Synchronization sequence extraction and timing correction system for uav positioning

Abstract

The application relates to the technical field of data processing, in particular to a synchronization sequence extraction and time delay correction system for positioning of a UAV, which comprises an original sequence acquisition module, a time delay data acquisition module, a time delay data correction module and a positioning result output module; the original sequence acquisition module acquires original sequences; the time delay data acquisition module synchronizes the original sequences and acquires time delay data; the time delay data correction module preliminarily corrects and suppresses the time delay data; and the positioning result output module outputs a final decision. The application synchronizes original sequences to obtain time delay data, and corrects the time delay data, so that the time delay data can be accurately estimated in real time, thereby improving the efficiency and accuracy of correction of the time delay data.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a synchronization sequence extraction and delay correction system for UAV positioning. Background Technology

[0002] In recent years, the problem of UAV positioning based on time difference of arrival (TDOA) has attracted widespread attention. Since the pulse length of a UAV image transmission signal is on the order of milliseconds and it often operates in low signal-to-noise ratio (SNR) environments, delay estimation presents challenges. To reduce the amount of data transmitted between observation stations, instead of directly transmitting complete waveforms, stations transmit a unique Zadoff-Chu (ZC) time synchronization sequence. While this sequence possesses good autocorrelation and resistance to frequency offset, existing methods for obtaining delay based on the time synchronization sequence are mostly limited to single-domain analysis, resulting in insufficient delay monitoring accuracy and failing to fully utilize the joint time-frequency characteristics of the signal. This leads to limited delay estimation accuracy in complex environments and makes it impossible to improve the accuracy of UAV signal delay estimation by combining multiple methods.

[0003] Chinese patent application CN105162746A discloses a method and system for estimating time delay and frequency offset based on CMMB. The method includes: generating a linear frequency modulated (LFM) signal; inserting the LFM signal as a synchronization signal into the baseband signal of each time slot and transmitting it via a radio frequency (RF) signal; a mobile terminal receiving the RF signal and extracting the synchronization signal therefrom; extracting autocorrelation features from the synchronization signal; transforming the autocorrelation feature signal to the frequency domain to obtain a spectrum signal; converting the spectrum signal into an autocorrelation time domain signal; and analyzing the autocorrelation time domain signal using a fuzzy function to obtain a joint estimate of the fuzzy domain time delay and frequency offset. Therefore, this scheme still suffers from the problem of relying solely on a single method to extract the synchronization sequence, failing to accurately estimate the time delay, and resulting in low efficiency in electronic data processing during time delay correction. Summary of the Invention

[0004] To address this issue, the present invention provides a synchronization sequence extraction and time delay correction system for UAV positioning, which overcomes the problems of low efficiency and insufficient accuracy in time delay data correction caused by using only a single method to estimate time delay data in the prior art.

[0005] To achieve the above objectives, the present invention provides a synchronization sequence extraction and delay correction system for UAV positioning, the system comprising:

[0006] The raw sequence acquisition module is used to acquire raw sequences;

[0007] The delay data acquisition module is used to synchronize the original sequence using the synchronization sequence extraction method to obtain the synchronization sequence, and to acquire the delay data based on the synchronization sequence.

[0008] The time delay data correction module is configured to preliminarily correct the time delay data according to the predicted clock drift amount to obtain corrected time delay data, acquire the first positioning result according to the corrected time delay data, acquire the residual error norm according to the first positioning result, perform suppression processing on the corrected time delay data according to the residual error norm, perform processing update on the suppression processing according to the suppression processing frequency, and perform processing optimization on the processing update according to the node interference degree.

[0009] The positioning result output module is configured to perform fusion processing on the first positioning result to obtain a fusion processing result, output the final decision according to the fusion processing result, perform frequency adjustment on the output process of the final decision according to the triggering frequency, and perform interference adjustment on the process of the frequency adjustment according to the node interference duration.

[0010] Further, when the time delay data acquisition module extracts the synchronization sequence from the original sequence by the synchronization sequence extraction method, the synchronization sequence extraction method comprises:

[0011] Step A01, calculating a cross-correlation value set Rrs according to the original sequence r(n), the ideal sequence complex conjugate s*(n), the sampling point sequence number n, the sliding window length m and the original sequence length Np, and setting obtaining the cross-correlation value set Rrs={Rrs1, Rrs2, Rrs3,..., Rrsn};

[0012] Step A02, performing peak value detection on the cross-correlation value set Rrs={Rrs1, Rrs2, Rrs3,..., Rrsn} to obtain a peak value Rrs(max) and a first peak value position Mpeak1;

[0013] Step A03, calculating a position error a according to the peak value Rrs(max), a previous window cross-correlation value Rrs(max-1) and a next window cross-correlation value Rrs(max+1), and setting obtaining the position error a;

[0014] Step A04, calculating a target peak value position Mpeak according to the position error a and the first peak value position Mpeak1, and setting Mpeak=Mpeak1+a, to obtain the target peak value position Mpeak;

[0015] Step A05, marking the peak value Rrs(max) and the target peak value position Mpeak in the original sequence to obtain a synchronization sequence;

[0016] The time delay data acquisition module acquires the time delay data according to the synchronization sequence, and calculates the time delay data ts according to the target peak position Mpeak and the sampling frequency fs, and sets ts=Mpeak / fs, to obtain the time delay data ts.

[0017] Further, the time delay data correction module preliminarily corrects the time delay data according to the predicted clock drift, and calculates the current clock drift tp according to the ground control station sending timestamp t1, the unmanned aerial vehicle receiving timestamp t2, the unmanned aerial vehicle sending timestamp t3 and the ground control station receiving timestamp t4, and sets tp=[(t2-t1)-(t3-t4)] / 2, to obtain the current clock drift tp.

[0018] The current clock drift tp and the current environment temperature are input into the clock drift prediction model to obtain the predicted clock drift ti, and the corrected time delay data tse is calculated according to the time delay data ts, the predicted clock drift ti and the compensation coefficient β, and sets tse=ts-β×ti, to obtain the corrected time delay data tse.

[0019] Further, the time delay data correction module acquires the first positioning result according to the corrected time delay data through the positioning result acquisition method, and the positioning result acquisition method comprises:

[0020] Step B01, the first reference point corrected time delay data tse1, the second reference point corrected time delay data tse2 and the third reference point corrected time delay data tse3 are acquired.

[0021] Step B02, the first positioning distance d1 is calculated according to the first reference point corrected time delay data tse1 and the speed of light c, and sets d1=tse1×c, to obtain the first positioning distance d1.

[0022] The second positioning distance d2 is calculated according to the second reference point corrected time delay data tse2 and the speed of light c, and sets d2=tse2×c, to obtain the second positioning distance d2.

[0023] The third positioning distance d3 is calculated according to the third reference point corrected time delay data tse3 and the speed of light c, and sets d3=tse3×c, to obtain the third positioning distance d3.

[0024] Step B03, the target positioning point coordinates (x, y, z) are calculated according to the first positioning distance d1, the second positioning distance d2, the third positioning distance d3, the reference node coordinates (x0, y0, z0), the first reference node coordinates (x1, y1, z1), the second reference node coordinates (x2, y2, z2), the third reference node coordinates (x3, y3, z3) and the target positioning point coordinates (x d ,y d ,z dThe positioning equations are constructed, and the following settings are made:

[0025]

[0026] Step B04: Solve the positioning equation to obtain the coordinates (x, y) of the target positioning point. d ,y d ,z d ), the coordinates (x) of the target location point d ,y d ,z d () is used as the first positioning result.

[0027] Furthermore, when the delay data correction module obtains the residual norm based on the first positioning result, it does so based on the first positioning result (x d ,y d ,z d ), the first positioning result measurement value (x) r ,y r ,z r ) Calculate the position vector difference r, and set Obtain the position vector difference r, and based on the position vector difference Obtain the residual norm rp and set... The residual norm rp is obtained;

[0028] When the delay data correction module performs suppression processing on the corrected delay data based on the residual norm, it compares the residual norm rp with the preset residual norm rp0, judges the compliance of the residual norm based on the comparison result, and performs suppression processing on the corrected delay data based on the judgment result, wherein:

[0029] When rp≤rp0, the delay data correction module determines that the residual norm meets the standard and does not perform suppression processing on the corrected delay data;

[0030] When rp > rp0, the delay data correction module determines that the residual norm does not meet the standard, and performs suppression processing on the corrected delay data until the residual norm meets the standard.

[0031] When the delay data correction module performs suppression processing on the corrected delay data, it performs suppression processing on the corrected delay data according to a suppression processing method, the suppression processing method including:

[0032] Step D01: Calculate the current delay confidence level pk' based on the previous time delay confidence level pk, the confidence level parameter u, and the previous time delay gain kk, and set... Obtain the current latency confidence level pk`;

[0033] Step D02, calculating the current gain kk` according to the current time delay credibility pk` and the credibility parameter u, setting to obtain the current gain kk`;

[0034] Step D03, calculating the second modified time delay data tse` according to the modified time delay data tse, the current gain kk` and the time delay measurement value tses, setting tse` = tse + kk × (tses-tse), to obtain the second modified time delay data tse`;

[0035] Step D04, replacing the modified time delay data tse with the second modified time delay data tse`, and obtaining the first positioning result according to the modified time delay data, and re-obtaining the residual norm according to the first positioning result, and re-judging the compliance of the residual norm according to the residual norm rp and the preset residual norm rp0, until the compliance of the residual norm is up to standard.

[0036] Further, when the suppression processing frequency pm is compared with the preset suppression processing frequency pm0, the situation of the suppression processing frequency is judged according to the comparison result, and the suppression processing is updated according to the judgment result, wherein:

[0037] When pm≤pm0, the time delay data correction module determines that the situation of the suppression processing frequency is normal, and does not update the suppression processing;

[0038] When pm>pm0, the time delay data correction module determines that the situation of the suppression processing frequency is abnormal, updates the suppression processing, adds machine learning assistance to the suppression processing to obtain double suppression processing, replaces the suppression processing with the double suppression processing, and re-performs suppression processing on the modified time delay data;

[0039] When the time delay data correction module replaces the suppression processing with the double suppression processing, the historical interference reference data is input into the interference suppression model, the model modified time delay data is obtained according to the interference suppression model, the modified time delay data is replaced with the model modified time delay data, and the modified time delay data is re-suppressed according to the suppression processing method.

[0040] Further, when the time delay data correction module optimizes the process of processing update according to the node interference degree, the node interference degree is obtained according to the node interference degree obtaining method, and the node interference degree obtaining method comprises:

[0041] Step C01, the pseudo-range error wj` is calculated according to the actual pseudo-range error wj and the maximum tolerable error wj0, and wj` = wj / wj0 is set to obtain the pseudo-range error wj`;

[0042] Step C02, the signal-to-noise ratio drop xj` is calculated according to the actual signal-to-noise ratio drop xj and the maximum tolerable signal-to-noise ratio drop xj0, and xj` = xj / xj0 is set to obtain the signal-to-noise ratio drop xj`;

[0043] Step C03, the drift dj` is calculated according to the comparison between the actual drift dj and the maximum tolerable drift dj0, and dj` = dj / dj0 is set to obtain the drift dj`;

[0044] Step C04, the pseudo-range error wj`, the signal-to-noise ratio drop xj`, and the drift dj` are normalized to obtain the normalized pseudo-range error wjc, the normalized signal-to-noise ratio drop xjc, and the normalized drift djc;

[0045] Step C05, the node interference degree uc is calculated according to the normalized pseudo-range error wjc, the normalized signal-to-noise ratio drop xjc, the normalized drift djc, the pseudo-range error weight w1, the signal-to-noise ratio drop weight w2, and the drift weight w3, and uc = wjc×w1+xjc×w2+djc×w3 is set to obtain the node interference degree uc;

[0046] When the node interference degree uc is compared with the preset node interference degree uc0 during the processing optimization of the process of updating the node interference degree, the state of the node interference degree is judged according to the comparison result, and the preset suppression processing frequency pm0 is processed and optimized according to the judgment result, wherein:

[0047] When uc≤uc0, the state of the node interference degree is determined as weak interference, and the preset suppression processing frequency pm0 is not processed and optimized;

[0048] When uc>uc0, the state of the node interference degree is determined as strong interference, and the preset suppression processing frequency pm0 is processed and optimized, the preset suppression processing frequency pm0 is processed and optimized by the optimization coefficient yx, yx = 0.42+0.22×e is set, wherein e is the base of natural logarithm, the optimized preset suppression processing frequency pm0` is obtained, pm0` = pm0×yx is set, the preset suppression processing frequency pm0 is replaced by the optimized preset suppression processing frequency pm0`, and the suppression processing frequency pm is compared with the preset suppression processing frequency pm0 again; -(uc-uc0)

[0049] ​The positioning result output module performs fusion processing on the first positioning result to obtain a fused positioning result and a positioning confidence zx, and takes the fused positioning result and the positioning confidence zx as a fusion processing result.

[0050] Further, when the positioning result output module outputs a final decision according to the fusion processing result, the positioning confidence zx is compared with a preset positioning confidence zx0, a positioning confidence compliance condition is judged according to a comparison result, a final positioning result is output according to a judgment result, and the final decision is output according to the judgment result, wherein:

[0051] When zx≥ zx0, the positioning result output module judges that the positioning confidence compliance condition is met, outputs the final decision, and the content of the final decision is that the fused positioning result is output as the final positioning result without final correction of the corrected time delay data.

[0052] When zx< zx0, the positioning result output module judges that the positioning confidence compliance condition is not met, outputs the final decision, and the content of the final decision is that the fused positioning result is not output as the final positioning result and the corrected time delay data is finally corrected.

[0053] Further, when the positioning result output module adjusts the output process of the final decision according to the trigger frequency, the trigger frequency cp is compared with a preset trigger frequency cp0, a trigger frequency condition is judged according to a comparison result, and the preset positioning confidence zx0 is adjusted according to a judgment result, wherein:

[0054] When cp≤ cp0, the positioning result output module judges that the trigger frequency condition is normal, and does not adjust the preset positioning confidence zx0;

[0055] When cp> cp0, the positioning result output module judges that the trigger frequency condition is abnormal, adjusts the preset positioning confidence zx0, adjusts the preset positioning confidence zx0 according to a frequency adjustment coefficient px, sets px=1.33-0.28×e, and obtains an adjusted preset positioning confidence zx0`, sets zx0`= zx0×px, replaces the preset positioning confidence zx0 with the adjusted preset positioning confidence zx0`, and recompares the positioning confidence zx with the preset positioning confidence zx0. -(cp-cp0)

[0056] ​Further, when the node interference duration tt is compared with the first preset node interference duration tt1 and the second preset node interference duration tt2 by the positioning result output module according to the interference adjustment process of the frequency adjustment of the node interference duration, the state of the node interference duration is judged according to the comparison result, and the preset trigger frequency cp0 is adjusted according to the judgment result, wherein:

[0057] When tt≤tt1, the positioning result output module determines that the state of the node interference duration is short time, and does not adjust the preset trigger frequency cp0;

[0058] When tt1<tt≤tt2, the positioning result output module determines that the state of the node interference duration is medium time, and adjusts the preset trigger frequency cp0, adjusts the preset trigger frequency cp0 according to the interference adjustment coefficient gr, sets Wherein e is the base of natural logarithm, the adjusted preset trigger frequency cp0` is obtained, cp0`=cp0×gr is set, the preset trigger frequency cp0 is replaced by the adjusted preset trigger frequency cp0`, and the trigger frequency cp is compared with the preset trigger frequency cp0 again;

[0059] When tt>tt2, the positioning result output module determines that the state of the node interference duration is long time, and manually corrects the corrected time delay data.

[0060] Compared with the prior art, the system collects the original sequence by the original sequence acquisition module, so as to facilitate the signal transmission between the synchronous ground control station and the unmanned aerial vehicle, and the system also synchronizes the original sequence by the time delay data acquisition module, and acquires the time delay data, so as to facilitate the specific quantification of the signal time error between the unmanned aerial vehicle and the ground signal receiving end, and facilitate the subsequent correction according to the time delay data. The system also preliminarily corrects and suppresses the time delay data by the time delay data correction module, so as to reasonably correct the time delay data at future time according to the predicted clock drift amount and suppress the multipath effect in the corrected time delay data, thereby improving the accuracy of the time delay data. The system also outputs the final decision by the positioning result output module, and finally corrects the corrected time delay data in real time according to the final decision, thereby improving the accuracy of the final positioning result and the efficiency of electronic data processing in the time delay correction process. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 It is a structure schematic view of the synchronization sequence extraction and time delay correction system for unmanned aerial vehicle positioning of the embodiment. DETAILED DESCRIPTION

[0062] In order to make the objects, technical schemes and advantages of the present application clearer, the following further describes the present application with reference to the embodiments; it should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0063] The preferred embodiments of the present application are described below with reference to the drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and not to limit the protection scope of the present application.

[0064] It should be noted that, in the description of the present application, the terms indicating the direction or positional relationship of "upper", "lower", "left", "right", "inner", "outer" and the like are based on the direction or positional relationship shown in the drawings, which is only for the convenience of description and does not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0065] In addition, it should also be noted that, in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. Those skilled in the art can understand the specific meaning of the above terms in the present application according to the specific circumstances.

[0066] Please refer to Figure 1 The system includes:

[0067] The original sequence acquisition module is used to acquire the original sequence;

[0068] The time delay data acquisition module is used to synchronize the original sequence by the synchronization sequence extraction method to obtain the synchronization sequence, and acquire the time delay data according to the synchronization sequence. The time delay data acquisition module is connected with the original sequence acquisition module;

[0069] The time delay data correction module is used to preliminarily correct the time delay data according to the predicted clock drift amount to obtain the corrected time delay data, acquire the first positioning result according to the corrected time delay data, acquire the residual norm according to the first positioning result, and suppress the corrected time delay data according to the residual norm. The processing update is also used to update the suppression processing according to the suppression processing frequency, and optimize the process of processing update according to the node interference degree. The time delay data correction module is connected with the time delay data acquisition module;

[0070] The positioning result output module is used for fusing the first positioning result to obtain a fusion processing result, outputting a final decision according to the fusion processing result, adjusting the output process of the final decision according to the triggering frequency, and adjusting the process of the frequency adjustment according to the node interference duration. The positioning result output module is connected with the time delay data correction module.

[0071] Specifically, the system is applied to a UAV positioning result output terminal, such as a ground control station and a mobile device. The system obtains time delay data by synchronizing original sequences, corrects the time delay data, and obtains a final decision, so as to accurately estimate the time delay data in real time, thereby improving the efficiency and accuracy of electronic data processing in the time delay correction process. The system acquires original sequences through an original sequence acquisition module, so as to synchronize the signal transmission between the ground control station and the UAV. The system synchronizes the original sequences and acquires time delay data through a time delay data acquisition module, so as to specifically quantify the signal time error between the UAV and the ground signal receiving end, and facilitate subsequent correction according to the time delay data. The system preliminarily corrects and suppresses the time delay data through a time delay data correction module, so as to reasonably correct the time delay data at future time according to the predicted clock drift and suppress the multipath effect in the corrected time delay data, thereby improving the accuracy of the time delay data. The system outputs a final decision through a positioning result output module, and finally corrects the corrected time delay data in real time according to the final decision, thereby improving the accuracy of the final positioning result and the efficiency of the time delay correction.

[0072] Specifically, the original sequence acquisition module acquires original sequences.

[0073] Specifically, the original sequence refers to an original signal sequence emitted by a UAV terminal to synchronize information with a ground control station. The embodiment does not limit the receiving method of the original sequence. For example, the ground control station can acquire the original sequence through an antenna array.

[0074] Specifically, the time delay data acquisition module acquires original sequences, so as to synchronize the signal transmission between the ground control station and the UAV, thereby improving the efficiency of original sequence extraction and time delay correction.

[0075] Specifically, when the time delay data acquisition module synchronizes the original sequences through a synchronization sequence extraction method, the synchronization sequence extraction method includes:

[0076] Step A01: calculating a cross-correlation value set Rrs according to the original sequence r(n), the ideal sequence complex conjugate s*(n), the sampling point sequence number n, the sliding window length m, and the original sequence length Np, and setting a set of cross-correlation values Rrs={Rrs1, Rrs2, Rrs3,..., Rrsn} is obtained;

[0077] Step A02, peak detection is performed on the set of cross-correlation values Rrs={Rrs1, Rrs2, Rrs3,..., Rrsn} to obtain a peak value Rrs(max) and a first peak position Mpeak1;

[0078] Step A03, a position error a is calculated according to the peak value Rrs(max), a previous window cross-correlation value Rrs(max-1) and a next window cross-correlation value Rrs(max+1), and is set as The position error a is obtained.

[0079] Step A04, a target peak position Mpeak is calculated according to the position error a and the first peak position Mpeak1, and is set as Mpeak=Mpeak1+a, to obtain the target peak position Mpeak.

[0080] Step A05, the peak value Rrs(max) and the target peak position Mpeak are marked in the original sequence to obtain a synchronization sequence.

[0081] Specifically, the r(n+m) refers to a sequence value after the original sequence is right-shifted by m sample points of the sliding window length value m, and the ideal sequence complex conjugate refers to an operation value that ensures phase matching of the ideal sequence in the cross-correlation value calculation process, such as an ideal sequence s(n)=e jθ The ideal sequence complex conjugate s*(n)=e -jθ , wherein e -jθ and e jθFor complex exponential signal, j is imaginary unit, θ is phase angle, the ideal sequence refers to an ideal noiseless synchronization signal template used for cross-correlation calculation with the original sequence, the specific acquisition method of the ideal sequence is not limited in the embodiment, and the related person skilled in the art can freely select according to actual needs, for example, inputting the sequence type and communication protocol standard of the original sequence into MATLAB to obtain the ideal sequence, the sampling point serial number refers to the sampling point serial number obtained by numbering the single sequence value in the original sequence as a sampling point, for example, the first sampling point is numbered as 1, the second sampling point is numbered as 2, the third sampling point is numbered as 3, and the nth sampling point is numbered as n, the sliding window length refers to the sliding step length of the sampling point when the cross-correlation value is calculated, the sliding window length is not limited in the embodiment, for example, the sliding window length m = 1 is set in the embodiment, the cross-correlation value set Rrs = {Rrs1, Rrs2, Rrs3,..., Rrsn} refers to a data set for measuring the cross-correlation degree between the original sequence and the ideal sequence, Rrs1 refers to the first cross-correlation value in the cross-correlation value set, Rrs2 refers to the second cross-correlation value in the cross-correlation value set, Rrs3 refers to the third cross-correlation value in the cross-correlation value set, and Rrsn refers to the nth cross-correlation value in the cross-correlation value set, the original sequence length refers to the total number of sampling points in the original sequence, and the acquisition method of the original sequence length is not limited in the embodiment, for example, the sequence length defined in advance by the communication protocol, the peak value detection refers to the process of obtaining the maximum cross-correlation value and its position in the cross-correlation value set, the peak value refers to the maximum cross-correlation value in the cross-correlation value set, the first peak value position refers to the specific position of the peak value in the cross-correlation value set, for example, when the sampling point serial number n = 5, the peak value Rrs(max) is obtained in the cross-correlation value set, then the first peak value position Mpeak1 = 5, the specific method of peak value detection is not limited in the embodiment, and the related person skilled in the art can freely select according to actual needs, for example, peak value detection is performed by MATLAB, the MATLAB refers to a calculation software capable of peak value detection, the full name of which is Matrix Laboratory, and the Chinese name is Mai Tei Lei Bu, the previous window cross-correlation value refers to the cross-correlation value of the position of the previous sliding window length of the first peak value position in the cross-correlation value set, and the next window cross-correlation value refers to the cross-correlation value of the position of the next sliding window length of the first peak value position in the cross-correlation value set, for example, when m = 5, the peak value is Rrs3, the previous window cross-correlation value is Rrs2, and the next window cross-correlation value is Rrs4, the constant coefficient 2 in the formula is obtained by mathematical fitting of a parabolic equation.

[0082] Specifically, the time delay data acquisition module marks the peak value in the original sequence, the peak value corresponds to the starting position in the original sequence, so as to obtain the time delay data according to the starting position in the original sequence, thereby improving the efficiency of time delay correction.

[0083] Specifically, when the time delay data acquisition module acquires the time delay data according to the synchronization sequence, the time delay data ts is calculated according to the target peak position Mpeak and the sampling frequency fs, and ts=Mpeak / fs is set to obtain the time delay data ts.

[0084] Specifically, the sampling frequency refers to the number of times of synchronizing the original sequence within a preset time, and the embodiment does not limit the preset time. For example, when the number of times of synchronizing the original sequence within a preset time 0.1 is set to 10 times, the sampling frequency fs=10 / 0.1 hertz.

[0085] Specifically, the time delay data acquisition module acquires the time delay data, and quantifies the signal time error between the unmanned aerial vehicle and the ground signal receiving end, so as to correct the time delay data, thereby improving the accuracy of unmanned aerial vehicle positioning.

[0086] Specifically, when the time delay data correction module preliminarily corrects the time delay data according to the predicted clock drift, the current clock drift tp is calculated according to the ground control station sending timestamp t1, the unmanned aerial vehicle receiving timestamp t2, the unmanned aerial vehicle sending timestamp t3 and the ground control station receiving timestamp t4, and tp=[(t2-t1)-(t3-t4)] / 2 is set to obtain the current clock drift tp.

[0087] The current clock drift tp and the current environment temperature are input into the clock drift prediction model to obtain the predicted clock drift ti, and the corrected time delay data tse is calculated according to the time delay data ts, the predicted clock drift ti and the compensation coefficient β, and tse=ts-β×ti is set to obtain the corrected time delay data tse.

[0088] Specifically, the ground control station sending timestamp refers to a time point at which the ground control station sends the positioning request data to the UAV at the current moment, the ground control station receiving timestamp refers to a time point at which the ground control station receives the response data sent by the UAV, the embodiment does not limit the acquisition method of the ground control station sending timestamp and the ground control station receiving timestamp, and a person skilled in the related art can freely select according to actual needs, such as acquiring through the system log of the ground control station, the UAV receiving timestamp refers to a time point at which the UAV receives the positioning request data, and the UAV sending timestamp refers to a time point at which the UAV sends the response data corresponding to the positioning request data to the ground control station, the embodiment does not limit the specific acquisition method of the UAV receiving timestamp and the UAV sending timestamp, and a person skilled in the related art can freely select according to actual needs, such as acquiring through the task instruction log of the UAV, the current environment temperature refers to a temperature value of the environment around the UAV at the current moment, the embodiment does not limit the specific acquisition method of the current environment temperature, and a person skilled in the related art can freely select according to actual needs, such as acquiring the current environment temperature through a temperature sensor, the clock drift prediction model refers to a convolutional neural network model that takes the current clock drift and the current environment temperature as input data and takes the predicted clock drift as output data, the embodiment does not limit the specific construction method of the clock drift prediction model, and a person skilled in the related art can freely select according to actual needs, such as training the convolutional neural network model by taking the historically occurred clock-related data and the corresponding predicted clock drift as a training set, the clock-related data includes the clock drift and the environment temperature, and the compensation coefficient refers to an adjustment parameter for correcting the time drift bias, the embodiment does not limit the specific acquisition method of the compensation coefficient, and a person skilled in the related art can freely select according to actual needs, such as obtaining the compensation coefficient by recursively fusing the historical clock drift through Kalman filtering.

[0089] Specifically, the delay data correction module corrects the future time delay data by predicting the clock drift, so as to improve the accuracy of the delay data.

[0090] Specifically, when the delay data correction module obtains the first positioning result according to the corrected delay data through the positioning result acquisition method, the positioning result acquisition method includes:

[0091] Step B01, obtaining the first reference point corrected delay data tse1, the second reference point corrected delay data tse2 and the third reference point corrected delay data tse3;

[0092] Step B02, the first positioning distance d1 is calculated according to the first reference point corrected time delay data tse1 and light speed c, it is set d1=tse1xc, first positioning distance d1 is obtained;

[0093] The second positioning distance d2 is calculated according to the second reference point corrected time delay data tse2 and light speed c, it is set d2=tse2xc, second positioning distance d2 is obtained;

[0094] The third positioning distance d3 is calculated according to the third reference point corrected time delay data tse3 and light speed c, it is set d3=tse3xc, third positioning distance d3 is obtained;

[0095] Step B03, the positioning equation is constructed according to the first positioning distance d1, second positioning distance d2, third positioning distance d3, reference node coordinates (x0, y0, z0), first reference node coordinates (x1, y1, z1), second reference node coordinates (x2, y2, z2), third reference node coordinates (x3, y3, z3) and target positioning point coordinates (x d ,y d ,z d ), it is set:

[0096]

[0097] Step B04, the positioning equation is solved, and target positioning point coordinates (x d ,y d ,z d ) are obtained, and the coordinates (x d ,y d ,z d ) of the target positioning point are taken as the first positioning result.

[0098] Specifically, the first reference point corrected time delay data refers to the corrected time delay data of a first known position coordinate point used for position determination of the target positioning point, the second reference point corrected time delay data refers to the corrected time delay data of a second known position coordinate point used for position determination of the target positioning point, and the third reference point corrected time delay data refers to the corrected time delay data of a third known position coordinate point used for position determination of the target positioning point. The first reference point, the second reference point, and the third reference point are not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs, as long as the first reference point, the second reference point, and the third reference point are known and can be used for positioning of the target positioning point. For example, the first reference point coordinate is set as (50, 0, 0), the second reference point coordinate is set as (0, 50, 0), and the third reference point coordinate is set as (25, 25, 10). The target positioning point refers to a place whose specific coordinate position needs to be determined. The reference node coordinate refers to the coordinate of an original known position reference point used for position determination of the target positioning point. The reference node is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs, as long as it is different from the known positions of the first reference point, the second reference point, and the third reference point. For example, a central computing node that aggregates all reference node data is designated as the reference node, and the coordinate of the reference node is (0, 0, 0). x0 refers to the value of the reference node coordinate on the x-axis of the space coordinate system, y0 refers to the value of the reference node coordinate on the y-axis of the space coordinate system, and z0 refers to the value of the reference node coordinate on the z-axis of the space coordinate system. x1 refers to the value of the first reference node coordinate on the x-axis of the space coordinate system, y1 refers to the value of the first reference node coordinate on the y-axis of the space coordinate system, and z1 refers to the value of the first reference node coordinate on the z-axis of the space coordinate system. x2 refers to the value of the second reference node coordinate on the x-axis of the space coordinate system, y2 refers to the value of the second reference node coordinate on the y-axis of the space coordinate system, and z2 refers to the value of the second reference node coordinate on the z-axis of the space coordinate system. x3 refers to the value of the third reference node coordinate on the x-axis of the space coordinate system, y3 refers to the value of the third reference node coordinate on the y-axis of the space coordinate system, and z3 refers to the value of the third reference node coordinate on the z-axis of the space coordinate system. x d refers to the value of the target positioning point coordinate on the x-axis of the space coordinate system, y d refers to the value of the target positioning point coordinate on the y-axis of the space coordinate system, and z dis the value of the target positioning point coordinate on the z-axis of the space coordinate system, and the space coordinate system refers to a mathematical framework used to describe the positions of the reference node coordinate, the first reference node coordinate, the second reference node coordinate, the third reference node coordinate, and the target positioning point coordinate in a three-dimensional space. The present embodiment does not limit the position of the origin of the space coordinate system, such as setting the reference node as the origin of the space coordinate system.

[0099] Specifically, the time delay data correction module constructs a positioning equation by selecting a reference node and three reference nodes to obtain a first positioning result by the time difference of the response data sent by the unmanned aerial vehicle to different reference nodes, so as to optimize the time delay data according to the first positioning result subsequently.

[0100] Specifically, when the time delay data correction module obtains the residual norm according to the first positioning result, the first positioning result (x d ,y d ,z d ) is used to calculate the position vector difference r, and the first positioning result measurement value (x r ,y r ,z r ) is set. The position vector difference r is obtained, and the residual norm rp is obtained according to the position vector difference , and the residual norm rp is set. The residual norm rp is obtained.

[0101] Specifically, the first positioning result measurement value refers to the true coordinate value of the target positioning point. The present embodiment does not limit the specific acquisition method of the first positioning result measurement value, and a person skilled in the art can freely select according to actual needs, such as obtaining the first positioning result measurement value by GPS, wherein the GPS refers to a global positioning system, and the x r refers to the value of the first positioning result measurement value on the x-axis of the space coordinate system, the y r refers to the value of the first positioning result measurement value on the y-axis of the space coordinate system, and the z r refers to the value of the first positioning result measurement value on the z-axis of the space coordinate system, and the residual norm refers to a value reflecting the difference between the first positioning result and the first positioning result measurement value.

[0102] Specifically, the time delay data correction module obtains the residual norm to measure the difference between the first positioning result and the true value, so as to subsequently correct the time delay data according to the residual norm, thereby improving the efficiency of correcting the time delay data.

[0103] Specifically, when the residual norm rp is compared with the preset residual norm rp0, the compliance of the residual norm is judged according to the comparison result, and the modified time delay data is suppressed according to the judgment result, wherein:

[0104] When rp≤rp0, the time delay data correction module determines that the compliance of the residual norm is up to standard, and does not suppress the modified time delay data;

[0105] When rp>rp0, the time delay data correction module determines that the compliance of the residual norm is not up to standard, and suppresses the modified time delay data until the compliance of the residual norm is up to standard.

[0106] Specifically, the preset residual norm refers to the preset value for judging the compliance of the residual norm, and the specific value of the preset residual norm is not limited in the embodiment, and can be freely selected by those skilled in the art according to actual needs. For example, the preset residual norm rp0=0.4 in the embodiment, the compliance of the residual norm refers to the compliance degree of the residual norm judged according to the residual norm and the preset residual norm, and the compliance of the residual norm includes up to standard and not up to standard.

[0107] Specifically, the time delay data correction module judges the compliance of the residual norm, and when the compliance of the residual norm is not up to standard, the modified time delay data is suppressed to suppress the multipath effect in the modified time delay data, thereby improving the accuracy of the modified time delay data.

[0108] Specifically, when the time delay data correction module suppresses the modified time delay data, the modified time delay data is suppressed according to the suppression method, and the suppression method includes:

[0109] Step D01, the current time delay reliability pk` is calculated according to the last time delay reliability pk, the reliability parameter u and the last time gain kk, and is set as pk`=pk+u×(pk-pk), the current time delay reliability pk` is obtained;

[0110] Step D02, the current gain kk` is calculated according to the current time delay reliability pk` and the reliability parameter u, and is set as kk`=kk+u×(kk-kk), the current gain kk` is obtained;

[0111] Step D03, the twice modified time delay data tse` is calculated according to the modified time delay data tse, the current gain kk` and the time delay measurement value tses, and is set as tse`=tse+kk×(tses-tse), the twice modified time delay data tse` is obtained;​​

[0112] Step D04, replacing the modified time delay data tse with the twice modified time delay data tse', and acquiring the first positioning result according to the modified time delay data, and re-acquiring the residual norm according to the first positioning result, and re-judging the compliance of the residual norm according to the residual norm rp and the preset residual norm rp0 until the compliance of the residual norm is up to standard.

[0113] Specifically, the last time delay credibility refers to a value for measuring the credibility of the modified time delay data at the last time. The present embodiment does not limit the specific acquisition method of the last time delay credibility. For example, the last time delay credibility is obtained by setting the initial value of the time delay credibility as 100 and updating the time delay credibility according to a credibility parameter u=0.95. The credibility parameter refers to a value for controlling the weight of the last time delay credibility. The last time gain refers to a coefficient for measuring the correction strength of the current time delay credibility on the last time delay credibility according to the last time delay credibility and the credibility parameter. The time delay measurement value refers to the time delay data directly measured by the unmanned aerial vehicle through UWB. The full name of UWB is Ultra-Wideband, and the Chinese name is Ultra-Wideband technology.

[0114] Specifically, the time delay data modification module suppresses the modified time delay data to perform secondary modification on the modified time delay data, thereby improving the monitoring accuracy of the time delay data.

[0115] Specifically, when updating the suppression processing, the time delay data modification module compares the suppression processing frequency pm with a preset suppression processing frequency pm0, judges the condition of the suppression processing frequency according to the comparison result, and updates the suppression processing according to the judgment result, wherein:

[0116] When pm≤pm0, the time delay data modification module determines that the condition of the suppression processing frequency is normal, and does not update the suppression processing.

[0117] When pm>pm0, the time delay data modification module determines that the condition of the suppression processing frequency is abnormal, updates the suppression processing, adds machine learning assistance to the suppression processing to obtain double suppression processing, replaces the suppression processing with the double suppression processing, and re-suppresses the modified time delay data.

[0118] Specifically, the suppression processing frequency refers to the number of times of suppression processing on the corrected time delay data within a preset time. The embodiment does not limit the acquisition method of the suppression processing frequency. For example, the suppression processing frequency is acquired through the specification of a receiver, which is a device used by a ground control station to receive the response data of the unmanned aerial vehicle. The preset suppression processing frequency refers to a preset value for judging the condition of the suppression processing frequency. The embodiment does not limit the specific numerical value of the preset suppression processing frequency, which can be freely selected by a person skilled in the art according to actual needs. For example, the preset suppression processing frequency pm0 is set to 4 times per second in the embodiment. The condition of the suppression processing frequency refers to the normal degree of the suppression processing frequency, which includes normal and abnormal conditions.

[0119] Specifically, the time delay data correction module judges the condition of the suppression processing frequency. When the condition of the suppression processing frequency is abnormal, machine learning is timely added to the suppression processing to reasonably match the suppression processing method in combination with various scene factors such as environmental position, signal strength, and unmanned aerial vehicle flight height, thereby enhancing the suppression accuracy of the multipath effect in the corrected time delay data and improving the efficiency of correcting the time delay data.

[0120] Specifically, when the time delay data correction module replaces the suppression processing with double suppression processing, the historical interference reference data is input into an interference suppression model to obtain model corrected time delay data according to the interference suppression model. The corrected time delay data is replaced with the model corrected time delay data, and the corrected time delay data is reprocessed according to the suppression processing method.

[0121] Specifically, the interference suppression model refers to a convolutional neural network model that takes historical interference reference data as input data and model corrected time delay data as output data. The embodiment does not limit the specific construction method of the interference suppression model, which can be freely selected by a person skilled in the art according to actual needs. For example, the historical unmanned aerial vehicle signal strength and unmanned aerial vehicle flight height are taken as historical interference reference data, and the historical interference reference data and its corresponding model corrected time delay data are taken as a training set to train the interference suppression model to obtain the interference suppression model.

[0122] Specifically, the time delay data correction module replaces the suppression processing with double suppression processing and adds an interference suppression model to the suppression processing to preliminarily adjust the corrected time delay data, so as to reduce the influence of environmental factors on the corrected time delay data, thereby improving the accuracy and efficiency of the suppression processing of the corrected time delay data.

[0123] Specifically, the delay data correction module optimizes the process of processing the update according to the node interference degree, and the node interference degree is obtained according to the node interference degree obtaining method, and the node interference degree obtaining method comprises:

[0124] Step C01, calculating the pseudo-range error wj` according to the actual pseudo-range error wj and the maximum tolerable error wj0, setting wj` = wj / wj0, and obtaining the pseudo-range error wj`;

[0125] Step C02, calculating the signal-to-noise ratio drop value xj` according to the actual signal-to-noise ratio drop value xj and the maximum tolerable signal-to-noise ratio drop value xj0, setting xj` = xj / xj0, and obtaining the signal-to-noise ratio drop value xj`;

[0126] Step C03, comparing the actual drift amount dj with the maximum tolerable drift amount dj0, and calculating the drift amount dj` according to the comparison result, setting dj` = dj / dj0, and obtaining the drift amount dj`;

[0127] Step C04, normalizing the pseudo-range error wj`, the signal-to-noise ratio drop value xj` and the drift amount dj` to obtain the normalized pseudo-range error wjc, the normalized signal-to-noise ratio drop value xjc and the normalized drift amount djc;

[0128] Step C05, calculating the node interference degree uc according to the normalized pseudo-range error wjc, the normalized signal-to-noise ratio drop value xjc, the normalized drift amount djc, the pseudo-range error weight w1, the signal-to-noise ratio drop value weight w2 and the drift amount weight w3, setting uc = wjc×w1+xjc×w2+djc×w3, and obtaining the node interference degree uc.

[0129] Specifically, the actual pseudo-range error refers to the deviation between the first positioning result measured value measured by GPS and the true geometric distance. The specific acquisition method of the actual pseudo-range error is not limited in the embodiment, and the related person skilled in the art can freely choose according to the actual demand, such as making the unmanned aerial vehicle measure the site with known true coordinates PC(x c ,y c ,z c ), and obtaining the measured value PB(x b ,y b ,z b ). The actual pseudo-range error wj is calculated according to the known true coordinates PC and the measured value PB, and set as The actual pseudo-range error wj is obtained, the maximum tolerance error is a preset value for calculating the pseudo-range error, and the maximum tolerance error is not limited in the embodiment. For example, the maximum tolerance error wj0 is set to 2 meters in the embodiment. The actual signal-to-noise ratio reduction value refers to the degree of reduction of the signal-to-noise ratio of the signal received by the unmanned aerial vehicle due to environmental interference. The signal-to-noise ratio refers to a specific value for measuring signal quality. The specific acquisition method of the actual signal-to-noise ratio reduction value is not limited in the embodiment. For example, the GNSS in the unmanned aerial vehicle can be used to acquire the signal-to-noise ratio VZ in the ideal environment and the signal-to-noise ratio VB in the current environment. The actual signal-to-noise ratio reduction value xj is calculated according to the signal-to-noise ratio VZ in the ideal environment and the signal-to-noise ratio VB in the current environment. It is set that xj = VZ - VB. The signal-to-noise ratio in the ideal environment refers to the best signal quality that the system can achieve in an interference-free and distortion-free environment. The specific acquisition method of the signal-to-noise ratio in the ideal environment is not limited in the embodiment. For example, the signal-to-noise ratio in the ideal environment is measured by placing the unmanned aerial vehicle in a laboratory environment. The maximum tolerance signal-to-noise ratio reduction value refers to a preset value for calculating the signal-to-noise ratio reduction value. The maximum tolerance signal-to-noise ratio reduction value is not limited in the embodiment. Those skilled in the art can freely select according to actual needs. For example, the maximum tolerance signal-to-noise ratio reduction value xj0 is set to -10 dB in the embodiment. The actual drift amount refers to the deviation between the actual position of the unmanned aerial vehicle and the target position when the unmanned aerial vehicle performs a task. The specific acquisition method of the actual drift amount is not limited in the embodiment. For example, the actual position (x v ,y v ,z v ) of the unmanned aerial vehicle is acquired by the GNSS in the unmanned aerial vehicle. The GNSS refers to a global navigation satellite system. The target position is not limited in the embodiment. For example, the target position is set to (x t ,y t ,z t ). The actual drift amount dj is calculated according to the actual position (x v ,y v ,z v ) of the unmanned aerial vehicle and the target position (x t ,y t ,z t ). It is set that The maximum tolerable drift refers to a preset value for calculating the drift. The present embodiment does not limit the maximum tolerable drift, and a person skilled in the related art can freely choose according to actual needs. For example, the present embodiment sets the maximum tolerable drift dj0=1.5 meters. The normalization process refers to a process of mapping the values of the pseudo-range error, the signal-to-noise ratio drop, and the drift to the [0, 1] interval. The present embodiment does not limit the specific way of normalization processing, and a person skilled in the related art can freely choose according to actual needs. For example, normalization processing is performed through paython. The pseudo-range error weight w1 refers to a coefficient for measuring the importance of the normalized pseudo-range error in the node interference degree. The signal-to-noise ratio drop weight w2 refers to a coefficient for measuring the importance of the normalized signal-to-noise ratio drop in the node interference degree. The drift weight w3 refers to a coefficient for measuring the importance of the normalized drift in the node interference degree. The present embodiment does not limit the pseudo-range error weight w1, the signal-to-noise ratio drop weight w2, and the drift weight w3, and a person skilled in the related art can freely choose according to actual needs. For example, the present embodiment sets w1=0.5, w2=0.3, and w3=0.2.

[0130] Specifically, the time delay data correction module acquires the node interference degree, so as to subsequently optimize the process of updating the node interference degree, thereby improving the efficiency of monitoring the time delay data.

[0131] Specifically, when the time delay data correction module optimizes the process of updating the node interference degree, the node interference degree uc is compared with the preset node interference degree uc0. The state of the node interference degree is judged according to the comparison result, and the preset suppression processing frequency pm0 is optimized according to the judgment result, wherein:

[0132] When uc≤uc0, the time delay data correction module determines that the state of the node interference degree is weak interference, and does not optimize the preset suppression processing frequency pm0.

[0133] When uc>uc0, the time delay data correction module determines that the state of the node interference degree is strong interference, and optimizes the preset suppression processing frequency pm0. The preset suppression processing frequency pm0 is optimized through the optimization coefficient yx, which is set as yx=0.42+0.22×e, where e is the base of natural logarithm. The optimized preset suppression processing frequency pm0` is obtained, which is set as pm0`=pm0×yx. The preset suppression processing frequency pm0 is replaced by the optimized preset suppression processing frequency pm0`, and the suppression processing frequency pm is compared with the preset suppression processing frequency pm0 again. -(uc-uc0)

[0134] ​Specifically, the preset node interference degree refers to a preset value for judging the state of the node interference degree, and the specific value of the preset node interference degree is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, the preset node interference degree uc0 is set to 0.32 in the embodiment. The state of the node interference degree refers to the strength of the node interference degree, and the state of the node interference degree includes weak interference and strong interference.

[0135] Specifically, the time delay data correction module judges the state of the node interference degree. When the state of the node interference degree is strong interference, the preset suppression processing frequency is reduced according to the optimization coefficient, and the suppression processing is updated in time. In the later period when the node interference degree maintains the state of strong interference, the rate of reducing the preset suppression processing frequency tends to be stable. According to the optimization coefficient, the constant term 0.42 in the optimization coefficient is the minimum value of the optimization coefficient, and the constant coefficient 0.22 is the change rate of the optimization coefficient. The change trend of the optimization coefficient is reduced from 0.64 to 0.42, so as to reasonably reduce the influence of the node interference degree on the processing update process, thereby improving the efficiency of correcting the time delay data.

[0136] Specifically, the positioning result output module fuses the first positioning result to obtain a fused positioning result and a positioning confidence zx.

[0137] Specifically, the fusion processing refers to a process of fusing the first positioning result and the first positioning result measurement value to finally obtain an accurate coordinate and a coordinate confidence of the current state. The specific manner of the fusion processing is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, the multi-sensor Kalman filter is taken as the specific manner of the fusion processing.

[0138] Specifically, the positioning result output module fuses the first positioning result to obtain a fused positioning result and a positioning confidence zx.

[0139] Specifically, when the positioning result output module outputs the final decision according to the fusion processing result, the positioning confidence zx is compared with a preset positioning confidence zx0. According to the comparison result, the positioning confidence is judged to meet the standard, and the final positioning result is output according to the judgment result, and the final decision is output according to the judgment result, wherein:

[0140] When zx≥ zx0, the positioning result output module determines that the positioning confidence meets the standard, and outputs a final decision, wherein the final decision is to output the fused positioning result as the final positioning result without performing final correction on the corrected time delay data.

[0141] When zx< zx0, the positioning result output module determines that the positioning confidence does not meet the standard, and outputs a final decision, wherein the final decision is not to output the fused positioning result as the final positioning result without performing final correction on the corrected time delay data.

[0142] Specifically, the final decision refers to an adjustment strategy for improving the accuracy of the final positioning result and the efficiency of time delay correction, which is made according to the positioning confidence meeting the standard. The preset positioning confidence refers to a preset value for judging whether the positioning confidence meets the standard. The specific value of the preset positioning confidence is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, zx0=0.8 is set in the embodiment. The positioning confidence meeting the standard refers to the degree of the positioning confidence meeting the standard, which is judged according to the positioning confidence and the preset positioning confidence. The positioning confidence meeting the standard includes meeting the standard and not meeting the standard. The final correction refers to a process of correcting the corrected time delay data by correcting the systematic errors of the unmanned aerial vehicle, thereby correcting the corrected time delay data. The systematic errors of the unmanned aerial vehicle refer to error values of the systematic errors of the unmanned aerial vehicle, which are highly related to the data collected by the sensor, such as receiver clock error and ionospheric delay. The specific method of the final correction is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, the corrected time delay data is finally corrected by a carrier phase quadratic correlation algorithm.

[0143] Specifically, the positioning result output module judges the positioning confidence meeting the standard, so as to output the final decision according to the positioning confidence meeting the standard, and finally correct the corrected time delay data in real time, thereby improving the accuracy of the final positioning result and the efficiency of time delay correction.

[0144] Specifically, when the positioning result output module adjusts the output process of the final decision according to the trigger frequency, the trigger frequency cp is compared with a preset trigger frequency cp0, the condition of the trigger frequency is judged according to the comparison result, and the preset positioning confidence zx0 is adjusted according to the judgment result, wherein:

[0145] When cp≤ cp0, the positioning result output module determines that the condition of the trigger frequency is normal, and does not adjust the preset positioning confidence zx0.

[0146] When cp > cp0, the positioning result output module determines that the trigger frequency is abnormal and adjusts the frequency of the preset location confidence zx0 according to the frequency adjustment coefficient px, which is set to px = 1.33 - 0.28 × e -(cp-cp0) Where e is the base of the natural logarithm, the adjusted preset positional reliability zx0` is obtained, zx0` is set to zx0×px, the preset positional reliability zx0 is replaced with the adjusted preset positional reliability zx0`, and the positional reliability zx is re-compared with the preset positional reliability zx0.

[0147] Specifically, the trigger frequency refers to the number of times resynchronization is triggered within a preset time period. Resynchronization refers to the process of re-acquiring the delay data according to the synchronization sequence, inputting the delay data into the delay data correction module and the positioning result output module to obtain the final positioning result. This embodiment does not limit the specific method of obtaining the number of times resynchronization is triggered. Those skilled in the art can freely choose according to actual needs, such as obtaining the number of times resynchronization is triggered through system logs. The preset trigger frequency refers to a preset value for judging the trigger frequency situation. This embodiment does not limit the specific value setting of the preset trigger frequency. Those skilled in the art can freely choose according to actual needs. For example, this embodiment sets the preset trigger frequency cp0 = 10 times / 0.1μs. The trigger frequency situation refers to the normality of the trigger frequency judged according to the trigger frequency and the preset trigger frequency. The trigger frequency situation includes normal and abnormal.

[0148] Specifically, the positioning result output module judges the trigger frequency. When the trigger frequency is abnormal, it rapidly increases the preset location confidence based on the frequency adjustment coefficient to output the final positioning result in a timely manner and perform final correction on the corrected delay data. When the trigger frequency remains abnormal in the later stages, the rate of increase of the preset location confidence tends to stabilize. The frequency adjustment coefficient is used to match this trend. In the frequency adjustment coefficient, the constant term 1.33 is the maximum value that the frequency adjustment coefficient can reach, and the constant coefficient 0.28 is the rate of change of the frequency adjustment coefficient, so that the trend of the frequency adjustment coefficient increases from 1.05 to 1.33. This is to reasonably reduce the impact of the trigger frequency on the output of the fusion processing result and the final correction of the corrected delay data, thereby improving the efficiency of delay correction.

[0149] Specifically, when the positioning result output module adjusts the frequency based on the node interference duration, it compares the node interference duration tt with the first preset node interference duration tt1 and the second preset node interference duration tt2. Based on the comparison result, it determines the state of the node interference duration and adjusts the preset trigger frequency cp0 based on the determination result.

[0150] When tt≤tt1, the positioning result output module determines that the duration of node interference is short and does not adjust the preset trigger frequency cp0 for interference.

[0151] When tt1 < tt ≤ tt2, the positioning result output module determines that the node interference duration is of medium duration, adjusts the preset trigger frequency cp0 for interference, and adjusts the preset trigger frequency cp0 for interference according to the interference adjustment coefficient gr. Where e is the base of the natural logarithm, the adjusted preset trigger frequency cp0` is obtained, cp0` is set to cp0×gr, the preset trigger frequency cp0 is replaced with the adjusted preset trigger frequency cp0`, and the trigger frequency cp is re-compared with the preset trigger frequency cp0;

[0152] When tt > tt2, the positioning result output module determines that the duration of node interference is long and performs manual correction on the corrected delay data.

[0153] Specifically, the node interference duration refers to the duration of multipath interference experienced by critical nodes when the UAV performs a positioning task. This embodiment does not limit the specific method for obtaining the node interference duration; those skilled in the art can freely choose according to actual needs, such as recording the node interference duration using Paython. The first preset node interference duration refers to the lower limit of the preset value for judging the state of the node interference duration, and the second preset node interference duration refers to the upper limit of the preset value for judging the state of the node interference duration. This embodiment does not limit the specific numerical settings of the first and second preset node interference durations; those skilled in the art can freely choose according to actual needs. For example, this embodiment sets the preset node interference durations tt1 = 6s and tt2 = 10s. The state of the node interference duration refers to the length of the node interference duration judged based on the node interference duration and the preset node interference duration. The state of the node interference duration includes short time, medium time, and long time. The manual correction refers to the process by which relevant technicians manually correct the corrected latency data, such as manually aligning the time series data directly through a visual interface to adjust the corrected latency data.

[0154] Specifically, the positioning result output module judges the duration of node interference. When the duration of node interference is moderate, the preset trigger frequency is rapidly reduced using an interference adjustment coefficient to adjust the frequency in a timely manner and increase the accuracy of the final decision. When the duration of node interference is between moderate and long, the trend of reducing the preset trigger frequency gradually stabilizes. An interference adjustment coefficient is set to match this trend. The constant term 0.74 in the interference adjustment coefficient is the minimum value of the interference adjustment coefficient, and the constant coefficient 0.16 is the rate of change of the interference adjustment coefficient, so that the trend of the interference adjustment coefficient decreases from 0.9 to 0.74. When the duration of node interference is long, the corrected delay data is corrected by manual intervention to select a reasonable method to reduce the impact of node interference duration on the final decision under different node interference duration states, thereby improving the efficiency of delay data correction.

[0155] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A synchronization sequence extraction and timing correction system for drone positioning, characterized in that, The system comprises: An original sequence acquisition module is configured to acquire an original sequence; A time delay data acquisition module is configured to synchronize the original sequence by a synchronization sequence extraction method to obtain a synchronization sequence, and acquire time delay data according to the synchronization sequence; A time delay data correction module is configured to preliminarily correct the time delay data according to a predicted clock drift amount to obtain corrected time delay data, acquire a first positioning result according to the corrected time delay data, acquire a residual norm according to the first positioning result, and suppress the corrected time delay data according to the residual norm, and update the suppression processing according to a suppression processing frequency, and optimize the process of the update according to a node interference degree; A positioning result output module is configured to fuse the first positioning result to obtain a fusion processing result, and output a final decision according to the fusion processing result, adjust the output process of the final decision according to a trigger frequency, and adjust the process of the frequency adjustment according to a node interference duration; The synchronization sequence extraction method comprises: Step A01, according to the original sequence , ideal sequence complex conjugate , sampling point sequence number , sliding window length , and original sequence length Calculate the cross-correlation value set Rrs, set Rrs , get the cross-correlation value set Rrs={Rrs1, Rrs2, Rrs3,..., Rrsn}; Step A02, peak detection is performed on the set of cross-correlation values Rrs={Rrs1, Rrs2, Rrs3,..., Rrsn} to obtain a peak value and a first peak position Mpeak1; Step A03, according to the peak value the previous window cross-correlation value and the next window cross-correlation value Calculate the position error a, set a , get the position error a; Step A04, calculating a target peak position Mpeak according to a position error α and a first peak position Mpeak1, setting Mpeak=Mpeak1+α, and obtaining the target peak position Mpeak; Step A05, marking the peak value in the original sequence and the target peak position Mpeak, to obtain a synchronization sequence; The time delay data acquisition module acquires the time delay data according to the synchronization sequence, calculates the time delay data ts according to the target peak position Mpeak and a sampling frequency fs, and sets ts=Mpeak / fs to obtain the time delay data ts.

2. The system for synchronization sequence extraction and timing correction for drone positioning of claim 1, wherein, The time delay data correction module preliminarily corrects the time delay data according to the predicted clock drift amount, calculates a current clock drift amount tp according to a ground control station sending timestamp t1, a UAV receiving timestamp t2, a UAV sending timestamp t3, and a ground control station receiving timestamp t4, and sets tp=[(t2-t1)-(t3-t4)] / 2 to obtain the current clock drift amount tp; The current clock drift amount tp and a current environment temperature are input into a clock drift prediction model to obtain a predicted clock drift amount ti, the corrected time delay data tse is calculated according to the time delay data ts, the predicted clock drift amount ti, and a compensation coefficient β, and tse=ts-β×ti is set to obtain the corrected time delay data tse.

3. The synchronization sequence extraction and timing correction system for drone positioning of claim 2, wherein, The time delay data correction module acquires the first positioning result according to the corrected time delay data by a positioning result acquisition method, and the positioning result acquisition method comprises: Step B01, acquiring first reference point corrected time delay data tse1, second reference point corrected time delay data tse2, and third reference point corrected time delay data tse3; Step B02, calculating a first positioning distance d1 according to the first reference point corrected time delay data tse1 and the speed of light c, and setting d1=tse1×c to obtain the first positioning distance d1; According to the second reference point corrected time delay data tse2 and the speed of light c, the second positioning distance d2 is calculated, and d2=tse2xc is set to obtain the second positioning distance d2; According to the third reference point corrected time delay data tse3 and the speed of light c, the third positioning distance d3 is calculated, and d3=tse3xc is set to obtain the third positioning distance d3; Step B03, constructing a positioning equation according to the first positioning distance d1, the second positioning distance d2, the third positioning distance d3, the reference node coordinates (x0, y0, z0), the first reference node coordinates (x1, y1, z1), the second reference node coordinates (x2, y2, z2), the third reference node coordinates (x3, y3, z3), and the target positioning point coordinates (x, y, z), and setting: , , , , , , , , , , , , , , , ， Step B04: Solve the positioning equation to obtain the coordinates of the target positioning point. , , ), the coordinates of the target location point ( , , () is used as the first localization result.

4. The synchronization sequence extraction and timing correction system for drone positioning of claim 3, wherein, When the delay data correction module obtains the residual norm based on the first positioning result, it does so based on the first positioning result ( , , ), first positioning result measurement value ( , , ) Calculate the position vector difference r, and set r = The position vector difference r is obtained, and according to the position vector difference r = Obtain the residual norm rp and set... The residual norm rp is obtained; When the residual norm rp is less than or equal to the preset residual norm rp0, the time delay data correction module determines that the residual norm meets the standard, and does not suppress the corrected time delay data. When the residual norm rp is less than or equal to the preset residual norm rp0, the time delay data correction module determines that the residual norm meets the standard, and does not suppress the corrected time delay data. When the residual norm rp is greater than the preset residual norm rp0, the time delay data correction module determines that the residual norm does not meet the standard, and suppresses the corrected time delay data until the residual norm meets the standard. When the residual norm rp is greater than the preset residual norm rp0, the time delay data correction module determines that the residual norm does not meet the standard, and suppresses the corrected time delay data until the residual norm meets the standard. Step D01, calculate the current time delay credibility pk` according to the last time delay credibility pk, the credibility parameter u and the last time gain kk, set pk`= , get the current time delay credibility pk`; Step D02, according to the current time delay credibility pk', the credibility parameter u, the current gain kk' is calculated, and kk' is set as , the current gain kk' is obtained; Step D03, according to the corrected time delay data tse, the current gain kk` and the time delay measurement value tses, the twice corrected time delay data tse` is calculated, and tse`=tse+kk×(tses-tse) is set to obtain the twice corrected time delay data tse`; Step D04, the corrected time delay data tse is replaced by the twice corrected time delay data tse`, and the first positioning result is obtained according to the corrected time delay data, and the residual norm is reacquired according to the first positioning result, and the residual norm meets the standard is rejudged according to the residual norm rp and the preset residual norm rp0, until the residual norm meets the standard.

5. The synchronization sequence extraction and timing correction system for drone positioning of claim 4, wherein, When the residual norm rp is less than or equal to the preset residual norm rp0, the time delay data correction module determines that the residual norm meets the standard, and does not suppress the corrected time delay data. When the residual norm rp is greater than the preset residual norm rp0, the time delay data correction module determines that the residual norm does not meet the standard, and suppresses the corrected time delay data until the residual norm meets the standard. When the residual norm rp is greater than the preset residual norm rp0, the time delay data correction module determines that the residual norm does not meet the standard, and suppresses the corrected time delay data until the residual norm meets the standard. When the residual norm rp is greater than the preset residual norm rp0, the time delay data correction module determines that the residual norm does not meet the standard, and suppresses the corrected time delay data until the residual norm meets the standard. When the residual norm rp is greater than the preset residual norm rp0, the time delay data correction module determines that the residual norm does not meet the standard, and suppresses the corrected time delay data until the residual norm meets the standard.

6. The synchronization sequence extraction and timing correction system for drone positioning of claim 5, wherein, The time delay data correction module obtains the node interference degree according to a node interference degree obtaining method when optimizing the process of updating according to the node interference degree, and the node interference degree obtaining method comprises: Step C01, calculating the pseudo-range error wj` according to the actual pseudo-range error wj and the maximum tolerable error wj0, setting wj`=wj / wj0, and obtaining the pseudo-range error wj`; Step C02, calculating the signal-to-noise ratio drop value xj` according to the actual signal-to-noise ratio drop value xj and the maximum tolerable signal-to-noise ratio drop value xj0, setting xj`=xj / xj0, and obtaining the signal-to-noise ratio drop value xj`; Step C03, comparing the actual drift amount dj with the maximum tolerable drift amount dj0, and calculating the drift amount dj` according to the comparison result, setting dj`=dj / dj0, and obtaining the drift amount dj`; Step C04, normalizing the pseudo-range error wj`, the signal-to-noise ratio drop value xj`, and the drift amount dj` to obtain the normalized pseudo-range error wjc, the normalized signal-to-noise ratio drop value xjc, and the normalized drift amount djc; Step C05, calculating the node interference degree uc according to the normalized pseudo-range error wjc, the normalized signal-to-noise ratio drop value xjc, the normalized drift amount djc, the pseudo-range error weight w1, the signal-to-noise ratio drop value weight w2, and the drift amount weight w3, setting uc=wjc×w1+xjc×w2+djc×w3, and obtaining the node interference degree uc; When optimizing the process of updating according to the node interference degree, the time delay data correction module compares the node interference degree uc with the preset node interference degree uc0, judges the state of the node interference degree according to the comparison result, and optimizes the preset suppression processing frequency pm0 according to the judgment result, wherein: When uc≤uc0, the time delay data correction module determines that the state of the node interference degree is weak interference, and does not optimize the preset suppression processing frequency pm0; When uc>uc0, the delay data correction module determines that the state of the node interference degree is strong interference, optimizes preset suppression processing frequency pm0, optimizes preset suppression processing frequency pm0 through optimization coefficient yx, sets yx=0.42+0.22×e -(uc-uc0)， Wherein, e is the base of natural logarithm, obtains optimized preset suppression processing frequency pm0`, sets pm0`=pm0×yx, replaces the preset suppression processing frequency pm0 with the optimized preset suppression processing frequency pm0`, and recompares the suppression processing frequency pm with the preset suppression processing frequency pm0. The positioning result output module performs fusion processing on the first positioning result to obtain a fused positioning result and a positioning confidence zx, and takes the fused positioning result and the positioning confidence zx as the fusion processing result.

7. The synchronization sequence extraction and timing correction system for drone positioning of claim 6, wherein, When outputting the final decision according to the fusion processing result, the positioning result output module compares the positioning confidence zx with the preset positioning confidence zx0, judges whether the positioning confidence meets the standard according to the comparison result, and outputs the final positioning result and the final decision according to the judgment result, wherein: When zx≥zx0, the positioning result output module determines that the positioning confidence meets the standard, outputs the final decision, and the content of the final decision is to output the fused positioning result as the final positioning result without finally correcting the corrected time delay data; When zx<zx0, the positioning result output module determines that the positioning confidence does not meet the standard, outputs the final decision, and the content of the final decision is not to output the fused positioning result as the final positioning result and to finally correct the corrected time delay data.

8. The synchronization sequence extraction and timing correction system for drone positioning of claim 7, wherein, When the positioning result output module adjusts the output process of the final decision according to the trigger frequency, the trigger frequency cp is compared with a preset trigger frequency cp0, the condition of the trigger frequency is judged according to the comparison result, and the preset position confidence zx0 is adjusted in frequency according to the judgment result, wherein: When cp≤cp0, the positioning result output module determines that the condition of the trigger frequency is normal, and does not adjust the preset position confidence zx0 in frequency. When cp>cp0, the positioning result output module determines that the triggering frequency is abnormal, adjusts the preset position confidence zx0 in frequency, adjusts the preset position confidence zx0 in frequency according to a frequency adjustment coefficient px, sets px=1.33-0.28×e -（cp-cp0） , where e is the base of natural logarithm, obtains the adjusted preset position confidence zx0`, sets zx0`=zx0×px, replaces the preset position confidence zx0 with the adjusted preset position confidence zx0`, and recompares the position confidence zx with the preset position confidence zx0.

9. The synchronization sequence extraction and timing correction system for drone positioning of claim 8, wherein, When the positioning result output module adjusts the interference according to the process of frequency adjustment, the node interference duration is compared with the first preset node interference duration and the second preset node interference duration , the state of the node interference duration is judged according to the comparison result, and the preset trigger frequency cp0 is adjusted according to the judgment result. When ≤ , the positioning result output module determines that the state of the node interference duration is short time, and does not perform interference adjustment on the preset trigger frequency cp0. When < ≤ , the positioning result output module determines that the state of the node interference duration is medium time, adjusts the preset trigger frequency cp0, adjusts the preset trigger frequency cp0 according to the interference adjustment coefficient gr, sets gr= , where e is the base of natural logarithm, obtains the adjusted preset trigger frequency cp0`, sets cp0`=cp0×gr, replaces the preset trigger frequency cp0 with the adjusted preset trigger frequency cp0`, and recompares the trigger frequency cp with the preset trigger frequency cp0. when > When the positioning result output module determines that the duration of node interference is long, it manually corrects the modified delay data.

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