UAV measurement and control signal capture method, related device and computer storage medium

Abstract

The present application provides a method for capturing UAV measurement and control signals, related devices and computer storage media. The predicted value of the Doppler frequency deviation of the UAV measurement and control signal is calculated based on the current time in the current low-orbit satellite ephemeris information, the distance between the current low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light; the rough estimated value of the Doppler frequency deviation of the UAV measurement and control signal is determined based on the sampling result of the UAV measurement and control received signal and the prediction error range; the rough estimated value of the Doppler frequency deviation of the UAV measurement and control signal is corrected using the Shannon interpolation algorithm to obtain the value of the Doppler frequency deviation of the UAV measurement and control signal; finally, the carrier frequency is compensated based on the rough estimated value and the precise estimated value of the Doppler frequency deviation of the UAV measurement and control signal to obtain the compensated UAV measurement and control signal. The frequency domain search range is effectively narrowed, the signal capture time is shortened, and the estimation accuracy of the Doppler frequency deviation is improved, thereby improving the accuracy of the UAV measurement and control signal.

Description

Technical Field

[0001] The present application relates to the field of UAV measurement and control communication technology, and in particular to a method for capturing UAV measurement and control signals, related devices and computer storage media. Background Art

[0002] At present, the UAV measurement and control signal acquisition methods based on low-orbit satellite communications are mainly based on the Partial Match Filter-Fast Fourier Transform (PMF-FFT) method and some improved PMF-FFT methods. The PMF-FFT method can accurately estimate the signal Doppler frequency offset and realize rapid signal acquisition in a large frequency offset environment. The frequency domain attenuation and scallop loss of the PMF-FFT method can be improved by the window function method and the zero padding method. The acquisition probability in the case of low signal-to-noise ratio can be improved by the frequency domain differential incoherent accumulation method. However, the above-mentioned improved methods have failed to narrow the frequency domain search range and reduce the acquisition time. At the same time, the frequency offset estimation accuracy of the above-mentioned improved methods is greatly affected by the number of partial match filters (PMF) and the number of Fast Fourier Transform (FFT) points. Under the condition of limited hardware resources, the Doppler frequency offset estimation accuracy cannot be further improved. Summary of the invention

[0003] In view of this, the present application provides a method for capturing UAV measurement and control signals, related devices and computer storage media, which effectively narrow the frequency domain search range, shorten the signal capture time, and improve the estimation accuracy of Doppler frequency deviation, thereby improving the accuracy of UAV measurement and control signals.

[0004] The first aspect of the present application provides a method for capturing a UAV measurement and control signal, comprising:

[0005] Obtaining the current low-orbit satellite ephemeris information; wherein the current low-orbit satellite ephemeris information includes the current time, the distance between the current low-orbit satellite and the drone, and the carrier frequency of the transmitted signal;

[0006] According to the current time, the distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light, the predicted value of the Doppler frequency deviation of the UAV measurement and control signal is calculated;

[0007] Sampling the UAV measurement and control received signal to obtain a sampling result; wherein the received signal carrier Doppler total frequency deviation during the sampling process is the difference between the initial received signal carrier Doppler total frequency deviation and the predicted value of the UAV measurement and control signal Doppler frequency deviation;

[0008] Determine a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range; wherein the prediction error range is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal taking into account the orbital height and orbital eccentricity of the low-orbit satellite;

[0009] The Shannon interpolation algorithm is used to correct the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal to obtain the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal;

[0010] The rough estimate value and precise estimate value of the Doppler frequency deviation of the UAV measurement and control signal are sent to the carrier digital oscillator for carrier frequency compensation to obtain the compensated UAV measurement and control signal; wherein the generation frequency of the carrier digital oscillator is the sum of the center frequency of the transmitting signal carrier and the total Doppler frequency deviation of the target receiving signal carrier; the total Doppler frequency deviation of the target receiving signal carrier is the sum of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, the rough estimate value of the Doppler frequency deviation of the UAV measurement and control signal and the precise estimate value of the Doppler frequency deviation of the UAV measurement and control signal.

[0011] Optionally, sampling the drone measurement and control received signal to obtain a sampling result includes:

[0012] Sampling is performed according to the number of sampling points, the pseudo code sequence, the center frequency of the carrier of the transmitted signal, the total Doppler frequency deviation of the carrier of the received signal, the signal sampling rate and the phase of the received signal to obtain the sampling result.

[0013] Optionally, determining a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range includes:

[0014] Performing partial matched filtering-Fourier transform on the sampling results to obtain L amplitude-frequency response results; wherein L is a positive integer;

[0015] Performing differential non-correlated accumulation according to all the amplitude-frequency response results to obtain a differential non-correlated accumulation result;

[0016] The peak value of the differential non-correlated accumulation result is detected according to the prediction error range to obtain a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal.

[0017] Optionally, performing peak detection on the differential non-correlated accumulation result according to the prediction error range to obtain a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal includes:

[0018] Determining a search range of differential non-correlated cumulative results according to the prediction error range;

[0019] In the search range of the differential non-correlated cumulative results, searching for the maximum differential non-correlated cumulative result;

[0020] A rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is generated according to the maximum differential non-correlated accumulation result.

[0021] The second aspect of the present application provides a device for capturing a UAV measurement and control signal, comprising:

[0022] An acquisition unit is used to acquire the current low-orbit satellite ephemeris information; wherein the current low-orbit satellite ephemeris information includes the current time, the distance between the current low-orbit satellite and the UAV, and the carrier frequency of the transmitted signal;

[0023] A calculation unit, used to calculate the predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time, the current distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light;

[0024] A sampling unit is used to sample the UAV measurement and control received signal to obtain a sampling result; wherein the received signal carrier Doppler total frequency deviation during the sampling process is the difference between the initial received signal carrier Doppler total frequency deviation and the predicted value of the UAV measurement and control signal Doppler frequency deviation;

[0025] A rough estimation unit is used to determine a rough estimation value of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range; wherein the prediction error range is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal taking into account the orbital height and orbital eccentricity of the low-orbit satellite;

[0026] A precise estimation unit, used to correct the rough estimation value of the Doppler frequency deviation of the UAV measurement and control signal by using a Shannon interpolation algorithm to obtain a precise estimation value of the Doppler frequency deviation of the UAV measurement and control signal;

[0027] The compensation unit is used to send the rough estimate value and the precise estimate value of the Doppler frequency deviation of the UAV measurement and control signal to the carrier digital oscillator to perform carrier frequency compensation to obtain the compensated UAV measurement and control signal; wherein the generation frequency of the carrier digital oscillator is the sum of the center frequency of the transmitting signal carrier and the total Doppler frequency deviation of the target receiving signal carrier; the total Doppler frequency deviation of the target receiving signal carrier is the sum of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, the rough estimate value of the Doppler frequency deviation of the UAV measurement and control signal and the precise estimate value of the Doppler frequency deviation of the UAV measurement and control signal.

[0028] Optionally, the sampling unit includes:

[0029] The sampling subunit is used to perform sampling according to the number of sampling points, the pseudo code sequence, the center frequency of the carrier of the transmitted signal, the total Doppler frequency deviation of the carrier of the received signal, the signal sampling rate and the phase of the received signal to obtain the sampling result.

[0030] Optionally, the rough estimation unit includes:

[0031] A transform unit, used for performing partial matched filtering-Fourier transform on the sampling result to obtain L amplitude-frequency response results; wherein L is a positive integer;

[0032] An accumulation unit, used for performing differential non-correlation accumulation according to all the amplitude-frequency response results to obtain a differential non-correlation accumulation result;

[0033] The coarse estimation subunit is used to perform peak detection on the differential non-correlated accumulation result according to the prediction error range to obtain a coarse estimation value of the Doppler frequency deviation of the UAV measurement and control signal.

[0034] Optionally, the coarse estimation subunit includes:

[0035] A determination unit, used to determine a search range of a differential non-correlated cumulative result according to the prediction error range;

[0036] A searching unit, configured to search for the maximum differential non-correlated cumulative result within the search range of the differential non-correlated cumulative result;

[0037] A generating unit is used to generate a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the maximum differential non-correlated accumulation result.

[0038] A third aspect of the present application provides an electronic device, including:

[0039] one or more processors;

[0040] a storage device having one or more programs stored thereon;

[0041] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for capturing the UAV measurement and control signal as described in any one of the first aspects.

[0042] A fourth aspect of the present application provides a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for capturing the UAV measurement and control signal as described in any one of the first aspects is implemented.

[0043] It can be seen from the above scheme that the present application provides a method for capturing UAV measurement and control signals, related devices and computer storage media, by calculating the predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time in the current low-orbit satellite ephemeris information, the distance between the current low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light; according to the sampling result of the UAV measurement and control received signal and the prediction error range, the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is determined; then, the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is corrected by the Shannon interpolation algorithm to obtain the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal; finally, the rough estimate and precise estimate of the Doppler frequency deviation of the UAV measurement and control signal are sent to the carrier digital oscillator to perform carrier frequency compensation to obtain the compensated UAV measurement and control signal. It effectively narrows the frequency domain search range, shortens the signal capture time, and improves the estimation accuracy of the Doppler frequency deviation, thereby improving the accuracy of the UAV measurement and control signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0045] Figure 1 A specific flow chart of a method for capturing UAV measurement and control signals provided in an embodiment of the present application;

[0046] Figure 2 A flowchart for determining a rough estimate of Doppler frequency deviation of a UAV measurement and control signal provided by another embodiment of the present application;

[0047] Figure 3 A flowchart of a peak detection method provided in another embodiment of the present application;

[0048] Figure 4 A schematic diagram of using a SinC function interpolation method to obtain a Doppler frequency offset estimate according to another embodiment of the present application;

[0049] Figure 5 A flowchart of a method for capturing UAV measurement and control signals provided in another embodiment of the present application;

[0050] Figure 6 A schematic diagram of a device for capturing UAV measurement and control signals provided in another embodiment of the present application;

[0051] Figure 7 A schematic diagram of an electronic device for implementing a method for capturing UAV measurement and control signals provided in another embodiment of the present application. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0053] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0054] It should be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0055] It should be noted that the concepts such as "first" and "second" mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0056] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0057] The present application embodiment provides a method for capturing a UAV measurement and control signal, such as Figure 1 As shown, the specific steps include:

[0058] S101. Obtain current low-orbit satellite ephemeris information.

[0059] Among them, the current low-orbit satellite ephemeris information includes the current time, the distance between the current low-orbit satellite and the UAV, and the carrier frequency of the transmitted signal.

[0060] It should be noted that, in general, the carrier Doppler frequency deviation caused by satellite motion is approximately within the range of ±5kHz, but low-orbit satellites are in a high dynamic environment, and the Doppler frequency deviation variation range will expand to tens of kHz or even hundreds of kHz. Since the frequency domain search range depends on the range of the Doppler frequency deviation, this will cause the signal capture time to increase exponentially. Therefore, the present application uses satellite ephemeris information to first make a preliminary prediction of the Doppler frequency deviation value of the UAV measurement and control signal carrier, and obtain the predicted value of the Doppler frequency deviation of the UAV measurement and control signal. Subsequently, the predicted value of the Doppler frequency deviation of the UAV measurement and control signal is passed to the signal carrier search control part, and within the error range of the carrier Doppler frequency deviation value assisted by the satellite ephemeris information prediction, the coarse frequency deviation and fine frequency deviation of the received signal carrier Doppler are estimated, which can greatly narrow the search range and reduce the capture time.

[0061] S102, calculating a predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time, the current distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal, and the speed of light.

[0062] In the specific implementation process of the present application, a spherical geometry method with lower computational complexity may be used but is not limited to it, and is not limited here.

[0063] Calculate the predicted value of Doppler frequency deviation of UAV measurement and control signal The formula can be as follows:

[0064] ;in, is the carrier frequency of the transmitted signal, the speed of light , is the current distance between the low-orbit satellite and the drone, is the radial velocity of the UAV and the satellite at the current moment, For the current moment.

[0065] S103: Sampling the UAV measurement and control received signal to obtain a sampling result.

[0066] The total Doppler frequency deviation of the received signal carrier during the sampling process is the difference between the total Doppler frequency deviation of the initial received signal carrier and the predicted value of the Doppler frequency deviation of the UAV measurement and control signal.

[0067] Specifically, the specific implementation method of sampling the UAV measurement and control received signal to obtain the sampling result may be, but is not limited to, sampling according to the number of sampling points, pseudo code sequence, center frequency of the transmitted signal carrier, total Doppler frequency deviation of the received signal carrier, signal sampling rate and received signal phase to obtain the sampling result, which is not limited here.

[0068] In the specific implementation process of this application, the following formula can be used for sampling to obtain the sampling result:

[0069] ;

[0070] in, is the number of sampling points, r I (m) is the I-channel sampling data (same-direction component), r Q (m) is the Q-channel sampling data (orthogonal component), j is the imaginary unit, is a pseudo code sequence, is the center frequency of the carrier of the transmitted signal, is the total Doppler frequency deviation of the received signal carrier, is the signal sampling rate, It should be noted that, in this application, after calculating the predicted value of the Doppler frequency deviation of the UAV measurement and control signal based on the current time, the current distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal, and the speed of light, the initial received signal carrier Doppler total frequency deviation is converted to ,and The error range of is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal. In general, the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal can be controlled within ±2kHz, which greatly reduces the search range of frequency capture in the subsequent stage and reduces the system capture time.

[0071] S104: Determine a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal based on the sampling result and the prediction error range.

[0072] The prediction error range is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, taking into account the orbital height and orbital eccentricity of the low-orbit satellite. In general, the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal can be controlled within ±2kHz.

[0073] Optionally, in another embodiment of the present application, an implementation of step S104 is as follows: Figure 2 As shown, including:

[0074] S201, performing partial matched filtering-Fourier transform on the sampling results to obtain L amplitude-frequency response results.

[0075] Wherein, L is a positive integer.

[0076] Specifically, using the PMF-FFT method, the normalized amplitude-frequency response of the system is:

[0077] ;

[0078] in, For the The magnitude-frequency response of the FFT output is , is the number of matched filters, For the length of each matched filter, , K is the number of FFT points.

[0079] S202: Perform differential non-correlated accumulation according to all amplitude-frequency response results to obtain differential non-correlated accumulation results.

[0080] Specifically, differential non-coherent accumulation is performed on the L-fold FFT output results to suppress noise interference and obtain differential non-coherent accumulation results. :

[0081] ;

[0082] S203: Perform peak detection on the differential non-correlated cumulative result according to the prediction error range to obtain a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal.

[0083] Specifically, the peak value of the differential non-correlated cumulative result is detected by predicting the error range, and a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is obtained, which significantly reduces the detection time of the peak search.

[0084] Optionally, in another embodiment of the present application, an implementation of step S203 is as follows: Figure 3 As shown, including:

[0085] S301. Determine a search range for differential non-correlated cumulative results according to a prediction error range.

[0086] Specifically, the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal obtained by the PMF-FFT method is , the rough estimation accuracy of the Doppler frequency deviation of the UAV measurement and control signal is .Pick , , ,but From the prior information in step S103, we know ,at this time , so the search range of the difference non-correlated cumulative result is .

[0087] S302: Search for the largest differential non-correlated cumulative result within the search range of the differential non-correlated cumulative result.

[0088] Continuing with the above example, Search for the largest cumulative result in the above range .

[0089] S303: Generate a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the maximum differential non-correlated accumulation result.

[0090] Continuing with the above example, the frequency deviation is marked as , so the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is After the rough frequency offset estimation is completed, the symbol phase in the code generator is the system symbol phase capture value, and the pseudo code alignment is completed. On the basis of the traditional PMF-FFT capture method, frequency domain differential incoherent accumulation and other processing measures are adopted to reduce the influence of noise and improve the signal capture probability.

[0091] S105. Correct the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal using the Shannon interpolation algorithm to obtain the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal.

[0092] It is understandable that since FFT is an integer operation, the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is generally rounded off. , so there is a certain Doppler estimation error.

[0093] To this end, this application uses the Shannon interpolation algorithm (SinC function interpolation method) to correct the coarse estimate of the Doppler frequency deviation of the UAV measurement and control signal, and obtains the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal, overcoming the cumulative loss caused by the FFT fence effect and segmented accumulation, and further improving the frequency deviation estimation accuracy.

[0094] Specifically, the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is , the peak detection is .make and are the Doppler frequency deviation markers on the left and right sides. , then at this time is the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal. and There is a significant difference in the value (specifically, it can be determined by setting a difference threshold, which can be but not limited to 10%. and If the value of is greater than 10%, there is an obvious difference), the SinC function interpolation method is used to correct the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal.

[0095] assumed , then select SinC function interpolation is performed between the data; otherwise, select Function interpolation is used between data, such as Figure 4 As shown. Let the SinC function interpolation expression be:

[0096] ;

[0097] by Take the case as an example, then:

[0098] ;

[0099] ;

[0100] therefore:

[0101] ;

[0102] Finish After solving, the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal is .

[0103] S106, sending the coarse estimation value and the precise estimation value of the Doppler frequency deviation of the UAV measurement and control signal to the carrier digital oscillator to perform carrier frequency compensation to obtain the compensated UAV measurement and control signal.

[0104] The frequency generated by the carrier digital oscillator (NCO) is the sum of the center frequency of the carrier of the transmitting signal and the total Doppler frequency deviation of the carrier of the target receiving signal, that is, The total carrier Doppler frequency deviation of the target received signal is the sum of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, the rough estimated value of the Doppler frequency deviation of the UAV measurement and control signal, and the precise estimated value of the Doppler frequency deviation of the UAV measurement and control signal, that is, . The carrier NCO generates a frequency It is sent to the carrier digital oscillator for carrier frequency compensation to obtain the compensated UAV measurement and control signal, thus completing the signal carrier synchronization.

[0105] like Figure 5 As shown, it is a flow chart of a method for capturing UAV measurement and control signals provided in an embodiment of the present application. First, ephemeris-assisted frequency deviation estimation is performed according to satellite ephemeris information to obtain , sample the UAV measurement and control receiving signal, obtain the sampling result, perform partial matched filtering-Fourier transform on the sampling result, and obtain L amplitude-frequency response results Then perform differential non-coherent accumulation on the L-times FFT output results to suppress noise interference and obtain differential non-coherent accumulation results , according to the prediction error range The peak value of the differential non-correlated accumulation result is detected at ±2kHz to obtain a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal. , and the total Doppler frequency deviation of the initial received signal carrier becomes Then, the Shannon interpolation algorithm (SinC function interpolation method) is used to roughly estimate the Doppler frequency deviation of the UAV measurement and control signal. Correction is performed to obtain the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal. .according to , and , generate the target received signal carrier Doppler total frequency deviation, and generate the carrier NCO generation frequency according to the target received signal carrier Doppler total frequency deviation and the transmission signal carrier center frequency, and send the carrier NCO generation frequency to the carrier digital oscillator for carrier frequency compensation to obtain the compensated UAV measurement and control signal, thus completing the signal carrier synchronization. The capture of UAV measurement and control signals based on low-orbit satellite communication is divided into three stages, which are carried out from three dimensions: Doppler frequency deviation range prediction, coarse Doppler frequency deviation estimation and fine Doppler frequency deviation estimation, step by step, to collaboratively complete the frequency compensation and symbol synchronization of the measurement and control signal, and finally achieve signal capture.

[0106] It can be seen from the above scheme that the present application provides a method for capturing UAV measurement and control signals, by calculating the predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time in the current low-orbit satellite ephemeris information, the distance between the current low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light; determining the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result of the UAV measurement and control receiving signal and the prediction error range; then, using the Shannon interpolation algorithm to correct the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal to obtain the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal; finally, the rough estimate and precise estimate of the Doppler frequency deviation of the UAV measurement and control signal are sent to the carrier digital oscillator for carrier frequency compensation to obtain the compensated UAV measurement and control signal. It effectively narrows the frequency domain search range, shortens the signal capture time, and improves the estimation accuracy of the Doppler frequency deviation, thereby improving the accuracy of the UAV measurement and control signal, and is suitable for UAV measurement and control scenarios based on low-orbit satellite communications with high dynamics and low signal-to-noise ratio.

[0107] The present application embodiment provides a device for capturing UAV measurement and control signals, such as Figure 6 As shown, specifically including:

[0108] The acquisition unit 601 is used to acquire the current low-orbit satellite ephemeris information.

[0109] Among them, the current low-orbit satellite ephemeris information includes the current time, the distance between the current low-orbit satellite and the UAV, and the carrier frequency of the transmitted signal.

[0110] The calculation unit 602 is used to calculate the predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time, the current distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light.

[0111] The sampling unit 603 is used to sample the UAV measurement and control received signal to obtain a sampling result.

[0112] The total Doppler frequency deviation of the received signal carrier during the sampling process is the difference between the total Doppler frequency deviation of the initial received signal carrier and the predicted value of the Doppler frequency deviation of the UAV measurement and control signal.

[0113] Optionally, in another embodiment of the present application, an implementation of the sampling unit 603 includes:

[0114] The sampling subunit is used to perform sampling according to the number of sampling points, the pseudo code sequence, the center frequency of the carrier of the transmitted signal, the total Doppler frequency deviation of the carrier of the received signal, the signal sampling rate and the phase of the received signal to obtain the sampling result.

[0115] The specific working process of the units disclosed in the above embodiments of the present application can be found in the corresponding method embodiments, which will not be repeated here.

[0116] The coarse estimation unit 604 is used to determine a coarse estimation value of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range.

[0117] Among them, the prediction error range is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal taking into account the orbital height and orbital eccentricity of the low-orbit satellite.

[0118] Optionally, in another embodiment of the present application, an implementation of the coarse estimation unit 604 includes:

[0119] The transform unit is used to perform partial matched filtering-Fourier transform on the sampling results to obtain L amplitude-frequency response results.

[0120] Wherein, L is a positive integer.

[0121] The accumulation unit is used for performing differential non-correlated accumulation according to all amplitude-frequency response results to obtain differential non-correlated accumulation results.

[0122] The coarse estimation subunit is used to perform peak detection on the differential non-correlated accumulation result according to the prediction error range to obtain a coarse estimation value of the Doppler frequency deviation of the UAV measurement and control signal.

[0123] For the specific working process of the units disclosed in the above embodiments of the present application, please refer to the corresponding method embodiments, such as Figure 2 As shown, no further description is given here.

[0124] Optionally, in another embodiment of the present application, an implementation of the coarse estimation subunit includes:

[0125] The determination unit is used to determine the search range of the differential non-correlated cumulative results according to the prediction error range.

[0126] The search unit is used to search for the maximum differential non-correlated cumulative result within the search range of the differential non-correlated cumulative result.

[0127] The generating unit is used to generate a rough estimation value of the Doppler frequency deviation of the UAV measurement and control signal according to the maximum differential non-correlated accumulation result.

[0128] For the specific working process of the units disclosed in the above embodiments of the present application, please refer to the corresponding method embodiments, such as Figure 3 As shown, no further description is given here.

[0129] The precise estimation unit 605 is used to correct the coarse estimation value of the Doppler frequency deviation of the UAV measurement and control signal by using the Shannon interpolation algorithm to obtain the precise estimation value of the Doppler frequency deviation of the UAV measurement and control signal.

[0130] The compensation unit 606 is used to send the coarse estimation value and the precise estimation value of the Doppler frequency deviation of the UAV measurement and control signal to the carrier digital oscillator to perform carrier frequency compensation to obtain the compensated UAV measurement and control signal.

[0131] Among them, the generation frequency of the carrier digital oscillator is the sum of the center frequency of the transmitting signal carrier and the total Doppler frequency deviation of the target receiving signal carrier; the total Doppler frequency deviation of the target receiving signal carrier is the sum of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, the rough estimated value of the Doppler frequency deviation of the UAV measurement and control signal, and the precise estimated value of the Doppler frequency deviation of the UAV measurement and control signal.

[0132] For the specific working process of the units disclosed in the above embodiments of the present application, please refer to the corresponding method embodiments, such as Figure 1 As shown, no further description is given here.

[0133] As can be seen from the above scheme, the present application provides a capture device for UAV measurement and control signals, which obtains the current low-orbit satellite ephemeris information according to the acquisition unit 601, and the calculation unit 602 calculates the predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time, the distance between the current low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light; the sampling unit 603 samples the UAV measurement and control received signal to obtain the sampling result. The rough estimation unit 604 determines the rough estimated value of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result of the UAV measurement and control received signal and the prediction error range; then, the precise estimation unit 605 uses the Shannon interpolation algorithm to correct the rough estimated value of the Doppler frequency deviation of the UAV measurement and control signal to obtain the precise estimated value of the Doppler frequency deviation of the UAV measurement and control signal; finally, the compensation unit 606 sends the rough estimated value and the precise estimated value of the Doppler frequency deviation of the UAV measurement and control signal to the carrier digital oscillator to perform carrier frequency compensation to obtain the compensated UAV measurement and control signal. It effectively narrows the frequency domain search range, shortens the signal capture time, and improves the estimation accuracy of the Doppler frequency offset, thereby improving the accuracy of the UAV measurement and control signal. It is suitable for high dynamic and low signal-to-noise ratio UAV measurement and control scenarios based on low-orbit satellite communications.

[0134] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0135] Another embodiment of the present application provides an electronic device, such as Figure 7 As shown, including:

[0136] One or more processors 701.

[0137] The storage device 702 stores one or more programs.

[0138] When the one or more programs are executed by the one or more processors 701, the one or more processors 701 implement the method for capturing the UAV measurement and control signal as described in any one of the above embodiments.

[0139] Another embodiment of the present application provides a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for capturing the UAV measurement and control signal as described in any one of the above embodiments is implemented.

[0140] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0141] It should be noted that the computer-readable medium mentioned above in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer readable signal media may also be any computer readable medium other than computer readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0142] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0143] Another embodiment of the present application provides a computer program product. When the computer program product is executed, it is used to execute any of the above-mentioned methods for capturing drone measurement and control signals.

[0144] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, the above-mentioned functions defined in the method of the embodiment of the present application are executed.

[0145] Although the subject matter has been described in language specific to structural features and / or method logic actions, it should be understood that the subject matter defined in this application is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing this application.

[0146] Although several specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present application. Certain features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0147] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above application concept. For example, the above features are replaced with (but not limited to) technical features with similar functions applied in the present application.

Claims

1. A method for capturing UAV measurement and control signals, characterized in that: include: Obtaining the current low-orbit satellite ephemeris information; wherein the current low-orbit satellite ephemeris information includes the current time, the distance between the current low-orbit satellite and the drone, and the carrier frequency of the transmitted signal; According to the current time, the distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light, the predicted value of the Doppler frequency deviation of the UAV measurement and control signal is calculated; Sampling the UAV measurement and control received signal to obtain a sampling result; wherein the received signal carrier Doppler total frequency deviation during the sampling process is the difference between the initial received signal carrier Doppler total frequency deviation and the predicted value of the UAV measurement and control signal Doppler frequency deviation; Determine a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range; wherein the prediction error range is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal taking into account the orbital height and orbital eccentricity of the low-orbit satellite; The Shannon interpolation algorithm is used to correct the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal to obtain the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal; The rough estimate value and the precise estimate value of the Doppler frequency deviation of the UAV measurement and control signal are sent to the carrier digital oscillator to perform carrier frequency compensation to obtain the compensated UAV measurement and control signal; wherein the generation frequency of the carrier digital oscillator is the sum of the center frequency of the transmitting signal carrier and the total Doppler frequency deviation of the target receiving signal carrier; the total Doppler frequency deviation of the target receiving signal carrier is the sum of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, the rough estimate value of the Doppler frequency deviation of the UAV measurement and control signal, and the precise estimate value of the Doppler frequency deviation of the UAV measurement and control signal; Determining a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range includes: Performing partial matched filtering-Fourier transform on the sampling results to obtain L amplitude-frequency response results; wherein L is a positive integer; Performing differential non-correlated accumulation according to all the amplitude-frequency response results to obtain a differential non-correlated accumulation result; According to the prediction error range, the search range of the differential non-correlated cumulative results is determined; In the search range of the differential non-correlated cumulative results, searching for the maximum differential non-correlated cumulative result; A rough estimate of the Doppler frequency deviation of the UAV measurement and control signal is generated according to the maximum differential non-correlated accumulation result.

2. The method for capturing UAV measurement and control signals according to claim 1, characterized in that: The sampling of the UAV measurement and control received signal to obtain the sampling result includes: Sampling is performed according to the number of sampling points, the pseudo code sequence, the center frequency of the carrier of the transmitted signal, the total Doppler frequency deviation of the carrier of the received signal, the signal sampling rate and the phase of the received signal to obtain the sampling result.

3. A device for capturing UAV measurement and control signals, characterized in that: include: An acquisition unit is used to acquire the current low-orbit satellite ephemeris information; wherein the current low-orbit satellite ephemeris information includes the current time, the distance between the current low-orbit satellite and the UAV, and the carrier frequency of the transmitted signal; A calculation unit, used to calculate the predicted value of the Doppler frequency deviation of the UAV measurement and control signal according to the current time, the current distance between the low-orbit satellite and the UAV, the carrier frequency of the transmitted signal and the speed of light; A sampling unit is used to sample the UAV measurement and control received signal to obtain a sampling result; wherein the received signal carrier Doppler total frequency deviation during the sampling process is the difference between the initial received signal carrier Doppler total frequency deviation and the predicted value of the UAV measurement and control signal Doppler frequency deviation; A rough estimation unit is used to determine a rough estimation value of the Doppler frequency deviation of the UAV measurement and control signal according to the sampling result and the prediction error range; wherein the prediction error range is the error range of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal taking into account the orbital height and orbital eccentricity of the low-orbit satellite; A precise estimation unit, used to correct the rough estimation value of the Doppler frequency deviation of the UAV measurement and control signal by using a Shannon interpolation algorithm to obtain a precise estimation value of the Doppler frequency deviation of the UAV measurement and control signal; A compensation unit, used for sending a rough estimate and a precise estimate of the Doppler frequency deviation of the UAV measurement and control signal to a carrier digital oscillator, performing carrier frequency compensation, and obtaining a compensated UAV measurement and control signal; wherein the generation frequency of the carrier digital oscillator is the sum of the center frequency of the transmitting signal carrier and the total Doppler frequency deviation of the target receiving signal carrier; the total Doppler frequency deviation of the target receiving signal carrier is the sum of the predicted value of the Doppler frequency deviation of the UAV measurement and control signal, the rough estimate of the Doppler frequency deviation of the UAV measurement and control signal, and the precise estimate of the Doppler frequency deviation of the UAV measurement and control signal; The rough estimation unit comprises: A transform unit, used for performing partial matched filtering-Fourier transform on the sampling result to obtain L amplitude-frequency response results; wherein L is a positive integer; An accumulation unit, used for performing differential non-correlation accumulation according to all the amplitude-frequency response results to obtain a differential non-correlation accumulation result; A coarse estimation subunit, used to perform peak detection on the differential non-correlated accumulation result according to the prediction error range, and obtain a coarse estimation value of the Doppler frequency deviation of the UAV measurement and control signal; The coarse estimation subunit comprises: A determination unit, used to determine a search range of a differential non-correlated cumulative result according to the prediction error range; A searching unit, configured to search for the maximum differential non-correlated cumulative result within the search range of the differential non-correlated cumulative result; A generating unit is used to generate a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal according to the maximum differential non-correlated accumulation result.

4. The device for capturing UAV measurement and control signals according to claim 3, characterized in that: The sampling unit comprises: The sampling subunit is used to perform sampling according to the number of sampling points, the pseudo code sequence, the center frequency of the carrier of the transmitted signal, the total Doppler frequency deviation of the carrier of the received signal, the signal sampling rate and the phase of the received signal to obtain the sampling result; The differential non-correlated accumulation results are used to generate a rough estimate of the Doppler frequency deviation of the UAV measurement and control signal.

5. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for capturing the UAV measurement and control signal as described in any one of claims 1 to 2.

6. A computer storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the method for capturing the UAV measurement and control signal as described in any one of claims 1 to 2 is implemented.

Images