variance . is broadband Gaussian noise interference, and its baseband form is . is the lth satellite signal received by the array, and its form is given by equation (7). Its baseband form is The expression is:

[0092] (18)

[0093] To receive satellite signal power, is a pseudo-random code, The influence of the time delay of the distributed array on the signal correlation and array signal processing is further analyzed.

[0094] By at time t=kT s To sample a continuous signal, where k is an integer, is the sampling interval, f s is the sampling rate of the reference array element, and the signal is expressed as , , For any digitized signal received at each antenna element, the discrete expression corresponding to equation (16) can be determined by equation (19):

[0095] (19)

[0096] in this case, Including the influence of steering vector and clock delay on signal phase, is the sampling delay between digitized baseband signals, which is composed of the second-order delay shown in equation (15) and the sampling rate of the reference array element:

[0097] (20)

[0098] The sampling delay is usually not an integer number of sampling points. Therefore, the proposed ideal impulse response is introduced to express the fractional sample delay. Equation (19) can be expressed as shown in Equation (21):

[0099] (twenty one)

[0100] in

[0101] (twenty two)

[0102] is the corresponding ideal impulse response.

[0103] In order to simplify the analysis, the present invention takes a distributed linear array composed of two array elements as an example to analyze how the sampling delay of the signal between the array elements affects the signal correlation. Figure 5 Shows different delay differences The sampling rate commonly used for Beidou B3I signals is selected: 21MHz. Combined with the analysis of delay in the previous section, the delay difference is set to .

[0104] The larger the clock delay, the lower the absolute value of the central channel tap and the relatively increased absolute value of the adjacent signal taps; this means that the signal power at the current sample k at the first antenna element will spread to the adjacent samples at the second antenna, resulting in a significant reduction in the cross-correlation between the received antenna signals.

[0105] In order to explain this effect more intuitively, the center tap is introduced The difference between the power of the tap and the cumulative power of all other taps, Pcb, is expressed as:

[0106] (twenty three)

[0107] The results are as follows: Figure 5 As shown, it can be seen that for lower total delays, Pcb is approximately 1, so that most of the power in sample k received on the first antenna is in the same sample when received on the second antenna; as the delay increases, Pcb gradually approaches -1, and the higher the sampling rate of the signal, the greater the change, which means that the power of the central sample is almost completely transferred to other samples, and the signal correlation between arrays is reduced. The only way to recover this power loss is through space-time anti-interference method STAP.

[0108] The difference between the distributed array structure and the conventional sparse array is that it does not contain sub-arrays, that is, the spacing between all array elements is greater than half a wavelength, which makes the array ambiguous in beamforming and doa estimation. Therefore, the present invention considers the formation of blind nulls for interference, selects the classic power inversion criterion, and forms nulls only in the interference direction. It does not require strict calibration, nor does it require the direction of arrival (DOA) information of the satellite signal, and has few implementation restrictions.

[0109] Space-time anti-interference processing is equivalent to adding a time domain filter to each array element channel. The time delay between antenna signals can be compensated through time domain taps. The tap spacing in the STAP processor is the delay between the signal components, usually 1 sampling point. The signal of the nth array element at the mth tap is:

[0110] (twenty four)

[0111] Where M is the number of time domain taps, usually an odd number, The vector representation of the signal received by the nth UAV, represents the antenna signal received by the mth tap. When M=1, it is pure spatial domain processing. Assume that the complex weight at the mth tap of the nth element is is the steady-state weight. Then the input signal is multiplied and added with its corresponding weight to obtain the STAP output y[k], that is:

[0112] (25)

[0113] (26)

[0114] (27)

[0115] x、 is the vector representation of the data, Represents the transposition operation, and the subscript PI represents that the calculation criterion of the weight is the space-time PI criterion. The space-time PI criterion uses a certain time domain tap output of a certain array element as the reference signal to ensure that the weighting coefficient of the output power of this signal is constant, and adjusts the array values ​​of other channels to minimize the power of the array output signal. Taking the mth time domain tap of the nth array element as the reference array element as an example, its optimization goal can be expressed as:

[0116] (28)

[0117] In the formula, It is an NM-dimensional column vector whose elements are all 0 except the n*mth element which is 1. Its expression is:

[0118] (29)

[0119] By solving the above formula, we can get the optimal weight vector expression under the PI criterion:

[0120] (30)

[0121] in, is a complex constant that normalizes the array weight vector; The space-time covariance matrix of the NM*NM input data vector, representing the correlation between all taps and elements, is defined as:

[0122] (31)

[0123] In the above equation, represents the expected value operator, Represents the conjugate transpose operation

[0124] The output power of the STAP processor is:

[0125] (32)

[0126] Since the signal, interference and noise are unrelated, and the signal power is much smaller than the noise and interference power, when considering the case where there is only one satellite signal and one interference, It can be expressed as:

[0127] (33)

[0128] Where R s is the expected signal covariance matrix, R J is the interference signal covariance matrix, is the noise signal covariance matrix, is a unit matrix of NM×NM. For each signal component, the covariance matrix can be organized into N2 sub-matrices of size M×M. Taking the interference signal as an example, its covariance matrix expression is shown in (34)

[0129] (34)

[0130] In this arrangement, the submatrices represents the correlation between array element p and array element q. In (34), the elements of the submatrix can be expressed as:

[0131] (35)

[0132] Where i is the i-th time domain tap of the p-th array element, and j is the j-th time domain tap of the q-th array element. The submatrix can be expressed as the inverse Fourier transform of the product of the power spectral density (PSD) of array elements p and q and the frequency domain antenna response.

[0133] (36)

[0134] In the above formula, is the clock delay difference between array elements p and q, is the power spectral density function of the signal. For a broadband Gaussian noise signal, its power spectral density function expression is:

[0135] (37)

[0136] is the pth array element in the direction The response to receiving a signal of frequency f, is the azimuth, is the elevation angle. The response pattern of an element in an ideal array is calculated using the following equation. For an element at coordinates (xn,yn,zn), the element pattern is given by:

[0137] (38)

[0138] in, is the radiation pattern of the element at the origin, The expression is:

[0139] (39)

[0140] In the above, it is assumed that the antenna is an ideal omnidirectional antenna, so it can be considered that The value of is always 1, and formula (36) can be simplified as:

[0141] (40) Through equations (36) to (40), the covariance matrix of each signal component received by the array can be theoretically generated, thereby obtaining the weights of space-time adaptive processing and finally obtaining the theoretical formula of the output signal power. Since matrix operations involve matrix inversion, it is difficult to solve the analytical expression. Therefore, the following uses the theoretical values ​​generated by the data stream and the simulation values ​​corresponding to the signal stream for analysis, mainly analyzing the impact of the change in the number of time domain taps on the broadband Gaussian interference suppression performance.

[0142] The anti-interference performance is measured by the interference suppression ratio and the output signal to noise ratio. The interference suppression ratio is defined as the ratio of the interference power received by a single element of the antenna array to the interference power output by the array. In actual calculations, the ratio of the input interference power to the total output signal power is generally used, and its expression is as follows:

[0143] (41)

[0144] The output signal-to-interference-noise ratio is the ratio of the output satellite signal power to the interference plus noise power, and its expression is as follows:

[0145] (42)

[0146] The simulation parameters are set as follows: the array is set to a two-element linear array, the satellite signal is a B3I BPSK signal, the bandwidth is 20.46MHz, the sampling rate is set to 21MHz, and the array element spacing is set to 3m. The total delay difference of the array element signal is set from 0 to 600ns, the input interference signal is broadband Gaussian noise interference, the bandwidth is 20MHz, the interference incident angle is 30°, the interference-to-noise ratio is 40dB, the signal-to-noise ratio is -20dB, and the corresponding interference-to-signal ratio is about 60dB. M represents the number of time domain taps. When M=1, that is, pure spatial domain processing, the interference suppression ratio and signal-to-noise ratio obtained are attenuated by more than 25dB when the delay is 10ns. This shows that the pure spatial domain processing method is very sensitive to time delay, has limited ability in distributed array anti-interference processing, and cannot suppress broadband interference.

[0147] When M is greater than 1, assuming that the signal-to-interference-noise ratio attenuation of 10 dB is the threshold for the receiver to resist interference, the relationship between the maximum delay that the space-time anti-interference processing can tolerate and the number of time domain taps M is as follows:

[0148] (43)

[0149] Table 1

[0150]

[0151] As described in Table 1 above, this shows that increasing the number of time domain taps can improve the delay compensation capability and allow a larger delay difference between array element signals, but this also means a significant increase in the amount of calculation.

[0152] In view of the problem of navigation broadband interference faced by small and micro drone clusters, the present invention proposes a distributed array construction method that is different from the traditional array. The drones in the cluster are regarded as array elements of the array antenna, and the central node processes the signals transmitted by each array element. Due to the large distance between drones and the different clock sources, there is a large delay deviation between the signals of the nodes. Therefore, the present invention focuses on analyzing the influence of the array element spacing, the clock error of the drone clock, and the crystal oscillator offset on the array signal processing, and models the above three factors as fixed and linearly growing delay deviation terms. First, the influence of the delay deviation on the correlation between signals is analyzed. The large delay deviation causes the power of the central sample to be almost completely transferred to other samples, resulting in a decrease in the correlation between the array signals or even no correlation at all. Therefore, it is necessary to introduce a time domain filter on the basis of spatial domain processing, and compensate for the delay through space-time adaptive processing. Then, the influence of the delay on the space-time anti-interference performance is further analyzed. The influence of the change in the number of time domain taps on the broadband Gaussian interference suppression performance under different delays is analyzed from both theoretical and signal flow simulation aspects. Finally, it is concluded that in order to effectively suppress broadband Gaussian interference, the delay of the time domain tap must be greater than the delay of the signal between the array elements.

[0153] The present invention also provides a drone cluster, the drone cluster includes a first drone and a plurality of second drones, the first drone and each of the second drones are provided with an array element and a time domain filter, the output channel of the array element is connected in series with the time domain filter, the drone cluster is connected for communication through each array element, each of the second drones transmits a received navigation signal to the first drone for processing through the array element, and the first drone includes:

[0154] a receiving module, configured to receive, through the first drone, initial navigation signals of each of the second drones and its own initial navigation signal to form an initial navigation signal data set;

[0155] An acquisition module, used to acquire the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element, and calculate the delay deviation according to the array element spacing between the first UAV and each of the second UAVs, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set, to obtain the delay deviation of each UAV in the UAV cluster;

[0156] The adjustment module is used to obtain the adjustment parameters of the time domain filter corresponding to each drone according to the delay deviation of each drone, and adjust the corresponding time domain filter according to each adjustment parameter.

[0157] The limitations and functions of each module of the first UAV in the present invention correspond to the broadband navigation interference suppression method of the above-mentioned UAV cluster equivalent array, and will not be repeated here.

[0158] Reference Figure 6 In the embodiment of the present application, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store various navigation signals, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the broadband navigation interference suppression method of the drone cluster equivalent array described in any of the above embodiments can be implemented.

[0159] Those skilled in the art will understand that Figure 6 The structure shown in is merely a block diagram of a portion of the structure related to the present application solution and does not constitute a limitation on the computer device to which the present application solution is applied.

[0160] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the broadband navigation interference suppression method for the drone cluster equivalent array described in any of the above embodiments can be implemented.

[0161] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0162] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, device, article or method including the element.

[0163] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of the claims of the present invention.

Claims

1. A broadband navigation interference suppression method for an equivalent array of a drone cluster, characterized in that: The method is implemented by a drone cluster, wherein the drone cluster includes a first drone and multiple second drones, the first drone and each of the second drones are provided with an array element and a time domain filter, the output channel of the array element is connected in series with the time domain filter, the drone cluster is communicated through the respective array elements, each of the second drones transmits the received navigation signal to the first drone for processing through the array element, and the broadband navigation interference suppression method of the drone cluster equivalent array is applied to the first drone, comprising: receiving, by the first drone, initial navigation signals of each of the second drones and its own initial navigation signal to form an initial navigation signal data set; Obtaining the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element, and calculating the delay deviation according to the array element spacing between the first UAV and each of the second UAVs, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set, to obtain the delay deviation of each UAV in the UAV cluster; The adjustment parameters of the time domain filters corresponding to the respective UAVs are obtained according to the time delay deviations of the respective UAVs, and the corresponding time domain filters are adjusted according to the respective adjustment parameters.

2. The broadband navigation interference suppression method of the UAV cluster equivalent array according to claim 1, characterized in that: The drone cluster is any one of a uniform rectangular array, a 4-element central circle array, a 7-element central circle array, and a distributed array.

3. The broadband navigation interference suppression method of the drone cluster equivalent array according to claim 1 is characterized in that: The first drone is a central drone; wherein the central drone is a drone having the smallest sum of distances to each drone in the drone cluster.

4. The broadband navigation interference suppression method of the UAV cluster equivalent array according to claim 1, characterized in that: The array element spacing between any two drones in the drone cluster is greater than half the wavelength of the carrier.

5. The broadband navigation interference suppression method of the drone cluster equivalent array according to claim 1, characterized in that: The step of obtaining the array element spacing between the first UAV and each of the second UAVs, as well as the clock error and sampling rate deviation of each array element, and calculating the delay deviation according to the array element spacing between the first UAV and each of the second UAVs, the clock error, the sampling rate deviation of each array element and the initial navigation signal data set to obtain the delay deviation of each UAV in the UAV cluster includes: Obtaining the spacing between the array elements of the first UAV and the array elements of each of the second UAVs, as well as the clock error and sampling rate deviation of each array element; According to the formula Calculate the first delay deviation and obtain the second delay deviation based on the clock difference , according to the formula Calculate the third delay deviation; where, , , They represent the first delay deviation, the second delay deviation, and the third delay deviation of the nth UAV in the UAV cluster, respectively. , represents transpose, is the elevation angle of the incident signal, is the azimuth of the incident signal, c is the speed of light, is the array element spacing d n The maximum delay value under represents the array element spacing between the nth UAV and the first UAV, represents the position coordinates of the nth drone, represents the sampling rate deviation between the nth UAV and the first UAV, k represents the sampling point index, represents the actual sampling rate of the first drone, represents the actual sampling rate of the nth UAV; According to the formula Get the delay deviation of each drone in the drone cluster.

6. The broadband navigation interference suppression method of the drone cluster equivalent array as claimed in claim 1, characterized in that: The time delay of the time domain tap in the time domain filter is greater than the time delay of the signal between the array elements.

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